The Pennsylvania State University
The Graduate School
College of Earth and Mineral Sciences
THE TUNICA MIRACLE, SIN AND SAVIOR IN AMERICA’S
ETHIOPIA: A POVERTY AND SOCIAL IMPACT ANALYSIS OF
CASINO GAMING IN TUNICA, MS
A Thesis in
Geography
by
Tracey L. Farrigan
© 2005 Tracey L. Farrigan
Submitted in Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy
May 2005 The thesis of Tracey L. Farrigan has been reviewed and approved* by the following:
Amy K. Glasmeier Professor of Geography and Regional Planning Thesis Advisor Chair of Committee
Adam Rose Professor of Geography and Environmental Economics
Martin Shields Associate Professor of Agricultural and Regional Economics
Chris Benner Assistant Professor of Geography
Roger Downs Professor of Geography Head of the Department of Geography
*Signatures are on file in the Graduate School.
ABSTRACT
One of the greatest methodological fallacies of the last half century in social research is the belief that science is a particular set of techniques; it is, rather, a state of mind, or attitude, and the organizational condition which allow that attitude to be expressed. (Dingwall 1992: 212, quoted in Lavalli 2000: 114)
Realist philosophy reflects the state of mind and realist methodology the organizational condition that allows for an open and sophisticated examination of the complexities of the social world. Yet, realist methodologies are underdeveloped and poorly understood in the field of geography, which limits geographers’ ability to translate their dynamic theories of the social world into as equally dynamic research in practice.
This study emphasizes the need for greater investment in the development, communication, and application of realist approaches by demonstrating the value of this approach to the study of persistent poverty. Specifically, the Poverty and Social Impact
Analysis (PSIA) framework developed by the World Bank as a means of assessing the distributional impacts of policy reform on vulnerable populations in developing nations is applied to a critical case in the United States––Tunica County, Mississippi, one of the nation’s historically most impoverished counties, previously known as America’s
Ethiopia . This comprehensive impact assessment of casino gaming as an economic development strategy in the Tunica area details the questionable politics of class, congruent with the region’s history of race relations, as the primary causal factor in determining the poverty outcome. This is accomplished by using a realist methodology to amass conclusive evidence to argue that despite the success of the casino industry in
Tunica County, where much has changed; much has tragically remained the same for the majority of the poor in this region. TABLE OF CONTENTS
List of Tables Page v List of Figures viii Acknowledgements x Chapter 1 Introduction 1 Chapter 2 Case Study Overview 21 Chapter 3 Poverty, Economy, and Policy 55 Chapter 4 Understanding Casino Gaming Impacts 76 Chapter 5 Historical Framework 128 Chapter 6 Growth of Gaming 165 Chapter 7 Impacts of Growth in Tunica 208 Chapter 8 Controversies and Contradictions of the Miracle 229 Chapter 9 Beneficiaries 263 Chapter 10 Sin and Savior 284 Chapter 11 Summary Conclusions 314 Appendix A Map Compendium 326 Appendix B Stakeholder Analysis 337 Appendix C Survey Instrument 345 Appendix D Select Frequency Tables 360
iv LIST OF TABLES
Table 1.1 Contrasts Between Positivist and Constructivist Page 5 Approaches Table 1.2 Contrast of Realist Philosophy to PSIA Philosophy 13 Table 2.1 Ten Key Elements of Poverty and Social Impact Analysis 28 Table 2.2 Defining Characteristics of Intensive and Extensive 42 Research Table 5.1 Unemployment Rate; United States County Mean, Delta 134 County Mean, Coahoma County (MS), and Tunica County (MS); 1960-1990 Table 5.2 Percent of Persons Below Poverty; United States County 134 Mean, Delta County Mean, Coahoma County (MS), and Tunica County (MS); 1960-1990 Table 5.3 Percent Households by Income Type; Mississippi and 135 Tunica County (MS); 1990 Table 5.4 Percent Race by Sex by Employment Status; Persons 16+ 136 Years Old; Tunica County (MS); 1990 Table 5.5 Percent Race of Householder Income; Black and White 136 Population; Tunica County (MS);1990 Table 5.6 Select Individuals and Household Level Statistics for 153 Comparison; North Tunica CDP (MS) and Town of Tunica (MS); 1990 Table 6.1 Assumptions of the Porter and S&P Models of Competitive 176 Dynamics Table 7.1 Gross Gaming Revenues by Casino Type; 1997 and 2002 210 Table 7.2 Commercial Casino Legalization and Opening Dates, 211 Number in Operation, and Gross Gaming Revenues by State; 2002 Table 7.3 Commercial Casinos; Number Employees, Employee 212 Wages, Gross Gaming Revenue, and Admissions by State; 2003 Table 7.4 Range of Statutory Gaming Tax Rates by State 214 Table 7.5 Casino Employment Comparisons by Number of Casinos 216 per State, 11-State Casino Workforce, State Workforce, and Gaming Industry Workforce; 2003 Table 7.6 Casino Operating History; North River Casino Regions, 220 MS; August 2004
v Table 7.7 Casino Credit, Wager, and Loss Limits by State Page 221 Table 7.8 Casino Number of Employees, Square Footage, and 222 Number of Games; Mississippi Casino Gaming Regions; 2004 Table 7.9 Amenities/Activities in Addition to Gaming; Tunica Co. 223 Casinos, MS; 2004 Table 7.10 Top Five Region/County by Admissions; Adjusted Gross 224 Revenue and AGR per Visitor; Post-1998 Casino Counties; 2001 Table 7.11 State Residence of Casino Visitors by Mississippi Casino 224 Region; 2000 Table 7.12 Top Ten Casino Markets Ranked by Gross Gaming 224 Revenue; 2002 Table 7.13 Yearly Employment Growth Rate and Impact of Casinos; 226 Top Ten Growth Countries out of Total Casino Counties in the U.S. Table 8.1 Growth Rates in Aggregate Industry Base Data; Tunica 233 County IMPLAN Model; 1990-1999 Table 8.2 Growth Rate in Casino Sector Base Data; Tunica County 234 IMPLAN Model; 1990-1999 Table 8.3 Casino Sector Percentage of Total Service Industry; Tunica 234 County IMPLAN Model; Base Data; 1999 Table 8.4 Employment and Income Multipliers; Aggregate Industries; 235 Tunica County IMPLAN Model; 1999 Table 8.5 Economic Diversification by Industry Sectors Gained 1990- 239 1999; Number Employed and Output by Sector 1999; Tunica County, MS Table 8.6 Industry Growth Sectors by Differential Growth Rate in 240 Output; Tunica County, MS; 1990-1999 Table 8.7 Casino Employment by Occupation Comparisons; Casino 244 Workforce, Gaming Industry Workforce, 11-State Casino Workforce, and National Workforce; 2003 Table 8.8 Casino Employment by Occupation Comparisons; Casino 245 Workforce, Gaming Industry Workforce, 11-State Casino Workforce, and National Workforce; White Workforce Population Only; 2003 Table 8.9 Casino Employment by Occupational Comparisons; Casino 246 Workforce, Gaming Industry Workforce, 11-State Casino Workforce, and National Workforce; Black Workforce Population Only; 2003
vi Table 8.10 Per Capita Income by Race/Ethnicity; Tunica Co., Page 250 Mississippi, US; 2000 Table 8.11 Select Distributional Characteristics of Median Household 251 Income and Earnings; Mississippi, Tunica County, North Tunica CDP, and the Town of Tunica; 1989 Table 8.12 County to County Migration Patterns; In-Flow and Out- 253 Flow for Tunica County; 1990-2000 Table 8.13 Commuters from Coahoma, De Soto, and Shelby Counties 255 to Tunica; Total 1970-2000; Average Wage and Workers by Service Industry Table 8.14 Allocation of Gaming Revenue; Tunica County 260 Expenditures; 1992-2001 Table 9.1 New Private Housing Units; Tunica County, MS; 1990, 270 1997, and 2002 Table 9.2 Select Housing Statistics; Tunica County, MS; 2000 270 Table 9.3 Geographic Variation in Median Housing Values; County 273 and Place; Tunica County and Mississippi; 2000 Table 9.4 Types of Crime and Percentages of Total Arrests; Tunica 278 County, MS; 2000 Table 10.1 Descriptives for Work Environment Effects Model 306 Table 10.2 Parameter Estimates for Work Environment Effects Model 307
vii LIST OF FIGURES
Figure 2.1 Regional Map of Tunica, Mississippi; Casinos* and Page 24 Vicinity Figure 2.2 Affinity Diagram of Methodological Processes 37 Figure 5.1 Population; Absolute and Cumulative Percent Change; 133 United States, Mississippi, Coahoma County (MS), and Tunica County (MS); 1900-1990 Figure 5.2 Comparative Diversity Index Values and Location 146 Quotients; Tunica County (MS); 1969-1989 Figure 6.1 Porter's Model of Industry Competitive Dynamics and 176 Mahon and McGowan's Social and Political Model of Industry Competitive Political Dynamics Figure 7.1 Cumulative Change in Gross Gaming Revenue; All 210 Gaming and Commercial Casino Gaming; 1993-2003 Figure 7.2 Consumer Spending on Commercial Casino Gaming; 212 U.S.; 1993-2003 Figure 7.3 Per Admission Tax Revenue and Gross Gaming Revenue; 213 State and State Average; 2003 Figure 7.4 Number of Jobs per Million Dollars of Gross Gaming 215 Revenue by Commercial Casino State; 2003 Figure 7.5 Mississippi Delta Casino Counties and Mississippi Casino 219 Regions Figure 7.6 Total Full- and Part-Time Employment; Tunica County, 226 MS; 1990-2000 Figure 8.1 Employment Location Quotients; Farming and 232 Agriculture, Fishing, Forestry Sectors; Tunica County, MS; 1990-1999 Figure 8.2 Employment Location Quotients; Service and All Other 232 Industry Sectors*; Tunica County, MS; 1990-1999 Figure 8.3 Ripple Effect of Service Industry Output; Tunica County; 237 1999 Figure 8.4 Cumulative Percent Change in Labor Force; Tunica 248 County and State of Mississippi; 1990-2001 Figure 8.5 Unemployment Rate; Not Seasonally Adjusted; Tunica 248 County (MS) and State of Mississippi; 1990-2001 Figure 8.6 Mississippi Tax Revenue from Gaming; State Allocation 257 and Local Government Transfers; 1993-2004
viii Figure 8.7 Percentage Distribution of Tunica County Gaming Tax Page 258 Revenue Figure 9.1 Illustrations of Crime, Addiction, and Sexuality 276
ix ACKNOWLEDGEMENTS
I express my gratitude to the many individuals who believed in me and my work and in so doing provided intellectual, financial, and personal support during my tenure as a graduate student at Penn State. I thank the members of my dissertation committee for their time and valuable advice on this work and in other areas of professional growth:
Martin Shields, Adam Rose, Chris Benner, and Amy Glasmeier—my friend, mentor, and committee chairman. I also give thanks to others among the Penn State faculty and staff who contributed to my development as a researcher and writer: Colin Flint, Lorraine
Dowler, Roger Downs, Timothy Kelsey, and Sherilee Carpenter. In addition, I offer special thanks to the National Science Foundation, Geography and Regional Sciences
Division of Behavioral and Cognitive Sciences, for the Doctoral Dissertation
Improvement Grant, which funded much of my dissertation research. For assistance with that research, I thank Sister Kay Burton, Melissa Joseph, Sikita Moody, Lillie Jean
Tillman, and the residents of Tunica and Coahoma counties, Mississippi, who participated in this study in one form or another and to whom this work is dedicated.
Finally, to my friends and family—Jennifer Fluri, Dave Jansson, Christine Jocoy, Isaac
Brewer, Christian Mostert, Samara Katz, Sheri Farrigan, Peggy Moses, and Betsy
Delevan—I am ever thankful for your love and relentless sense of hope.
x CHAPTER 1
INTRODUCTION
[T]he nature of geography has always been contested and negotiated…. It is, therefore, open to debate, to criticism, and to revision. (Livingstone 1992: 3-4)
Despite more than four decades of academic research on persistent poverty, we have only inconclusive and misleading evidence regarding the processes that create, maintain, and/or alleviate poverty conditions in a particular place. A common characteristic of these perspectives is that they employ an economistic philosophy (i.e., one based on established economic theory and related analytical approaches to research) to explain poverty phenomena. Where that explanation fails, there is a tendency to submit to some form of cultural determinism. Geographers, on the other hand, frequently recognize the limitations of this approach as a lack of regard for the complexities of the social world, such as the interrelatedness of economic, social, cultural, and political forces—their associations, embeddedness, and entanglements in time and space.
In other words, compartmentalizing poverty into economic or cultural ‘boxes’ makes it impossible to disclose the manner in which poverty unfolds in particular contexts over time. Further, being sensitive to this makes all theory limited or partial, which challenges our ability to clarify the conditions and means for inquiry (Thrift 1996).
Thus, it is understood that a definitive analytical solution for the comprehensive study of poverty, or of any social phenomena, does not exist. Still, there is a need for the discovery of information. Left untapped in the case of poverty, this lack of information retards our ability to contribute to a more open and evidence-based dialogue about its causes, conditions, and solutions .
1 I argue that looking at the world through the lens of realist philosophy (as defined later in this chapter) offers a potential means for that discovery of information, but in so doing acknowledge that realist methodology is loosely understood, underdeveloped, and rarely applied in the field of geography. Thus, in order to explore that potential it is imperative that we experiment within and inform the methodological process, such that more rigorous analysis may be achieved with future research endeavors. Therefore, in completing the research presented, the following methodological objectives were in mind: (1) Build on earlier experiences; (2) strengthen analytical capacity; (3) maintain flexibility and openness with respect to data, tools, and methods; and (4) increase transparency in the links among poverty, economy, and policy.
1.1 APPROACH TO RESEARCH
Over the last several decades geography has gone through substantial soul- searching to identify its distinguishing characteristics, by asking: “How do we know what we know in geography and what is a legitimate means for creating that knowledge?”
Answering that two-part question is difficult given the scope of the field of geographic study. That is, geographic research deals with phenomena with differing views on the nature of reality or what’s out there to know ( ontology ), what and how we can know about it ( epistemology ), how we can go about acquiring knowledge ( methodology ), which procedures are appropriate to use to acquire it ( methods ), and which data can we collect
(sources )? This presents conflict in practice because it is understood that the answers to each of those questions serve as the building blocks of research (Grix 2002). 1
1 That said, it is recognized that some social scientists argue that the connection is not a necessary one (e.g., Bryman 1984; Hammersley 1992).
2 From a philosophical and theoretical standpoint, human geographers have shown a fundamental concern with ontology and epistemology and in so doing have made great strides in overcoming that internal conflict as well as in making contributions to all social science in terms of the way we think about the nuances and complexities of the world
(e.g., Thrift 1999). However, far less progress has been made methodologically with respect to moving from conceptualization to practical research and back again (Pratt
1995). That is, the question remains; how should a geographer operationalize those abstractions in his/her search for evidence and further understanding? My critique, and that of other geographers in recognizing this shortcoming, is that a fundamental flaw is prevalent in human geography whereby there is inconsistency when moving from philosophy (ontology and epistemology) to practice (methodology and methods). For example, as Lees (2003: 107) explained following examination of the situation in ‘new’ urban geography:
Despite the salience of issues of method and methodology and the cultural turn, I find these little discussed… method and methodology are for the most part inconveniences in the world of ‘have theory will travel.’…. New’ urban geographers are ‘users’ of qualitative methods, but they seldom outline how they have used these methods or their relationship to the theoretical tracts that they follow. In other instances, they make a case for method and methodology but do not then follow this through in their research and writings.
This situation may be a reflection of the geographers’ failure to construct a transparent methodology that is consistent with their epistemology and/or a lack of understanding of the difference between method and methodology, and the relevance of the latter as a bridge between philosophy and practice. For example, Yeung (1997: 55) argued that:
3 Methods are surely important, but their importance cannot be exercised unless they are supported by strong philosophical claims at the ontological and epistemological levels. This is precisely the reason why positivism and empiricism have failed because they offer easily accessible and ‘objective’ methods (e.g., quantification and statistical methods) without resolving some fundamental philosophical problems embedded in Humean empiricism and logical positivism….
The latter comment suggests that when translating philosophy into practice, geographers have a wide range of methodologies to choose from and that differing epistemological stances create some degree of polarization in the action of selecting from among them. Following the example given, empiricism in association with a positivist epistemology and modernism sits on one end of the continuum of knowledge creation while on the other end we find instrumentalism, which lends itself to a constructivist epistemology and the post-modern critique (Summer and Tribe 2004).
Both are understood as legitimate intellectual practices in geography, but the main difference is that positivism is ontologically posited on the contention that reality and universal ‘truths’ are observable and that these truths can be observed in an objective manner by the researcher (Giere and Richardson 1997). On the flip side, constructivism is posited ontologically on the premise that reality does not exist independently from our experiences and in so doing argues that the world is made up of multiple realities that are intangible, local, and specific in nature. Therefore, it is understood that interaction between the researcher and the researched is necessary to move beyond individual subjectivity and to achieve a deeper and more inclusive understanding of the nature of the world. Table 1.1 further demonstrates the difference between the two approaches.
4 Table 1.1 Contrasts Between Positivist and Constructivist Approaches
Question Positivist Constructivist
A definable 'reality' or 'truth' There is no 'reality' or 'truth' What is reality? exists and is observable beyond our experiences What is the goal of A more informed construction of Acquisition of the 'truth' academic enquiry? the world How are the The researcher is independent of The researcher is not independent researcher and the the 'researched' of the 'researched' 'researched' related? What should be the Subjectivity is celebrated as part of None, objectivity is sought role for values? 'reality' Predominantly based on discourse Predominantly based on What kind of and meaning with the aim of operability or measurability and approach? seeking a more informed with the aim of seeking 'evidence' understanding of the world What kind of data are Traditionally predominantly Traditionally predominantly preferred? quantitative qualitative
What are examples of Dollar and Kraay (2002) Growth Narayan et al. (2002) Voices of the such studies in is Good for the Poor Poor poverty research?
Source: Adapted from Summer and Tribe (2004), p. 4.
A positivist methodology typically appeals to geographers as a scientific search for ‘truth’ through an objective lens, usually with a quantitative basis, while a constructivist methodology appeals to geographers as a subjective search for meaning and understanding of the human condition with a qualitative orientation. As an example of what this means in practice, consider an economic geographer who is conducting poverty research. When seeking to define poverty, the positivist approach would likely invoke an income or consumption-based definition of poverty and quantitative analysis of secondary data. The constructivist approach would consist of a broader definition of poverty that includes non-economic dimensions of security, vulnerability, and
5 empowerment, with qualitative analysis of primary data. In sum, just within the sub-field of economic geography, given the same question, two very different ends of the research continuum can be counter-posed in relation to one subject matter, which without a doubt would produce very different outcomes. Yet, as with the differing epistemologies, both sets of results would be considered legitimate.
However, this polarization is not necessary as there is a midpoint along the continuum. For example, geographic study can be normative when it is not so much concerned with knowledge creation for its own sake, but rather knowledge creation as a means for contributing to improved well-being. In this case, the ontological stance may be one of realism ,2 which creates a distinction between physical reality (positivist) and human cognition (constructivist) such that a physical reality exists independently of our cognition but our ability to appraise it objectively is limited by the fact that we are dependent observers of the events under study. In that vein, in the eyes of a realist all knowledge is fallible.
Thus, with realists knowledge is accepted as a social construct (e.g., one’s description of their own understanding of poverty and experience of being poor), but one that aims to explain a physical reality (e.g., social and physiological aspects of being poor such as illiteracy and malnutrition). The former acknowledges subjectivity (e.g., qualitative data captured at the scale of the individual) and the latter objectivity (e.g., quantitative data captured at the scale of the nation). In conjunction, bias is associated with each, such as bias in values (e.g., by accepting that poverty is a multi-dimensional
2 There are a number of different forms of realism. Most geographers follow the critical scientific form as associated with the works of Bhaskar (1997), Harre (1985, 1986), Sayer (1992, 2000), and Keat and Urry (1982). Therefore, the use of the terms realism and realist in this work are generally understood as such.
6 concept) and bias in data (e.g., by recognizing that bias is associated with the definition of an indicator). Accordingly, realism allows for the best of both worlds and in so doing presents the possibility for obtaining a more complete and accurate picture of the phenomenon under study and its context.
Yet, despite the methodological implications, relatively few studies have made rigorous attempts to move realism beyond the state of conceptualization (e.g., Layder
1990, 1993; Sayer 1992, 1993). Allen (1983: 183) claimed that this was due to the fact that, analytically, realism sought to:
Conceptually specify… objects, their properties, and their potential range and scope. But it takes this aim upon itself with little in the way of accompanying methodological prescriptions to achieve its goal.
This becomes clearer when we examine what might be considered a realist methodology.
1.1.1 REALIST METHODOLOGY
Realists believe in the relative importance of causal powers, generative mechanisms of objects in explanation, and abstraction as tools for the reclamation of reality. However, the key methodological questions are for the most part left unanswered: How can these things be abstracted and where does one begin? That is, how exactly does a realist go about conducting research? The lack of clarity in response to those questions is in many ways indicative of the philosophy, which lends itself to methodological pragmatism and a simultaneous inductive-deductive dialect. In other words, “it is not the mechanical application of standard tools” that is of concern to the realist researcher, rather, “knowledge of the subject is crucial, coupled with research on the particular applications and contexts” (Sayer, 2000: 23). Thus, no one set of research
7 guidelines is prescribed, but under certain circumstances some are deemed more relevant than others. This depends to a large extent upon the research topic and context (Layder
1988). Accordingly, where methods are concerned, any and all have potential— qualitative, quantitative, or some combination—as a means for capturing, analyzing, and/or reworking conceptions of social processes’ (Allen 1983). However, there are few methods that are typically employed by realists, as explained below.
1.1.1.1 REALISM IN PRACTICE
The realist approach is basically a posteriori , given the social reproduction of knowledge. The realist seeks to reconstruct the properties of causal structures through constant reflection and critique (Yeung 1997). Causal mechanisms are seen as both historical and contextual. Therefore, the realist must abstract and stipulate their historical and contextual circumstances. Realist geographers use three general methods to meet that goal. The first is iterative abstraction. This is used most often and is supported heavily by Sayer who argues that (1992: 86):
To be practically-adequate, knowledge must grasp the differentiations of the world; we need a way of individuating objects, and of characterizing their attributes and relationships. To be adequate for a specific purpose it must ‘abstract’ from particular conditions, excluding those which have no significant effect in order to focus on those which do. Even where we are interested in wholes we must select and abstract their constituents.
The purpose of iterative abstraction is to “obtain knowledge of real structures or mechanisms which give rise to or govern the flux of real phenomena of social and economic life” (Lawson 1989: 69, original emphasis). Still, there is no formal method of abstraction. As a general rule, the realist starts with an empirical problem and proceeds to abstract the necessary relation between the concrete phenomenon and its deeper causal
8 structures, giving rise to generative mechanisms. As more evidence is collected the realist can reaffirm or revise the current abstraction and continues to do so in an iterative fashion until no further contradictory evidence is found to exist and the ‘alleged’ generative mechanisms are believed to be powerful enough to explain the concrete phenomenon. This is known more widely as ‘retroduction’, in which a general argument
“moves from a description of some phenomenon to a description of something which produces it or is a condition for it” (Bhaskar 1986: 11).
The second general method used is grounded theory. This is a qualitative research method that uses a systematic set of procedures for generating and testing theory about phenomenon (Strauss and Corbin 1990). In summary, grounded theory involves a complex analysis of data and theory through evolving interpretations, the linking of concepts, the collection, coding, and memoing of data, potential use of experimental data, and grounding that data in elements of induction, deduction, and verification (Strauss and
Corbin 1990). This method can be used to reinforce iterative abstraction whose theoretical categories need to be grounded in empirical evidence; however, it is rarely applied by realist geographers. That is, aside from a few limited cases (e.g., Pratt 1994), in geography grounded theory is used most often for inductive reasoning alone, to discover theories rather than iterative abstractions of necessary relations as would be of interest to the realist geographer (Pratt 1995; Yeung 1997).
The third method, or more appropriately, group of methods, is triangulation.
Triangulation emphasizes a multi-method approach but it is not set in the language of qualitative-quantitative mixing, as it does not necessarily incorporate both in its methodological form. This is apparent in Denzin’s (1970) explanation of ways in which
9 triangulation can be approached. The first is data triangulation, in which various forms of data with respect to time, place, person, and/or level, are used in the analysis. The second is investigator triangulation, whereby multiple researchers observe and report on the same phenomenon. The third is theoretical triangulation, which offers multiple perspectives on the same object or set of objects. The fourth, and final, is methodological triangulation, which can be between-method (the use of unlike methods) or within-method (variations within the same methodology). Regardless, no matter what form triangulation takes, the general purpose is to provide corroborating evidence (Creswell 1998). In realist research this multi-layered approach is integral to the discovery process because it helps to reveal different facets of the social world. Yet, such an approach is rarely recognized in terms of triangulation by realists. This may be because choice of method for realists is based more on perceived need than design.
The methods noted address some of the procedures used by realists in acquiring knowledge, but they do not represent methodological guidelines in their own right. What we can glean from them is that realism in practice is based on a combination of conceptualization, explanation, and empirical validation of the phenomenon under study, with a concern for generative mechanisms and contextual contingency. These methodological components may not seem specific to realism on the surface, but they are in terms of purpose and execution. For instance, most explanatory studies, whether conducted under the auspices of empiricism or otherwise, begin with conceptualization through a critique of existing work (e.g., a literature review). This is also true of realism, but the purpose of that critique is to present a platform for re-conceptualization of phenomenon that is geared toward guiding the research process in a way that offers a
10 greater appreciation for capturing and understanding the complexities of the social world
(Sarre 1987; Walton 1995).
1.1.1.2 APPLICATION TO THE FIELD
The meaning of realist research is still an emerging issue set within a wider debate regarding research methods in geography. In consequence, it may be the case that in geography, “the realist philosophy is unable to capture its fair share of ‘methodological battles’ largely because of its opaque method” (Yeung 1997: 56). 3 Yet, there are a number of implications for the application of a realist approach to geographic research.
Following the logic of Lawson and Stacheli (1990), the first is that realists recognize that there is a ‘one-to-many’ relationship between cause and effect that stems from the understanding that the social world is open. As a result, single processes may generate multiple outcomes and similar outcomes may result from different processes. This forces realists to focus on process rather than pattern.
The second reason is that the realist use of abstractions operating at different levels helps them to build theories that explain social phenomenon in place at specific moments in time. This involves recursive research that assists in the understanding of the
‘lived’ world. The third reason to use a realist approach given by Lawson and Stacheli is that realists combine methodologies in different rounds of the research process in order to meet iteration demands. This raises questions that may require qualitative and/or quantitative techniques. For instance, quantitative methods may help identify general
3 This is not to imply that realism is not criticized beyond its lack of methodological development, indeed like all other philosophies imbibed in the whole of geography it has been heavily critiqued from an ontological and epistemological perspective as well. For some of that debate see Johnston (1997) and Lawson and Stacheli (1990, 1991).
11 patterns that can resolve certain questions or confirm expected outcomes, but they may also point out that for certain questions pertaining to the operation of causal processes qualitative research methods may be of more use. As such, the realist takes advantage of the benefits of both forms of inquiry.
1.2 STUDY RATIONALE
The aforementioned points to the fact that in realist philosophy it is understood that what can be known and how knowledge can be produced is dependent on the ‘things’ that we study and the ‘aims’ of our research (Sayer 1992). Building from a realist perspective, the aim of this study is to demonstrate a means by which a realist philosophical point of departure can be implemented within economic and social geography. This is accomplished by using a case study of one of the most complex, contentious, and indeterminant problems––the existence and persistence of deep poverty in the face of public policies that are either explicitly or by implication presumed to be able to tackle and ameliorate the situation. In so doing, I follow an established methodological framework for conducting poverty research, Poverty and Social Impact
Analysis (PSIA; World Bank 2003), which embodies the methodological components noted in conjunction with the practice of realism ( see Table 1.2 for comparison).
12 Table 1.2 Contrast of Realist Philosophy to PSIA Philosophy
Building Block Research Realist Philosophy PSIA Philosophy of Research Question
A definable physical reality Poverty is a multi- exists and is observable, but dimensional construct, What's out there observation is based on consisting of an objective Ontology to know, what is human cognition and physical reality and a reality? therefore all we can truly subjective psychological know are the social constructs reality of that reality
By seeking a deeper By capturing, analyzing, understanding of the lived and/or reworking conceptions How can we experiences of the poor and Epistemology of social processes, their know? the processes that produce, generative mechanisms and maintain, and/or alleviate contextual contingencies their condition
Through systematic Through abstraction, assessment of How can we go inductive and deductive social/economic Methodology about acquiring reasoning, immanent critique, relationships that is knowledge? empirical validation exploratory, confirmatory, and participatory
Which None--it depends on the None--the determination of procedures are Method phenomenon under study and methods is based on an most the aims of the research emergent research process appropriate?
None--data may be None--data may be What kind of qualitative or quantitative, qualitative or quantitative, Sources data are objective or subjective, objective or subjective, preferred? primary or secondary primary or secondary
13 1.2.1 THE PSIA CONCEPT
The World Bank (2003) advances a framework for analyzing poverty impacts according to opportunity, empowerment, and security, emphasizing the need to look beyond general and aggregated economic indicators. The development of this framework stems from the recognition that there is a need to simultaneously achieve economic development and poverty reduction. However, the link between the two, and essentially between poverty analysis and policy prescriptions, has consistently been weak, largely because of the multi-dimensionality of poverty that does not fall entirely within economic boundaries and therefore cannot be framed as such. As a consequence, the poverty impact of any instrument of change remains unknown. Poverty is not captured in enough detail and evaluative information is fragmented at best.
For instance, historically, poverty analysis was characterized by a classical statistical approach based on a set of standard socio-economic indicators, with poverty measured in terms of an income line derived from household surveys (Citro and Michael
1995). Recent research has shown that this economic-driven approach fails to capture the multiple dimensions of poverty—“Although poverty is generated by the systemic contradictions that mark all capitalist societies, these contradictions tell us little about poverty’s everyday reality” (Harvey 1993: 20). For example, research that has sought to gain knowledge about that reality has revealed a number of tensions associated with inadequate economic resources (Gutkind 1986), such as insecurity, physical and social isolation, lack of access to information, distrust in government institutions, lack of self- respect and self-worth, and powerlessness. In those instances, it is recognized that
14 income maximization may be less important to the poor than decreasing vulnerability
(Chambers 1983; Cornia et al. 1987; Moser and Holland 1997).
Therefore, a deeper understanding of the lived experiences of the poor and the processes that produce, maintain, and/or alleviate their condition is necessary (Carvalho and White 1997). However, from a methodological standpoint it is recognized that conducting such a comprehensive study of the social world requires what Barrett (2001) referred to as simultaneous mixing , a “multifaceted integration of qualitative and quantitative methods,” which begins by seeking to answer generic questions like (92):
1) What does it mean to be poor or vulnerable in this setting? How does this vary across individuals, households, and communities and over time? (i.e., are we asking the right questions of the right people at the right time?) 2) Derivative from 1), are we measuring the correct variables and in the right manner? 3) Is our inference of the qualitative and quantitative data on those variables consistent (a) across research methods (a test of robustness) and (b) with local expressions of understanding of the problem(s) (a test of relevance)?
However, the way in which we go about answering those questions and the manner in which the end goal is reached—an expressed assessment of impacts—is not a cookbook process. As noted by Neubert (2000) in considering a methodology for social impact analysis of poverty alleviation programs and projects (1):
While a standardized set of tools is available for the economic and technical evaluation of projects, methods of covering the social dimension, which are of prime importance for impact analysis, have yet to reach maturity.
The social dimension referenced above is that defined by the World Bank, meaning the welfare of human beings, to include their quality of life, the quality of their
15 education, and the quality and sustainability of their institutions and relations. Thus, from the perspective of development policy, the social dimension represents a cross- current of the cultural, political, and economic dimensions of a society. Over the last decade the World Bank has sought to operationalize that reference frame with respect to assessing the distributional effects of economic development policy in a manner that is not only scientifically tenable, but also transparent and practical. The result of that effort is a research methodology referred to as Poverty and Social Impact Analysis (PSIA).
However, PSIA is not a product. As with Realism it is a process and like simultaneous mixing it is not a strictly sequenced process. Knowledge acquisition takes place through a systematic assessment of social and economic relationships that is exploratory, confirmatory, and participatory in nature. Thus, in terms of content, PSIA is a research framework and an analytical tool-kit . Study design is an emergent process that requires an iterative mixing of methods and therefore takes form around an open and therefore ambiguous research rubric (Robb 2003), which in its simplest form may consist of:
Explanation of the logic behind the instrument of change and its links to poverty using economic rationale and contextual knowledge; Use of secondary data to make some poverty links; Purposive research to analyze the effects of change; and Economic modeling.
1.2.2 RESEARCH OBJECTIVE
PSIA has been used extensively in the analysis of the poverty-effects of policy reform in developing nations (e.g., Armenia, Chad, Uganda), 4 yet its application to the
United States and other developed nations is lacking. This study bridges that research
16 gap by adopting PSIA as a guide in investigating and presenting the poverty impacts of casino gaming as an economic development strategy in Tunica County, Mississippi. The objective of this study, however, was by no means to suggest PSIA as a methodological recipe for all realists or that a realist approach is far superior to any other. Rather, the objective was to demonstrate a research process that is more open than standard theoretical approaches (e.g., purely economistic perspectives that are limited to established economic theories). In accomplishing this, my goal is to bring to the fore evidence that would otherwise be missed. This includes evidence that challenges existing stereotypes about the characteristics of the poor or the processes that produce, maintain, or alleviate poverty conditions––that is, evidence that lends itself to a more critical and emancipatory human geography than that produced via other avenues.
1.3 CHAPTER REFERENCES
Allen, J. 1983. In Search of a Method: Hegel, Marx, and Realism. Radical Philosophy. 35: 26-33.
Barrett, C. 2001. Integrating Qualitative and Quantitative Approaches: Lessons from the Pastoral Risk Management Project. In R. Kanbur, ed. Q-Squared: Qualitative and Quantitative Methods of Poverty Appraisal. New Delhi: Permanent Black.
Bhaskar, R. 1986. Scientific Realism and Human Emancipation. London: Verso.
Bhaskar, R. 1997. A Realist Theory of Science. London: Verso.
Bryman, A. 1984. The Debate About Quantitative and Qualitative Research: A Question of Method or Epistemology? British Journal of Sociology. 35: 75-92.
Carvalho, S. and H. White. 1997. Combining the Quantitative and Qualitative Approaches to Poverty Measurement and Analysis: The Practice and the Potential. Technical Paper No. 366. Washington DC: World Bank.
Chambers, R. 1983. Putting the Last First. London: Longman.
4 Full documentation of country experiences with PSIA is available online at www.worldbank.org.
17 Citro, C. and R. Michael, eds. 1995. Measuring Poverty: A New Approach. Washington DC: National Academy Press.
Cornia, G., R. Jolly, F. Stewart, eds. 1987. Adjustment With a Human Face: Protecting the Vulnerable and Promoting Growth. Oxford: Clarendon Press.
Creswell, J. 1998. Qualitative Inquiry and Research Design: Choosing Among Five Traditions. Thousand Oaks, CA: Sage Publications.
Denzin, N. 1970. The Research Act: A Theoretical Introduction to Sociological Methods. Chicago: Aldine.
Giere, R. and A. Richardson, eds. 1997. Origins of Logical Empiricism. Minneapolis: University of Minnesota Press.
Grix, J. 2002. Introducing Students to the Generic Terminology of Social Research. Politics. 22(3): 175-186.
Gutkind, E. 1986. Patterns of Economic Behavior Among the American Poor. New York: St. Martin’s Press.
Hammersley, M. 1992. Deconstructing the Qualitative-Quantitative Divide. In Brannen, J., ed., Mixing Methods: Qualitative and Quantitative Research. Aldershot: Avebury. Pgs. 39-55.
Harre, R. 1985. The Philosophies of Science. Oxford: Oxford University Press.
Harre, R. 1986. Varieties of Realism: A Rationale for the Natural Sciences. Oxford: Blackwell.
Harvey, D. 1993. Potter Addition: Poverty, Family, and Kinship in a Heartland Community. Aldine de Gruyter.
Johnston, R. 1997. Geography and Geographers: Anglo-American Human Geography Since 1945. New York: Oxford University Press.
Keat, R. and J. Urry. 1982. Social Theory as Science. London: Routledge and Kegan Paul.
Lavalli, T. 2000. Exploring the Nature of Qualitative Research: Assumptions, Attributes, Definitions, and Antecedents. Published Dissertation, The California Institute of Integral Studies, San Francisco, CA.
Lawson, T. 1989. On Abstraction, Tendencies, and Stylised Facts: A Realist Approach to Economic Analysis. Cambridge Journal of Economics. 13: 59-78.
18 Lawson, V. and Staeheli, L. 1990. Realism and the Practice of Geography. The Professional Geographer. 42: 13-20.
Lawson, V. and Staeheli, L. 1991. On Critical Realism, Human Geography and Arcane Sects! The Professional Geographer. 43: 231-233.
Layder, D. 1988. The Relation of Theory and Method: Causal Relatedness, Historical Contingency, and Beyond. Sociological Review. 36: 441-463.
Layder, D. 1990. The Realist Image in Social Science. London: Macmillan.
Layder, D. 1993. New Strategies in Social Research. Cambridge: Polity Press.
Lees, L. 2003. Urban Geography: ‘New’ urban geography and the ethnographic void. Progress in Human Geography . 27(1): 107-113.
Livingstone, D. 1992. The Geographical Tradition. Oxford: Blackwell.
Moser, C. and J. Holland. 1997. Household Responses to Poverty and Vulnerability. World Bank: New York.
Neubert, S. 2000. Social Impact Analysis of Poverty Alleviation Programmes and Projects: A Contribution to the Debate on the Methodology of Evaluation in Development Cooperation.
Pratt, A. 1994. Uneven Re-production: Industry, Space, and Society. Oxford: Pergamon Press.
Pratt, A. 1995. Putting Critical Realism to Work: The Practical Implications for Geographical Research. Progress in Human Geography. 19: 61-74.
Robb, C. 2003. Poverty and Social Impact Analysis—Linking Macroeconomic Policies to Poverty Outcomes: Summary of Early Experiences. IMF Working Paper WP/03/43. International Monetary Fund.
Sarre, P. 1987. Realism in Practice. Area . 19: 3-10.
Sayer, A. 1992. Method in Social Science: A Realist Approach. 2 nd ed. London: Routledge.
Sayer, A. 1993. Postmodernist Thought in Geography: A Realist View. Antipode. 24: 320-344.
Sayer, A. 2000. Realism and Social Science. Thousand Oaks, CA: Sage Publications.
19 Strauss, A. and J. Corbin. 1990. Basics of Qualitative Research: Grounded Theory Procedures and Techniques. Thousand Oaks, CA: Sage Publications.
Summer, A. and M. Tribe. 2004. The Nature of Epistemology and Methodology in Development Studies: What Do We Mean By ‘Rigour’? Paper prepared for “The Nature of Development Studies,” DSA Annual Conference, “Bridging Research and Policy,” Church House, London, 6 November 2004.
Thrift, N. 1996. Spatial Formations . London: Sage.
Thrift, N. 1999. Steps to an Ecology of Place. In D. Massey, J. Allen, and P. Sarre, eds. Human Geography Today. Cambridge: Polity Press. Pgs. 295-322.
Walton, J. 1995. How Real(ist) Can You Get? Professional Geographer. 47(1): 61-65.
World Bank. 2003. A User’s Guide to Poverty and Social Impact Analysis. Poverty Reduction Group (PRMPR) and Social Development Department (SDV). Washington DC: World Bank.
Yeung, H. 1997. Critical Realism and Realist Research in Human Geography: A Method or a Philosophy in Search of a Method. Progress in Human Geography. 21(1): 51-74.
20 CHAPTER 2
CASE STUDY OVERVIEW
Some 444,000 Mississippians—16.8 percent, or one in five—lived below the poverty level in 1999…. Pockets of economic deprivation remain in the Delta and southeast regions of this state that rival the most abject poverty in Third World countries. (Salter 2003: 2)
Nearly forty years after the U.S. government declared war on poverty, abject poverty remains the greatest challenge faced in the Mississippi Delta and in other historically poor regions of the country. Why does poverty persist? Policy makers striving for economic growth are challenged by the conflicts between growth and development that prevent certain communities and individual social groups from making sustained progress. The effects of growth can be contradictory; changes under the growth rubric, such as in capital, labor, finance, communications, and production, may not lead to socio-economic development and may further serve to reinforce existing inequalities and prevailing quality of life concerns. Thus, the contradictions of growth and resultant social and economic conflicts are a part of the fabric of persistent poverty.
Special attention must be paid to the proliferation of those conflicts and how they manifest in place to allow poverty conditions to persist rather than decease. Most empirical and geographical work that tests the ambiguous effects of growth on poverty populations in the United States is limited, particularly where certain economic development strategies have been employed. This research enhances our understanding of those dynamics through a case study analysis of the social and economic impacts of commercial casino gaming as an economic development strategy on a targeted poverty
21 population in Mississippi and the contextual and contingent factors that have shaped those impacts. 5
2.1 STUDY CONTEXT
Situated just thirty miles south of Memphis, Tennessee (see figure 2.1 for relative location), Tunica County represents the heart of Mississippi River Delta country, dotted by catfish ponds and vast acreage of the nation’s richest farmland, planted in cotton, rice, and soybeans . Yet it is not the natural environment that visitors to Tunica County find so striking, but rather the sharp contrast of that environment to the Las Vegas style strip development of casinos that serves as their destination. Amidst the billboards and newly planted boulevards that animate the gateway to “the South’s Casino Capital” (TCVB
2002), it is difficult to imagine the scene that once greeted visitors to the county, an area labeled “America’s Ethiopia” in 1985 by the Reverend Jesse Jackson ( Detroit News
1999).
… Rev. Jesse Jackson brought national attention to Tunica County with his visit to Tunica’s “Sugar Ditch,” where residents lived in poverty. A nearby drainage ditch was used to disperse household waste… Using a television crew from CBS’s 60 Minutes , Jackson broadcast to the world that Tunica County was the poorest county in the United States, calling it “America’s Ethiopia.” (TCM 2003: n.p.)
Prior to the last decade, Tunica County was recognized as the poorest county in the poorest state not only by the media, but by the government as well (TCVB 2002; US
Census 1993). Among the 219 Lower Mississippi Delta Counties (US Congress 1988a), in a 1988 congressional hearing, the federal government deemed Tunica County “the
5 For this study commercial casinos are defined to include private sector land-based, riverboat, and dockside casinos. The term gaming has come to refer to legal forms of gambling only while gambling refers to both illegal and legal activities. In this study the terms are used interchangeably.
22 epicenter of the problem in the Delta” according to poverty, income, unemployment, health, and education indicators (US Congress 1988b: 66). That designation is seemingly just. According to the US Census Bureau, in 1989 nearly 57 percent of Tunica County’s population lived in poverty, while the regional county average was just over 25 percent as was the state of Mississippi, and the national average was only 13 percent. However, since that time Tunica County has cut its poverty and unemployment rates in half and brought its per-capita income to near par with the state (BEA 2002; BLS 2002; US
Census 2001). 6
The rapid and drastic economic turnaround in Tunica County has been attributed to growth in the gaming industry following the passing of the Mississippi Gaming
Control Act of 1990 (Snyder 1999). The legislation allowed for dockside gaming operations on a local county option basis for counties on the Gulf Coast and along the
Mississippi River ( Comprehensive 2002). Mississippi casino development began in 1992 and in October of that same year Splash Casino, the first in Tunica County, opened to an unanticipated number of patrons. It was the beginning of what would become the largest concentration of casinos along the state’s river shore (Meyer-Arendt 1998), with an impact on the county that has since been popularized as “The Tunica Miracle.”
6 See Appendix A for comparison of economic health indicators over time among Mississippi counties.
23 Figure 2.1 Regional Map of Tunica, Mississippi; Casinos* and Vicinity
*Tunica County casino locations are designated by numbers 1 through 9; west of old Highway 61 Source: Tunica Convention and Visitors Bureau (2005)
2.2 PROBLEM STATEMENT, OBJECTIVE, & RESEARCH QUESTIONS
The relationship between economic growth and poverty outcomes is not easily understood. Therefore, this research sought to establish a measure of the Tunica Miracle with respect to the poverty population, positing that:
24 a) The benefits of economic growth are not necessarily evenly distributed and the nature of that distribution is determined by a host of economic and non-economic factors, many of which are not captured in standard impact studies.
b) Attempts at universal measures of poverty impacts have not included the meaning poor people place on their own situation and this limited viewpoint obscures our understanding of the poverty outcome and its relationship to economic growth.
Accordingly, the objectives of the case study were to:
Gain an understanding of the Tunica miracle from the perspective of a standard economic impact analysis approach;
To question that miracle, defined in such a way, by re-conceptualizing it and investigating it from the standpoint of realist philosophy; and
To capture the voice of the poor by operationalizing the World Bank’s poverty and social impact analysis methodological framework in the context of the United States.
The research questions that were addressed consisted of a combination of descriptive (how does x vary with y?), interpretive (what is y?), and explanatory (does x cause y?) questions as a means to both effectively meet the research objectives and to triangulate in a number of ways (e.g., data, theory, method). Listed in the order that they are answered in this document:
1) Ontologically, epistemologically, and methodologically: a. How do we think about poverty—how is it defined, understood, and identified? b. What kinds of policy approaches are typically taken to alleviate poverty, based on our understanding of what causes it? c. How is economic development understood in relation to poverty alleviation?
2) Considering casino gaming: a. How is it understood as an economic development strategy (i.e., as a moral vs. economic issue)? b. What are the potential outcomes of casino development in general and as a means for alleviating distressed areas? c. In what way are the outcomes typically measured and interpreted?
25 3) Given the history: a. How did Tunica become the poorest county in the United States? b. What is the legacy of casino gaming in the United States and Mississippi? c. How did the development of casinos transpire in Tunica?
4) Measuring the impacts: a. What are the global impacts of casino development in Tunica (e.g., at the county-level unit of analysis)? b. What are the distributional impacts with respect to the poor (e.g., at the household- and place-level unit of analysis)?
5) From the perspective of the poverty population (e.g., at the individual-level unit of analysis): a. What is the meaning of poverty and well-being? b. How is gaming perceived morally and economically? c. How has their life or the lives of people they know changed as a result of casino development? d. How do the answers to the previous questions conflict or confirm what was previously understood (i.e., thought to be known)?
6) In conclusion: a. What is the outcome with respect to the Tunica miracle? b. What does this suggest in terms of re-conceptualizing how with think about poverty and the means to alleviate it? c. What does this demonstrate methodologically? d. What is the relevance of this study and realist methodology to the field of geography?
2.3 METHODOLOGICAL FRAMEWORK
Impact analysis stems from the 1930s, but developed more substantially since the
1960s with the recognition that social impacts needed to be considered along with economic (Farrigan 1999; McDonald 1990; Rossini and Porter 1983). Economic impact analysis generally centers on growth in reference to income, employment, and taxes
(Cantor et al. 1985; Davis 1990). Social impacts refer to “adaptation on the part of a social system to external agents of change and/or endogenous change" or “the social consequences of actions, including change to norms, beliefs, perceptions, and values”
(Barrow 2000: 1). Therefore, social impact assessment (SIA) may incorporate economic
26 as well as demographic, psychological, institutional, locational (displacement and relocation), community (cohesion and belief system), individual (lifestyle and well- being), and other impacts of social consequence (e.g. Clark and Soulsby 1998; Crook and
Moroney 1995; Grady et al. 1987; Levine 1983).
Poverty and social impact analysis (PSIA), which refers to the analysis of the distributional impacts of policy reforms on the well-being of different stakeholders, with particular focus on the poor and other vulnerable groups (World Bank 2002), evolved concurrently with SIA in the fields of anthropology, political science, planning, economics, sociology, engineering, and psychology (Carley and Bustelo 1984). Yet many of the methods that are considered standard today were developed by the World
Bank since the 1960s (Finsterbusch et al. 1990; Rickson et al. 1990). Despite this lengthy development process, the systematic undertaking of PSIA has proved difficult due to multiple challenges: lack of data for distributional assessment, policy that crosses over scales and differs across time in both implementation and effect, the ability to make comparisons of impacts given other factors of change, and a lack of methods that allow for rigorous assessment (World Bank 2002). Thus, PSIA must be approached from a variety of avenues that reflect the study objectives and context and where possible, integrate economic and social analyses. Although no exact methodological template exists for doing so, ten key elements for advising PSIA are at the core of its conceptual framework (World Bank 2003). Those key elements are shown in table 2.1 and are explained in detail in the remainder of this section.
27 Table 2.1 Ten Key Elements of Poverty and Social Impact Analysis
1 Asking the right questions 2 Identifying stakeholders 3 Understanding transmission channels 4 Assessing institutions 5 Gathering data and information 6 Analyzing impacts 7 Contemplating enhancement and compensation measures 8 Assessing risk 9 Monitoring and evaluating impacts 10 Fostering policy debate and feeding back into policy choice Source : World Bank (2003)
2.3.1 ASKING QUESTIONS AND IDENTIFYING STAKEHOLDERS
The first element is asking the right questions. This involves identifying the instrument(s) of change that may impact the distribution of income and/or assets. The next step is to formulate questions for analysis given the instrument(s) of change and the underlying problems that it is meant to address. The second element is identifying stakeholders . This is important because not only are stakeholders affected by policy choices, but some stakeholder groups may also influence whether or not select policies are adopted and/or how they are implemented. This is a key component in the analysis of poverty and social impacts because identifying the position of various actors is essential to understanding the behavioral responses that condition impacts and, therefore, the likelihood that the instruments of change will lead to success.
Yet, stakeholder analysis extends beyond the identification of groups and their stated or unstated interests to the nature and degree of their ability to mobilize behind a common purpose. An example would be the extent to which a segment of the population is atomized or unable to organize in order to voice their opinion in support of or against a policy. While political economy issues and social tensions of that nature can be
28 unearthed by the examination of secondary resources (e.g. news media and academic research), key informant interviews, special surveys, and focus groups may be necessary to analyze the interests and influence of special interest groups and less organized stakeholders. Other aspects of political economy examined under the rubric of stakeholder analysis may include ownership assessment, which offers an estimate of potential resistance to policy change and levels of government influence based on the asset base of the stakeholder (e.g., major landowner).
2.3.2 TRANSMISSION CHANNELS AND INSTITUTIONS
Once stakeholder analysis has been completed, the next step is to identify the channels through which policy is expected to impact each stakeholder group. As such, the third element is to gain an understanding of transmission channels. This analysis requires that hypotheses and assumptions related to anticipated impacts be explicitly stated so that they may be empirically tested via various economic and social analysis techniques. Impacts occur through five main transmission channels: employment, prices
(e.g., production, consumption, and wages), access to goods and services, transfers and taxes, and assets. Each has distinct impacts on individual stakeholder groups, which may be characterized as direct or indirect, short-term or long-term. As such, it is possible that a single stakeholder group may incur both positive and negative impacts at different points in time and/or through different transmission channels.
Institutions, as one type of stakeholder group (e.g., social or market), potentially affect the impact of policy on the welfare of different types of households and their aggregation, such as the poverty population. Therefore, assessing institutions is the fourth element of good poverty and social impact analysis. Two key areas of interest
29 may be found within this assessment: market structure and implementing agencies. The first approach is to obtain an understanding of the context-specific market structure. This requires identifying the nature of the market (e.g., monopoly) and the market structure determinants (e.g., regulation as a form of restriction to entry). Having such information in hand assists in the identification of the enabling conditions that would need to exist within the market to produce better outcomes for the poverty population.
An examination of implementing agencies consists of assessing the impacts likely to arise within government or other agencies because of the existence and implementation of the policy or reform. This may occur by way of level of responsibility or characterization of the flow of decision-making, information, or resources among organizations or revenue/expenditure categories (e.g., fiscal spending on community services). The two main data collection methods for the analysis of implementing agencies are organizational mapping and the institutional assessment tool.
2.3.3 DATA COLLECTION
The fifth element of PSIA is gathering data and information for impact assessment. This is not mutually exclusive from the previous elements, but differs by focusing directly on assessing the data needs, availability, and collection of data for discrete steps of analysis. This requires: determining desirable data, taking stock of existing data and similar analyses, coping with current data limitations, and considering how to address data limitations in the future. These tasks may be particularly arduous because PSIA is typically data intensive. Further, the characteristic of that intensity is dependent on the type of policy or reform under examination and the analytical
30 techniques employed—data collection instruments may be open- or close-ended, data type may be numeric or non-numeric, and methods of analysis may be quantitative or qualitative, data and analysis may be required for multiple time periods and/or scales of analysis (e.g., geographic), etc.
One of the major strengths of PSIA is its emphasis on multidisciplinary analysis.
Accordingly, it is suggested that the application of a mixture of qualitative and quantitative data and methods enables the researcher to “elucidate history, context, process, and identification of transmission channels and differential impacts” (World
Bank 2003: 16). As such, the most desirable data for PSIA allow the mixing of quantitative and qualitative methods because doing so leverages the benefits of both and allows for the validation of results through triangulation.
Data-related stock taking requires investigating data availability, considering form
(e.g., electronic), location (available on the Internet), content (completeness, unit of measurement, etc.), cost (is purchase required?), and validity. An associated step is determining the capabilities of local agencies and ascertaining their assistance. Where data limitations exist, a decision must be made to either adapt the analysis to existing data or engage in primary data collection to fill critical gaps. In most instances, decisions will be guided by the time and resources (e.g., money) at the researcher’s disposal, in addition to economic and political pressure for action where present. If analysis must be completed without adequate or the most appropriate data, then steps should be offered to improve upon that information in the future.
31 2.3.4 ANALYZING IMPACTS
The sixth element is analyzing impacts. Beginning with general considerations with respect to choosing approaches to the analysis of poverty and social impacts, it is important to consider the relevance of indirect and induced impacts, data availability, time constraints, and capacity. First, if the instruments of change are expected to transmit through multiple channels and there is a significant potential for multiplier effects, then the choice of analytical method(s) should reflect the need to capture such impacts.
Second, data availability, time constraints, and other issues of capacity that may constrain the research process, as discussed in the previous section, must be factored into the analytical design.
In so doing, it should be kept in mind that a goal of PSIA is to improve engagement with research designs that reflect the complexity of the phenomenon under study. Therefore, an objective in the selection process should be to produce information that enhances the decision-making and evaluation capacity for policymakers, local practitioners, and other users, over that which is typically available. For instance, where econometric modeling is traditionally used, various forms of social impact assessment can be integrated into that analysis by helping to define hypotheses, model parameters, and explanatory variables. One technique for doing so is referred to by World Bank analysts as participatory econometrics.
According to the rubric of participatory econometrics, the researcher collects and analyzes his/her own data, goes into the field with an open mind, allows the study population to participate in the research, and actively integrates qualitative and
32 quantitative findings (Rao 2002). Thus, the typical participatory econometric research process consists of (Rao 2003):
1) Conducting focus groups and interviews to gain a participatory understanding of issues; 2) Constructing a survey instrument that integrates understandings from the field; 3) Deriving hypotheses from qualitative work and testing those hypotheses with survey data; 4) Enhancing qualitative findings with quantitative analysis using iterative or Bayesian methods, and; 5) Returning to the field to validate research findings.
There are several benefits. First, research hypotheses are grounded in the reality of the poor. In addition, functional forms and causal connections are located and understood through the eyes of the research participants, which helps with identifying and comprehending the nature of measurement error. Most importantly, context is taken into full consideration, including factors and functions of social, cultural, political, economic, and psychological systems.
However, a multitude of individual social and economic tools are utilized with
PSIA. Among the most common analytical approaches are direct impact analysis (DIA), behavioral analysis, and equilibrium modeling. DIA is a measure of change that assumes no behavioral response from affected groups. It includes SIA, simple incidence analysis, and poverty mapping, which have been used to study impacts of government subsidies
(Marcus 2002), poverty trends and growth performance (Mujeri 2000), and income as a poverty indicator (Laderchi 1997). Behavioral analysis extends DIA to include behavioral responses of households and economic agents. Methods include participatory poverty assessments, SIA, behavioral incidence analysis, and social capital assessment, which have been used to examine housing and deprivation (Evans and Hance 1998),
33 gender and poverty (Whitehead and Lockwood 1999), and reduction strategies (World
Bank 2000).
Finally, equilibrium models (partial and general) are useful in analyzing policy that has high feedback effects and provide a rich measure of impacts when integrated with other analyses. They include multi-market models, reduced form techniques, social accounting matrices, and input-output analysis. In relation to poverty, they have been used to study responses to rising prices (Nagvi and Akbar 2000), impacts of natural resource use (Greeley 1987), and effects of microeconomic reform (Akinboade 1998).
2.3.5 ENHANCEMENT, RISK, AND EVALUATION
PSIA is undertaken in part as an informational means of assisting in the maximization of welfare gains for vulnerable groups from policy reform, particularly with respect to compensation mechanisms. Thus, element seven is contemplating enhancement and compensation measures. In short, the analytical work produced by
PSIA can provide options in finding and setting the appropriate solutions for poverty reduction, and possibly, economic development in conjunction. This may involve considering alternative designs that may enhance or replace existing policy and its implementation and evaluation, the basis on which decisions regarding compensation measures are made, and the delay or suspension of instruments of change as suggested by differences in short- and long-term benefits.
Element eight is assessing risk , which aims to examine the potential risk underlying the assumptions of the analysis that might otherwise go unrecognized. Four types of risk are generally considered in PSIA: (1) Institutional risk—incorrect assumptions made about institutional performance. (2) Political economy risk—where
34 powerful stakeholder groups undermine policy objectives. (3) Exogenous risk—shocks to the external environment, which impact the vulnerability levels of the poor, such a regional economic crisis. (4) Other country risk—threat of political instability or increased social tensions.
Three main methods exist for conducting risk analysis: risk assessment, sensitivity analysis, and scenario analysis. Risk assessment systematically identifies risk, including risks associated with the sociopolitical and institutional context or behavioral responses that have the potential to undermine the policy under consideration. Sensitivity analysis is typically applied when quantitative economic models have been used in the impact analysis, whereby variations in the magnitude of model parameters are tested with respect to their sensitivity to the model’s outcomes. Scenario analysis considers differences in policy impacts based on scenarios composed of the social, economic, political, cultural, and technological outcomes that drive change.
Element nine consists of monitoring and evaluating impacts. Monitoring specifically involves the tracking of the progress of an instrument of change, as measured by indicators of inputs, outputs, and outcomes. Evaluation, on the other hand, consists of the analysis of changes in those indicators. This includes determining what has contributed to changes in outcomes for various stakeholders (e.g., households and institutions). One way to achieve this is to choose a select set of indicators, making assumptions explicit and tracing those indicators through transmission channels.
35
2.3.6 FOSTERING POLICY DEBATE
A critical aspect of PSIA is that efforts are taken to ensure that lessons learned from the analysis actually inform and affect public policy. Therefore, the tenth and final element is fostering policy debate and feeding back into policy choice. One way to achieve this is to disseminate the variety and depth of information uncovered in conducting the research, as well as the results of the analysis, to the public and to key stakeholders in particular. This can be taken a step further by organizing a policy forum in which insights can be gained through the discussion of policy impacts. Convening such forums, however, comes with risks, particularly where conflicting interests among stakeholders may produce open hostility. Another risk is that with the sharing of information, stakeholders make the assumption that constructive debate automatically feeds into reform. Therefore, if PSIA is to feed back into policy choice in the context of forum or other means of discussion, issues of social accountability and integration into existing political processes must also be entertained.
2.4 RESEARCH PROCESS
In this section the research process is illustrated as actually undertaken in applying the PSIA framework and realist methodology to the Tunica case. Figure 2.2 offers an affinity diagram of those constructs as a means to guide the discussion and to help maintain the emphasis on the methodological component in the research design. It should be noted, however, that the linear diagram is a representation of reduced-form; as such it fails to capture the critical nuances and iterative aspects of each process.
36 Figure 2.2 Affinity Diagram of Methodological Processes
Realist PSIA Research Methodology Framework Process
Literature Asking Exploratory Review Questions Research
Immanent Identifying Purposive Critique Stakeholders Investigation
Reconcept- Transmission Critical ualization Channels Analysis
Assessing Applied Theory Abstraction Institutions
Empirical Data Participatory Validation Collection Research
Extensive / Analyzing Derivation of Intensive Impacts Hypotheses
Compensation, Confirmatory Triangulation Risk, Evaluation Analysis
Grounded Fostering Policy Validate Theory Debate Findings
2.4.1 RESEARCH CHRONOLOGY
The study began in spring 2000 with an exploratory site visit. 7 The research consisted mainly of observation and purposive conversations related to locational aspects of casino development and the employment and housing conditions of the poverty population. This immediately brought to mind a number of questions regarding the distribution of the benefits of economic growth associated with the gaming industry,
7 The PSIA framework was still under development by the World Bank at that time and would not reach formal completion until 2003 (an ongoing methodological development process). I became aware of it in
37 potential negative consequences, and whether or not the perspective of the poor was being represented with respect to decision-making processes and impact assessments associated with economic and community development.
The site visit was followed by further exploration into those topics through a review of literature on our understanding of poverty and in relation to common policy prescriptions, focusing on economic development. Also examined was the literature on casino gaming, including the manner in which it is understood as an economic development and/or growth strategy, potential economic and social outcomes and their relation to poverty alleviation, as well as the means by which those outcomes are typically measured and interpreted. In conjunction, completed impact analyses of the
Tunica case as well as others in the United States where commercial casino gaming had recently been adopted were sought and reviewed. This was useful for identifying theoretical, empirical, methodological, and analytical gaps in the literature.
That work was followed by a purposive site visit in summer 2001. Informal interviews and content analysis were conducted. 8 The interviews were mainly with community leaders and institutional representatives, among whom were those typically quoted in popular media reports and academic research on the historical development of
Tunica’s gaming industry and its impacts. This research, together with other information gathered thus far in the study, facilitated a critical analysis of message content in written and verbal forms and aided in the process of identifying stakeholders, understanding
2001 and immediately began to apply the constructs of PSIA to my work on poverty issues in Tunica and elsewhere. As such, my research has evolved conjointly with the methodology. 8 I make a distinction here between informal and formal content analysis. Many forms of analysis involve the examination of message content, both qualitative and quantitative, that are loosely referred to as content analysis in the social science literature. There is also an explicit, systematic and quantitative technique that is known as content analysis in both the social and natural sciences. I refer to the former as informal
38 transmission channels, assessing institutions, and constructing a historical basis for social and economic conditions in Tunica and the surrounding area.9
Thus, along the lines of the realist method of abstraction, given the social reproduction of knowledge and immanent critique, I began to reconstruct causal mechanisms and their historical and contextual realization. This was aided by adopting a more concrete theorization of the objects of investigation (e.g., social, cultural, economic, and political processes), which involved the engagement of a social and political model of Porter’s (1990) theoretical framework of competitive advantage. This is a key aspect of the research process and therefore commands a bit more explanation in relation to the realist method of abstraction.
2.4.1.1 ABSTRACTION REVISITED
Going back to the discussion on abstraction, in short, the purpose of this aspect of the study is to ‘abstract’ attributes and relationships from certain conditions or ‘concrete’ phenomena in order to determine which attributes and relationships have a significant causal effect and which do not. A ‘concrete object’ represents the whole, the unity of diverse elements or forces (if significantly causal). An ‘abstract object’ is a partial aspect of a concrete object that has been isolated for the sake of empirical examination.
content analysis and the latter as formal content analysis. For further explanation of the difference, see Neuendorf (2002), for example. 9 In one manner or another, I employed all of the ten key elements of PSIA in my research. Yet, given the variety of tools used and the degree to which detailed explanation would detract from the focus on process, I only elaborate further on stakeholder analysis. I do so because I found it to be one of the most critical aspects of my research process. That elaboration on stakeholder analysis can be found in Appendix B. For detailed information on other tools used in this research and elsewhere in the application of PSIA to developing nations, see World Bank (2003) or visit the PSIA website at www.worldbank.org. .
39 Although concrete objects are real, they are not likewise reducible to the empirical and therefore our concepts of them on the outset may be superficial or chaotic (Sayer 1992).
This ‘chaotic conception’ may lead to bad abstractions, such as those based on unnecessary relationships or inappropriate divisibility of those relationships to the point that they are not recognizable. In order to avoid this, a realist necessarily invokes a theorization of the objects of investigation and incorporates a reflection of it into the research process (Yeung 1997). From there, the process of abstraction continues until
‘theoretical saturation’ is reached. At this point, abstraction no longer adds to theoretical rigor and empirical evidence is strong enough to support postulated causal mechanisms.
The aforementioned theoretical framework of competitive advantage represented such a reflection in this case, critical analysis facilitated and informed the process of abstraction, and the continued research process served as the vehicle for empirical validation.
2.4.1.2 DATA COLLECTION AND ANALYZING IMPACTS
The methodological framework that forms the basis of this study calls for both extensive and intensive research. The defining characteristics are given in Table 2.2.
Both intensive and extensive research methods were used throughout the research process, but it was not until this point in my actual research process that I made a clear distinction between the two. On the one hand, I engaged in extensive research in order to understand the impacts of casino development for the Tunica area population on the whole (e.g., defining characteristics, common patterns, etc.). Data collected were mainly secondary, derived from national, private, and local sources (e.g., Census Bureau, MIG, and Tunica County Tax Assessor’s Office) and deduction of impacts stemmed from
40 standard economic impact methods (e.g., input-output and shift share analysis). On the other hand, I engaged in intensive research based on the need to better understand the actualities of the lived experience of the poor and their perspective of the ‘miracle.’ I did so by utilizing participatory econometrics. That approach was chosen because it not only offered a viable means for obtaining the perspectives of the poor with respect to outcomes, but also for discovering new hypotheses (i.e., tendencies) with regard to the causal mechanisms of those outcomes.
Thus, the next step in the field work-related aspect of the research process was the application of participatory econometrics. Accordingly, another site visit was conducted
(fall 2002) to gain access to the poverty population and begin/plan the facilitation of participatory research. This involved meeting with community gatekeepers (advocates for the poverty population), who introduced me to key informants (members of the poverty community), and who together helped to confirm the logic/purpose of the research, the structure of the research questions, and the data collection methods. They were also instrumental in identifying information-rich stakeholders (i.e., those to target for interviews and participation in focus groups) and the overall planning of the implementation process.
41 Table 2.2 Defining Characteristics of Intensive and Extensive Research
Characteristic: INTENSIVE EXTENSIVE
How does a process work in a What are the regularities, common particular case or small number of patterns, distinguishing features of Research question cases? What produces a certain a population? How widely are change? What did the agents actually certain characteristics or processes do? distributed or represented?
Relations Substantial relations of connection Formal relations of similarity
Type of groups studied Causal groups Taxonomic groups
Causal explanation of the production Descriptive 'representative' Type of account of certain objects or events, although generalizations, lacking in produced not necessarily representative ones explanatory penetration
Large-scale survey of population Study of individual agents in their or representative sample, formal Typical methods causal contexts, interactive interviews, questionnaires, standardized ethnography--qualitative analysis interviews--statistical analysis
Although representative of a Actual concrete patterns and whole population, they are contingent relations are unlikely to be unlikely generalizable to other representative, average, or populations at different times and Limitations generalizable--necessary relations places--problem of ecological discovered will exist wherever their fallacy in making inferences about relations are present individuals--limited explanatory power
Appropriate tests Corroboration Replication
Source: Adapted from Sayer (1992), p. 30.
The next round of field research took place during spring 2003, at which time a number of data collection techniques were employed, including informal and formal interviews, direct observation, transect walks, projective techniques, focus groups, and a community survey. This information was used to derive hypotheses about the causal processes of casino gaming impacts and distributional effects on the poverty population
42 (e.g., the role of moral concerns in determining employment outcomes), which would be tested with survey data. The survey is the primary research component of participatory econometrics. I will elaborate on this process further.
The need for and focus of the survey was based on understandings gained from the field relating to discoveries made during the prior participatory steps in the research process. Most of those ‘understandings’ match up with those derived from the literature, but center mainly on issues of access and perception of outcomes, particularly with respect to the conflict between the impacts on societal well-being versus that of the individual. Accordingly, the survey design was purposive with the objective of gaining insight into the poverty population’s perceptions of indicators of distributional outcomes, particularly with respect to subjective well-being. As such, it is important to acknowledge the definitional difficulties of well-being and to make clear the meaning of subjective well-being with respect to this study.
2.4.1.2.1 SUBJECTIVE WELL-BEING
The terms subjective well-being and quality of life are often used interchangeably, yet both are elusive in that there is no standard definition for either concept. However, quality of life is often measured and referred to as consisting of both objective and subjective components (e.g., Diener and Suh 1997). Those components commonly include aspects of health, social and family relationships, emotional and material well- being, and participation in work and community (e.g., Cummins 1996). Therefore, the term quality of life may be expressed as an all-encompassing concept of well-being that moves beyond the economistic view of income-based standards of livelihood assessment.
43 Accordingly, the concept of well-being is generally associated with similar aspects of life
(e.g., Andrews and Withey 1976; Easterlin 2001), using both objective and subjective measures, but is more typically understood as the conditions that enable one to function optimally in all areas of life and thereby sustain a certain level of quality of life.
Those conditions may include feelings of satisfaction with one’s life overall or the subjective assessment of specific circumstances (Diener 2000), whether or not those circumstances are clearly elements of personal well-being. That is, objectively, some circumstances may have a direct impact on individual quality of life while others may directly affect social quality of life. Yet, subjectively, both have the potential to impact upon personal well-being depending upon the manner in which one self-identifies as a member of society (Rholes and Bailey 1999). For instance, where economic development is concerned, an individual may not derive direct benefit from that development if they are not involved in that economic activity firsthand (e.g., employment), but as that development impacts upon the quality or sustainability of the society in which the individual lives, they may derive some value that contributes to their subjective well-being based on their perception of what constitutes a good society and their membership within it.
Thus, given the complexity of definition, for the purposes of this study, well- being is broadly understood as one of many domains of quality of life and subjective well-being is one of many multi-dimensional factors within that domain. For example, religious or spiritual well-being may be thought of as a distinct dimension of subjective well-being (Moberg 1979). Yet, in order to make the proposed linkages, the critical question is: Does religion contribute significantly to other factors of well-being and/or
44 serve as a conditioning aspect of quality of life? Prior research supports the latter by suggesting that individuals with high levels of intrinsic faith (spirituality) or formal involvement with religious groups express a greater degree of satisfaction with the quality of their life (Petersen and Roy 1985). Further, in support of the former, depending on how religiosity is measured, there is evidence to suggest that religious faith and practice are positively associated with physical and mental well-being (Ferraro and
Albrecht-Jensen 1991). A similar line of inquiry is followed in a later chapter, where subjective measures of casino impacts and their association with religion are the focus.
2.4.1.2.2 SURVEY DESIGN AND ADMINISTRATION
The target population consisted of residents from two poverty enclaves in the
Tunica County labor market—one within the county and one without, the first ten miles from the casinos and the second approximately thirty-five miles away. Both communities share a similar history (politically, culturally, and economically), including designation as the most abject within the region where poverty and policy are concerned.
For residents of each, there is little opportunity to work outside of the casinos. The two communities were selected for those reasons as well as the opportunity that selection affords in terms of doing comparative analysis. One point of examination was those who may potentially benefit from both jobs and tax revenues (e.g., investment in community services) as opposed to those whose benefit may only be employment related. The survey instrument was comprised of detailed questions pertaining to gaming industry impacts on six subjective domains (i.e., environments), including living, financial, work, community/social, health/nutritional, and attitudes/beliefs. The structure of the questions
45 was variable (e.g., open-ended, scalar, etc.), aimed at collecting quantitative and qualitative data of both an objective and subjective type, but predominantly the latter.
Thus, the survey format was sensitive in nature and targeted toward a somewhat hidden population whose socio-cultural history left them protected in terms of their willingness to provide candid responses. Accordingly, community gatekeepers and key informants participated in conducting the survey door-to-door and individuals were told that the information that they provided would not be used in any way in conjunction with their names or place of residence. In both communities there was a high level of cooperation and interest in the research—although many were skeptical at first, fearing that the research was in some way affiliated with the casinos or community leaders and that there might be repercussions for not providing the correct answers, such as the loss of a casino job or community support services for citing negative impacts. Once they were reassured by the gatekeeper or key informant, they provided seemingly open and honest responses and offered thanks for considering their opinion, noting that they had typically been ignored throughout the casino development process.
Altogether, 240 responses were obtained, representing 33.4 percent of the survey population (i.e., two-community poverty population age 18 to 64).10 However, few questionnaires were answered in full. This was the case mainly because the survey was difficult for some due to the fact that many of the respondents lacked the skills necessary to complete the survey on their own (i.e., some could not read or write). 11 Thus, in some
10 The number of respondents is within the minimum sample size for small populations given a 95 percent level of confidence and a 5.25% margin of error, following Rea and Parker (1997: 120). 11 The survey pilot indicated that it should take respondents up to 30 minutes to complete the questionnaire. This was based on a 7 th to 8 th grade reading level, which seemed appropriate during the instrument design process. However, during implementation it was discovered that the literacy level of the survey population was far worse than that indicated by secondary data sources or local informants—a 4 th to 5th grade reading level would have been more appropriate.
46 instances, surveys were left with family members who would help with survey completion over the course of several days and completed surveys would be picked up or delivered to the community gatekeeper or key informant by a family member. This process introduced the potential for many forms of bias, but it was deemed necessary in order to access and glean insight from typically marginalized individuals within the study community.
2.4.1.3 MAKING SENSE OF IT ALL
The data and analysis from both extensive and intensive research were combined in order to gain as holistic a measure of impacts as possible. Evaluation of impacts was conducted on the basis of data triangulation (e.g., time, place, level) and topic area (e.g., impacts of growth, poverty impacts) determined in conjunction with the original study objectives and research questions, as well as by those that emerged during the research process. With respect to the latter, econometric analysis was conducted as a means to confirm and enhance qualitative findings and further empirically validate particular concepts and relationships theorized during the process of abstraction, such as those associated with alternative ways for measuring or viewing outcomes and the assessment of risk from the standpoint of political economy. Specifically, scenario analysis was completed in order to analyze the interplay of poverty, religion, and economy.
The final step in the research process was to seek further validation of findings by sharing the results of the study with research participants and academic researchers who are in a position to judge or inform the research based on methodological or subject expertise. This was the purpose of the final field visit, which took place during the
47 summer of 2004. At that time, results were shared and discussed with key informants and community gatekeepers and a presentation was made to faculty and graduate students of the Sociology and Anthropology Department at the University of Mississippi.
2.5 CHAPTER SUMMARY
The process of conducting poverty and social impact analysis poses many challenges. The comprehensive data necessary to conduct analysis may not be readily available or collectible. Analytical constraints exist on a number of fronts, including difficulties in: assessing both macro- and micro-economic instruments of change and impacts, capturing the complexity of context-specific relationships with respect to time and behavior (e.g., household, institutional, market), identifying inter-temporal impacts
(i.e., short-term and long-term), rigorously assessing differences in outcomes based on the instrument of change versus other factors, and addressing these challenges given the analytical tools available.
It also poses challenges in terms of methodological transparency and the reporting of the findings given the fact that, for example, the research design and theoretical basis are emergent processes. Accordingly, the researcher simultaneously operates in a deductive-inductive research framework, seeking both conceptual understanding and verification, and gaining knowledge via a cumulative and iterative process. In so doing, the realist challenges conceptions of empirical causation and scientific methodology
(Sayer 1992). Thus, naturally it is impossible to offer explanation in a linear or cause and effect format, such as by stating that “I did this (method x), which produced this information (outcome y), which led me to conclude that (result z).” Yet, from the realist
48 perspective, knowledge cannot be evaluated independently of its production or use
(Bhaskar 1979); therefore, the realist has a responsibility to offer explanations of both. In this chapter I attempted the former and in the remainder of this document I seek to do the latter.
2.5.1 CHAPTER OUTLINE
The first step toward PSIA requires investigation of alternative views of poverty and the relationship between poverty and policy or other factors of change, which in this case is economic growth related to casino development. That is, one must have some initial understanding of poverty causes, conditions, policy prescriptions, and outcomes with which to ground the analysis. In accordance, chapter 3 offers a general framework of poverty, economy, and policy. Then I present an overview of existing research into the impacts of casinos as a form of economic development, such that an understanding of expected outcomes and related hypotheses emerge (chapter 4).
Next I launch into the case study, beginning with a historical analysis of poverty and economy in Tunica. Thus, in chapter 5 the historical framework is laid out, within which an economic rationale for poverty is considered in conjunction with social, cultural, and political factors of underdevelopment, deprivation, and inequality. Chapter
6 delves deeper into the broader economic and political context of casino development and draws parallels to the situation in Mississippi while also unearthing the specific conditions under which the establishment of the casino industry took place in Tunica. I then move to an analysis of the impacts of that development at various geographic scales
(e.g., county, community/neighborhood, household) and across different strata of the
49 social and economic environment (e.g., landed-elite, local businesses, etc.), eventually focusing on the poverty population (chapters 7-9).
In chapter 10, I tie aspects of each of the prior chapters together by focusing on religion and its relationship to employment in the casinos for the poverty population as well as their subjective assessment of the casinos’ impact on various strands of well- being. Finally, in chapter 11, I draw conclusions about the poverty outcome in Tunica and what we learn from the Tunica case with respect to re-conceptualizing how we think about poverty determinants and means for alleviation. In so doing, I identify the risks associated with assumptions about the relationship between economic growth and poverty reduction. These include assumptions about the behaviors of agents and institutions, the channels through which growth and poverty are transmitted, and the manner in which we can analyze these things to better inform economic development policy.
2.6 CHAPTER REFERENCES
Akinboade, O. 1998. Macroeconomic Reform and the Poor in the Gambia: A Computable General Equilibrium Analysis. Canadian Journal of Development Studies. 19(1): 133-151.
Andrews, F. and S. Withey. 1976. Social Indicators of Well-Being. New York: Plenum.
Barrow, C. 2000. Social Impact Assessment: An Introduction. London: Arnold.
Bhaskar, R. 1979. The Possibility of Naturalism: A Critique of the Contemporary Human Sciences . Atlantic Highlands NJ: Humanities Press.
Cantor, L., S. Athinston, and F. Leistritz. 1985. Impact of Growth: A Guide for Socioeconomic Impact Assessment and Planning. Chelsea MI: Lewis Publishers.
Carley, M. and E. Bustelo. 1984. Social Impact Assessment and Monitoring: A Guide to the Literature. Boulder: Westview Press.
50 Clark, E. and A. Soulsby. 1998. Organization-Community Embeddedness: The Social Impact of Enterprise Restructuring in the Post-Communist Czech Republic. Human Relations. 51(1): 25-50.
Comprehensive Plan, Tunica County, Mississippi. 2002 October. Tunica: Allen and Hoshall.
Crook, A. and M. Moroney. 1995. Housing Associations, Private Finance and Risk Avoidance: The Impact on Urban Renewal and Inner Cities. Environment and Planning A. 27(11): 1695-1712.
Cummins, R. 1996. The Domains of Life Satisfaction: An Attempt to Order Chaos. Social Indicators Research. 38: 303-328.
Davis, H. 1990. Regional Economic Impact Analysis and Project Evaluation. Vancouver: UBC Press.
Detroit News . 1999 16 April. Casinos Transform Poorest County: Mississippi Delta Area Was Once Called America’s Ethiopia. Accessed 02/17/01.
Diener, E. 2000. Subjective Well-Being. American Psychologist. 55(1): 34-35.
Diener, E. and E. Suh. 1997. Measuring Quality of Life: Economic, Social, and Subjective Indicators. Social Indicators Research. 40: 189-216.
Easterlin, R. 2001. Subjective Well-being and Economic Analysis: A Brief Introduction. Journal of Economic Behavior and Organization. 45: 225-226.
Evans, R. and M. Hance, eds. 1998. Legalized Gambling For and Against. Chicago: Open Court.
Farrigan, T. 1999. FIT-4-NH: A Fiscal Impact Tool for New Hampshire Communities. Master’s Thesis. Durham NH: University of New Hampshire.
Ferraro, K. and C. Albrecht-Jensen. 1991. Does Religion Influence Adult Health? Journal of the Scientific Study of Religion. 30: 193-202.
Finsterbusch, K., J. Ingersoll, and L. Llewellyn. 1990. Methods for Social Analysis in Developing Countries. San Francisco: Westview Press.
Grady, S., et al. 1987. Socioeconomic Assessment of Plant Closure: Three Case Studies of Large Manufacturing Facilities. Environmental Impact Assessment Review. 7(2): 151-165.
51 Greeley, M. 1987. Energy and Agriculture: Interactions and Impact on Poverty. Institute of Development Studies Bulletin. 18(1): 47-54.
Laderchi, C. 1997. Poverty and Its Many Dimensions: The Role of Income as an Indicator. Oxford Development Studies. 25(3): 345-360.
Levine, A. 1983. Psycho-social impact of Toxic Chemical Waste Dumps. Environmental Health Perspectives. 48(February): 15-17.
Marcus, R. 2002. Social Funds as Instruments for Reducing Childhood Poverty: Lessons from Save the Children’s Experience. Journal of International Development. 14(5): 653-666.
McDonald, G. 1990. Regional Economic and Social Impact Assessment. Environmental Impact Assessment Review. 10(1-2): 25-36.
Meyer-Arendt, K. 1998. From the River to the Sea: Casino Gambling in Mississippi. In K. Meyer-Arendt and R. Hartmann, eds. Casino Gambling in America: Origins, Trends, and Impacts. New York: Cognizant Communication Corporation.
Moberg, D., ed. 1979. Spiritual Well-Being. Washington DC: University Press of America.
Mujeri, K. 2000. Poverty Trends and Growth Performance: Some Issues in Bangladesh. Pakistan Development Review. 39(4) Pt.2: 1171-1191.
Nagvi, Z. and M. Akbar. 2000. How do the Poor Respond to Rising Prices? Pakistan Development Review. 39(4) pt.2: 827-842.
Neuendorf, K. 2002. The Content Analysis Guidebook. Thousand Oaks: Sage Publications.
Peterson, L. and A. Roy. 1985. Religiosity, Anxiety, and Meaning and Purpose. Review of Religious Research. 27: 49.
Porter, M. 1990. Competitive Advantage of Nations. New York: The Free Press.
Rao, V. 2002 May 18. Experiments in “Participatory Econometrics”: Improving the Connection Between Economic Analysis and the Real World. Economic and Political Weekly. May 18. Available Online at
Rao, V. 2003. Experiments with “Participatory Econometrics” in India: Can Conversation Take the Con Out of Econometrics? In R. Kanbur, ed. Q-Squared: Combining Qualitative and Quantitative Methods in Poverty Appraisal. New Delhi: Permanent Black.
52 Rea, L. and R. Parker. 1997. Designing and Conducting Survey Research: A Comprehensive Guide. San Francisco: Jossey-Bass Publishers.
Rholes, W. and S. Bailey. 1999. The Effects of Level of Moral Reasoning on Consistency Between Moral Attitudes and Related Behaviors. Social Cognition. 2(1): 32-48.
Rickson, R., J. Western, and R. Burge. 1990. Social Impact Assessment: Knowledge and Development. Environmental Impact Assessment Review. 10: 1-10.
Rossini, F. and A. Porter, eds. 1983. Integrated Impact Assessment. Boulder: Westview Press.
Salter, S. 2003. Medicaid: The Wedge Issue. The Clarion Ledger. April 27. Available online at
Sayer, A. 1992. Method in Social Science: A Realist Approach. 2 nd ed. London: Routledge.
Snyder, J. 1999 September. The Effects of Casino Gaming on Tunica County, Mississippi: A Case Study 1992-1997. Mississippi State University Social Science Research Center.
Tunica Convention and Visitor’s Bureau (TCVB). 2002. Tunica Mississippi10 Years: The Tunica Miracle, The Economic Impact of Gaming and Tourism 1992-2002. Tunica MS: Tunica Convention and Visitor’s Bureau.
Tunica County Museum (TCM). 2003 March. Civil Rights in Tunica, Education in Tunica County, The Story of the Tunica County Casinos, and Sugar Ditch. Permanent exhibits. Tunica County, Mississippi.
US Bureau of Economic Analysis (BEA). 2002. U.S. Department of Commerce. Regional Accounts Data.
US Bureau of Labor Statistics (BLS). 2002. U.S. Department of Labor. Local Area Unemployment Statistics.
US Census Bureau. 1993 August. Statistical Brief: Poverty in the United States— Changes Between the Censuses. SB/93-15. Accessed 10/03/02.
US Census Bureau. 2001 December. Small Area Income and Poverty Estimates. Tables for States and Counties by Income Year and Statistic.
53
U.S. Congress. 1988a. A Bill to Establish the Lower Mississippi Delta Development Commission. Joint Hearing Before the Committees on Environment and Public Works and Small Business. Senate, 100 th Congress, 2 nd Session, June 28 th . Washington DC: U.S. Government Printing Office.
U.S. Congress. 1988b. A Bill to Establish the Lower Mississippi Delta Development Commission. Hearing Before the Subcommittee on Economic Stabilization of the Committee on Banking, Finance, and Urban Affairs. House of Representatives, 100 th Congress, 2 nd Session, June 28 th . Washington DC: U.S. Government Printing Office.
Whitehead, A. and M. Lockwood. 1999. Gendering Poverty: A Review of Six World Bank African Poverty Assessments. Development and Change. 30(3): 525-555.
World Bank. 2000. World Development Report 2000/2001: Attacking Poverty .
World Bank. 2002 April (draft). A User’s Guide to Poverty and Social Impact Analysis. Poverty Reduction Group (PRMPR) and Social Development Department (SDV).
World Bank. 2003. A User’s Guide to Poverty and Social Impact Analysis. Poverty Reduction Group (PRMPR) and Social Development Department (SDV). Washington DC: World Bank.
Yeung, H. 1997. Critical Realism and Realist Research in Human Geography: A Method or a Philosophy in Search of a Method. Progress in Human Geography. 21(1): 51-74.
54 CHAPTER 3
POVERTY, ECONOMY, AND POLICY
[The] encompassing image of poverty… is poverty of opportunity… Poverty of income is often the result, poverty of opportunity is often the cause. (UNDP 1999: 6)
During the 1990s the U.S. economy underwent enormous growth. For the most part, those regions of the country that had the greatest growth were also those that had the most rapid and extensive reductions in poverty. However, even in those places, poverty persists. This relentlessness of poverty in the face of economic growth, past and present, has generated debate about its causes and appropriate policy responses. The economics of poverty is central to this debate because although physiological and psychological causes and effects are widely recognized, poverty is predominantly viewed as an economic phenomenon (Yapa 1996).
In this chapter I provide an overview of the dominant discourses on persistent poverty and proceed with a review of the major theoretical approaches that aim to describe the causes of poverty with a particular focus on their economic attributes. In so doing, I introduce the issues that are typically raised in policy debates on poverty reduction efforts and abstract from that the gaps in the research––that which remains unanswered or ill-addressed when seeking to know: What is poverty? Why does it exist?
Where does the evidence come from? How do policy makers approach the problem?
What is it about space that makes a difference?
55 3.1 POVERTY DISCOURSE
Duncan (1992) argued that stereotypes are obstacles to overcoming poverty’s persistence. They are embedded in metaphors and other language that defines pathways for knowledge and help exclude serious examination of contentious growth discourses
(Wilson, D. 1996), such as the “undeserving poor” (Katz 1989). Other examples include:
Vicious circle of poverty—behaviors like poor work habits, weak or deviant family organization, weak labor force attachment, and substance abuse, manifest as patterns of consequence or adaptation to poverty (Ropers 1991; Waxman 1983); Culture of poverty—the previous behaviors are ingrained in the values, morals, and lifestyle of a subset of society and passed on through acculturation and socialization (Banfield 1970; Lewis 1968); and, Urban underclass—viewed as economic, behavioral, and spatial, where members are poor with manifest behaviors and live in high poverty areas characterized by the cultural transmission of poverty (Auletta 1982; Besharov 1996; Wilson 1987).
Speaking to that cultural perspective, with respect to persistent poverty in the Natchez region of Mississippi, Davis (2001: 4) conceded that:
[t]he cultural argument, after all, might imply the possibility of escape for the individual who could rise above debilitating group trappings; the biological carried a life sentence without possibility of release. The seemingly benign nature of the cultural argument, however, made it that much more insidious. There was in fact no escape.
O’Connor (2001: 244) agreed that this form of “poverty knowledge” is the basis of the emphasis on “dependency, illegitimacy, and intergenerational transmission as growth areas for research and reform,” thus ignoring limited opportunity structure as poverty’s primary causes (Lichter and McLaughlin 1995; Tickamyer and Duncan 1990).
Rejecting the polarization of cultural and structural perspectives, Fitchen (1981) found that where limited opportunity structure and the experience of poverty results in a lack of work motivation, motivation becomes a derivative cause of poverty and thereby
56 adds to its persistence. As such, culture emerges as a legitimate cause of poverty where the memory of a limited opportunity structure and its psychological effect (Allen 1970), rather than or in addition to the lived experience (Woods 1975), becomes intergenerational (e.g., Gutkind 1986). This cycle can predestine life in poverty for some, inherited through race, economic status, or parental occupation, thereby adding individual factors to persistence (Duncan 1999).
Research into the spatial context of poverty emphasizes a similar complexity in defining risk (e.g., Lyson and Falk 1993; Jargowsky 1997; Lynn and McGeary 1990).
This work suggests that not only is poverty conditioned by place, but that its correlates vary relative to location, which carries with it a history that presents unique identity spaces—such as those structured by agriculture, its links to race relations, and the social consequences of economic restructuring (e.g., Fitchen 1991; Swanson et al. 1994). This adds social relations, which are spatially structured and embedded in place (Adams et al.
2001) to the issue of persistence, such that understanding poverty requires knowledge of the ideas, attitudes, beliefs, and assumptions underlying commonly accepted and taken- for-granted social patterns (Chamberlin 1999). However, when linking the cause of poverty and potential strategies to overcome its persistence, a more theoretical, economic approach is commonly taken.
3.2 POVERTY THEORIES
Poverty theories similarly follow individual, structural, and cultural categories
(e.g., Kelso 1994), in conjunction with contextually specific concepts like inequality, geography, and social relations (e.g., Page and Simmons 2000; Smith 1987). Individual
57 perspectives center on human capital theory, where economic returns to the labor market are minimized by individualized attributes, such as residential mobility, which equalizes labor market returns across space (Berry 1967; Kale 1989). Human capital effects that differ in relation to poverty reflect variations in labor productivity that result from some measure of relative disadvantage, such as discrimination, labor market segmentation, or a background that prevents acquisition of skills (Sakamoto and Chen 1991). Status attainment views poverty as a case of low-income achievement due to personal factors that prevent competitiveness in the labor market (Blau and Duncan 1967; Hauser and
Featherman 1977).
Structural theories suggest that inequities and deprivations are grounded in economic and power structures and distributional systems that impede the poor from taking advantage of the resources available to them (Green and James 1993; Schram
1998). These constraints obstruct access to both internal (e.g., education) and external
(e.g., land) assets (Moser 1998). In the dual economy, industry bifurcation results in higher rewards for worker attributes in one market than the other (Hauser 1980). Dual labor market theory is much the same, but is in reference to occupation. The split is between the primary and secondary sector, while labor market segmentation theory extends this to race and gender (Kalleberg et al. 1982; Kreckel 1980). Spatial mismatch theory focuses on the effects of economic restructuring (Kasarda 1989), such as the loss of high-pay, low-skill jobs (Bluestone and Harrison 1982), which results in the geographic isolation of workers from emerging employment centers (Carlson and
Theodore 1997). Parallel to spatial mismatch is uneven economic development theory,
58 where industry location does not result in the same benefits everywhere. This theory is often associated with differences in wages and job security (Brown and Hirschl 1995).
Given the explanations thus far, it is understood that structural perspectives are not mutually exclusive. Rather, they are integrated and continuous with regard to both space and time (Dwight 1999). Likewise, cultural perspectives reflect individual and structural interactions by “recognizing structural antecedents to sub-cultural normative development which then shape human capital acquisition” (5). A compromise is found in the human capability concept, which considers both physiological and sociological deprivations while focusing on the expansion of opportunities (Sen 1983)—poverty is a state that revolves around a lack of opportunity derived from structural and individual constraints (Kelso 1994).
3.3 PRESCRIPTIONS FOR CHANGE
Ameliorative efforts based on the human capability concept emphasize empowerment of those experiencing poverty, facilitation of their participation in their own social realm as well as in greater society, and upward socioeconomic mobility (e.g.,
Shanmugaratnam 2001). Yet, case studies past and present point out that the operational imperatives of this all-inclusive approach are plagued by definitive issues, such as the means to and constitution of empowerment, an enabling environment, and healthy participation (e.g., Aigner et al. 1999; Kramer 1969).
Thus, ideologically, policy has embraced both individual and structural perspectives with an emphasis on individual responsibility in improving welfare position and the availability of employment opportunity as the key poverty determinant
59 (Glasmeier 2002; O’Neil 1985). That is, poverty and its correlates (e.g., inequity, vulnerability, exclusion, and underdevelopment) are directly linked to the inability of the economy to provide an adequate number of full-time jobs at the skill level of the available labor force (Kelso 1994). As such, the focus has remained on economic development geared toward opportunity structure, operating mainly through the market, with an emphasis on job training initiatives and growth in “supply of good-quality jobs”
(Tomaskovic-Devey 1987: 71).
Yet, the link between economy and persistent poverty depends on how the policy relationship is defined. The policy dilemma is that all of the causal explanations presented have at least some measurable degree of support. Further, the complexity of the poverty phenomenon as a dynamic process suggests that different contexts at various periods of time may produce disparate constraints that may (or may not) need to be addressed by alternative policies. Therefore, in order to evaluate the impacts of economic-based prescriptions for change, such as job growth, a clear understanding of the linkages between theories of causation and associated policies is necessary.
Accordingly, the remainder of this chapter presents a number of the dominant theoretical frameworks on the causes of economic poverty (Blank 2003), integrated with policy implications and research questions. This summary serves as a means of understanding the manner in which standard policy prescriptions serve as only a partial solution to a complex problem.
60 3.3.1 ECONOMIC UNDERDEVELOPMENT
Underlying much economic analysis of poverty is the presumption that poverty is produced by the absence of markets (e.g., Mate 2000). For instance, in agricultural economies the absence of an effective market translates into the lack of access to things like credit and infrastructure, all of which limit the ability of farmers to participate in long-term investment. In association, surplus labor may be due to scant opportunity for employment in other sectors that would otherwise replace or supplement farm income.
Thus, in the case of an underdeveloped market economy, “people’s talents, skills, and aspirations are frustrated and wasted, denying them the opportunity to lead productive and satisfying lives” (Tafuna’i 2002: 1).
This explanation is evoked mainly when considering the poverty of developing nations, but it has historical links to US poverty debate with respect to persistent poverty areas (e.g., US Congress 1971; US OCPD 1979), such as Appalachia, the Mississippi
Delta, and across Native American lands (e.g., Kaufman et al. 1966; President’s 1967;
US Congress 1988a, 1991). In those historically underdeveloped regions, poverty is understood to replicate itself over time because lack of economic opportunity translates into lack of individual and community resources. For instance, the fundamental building blocks for improving the situation in these places, such as access to basic standards of education and a decent physical environment in which to live, are and have consistently been lacking in large part due to insufficient funding (Moore 2001; Rural 1993).
Therefore, there is a synergy among government capacity, economic growth, and poverty reduction for which not only the presence of funds must be considered, but also the size and type of investment (Mehrotra and Delamonica 2002).
61 The proposed solution to the economic underdevelopment problem is to expand markets in poor areas, generally by way of external investment, such that those funds serve as the catalyst for economic development. The assumption is that the external funds will prompt private firms to invest in the area, bringing jobs and financial capital into the local economy, thereby supporting local entrepreneurship. This activity will also contribute to the government coffer, which will be transferred to the population through public sector investment in infrastructure and social services.
The major contention with this approach is that the ability for a place to attract external investment is based on local capacity to provide adequate infrastructure, an appropriately skilled labor force, and financial incentive (e.g., tax breaks) (Amis and
Grant 2001). Thus, the policy ends precludes the means. Another issue is that this approach implies a trickle-down effect, whereby it is assumed that economic growth will result in overall improvement in quality of life. That is, enhanced economic performance and increased welfare are mutually reinforcing (King et al. 1994). Yet, without policy setting priority to reduce disparities in the distribution of benefits, there is no guarantee that all citizens will reap the rewards of economic growth, particularly the poor (Mehrotra and Delamonica 2002).
This raises a number of questions where market expansion via external investment is pursued for the sake of economic development and poverty reduction:
To what extent is government capacity linked to the ability to obtain external investment and achieve economic development and poverty reduction in conjunction? How does external investment filter through the local economy and feedback into itself? What are the distributional impacts of economic development derived from the investment at hand?
62 3.3.2 MARKET PARTICIPATION
“[P]overty occurs because some individuals within market economies are either unprepared or unable to participate in them productively” (Blank 2003: 6). In other words, those who are not able to gain access to resources through the sale of labor or any other means are forced to survive in the absence of those resources. This inability to participate in the market can be caused by many things. Some may be unable to participate simply due to age or physical inability (e.g., children, elderly, disabled).
Others may be unable to participate because they lack the productive means to do so, such as the required labor market skills. In the latter case, participation is often achieved through low-wage, part-time work that offers limited economic gains.
Therefore, where the relationship between economic development and poverty is understood as such, the typical policy prescription is twofold: (1) Investment in education and training programs in order to increase the productive capabilities of the population; and (2) further investments in economic development aimed at increasing job opportunities, thereby reducing levels of unemployment and underemployment. As noted previously, this combined individual and structural emphasis on opportunity dominates the direction of policy in the United States.
The main problem with this approach is that it does not afford immediate poverty alleviation nor does it guarantee relief for those in dire need. For instance, for individuals whose ability to participate in the market is limited by lack of skills, there is a lag period before they are able to take advantage of employment opportunities. Further, competition for those jobs must also be considered, such as that created by employment based migration. Thus, the main questions raised by this approach are:
63 How good is the match between jobs produced and the skill level of the existing labor pool? What is the prognosis for future employment given the characteristics of educational/training investment and individual needs? Who gets the jobs (e.g. local unemployed or migrants, are they those among the poverty population)?
3.3.3 MARKET DYSFUNCTIONALITY
Within this framework, the market is inherently dysfunctional in that the creation of wealth for some results in poverty for others. A range of theoretical perspectives attempt to explain this notion. For instance, Marxists believe that capitalism is to blame, whereby those who must sell their labor in order to live are exploited in the process of production (Daly 1971; Peet 1975). Institutionalists refer to a dual labor market (Wachter et al. 1974), in which one sector holds the political and economic power necessary to obtain greater benefits and reduced vulnerability within the market, while the other sector bears the brunt of market instability for the sake of lesser compensation. In both instances (i.e., Marxian and institutionalist), with economic development, distributive conflicts exist among agents due to characteristic differences in capital/labor shares
(Alesina and Rodrik 1994).
Another perspective, found in mainstream economics, is Schumpeter’s “creative destruction,” which given the history of economic analysis (Swedberg 1991) suggests that as technological change takes place, so too does displacement and unemployment.
That is, technological change has an affect on labor demand that produces income inequities (Blackburn and Bloom 1987). For instance, when the skills of the pre-existing labor force become obsolete in the midst of change, levels of employability are reduced, increasing the potential for long-term economic hardship. Therefore, it is understood that
64 in these instances poverty is caused by the organization and structure of the economy rather than by individual factors. The policy response is to limit the market, such as by diverting or regulating external investment or by establishing protective policies (e.g., minimum wage laws). In other words, a regulated market will reduce the potential for poverty. The relative questions then are:
Who is in a position to reap the rewards of the existing and/or changing market structure? What is being done to assist those who are negatively impacted (or not impacted at all) by changes in market structure and how successful are those efforts? What is the relationship between market intervention and economic development (e.g.,. is development hindered by regulation)?
3.3.4 SOCIAL AND POLITICAL PROCESS
From this perspective the economic system is reflective of a social system (Rand
1979), such that the market serves as a vehicle for social and political processes. This includes behaviors related to such things as elitism, corruption, and discrimination that may manifest as forms of economic exclusion, such as concentrations of poverty among specific segments of the population. Therefore, in the extreme case, there is no causal link between the market and poverty. The former is merely a transmitter of social norms or disruptive forces (e.g., war).
However, it is rarely the case that the market is wholly exogenous. Rather, as
Polanyi suggested, economic life is embedded in social life whereby economic action is a form of social action and vice versa (Lazar 1996). For instance, the initial causal factor may exist external to the market (e.g., discrimination), but is reinforced and perpetuated through the functioning of the market (e.g., concentration of women in low-paying jobs), such that market structure becomes a derivative cause of the factors that reproduce
65 poverty (e.g., children of female-headed families). Given that, the policy response is typically situation specific. That is, the approach may include non-market and/or market responses, and in the case of market responses, they may be either regulatory or open market directed. Yet, efforts to redistribute income are often a part of the policy framework, generally in the form of direct subsidies to the poor.
This perspective suggests a deeper understanding of the relationship between economy and society than do the other perspectives. Therefore, the major questions posed are:
What is the nature of the political and social systems in the area of interest and how do they relate to market structure? How have political and social norms served as intervening forces of economic development (or lack there of) and poverty alleviation (or generation)?
3.3.5 INDIVIDUAL BEHAVIOR
This perspective observes poverty as the outcome of behavioral decisions made by individuals. This is based on the notion that individual attributes rather than structural forces (e.g., economic, social, political, etc.), which are outside their control, are to blame for the situation in which the poor find themselves. Hence, from this viewpoint, the poor are active agents in the limiting of access to economic resources, thereby increasing their own poverty potential. This is true of those who choose low-income life-styles, such as
“beach bums” or members of select religions, which is typically acceptable behavior in
American society.
However, it is often the case that behavior-based poverty is seen in a negative light, associated with deviance such as substance abuse and promiscuity. These activities are embodied in some theories of persistent poverty (e.g., culture of poverty), particularly
66 with respect to intergenerational poverty, whereby children who observe such behaviors are expected to engage in similar activities. This perspective suggests that poverty is the result of learned behavior. As such, the logical policy response is to encourage those individuals to behave differently. Accordingly, the market is seen as an exogenous factor and therefore economic development does not come under policy consideration. Also, investments in poverty alleviation activities are not recommended, as they are more likely than not to support dysfunctional behaviors. Instead, the policy orientation typically involves the funding of support and policing activities, such as rehabilitation programs and criminal sanctions.
More common, however, is the idea that dysfunctional behaviors are emergent properties of limited opportunity. That is, the market is a causal factor of self-destructive pathways or social pathologies (Horwitz 1984), where alternative behaviors are chosen by individuals in recognition of little opportunity to change their life course with respect to the economic circumstances under which they find themselves. In this case, the policy response is investment in poverty prescriptions that focus on reducing barriers to opportunity, particularly for traditionally disadvantaged populations and historically excluded groups. This would include market and non-market-oriented policies similar to those discussed under market participation and social and political process. This perspective, therefore, begs the following questions:
Under what circumstances, if any, is poverty a matter of choice for the study population? Does increased opportunity (e.g., for employment) impact behaviors associated with economic poverty (e.g., failure to seek employment)?
67 3.3.6 POVERTY ALLEVIATION
This theoretical framework focuses on the idea that poverty is caused by efforts to alleviate poverty. For instance, poverty alleviation strategies based in the public assistance system, such as direct cash assistance, create disincentives for individuals to engage in behaviors that would promote movement out of poverty (Kodras 1986). In the
United States this has been a core concern of policy debate centered on the issue of welfare dependency (Shapiro and Young 1989), which is associated with the behavioral traits discussed in the previous section. Critics argue that the opportunity for cash assistance for particular types of families creates an incentive for the creation of those types of families and their prolonged dependence on welfare (Rank 1986). For example, out of wedlock childbearing is encouraged by direct assistance to single-female-headed families, thereby producing a plethora of families of that type. Further, similar behavior is encouraged across generations as children of those families develop like behavioral traits (Murray 1984), such that poverty begets poverty through learned welfare dependency.
Given this perspective, the policy response has been to limit direct assistance to the short term wherever possible––to offer time-limited aid as a means of alleviating immediate need (e.g., wage subsidies), while investing more heavily in development policies that eliminate economic opportunity constraints in the long run (e.g., education and job creation). In relation, the primary research questions are:
What is the degree of dependency on government aid for the study population? How have circumstances associated with economic development reduced the level of dependency?
68 3.4 CHAPTER SUMMARY
In this chapter I examined poverty discourses and causal theories of poverty and the policy debates with respect to economic poverty. This review makes it clear that there is no shortage of perspectives on the causes of poverty and the outcomes of its persistence. Likewise, beliefs about the validity of those perspectives produce different policy recommendations. Rarely are those recommendations exclusive to one perspective. Rather, they reflect the complexity of poverty and the fact that although typically viewed as an economic phenomenon, it is equally embedded in social, political, and cultural systems.
The policy challenge is to simultaneously achieve economic development and poverty reduction given those systems. The link between the two, and essentially between poverty analysis and policy prescriptions, has consistently been weak. Poverty policy has been formulated mainly based on the market, yet poverty is multi-dimensional.
It does not fall entirely within economic boundaries and therefore cannot be framed as such. Yet policy prescriptions and evaluations of them presume that all objects react the same way despite the myriad of possibilities. The consequence is that the poverty impact of any instrument of change remains unknown, poverty is not captured in enough detail and evaluative information is fragmented at best. The next chapter launches into the case study, which illustrates the complexity of the problem and suggests a means for a more holistic accounting of poverty impacts.
69 3.5 CHAPTER REFERENCES
Adams, P., et al., eds. 2001. Textures of Place: Exploring Humanist Geographies. Minneapolis: University of Minnesota Press.
Aigner, S. et al. 1999. Dynamics to Sustain Community Development in Persistently Poor Rural Areas. Community Development Journal. 34(1): 13-27.
Alesina, A. and D. Rodrik. 1994. Distributive Politics and Economic Growth. The Quarterly Journal of Economics. 109(2): 465-490.
Allen, V., ed. 1970. Psychological Factors in Poverty. Chicago: Markham Publishing Company.
Amis, P. and U. Grant. 2001. Urban Economic Growth, Civic Engagement, and Poverty Reduction. Journal of International Development. 13: 997-1002.
Auletta, K. 1982. The Underclass. New York, Random House.
Banfield, E. 1970. The Unheavenly City. Boston: Little Brown.
Berry, B. 1967 December. Strategies, Models, and Economic Theories of Development in Rural Regions. Agricultural Economic Report No. 127. Washington DC: ERS-USDA.
Besharov, D. 1996. Poverty, Welfare, Dependency, and the Underclass: Trends and Explanations. In M. Darby, ed. Reducing Poverty in America: Views and Approaches . Thousand Oaks, CA: Sage Publications.
Blank, R. 2003. Poverty, Policy, and Ethics: Can An Economist be Both Critical and Caring? Paper prepared for the meetings of the Association for Social Economics, Washington DC, January.
Blau, P. and O. Duncan. 1967. The American Occupational Structure. New York: Wiley.
Bluestone, B. and B. Harrison. 1982. The Deindustrialization of America: Plant Closings, Community Abandonment, and the Dismantling of Basic Industry. New York: Basic Books.
Brown, D. and T. Hirschl. 1995. Household Poverty in Rural and Metropolitan-Core Areas of the United States. Rural Sociology. 60(1): 44-66.
Carlson, V. and N. Theodore. 1997. Employment Availability for Entry-Level Workers: An Examination of the Spatial-Mismatch Hypothesis in Chicago. Urban Geography. 18(3): 228-242.
70
Chamberlin, J. 1999. Upon Whom We Depend: The American Poverty System . New York: Peter Lang.
Davis, J. 2001. Race Against Time: Culture and Separation in Natchez Since 1930. Baton Rouge: Louisiana State University Press.
Duncan, C. 1992. Rural Poverty in America. New York: Auburn House.
Duncan, C. 1999. Worlds Apart: Why Poverty Persists in Rural America . New Haven, Yale University Press.
Dwight, L. 1999. Is Urban Black Poverty Unique? An Analysis of Individual and Structural Predictors of Poverty. Doctoral Dissertation. State College PA: The Pennsylvania State University.
Fitchen, J. 1981. Poverty in Rural America: A Case Study . Boulder, Westview Press.
Fitchen, J. 1991 . Endangered Spaces, Enduring Places: Change, Identity, and Survival in Rural America. Boulder: Westview Press.
Glasmeier, A. 2002. One Nation, Pulling Apart: The Basis of Persistent Poverty in the USA. Progress in Human Geography. 26(2): 155-173.
Green, R. and D. James. 1993. Is Job Accessibility a Serious Problem for Black Workers? Review of Radical Political Economics. 25(3): 85-92.
Gutkind, E. 1986. Patterns of Economic Behavior Among the American Poor. New York: St. Martin’s Press.
Hauser, R. 1980. On Stratification in a Dual Economy. American Sociological Review. 4: 702-712.
Hauser, R. and D. Featherman. 1977. The Process of Stratification . New York: Academic Press.
Jargowsky, P. 1997. Poverty and Place: Ghettos, Barrios, and the American City. New York: The Russell Sage Foundation.
Kale, S. 1989. Theoretical Contributions to the Understanding of U.S. Nonmetropolitan Economic Change. Economic Development Quarterly. 3(1): 58-69.
Kalleberg, A. et al. 1982. Economic Segregation, Worker Power, and Income Inequality. American Journal of Sociology. 87: 651-683.
71 Kasarda, J. 1989. Urban Industrial Transition and the Underclass. Annals of the American Academy of Political and Social Science. 501: 26-47.
Katz, M. 1989. The Undeserving Poor: From the War on Poverty to the War on Welfare. New York: Pantheon Books.
Kaufman, H., K. Wilkinson, and L. Cole. 1966. Poverty Programs and Social Mobility: Focus on Rural Populations of Lower Social Rank in Mississippi and the South. State College MS: Social Science Research Center, Mississippi State University.
Kelso, W. 1994. Poverty and the Underclass: Changing Perceptions of the Poor in America. New York: New York University Press.
King, G., et al. 1994. Designing Social Inquiry: Scientific Inference in Qualitative Research. Princeton: Princeton University Press.
Kodras, J. 1986. Labor Market and Policy Constraints on the Work Disincentive of Welfare. Annals, Association of American Geographers. 76: 228-246.
Kramer, R. 1969. Participation of the Poor: Comparative Community Case Studies in the War on Poverty. Englewood Cliffs, NJ: Prentice-Hall.
Kreckel, R. 1980. Unequal Opportunity Structures and Labor Market Segregation. Sociology. 14: 525-550.
Lazar, D. 1996. Competing Economic Ideologies in South Africa’s Economic Debate. The British Journal of Sociology. 47(4): 599-626.
Lewis, O. 1968. The Culture of Poverty. In D. Moynihan, ed. On Understanding Poverty: Perspectives from the Social Sciences. New York: Basic Books.
Lichter, D. and D. McLaughlin. 1995. Changing Economic Opportunities, Family Structure, and Poverty in Rural Areas. Rural Sociology. 60(4): 688-706.
Lynn, L. and M. McGeary, eds. 1990. Inner City Poverty in the United States. Washington DC: National Academy Press.
Lyson, T. and W. Falk. 1993. Forgotten Places: Uneven Development in Rural America. Kansas City: University Press of Kansas.
Mehrotra, S. and E. Delamonica. 2002. Public Spending for Children: An Empirical Note. Journal of International Development. 14: 1105-1116.
Moore, R., ed. 2001. The Hidden America: Social Problems in Rural America for the 21 st Century. Selinsgrove PA: Susquehanna University Press.
72 Moser, C. 1998. The Asset Vulnerability Framework: Reassessing Urban Poverty Reduction Strategies. World Development. 26(1): 1-19.
Murray, C. 1984. Losing Ground. New York: Basic Books.
O’Connor, A. 2001. Poverty Knowledge: Social Science, Social Policy, and the Poor in 20 th Century U.S. History. Princeton: Princeton University Press.
O’Neill, H. 1985. Creating Opportunity: Reducing Poverty Through Economic Development. Washington DC: The Council of State Planning Agencies.
Page, B. and J. Simmons. 2000. What Government Can Do: Dealing with Poverty and Inequality . Chicago: The University of Chicago Press.
Peet R. 1975. Inequality and Poverty: A Marxist-Geographic Theory. Annals, Association of American Geographers. 65(4): 564-571.
President’s National Advisory Commission on Rural Poverty. 1967. The People Left Behind: A Report. Washington DC: U.S. Government Printing Office.
Rand, A. 1979. Introduction to Objectivist Epistemology. New York: New American Library.
Rank, M. 1986. Family Structure and the Process of Exiting from Welfare. Journal of Marriage and the Family. 48(3): 607-618.
Ropers, R. 1991. Persistent Poverty. New York: Insight Books.
Rural Sociological Task Force on Persistent Rural Poverty, The. 1993. Persistent Rural Poverty in America. Boulder: Westview Press.
Sakamoto, A. and M. Chen. 1991. Inequality and Attainment in a Dual Labor Market. American Sociological Review. 56(3): 295-308.
Schram, S. 1998. Structural Inequalities Contribute to Poverty in Single-Parent Families. In L. Shein, ed. Inequality: Opposing Viewpoints in Social Problems . San Diego: Greenhaven Press.
Sen, A. 1983. Poor, Relatively Speaking. Oxford Economic Papers. 35(2): 153-169.
Shanmugaratnam, N. 2001. On the Meaning of Development: An Exploration of the Capability Approach. Forum for Development Studies. 28(2): 263-288.
Shapiro, R. and J. Young. 1989. Public Opinion and the Welfare State: The United States in Comparative Perspective. Political Science Quarterly. 104(1): 59-89.
73 Smith, D. 1987. Geography, Inequality, and Society . Cambridge, Cambridge University Press.
Swanson, L., et al. 1994. African Americans in Southern Rural Regions: The Importance of Legacy. Review of Black Political Economy. 22(4): 109-124.
Swedberg, R. 1991. Major Traditions of Economic Sociology. Annual Review of Sociology. 17: 251-276.
Tafuna’I, A. 2002. Poverty of Opportunity. Paper presented at the 3 rd Biennial Conference of the International Development Studies Network of Aotearoa, New Zealand. Massey University, Palmerston North, New Zealand, December 5-7.
Tickamyer, A. and C. Duncan 1990. Poverty and Opportunity Structure in Rural America. Annual Review of Sociology 16: 67-86.
Tomaskovic-Devey, D. 1987. Labor Markets, Industrial Structure, and Poverty: A Theoretical Discussion and Empirical Example. Rural Sociology . 52(1): 56-74.
UNDP. 1997. Human Development Report. United Nations Development Program. Available online at
US Congress. 1971. The People Left Behind—Four Years Later: A Report on the Effectiveness of Implementation of the Recommendations of the Presidential Commission on Rural Poverty. Senate, 92 nd Congress, 1 st Session. Washington DC: U.S. Government Printing Office.
US Congress. 1988a. Appalachia Revisited: The Persistence of Hunger and Poverty in West Virginia. Hearing Before the Select Committee on Hunger. House of Representatives, 100 th Congress, 2 nd Session. Washington DC: U.S. Government Printing Office.
US Congress. 1991. Mississippi Revisited: Poverty and Hunger Problems and Prospects. Hearing Before the Select Committee on Hunger. House of Representatives, 102 nd Congress, 1 st Session. Washington DC: U.S. Government Printing Office.
US Office of Community Planning and Development (OCPD). 1979 June. Pockets of Poverty: An Examination of Needs and Options. Washington DC: U.S. Department of Housing and Urban Development.
Wachter, M., R. Gordon, M. Piore, and R. Hall. 1974. Primary and Secondary Labor Markets: A Critique of the Dual Approach. Brookings Papers on Economic Activity. 1974(3): 637-693.
Waxman, C. 1983. The Stigma of Poverty: A Critique of Poverty Theories and Policies. New York: Pergamon Press.
74
Wilson, W. 1987. The Truly Disadvantaged: The Inner City, The Underclass, and Public Policy. Chicago: University of Chicago Press.
Wilson, W. 1996. When Work Disappears: The World of the New Urban Poor. New York: Alfred A. Knopf, Inc.
Woods, M. (1975). Achievement, Motivation, and Poverty. Poverty: A New Perspective . Lexington, University of Kentucky.
Yapa, L. 1996. What Causes Poverty?: A Postmodern View. Annals of the Association of American Geographers. 86(4): 707-728.
75 CHAPTER 4
UNDERSTANDING CASINO GAMING IMPACTS
Gambling involves simply sterile transfers of money or goods between individuals, creating no new money or goods. Although it creates no output, gambling does nevertheless absorb time and resources. When pursued beyond the limits of recreation, where the main purpose after all is to kill time, gambling subtracts from the national income. (Samuelson 1976: 425)
Recreational gambling has become the fastest growing component of the entertainment economy (Mandel et al. 1994). That growth reflects a dramatic rise in gambling activity on the part of American citizens over the last twenty years. More importantly, the revenues accrued by industry and government in such a short period have been equally substantial (Marshall 2000). Yet, the benefits of casino industry growth are widely debated. Industry spokespersons argue that gaming, and casino gaming in particular, serves as a valuable provider of income through employment and tax revenue while also fostering secondary gains as those monies ripple through the economy (Arthur Anderson 1996). As such, reported impacts typically consist of aggregate economic measures tied to industry contribution.
Others argue that the economic focus has led to an inadequate assessment of the costs of gaming and its net impact on society, which many believe to be negative (e.g.,
Goodman 1994; Henriksson and Lipsey 1999a; Teske and Sur 1991). In response, analysts seeking to understand the distributional impacts of the industry as an economic development strategy have pointed out the difficulty of weighing its costs and benefits.
Thus, the intent of this chapter is to glean from the literature an understanding of how others have attempted to rationalize the existence and benefits of gambling; how casino
76 gaming is perceived, measured, and interpreted as an economic development strategy and to abstract from that the distinguishing characteristics, relationships and processes of casino development in particular socio-economic and political contexts. (This discussion focuses on the commercial casino segment of the gaming industry.)
4.1 GENERAL ASSESSMENT ISSUES
The proliferation of casino gaming development in its various forms (i.e., riverboat, land-based, tribal, commercial) has centered on the issue of economics.
Communities see the industry as a significant source of job growth, tax revenues for education and capital projects, as well as broad-based economic development. Reports from new casino gaming developments in various locales have chronicled industry investments in casino establishments and anticipated community outcomes, such as rising property values and their benefit to property owners and the boon of new revenues that governments will find available to them. A comparison of these reports illustrates the fact that the timing of casino development assessment is critical. For instance, there is often a significant lag period before expected gains are realized (Stokowski 1993), particularly with regard to economic development. Gains may stem from the investment of casino revenues on education, infrastructure, and redevelopment or the diversification of the economy that may result from the casino as stimulus (Rose and Assoc. 1998).
However, other impacts may peak in the early stages of development, such as those associated with casino construction.
Traditional economic impact studies of casino development rarely capture the broader long-term effects, and fewer still analyze distributional outcomes. More
77 troubling is the prevalence of bias in the literature regarding the divergent perspectives on the overall impacts of casinos, particularly in line with the industry or government agency that funded the study (Rose and Assoc. 1998). This manifests in the form of unrealistic assumptions and the omission of factors that may influence net effects (e.g., only reporting economic benefits), resulting in a noncomparison of economic costs (Goodman
1994). This may include costs linked to spillover effects, such as the consideration of local impacts only. Such an omission ignores casino effects on the wider geographic area, such as those associated with highway congestion.
Another assessment issue arises with regard to data availability. Data collection, in terms of time and form, varies across government agencies and within the industry.
Fiscal years and reporting procedures for government and industry may differ; some data may be collected annually while other data, usually those associated with social rather than economic factors, may only be collected randomly or over larger intervals of time; some indicators of casino impacts may be excluded altogether because they are not easily represented as quantitative data or are proprietary in nature. As such, there is the potential for the introduction of much data-related error in analytical models of casino impacts.
Awareness of these issues serves as a backdrop to understanding the broad range of casino gaming impacts presented in the literature. In addition, the magnitude of those impacts must also be weighed against the context of the development (Meyer-Arendt
1995). For example, the laws that regulate casino operations ultimately determine lucrative gaming sites and their potential to develop as a base industry (Christiansen
1998; Eadington 1995a). Since Mississippi statutes and gaming regulations are similar to
78 those of Nevada, casino clusters that are quickly evolving into resort destinations have developed in Tunica County and on the Gulf Coast near Biloxi (Eadington 1999).
Research suggests that these exotic or mega-casino complexes have the greatest draw on external populations and the largest resultant economic effect (Eadington 1998).
Therefore, comparison of impacts between developments must consider things like political climate with respect to the regulatory framework of the location and the scale effects of agglomeration in addition to other industry, social, economic, and political factors.
With this in mind, drawing mainly from studies of land-based and riverboat casino gaming sites, a vast array of real and potential impacts of gaming development on individuals, communities, and regions is discussed in the remainder of this chapter. I begin by engaging the literature on the economics of casinos in relation to their attraction as an economic development strategy, focusing on employment- and revenue-based impacts. I then turn to the issue of social welfare by exposing the arguments around the social costs of casino gaming. In so doing and as part of the realist methodology, I develop a summary of hypotheses or tendencies on the economic, fiscal, social, and distributional (e.g., poverty) impacts of casino development.
4.2 ECONOMIC DEVELOPMENT
Studies of initiatives in support of gaming as an economic development strategy focus mainly on the siting of casinos at the scale of the community (e.g., Aasved and
Laundergan 1993; Blevins and Jensen 1998a; Browne and Kubasek 1997; Bush et al.
1994; Chacko 1995). At the heart of any one of those campaigns to legalize and attract
79 casinos was the belief that they would create jobs, foster economic growth, improve personal and community wealth, and provide new revenues while reducing local taxes.
In addition, in many instances social benefits were expected in terms of providing increased financing for things of value to the community, such as education and historic/heritage preservation (e.g., Chadbourne et al. 1997). Thus, it is recognized that the promulgation of casinos for the sake of economic development is tied to the idea that a net public good will be derived from the endeavor.
Those expectations are inextricably linked to the classical policy assumption that development will directly produce changes in socio-economic structure (primary impacts), indirectly produce changes in local living conditions (secondary impacts) and invoke human responses to change (tertiary impacts), all of which feed into one another
(Barrow 2000). Accordingly, from the policy perspective, the benefits of casinos are multiplicative in that they are expected to add substantially to government coffers through increased tax revenue and promote economic development through job creation such that greater value is achieved for society and thereby greater utility is derived by individuals as members of that society. Thus, directly or inadvertently (i.e., trickling down), economic development is expected to produce poverty and social outcomes. The majority of this chapter is dedicated to understanding casino impacts in relation to job creation, tax revenue, social welfare, and within the latter, the poverty population.
80 4.2.1 JOB CREATION
The job count created by casino development is the most common way to measure the direct impacts of gaming in a community (Grinols 2001). While it is difficult to argue that casinos have not provided a substantial amount of jobs, a number of issues challenge whether or not employment indicators offer an accurate measure of casinos’ impact on the local economy, and therefore the extent to which there is associated development (Eadington 1995b; Gross 1998). For instance, the value of those jobs to the residents is rarely computed. Neither are the direct impacts to businesses and households that do not operate through prices and markets (Grinols 2001). In order to capture those nuances, the following paragraphs touch upon the most articulated hypotheses associated with job creation, directly or indirectly. Thus, the summary hypotheses presented here, as well as those offered throughout the chapter, are not exclusive. They are parsed out for ease of discussion, but in truth are intricately related and thereby may and should appear to spillover into one another in their definition.
4.2.1.1 THE MULTIPLIER HYPOTHESIS
Most impact studies are based in one way or another on the multiplier hypothesis, which contends, for example, that the income earned by casino employees circulates through the local economy through the purchase of goods and services, thereby creating a demand that generates jobs and growth in other industry sectors. In that respect, direct employment figures would underestimate the casino industry’s economic impact on that community. Yet, context has been found to be a major factor in determining the extent and direction of that impact. For instance, Eadington (1995b) claimed that the multiplier
81 effect is greatest where casinos have located in natural tourist areas, with a support infrastructure already in place. Still, other mitigating factors are identified in the literature, such as those suggested by Blevins and Jensen (1998b) in a study of four former mining towns in South Dakota and Colorado that had adopted limited stakes gaming as an economic revitalization strategy. While all efforts built upon the Old West image and heritage tourism base, the researchers found that differences in legislation resulted in different patterns of development and ultimately different forms of impacts and varying degrees of effect.
4.2.1.2 THE CROWDING OUT AND CANNIBALIZATION HYPOTHESES
The majority of the negative economic impacts found in the comparative study of
South Dakota and Colorado, and the most commonly cited overall, are associated with the crowding out and cannibalization hypotheses (Eadington 1995b; Goodman 1995).
These suggest that the monies spent at the casinos by local citizens merely represent a redistribution of existing revenue rather than the production or incision of new wealth into the economy (McMillen 1991; Van Der Slik 1990). They represent funds that would have otherwise been spent at local establishments, such as a locally owned restaurant instead of a casino restaurant or on other forms of entertainment. Thus, there is a potential for negative impacts to pre-existing businesses due to substitution effects, which are not necessarily borne solely by businesses in the casino community. For instance, although new jobs may be created, other jobs may be lost due to the diversion of funds from pre-existing businesses in and around the casino community. This was found to be true in an analysis of riverboat casino impacts in Illinois (Grinols and Omorov 1996). In
82 that study it was concluded that for every job created by the casino, one or more jobs were lost in pre-existing businesses in the surrounding area. In this case, employment figures would overestimate the full impact of the casinos, and in so doing, trivialize the potential costs to the host community as well as those for surrounding communities.
4.2.1.3 THE EXPORT BASE OR INTERNATIONAL TRADE HYPOTHESIS
The exception to crowding out occurs when the majority of casino visitors come from outside the local area and travel to that location solely to visit the casino. In effect, this situation represents the exportation of gaming services to other parts of the country or the world . According to this export base or international trade hypothesis, casinos will fail to have a positive economic impact on the community if they are unable to attract patrons from outside the local area. This failure will lead to their being considering an invalid strategy for economic development (Eadington 1996; Goodman 1994, 1995). As similarly articulated by Rose (1995: 34):
A casino acts like a black hole sucking money out of a local economy. No one cares if you suck money out of tourists, but large-scale casinos that do not bring in more new tourist dollars than they take away from local players and local businesses soon find themselves outlawed.
This dynamic between economic development policy and the casino as an economic development strategy is best expressed by Grinols (1994: 9) in his oft-cited comparison of casinos to factories and restaurants:
A factory, when it locates in an area, sells to the rest of the country. Its payroll, materials purchases, and profits spent locally are new money to the area that represents tangible goods produced. On the other hand, adding a new restaurant that caters to local population in an area simply takes business from local firms. The question for a
83 particular region therefore is: Is a casino more like a factory or a restaurant? In Las Vegas, casinos are more like factories because they sell gambling services to the rest of the Nation. In most other parts of the country, gambling is like a restaurant, however, drawing money away from other businesses, creating no economic development, but leaving social costs in the wake.
This suggests that casinos that are able to export their product may be deemed as appropriate forms of economic development, that is, more likely than not creating larger and more positive economic impacts than those whose customer base is for the most part localized (Eadington 1996; Thompson as cited in MacIsaac 1994). Evidence in support of this idea can be found by comparing impact studies of casino developments and associated studies of patron residency. For instance, Atlantic City casinos, which attract more out-of-state customers than do Louisiana casinos, are reported to have the larger multipliers of the two (Hamer 1995; Harrison 1992; Oakland Econometrics 1996;
Perniciaro 1995).
Yet, it should be noted that this is not always the case; the multiplier depends on the internal structure of the economy. In conjunction, in some local economies ‘export’ is not a necessary condition for economic development, but the introduction of gambling as a new consumer good alone can serve as an engine for growth and increase aggregate social welfare (Walker 1998). For example, the industry may provide residents with more choice and opportunity with respect to spending their money locally. This may be explained in the logic of realism which, simplified, states that there is a distinction between what forces change and what allows for change and that difference in a structure’s causal power can be influenced by the actions of individuals (Sayer 1985).
84 Thus, in many ways, the economic impacts of casino development are dependent on the structure and growth potential of the industry in place, including their ability to monopolize or to achieve economies of scale through agglomeration in addition to their success at capturing a significant share of tourist dollars (Gazel 1998). Accordingly, casino developments that are able to establish themselves as resort destinations stand a better chance of impacting the local economy positively in terms of generating income and wealth that may filter through the economy in a multiplicative way (Gross 1998;
Przybylski et al. 1998). Yet, this does not rule out issues associated with crowding out and cannibalization. For example, where they serve a fixed budget population, they may simply displace existing demand (Felsenstein et al. 1999). Further, there remains not only competition between casinos and local businesses for customers, but also for employees. In other words, where labor surpluses do not exist in relation to the skills in demand, casino development may negatively impact other businesses by creating labor shortages.
4.2.1.4 THE INCOME HYPOTHESIS
Another issue associated with employment as an indicator of casino impacts is income potential. The income hypothesis states that the introduction of a casino into an economy results in higher levels of personal income. Yet, studies that support this hypothesis are criticized on a number of counts. For example, some claim that the use of certain analytical methods, such as input-output analysis, distorts impacts by failing to consider the issue of crowding out in the derivation of income multipliers (Ryan and
Speyrer 1999). In addition, increases in personal income are often estimated in the
85 aggregate at the state or county level (e.g., Walker and Jackson 1998), thereby failing to provide a fair representation of local and distributive impacts, which may be mitigated by a number of factors. For instance, depending on the point of view taken, the casino industry is or is not labor intensive, but there is agreement that most of the jobs created are low wage (Field 2000; MESC 2000). Therefore, although increased income levels may result given pre-existing employment conditions, it is questionable whether that increase is representative of a living wage. Further, the industry is characterized by high turnover rates, a lack of benefits, and part-time employment (Henriksson and Lipsey
1999; Stedham and Mitchell 1996), thereby suggesting the low levels of employment security and high rates of underemployment typically associated with the service industry.
4.2.1.5 THE TOLL HOUSE AND ECONOMIC ISLAND HYPOTHESES
In relation to the income hypothesis, if the introduction of a casino does not lead to a positive change in income distribution, simply replaces existing employment with casino jobs, or if those positions are filled by in-migrants or commuters, then little change in the economic welfare of the local population may result (Persky 1995). Conditions such as these have been found to be true, such as in the case of Windsor’s (Canada) mega-casino strategy for economic revitalization and represent the toll house hypothesis.
In this case, new jobs are created and casino patrons are attracted from outside the host community. As such, it would normally be assumed that a net economic benefit arrives at through resident income and the spending of that income within the community (i.e., in non-casino industry businesses).
86 However, the new employees come from the region surrounding the host community, and as a result, commute or relocate to the host community. In either case, they are paid with casino revenues generated by outside patrons. Thus, the earnings of locals go unchanged as does their buying and selling patterns. The prices under which those exchanges take place remain the same as well, unless of course prices are bid up by shortages produced by an influx of new residents (e.g., real estate). Some additional spending may take place locally by those new residents, but if the majority of casino employees commute, then the potential for their income to circulate through the local economy is significantly reduced (Tiebout 1956).
At any rate, net new jobs have been created and employment has gone up, but that growth translates into limited (if any) economic development and benefits to pre-casino residents. As explained by Grinols (2001: 5):
Casinos operate like a toll house that uses the town as a platform for conducting its business. Money enters and money leaves. While total economic activity in the vicinity of the town rises, shifting the location of jobs without an increase in well being is not economic development, even though the local economy experiences enlargement.
This is much like the example of the casino as a restaurant as opposed to a factory and is closely linked to the idea of the casino as an economic island.
The economic island hypothesis represents casinos as an economic complex, spatially situated in place (i.e., physically located in a community) while operating external to the local economy. That is, the casino industry typically attempts to capture patrons by providing ancillary services (e.g., eating, sleeping, transport, and shopping opportunities) on casino premises, such that all or the majority of tourist spending is conducted on site. As such, little spending of tourist dollars takes place outside the
87 casinos in host community establishments and therefore increased business activity fails to result as does the creation of additional jobs within those businesses. Further, tourist dollars previously spent in community establishments may be lost as their services are substituted by those of the casinos. Hence, cannibalization may take place—local businesses go under and pre-existing jobs are lost (Hsu 1999).
4.2.2 TAX REVENUE
The prior discussion points out that job creation is of little consequence unless it serves as a vehicle for increasing value within a given society and for the individuals within that society (e.g., increased utility). Thus, in some instances jobs associated with casinos may be a good indicator of economic development and increased welfare, while in other instances they may not. The outcome is mainly a product of the local context and intervening factors of development. Likewise, the same can be said of tax revenues.
For instance, the fiscal benefits of casino development are muddied by tax breaks, subsidized infrastructure, and other competing market incentives (Borden et al. 1996;
Grinols and Omorov 1996). Added to that is the potential for derivative effects, such as spiraling tax valuations that lead to rent inflation, declining sales tax revenues where people substitute gambling for other local expenditures, and increases in demand for public services as new people move in to take casino jobs, which may lead to residential displacement, business closures, and fiscal insolvency (Williams 1996).
Thus, serious questions are raised about the real revenue effects of gambling and whether or not it is proper business for governments to be involved in given associated administrative costs (Lindaman 2002). Still, state and local governments view tax
88 revenue as the most lucrative aspect of gaming industry development (Sylvester 1992).
This attitude is derived in large part from looking at the case of Nevada as the primary example of what casinos contribute in the form of taxes. In Nevada, funds generated by the casino industry make up half of the state’s revenues; however, the Nevada situation is an anomaly and thereby should not be viewed as the norm (Gold 1994). As noted by one industry leader (Promus 1994a: 3):
Despite casino gambling’s promise as a source of economic development and tax revenue; gaming should not be viewed as a panacea for the fiscal woes of a state or local jurisdiction. Casino gaming is more appropriately viewed as an amenity that in smaller metropolitan areas can be a cornerstone in the local tourism/entertainment market, and in larger metropolitan areas as simply another component of a regional tourism/entertainment package.
Yet at the same time it is recognized that the smaller the region, the greater the potential benefit because of the likelihood that the bulk of patrons will come from outside of that region. The problem is that the greater the chance of industry health, and therefore tax revenue success, the more likely the chance of over-dependence, which is the first tax revenue-related hypothesis to be discussed and is related in one way or another to the rest of those presented here.
4.2.2.1 THE DEPENDENCY HYPOTHESIS
The introduction of a pro-gambling policy in a place is more often than not precipitated by state and local budgetary crisis (e.g., Rothschild 2002). As noted previously, this has been the case throughout history and more recently with the case of
Nevada where legalized gambling was introduced during the 1930s in an effort to offset the fiscal woes of the Depression, followed by Atlantic City as a means for downtown
89 revitalization and restoration of the tourist base, and other distressed urban and rural areas, such as Detroit and Mississippi (Rich 1990; Rivenbark 1998). Yet, although increasingly accepted as such, reliance on gaming revenues for fiscal health can be problematic for a number of reasons (NCALG 2001). Mainly at issue is that tax revenue dependency in support of basic services is risky business given the uncertainty of the continued profitability of the industry and the longevity of casino establishments in a particular place. This was evident in New Orleans, for example, where within a matter of nine weeks two riverboat casinos closed their doors, leaving the City with $3 million in uncollected taxes and fees. With the closing of yet another casino, this one land-based, the city was faced with a 5 percent budget cut and 1,000 unemployed casino workers
(Anderson and Charles 1995; Going for Broke 1995). Thus, the degree to which government is dependent on casino gaming revenues can be detrimental to the overall and continued welfare of a society.
4.2.2.2 THE DOMINO AND MARKET SATURATION HYPOTHESES
Profitability and longevity are determined by a number of factors, including the domino effect. The domino effect, or reaction of neighboring jurisdictions, is believed to be a significant determinant of whether or not governments collect anticipated revenues.
For instance, in the case of Iowa mentioned earlier, the state was successful in acquiring gambling revenues until Illinois adopted riverboat casino gaming and did so with fewer restrictions. Revenues quickly dropped for the Iowa casino industry and many of the riverboats left. Iowa responded by relaxing its gambling policies, which helped to save the industry in that jurisdiction, but in turn resulted in substantial job and tax revenue loss
90 in Illinois. Similar situations are discussed in chapter 6 with regard to the adoption and regulatory framework of riverboat casinos in Mississippi and its impact on the industry elsewhere.
This expansion of the industry and related competition for casinos and their patrons is leading to market saturation and threatening the collapse of many casino and non-casino gaming ventures (e.g., Turner 1994). Competition and associated risk not only resides between gaming interests (e.g., states and communities), but also within the industry and among varieties of gaming tax revenue. For instance, there are many reports that charitable gambling, wagering on horse races, participation in lotteries, and associated revenues have been in decline since the expansion of casinos (e.g., Going for
Broke 1995; Mooney 1992). Such findings have serious public finance implications in
Illinois, for example, where lottery revenues dropped by about 25 percent with the incision of riverboat casinos into the state’s economy ( Lottery Official Blaming 1994).
Further, in Florida it was predicted that although casino gaming revenue would be substantial, it would be coupled with decreases in sales tax and revenues stemming from pari-mutuel and lottery gaming activities (Florida Office 1994).
4.2.2.3 THE TEMPORAL HYPOTHESIS
This hypothesis points to the difficulty, and often the inability, of local governments to control the course of casino development over time, and therefore its differential impacts in the short and long run. In the case of Colorado referenced previously, rapid growth took place and host communities were rewarded with sizeable revenue pools, but just as quickly non-casino businesses went bankrupt, property taxes
91 escalated to unprecedented levels, and the casinos shutdown. In the wake of the casinos’ demise, one town found itself lacking basic community service businesses (e.g., grocery store, laundry, and gas station) and was faced with substantial fiscal strain associated with the town’s infrastructure due to unanticipated growth in traffic, crime, and pollution
(Distressed Cities 1993). In contrast to the situation in Colorado, in South Dakota local businesses apparently thrived alongside the casinos (South Dakota Legislative 1998). In one community growth in retail sales outpaced that of the state (WEFA Group 1994).
Such mixed results are not unusual, even within one place, particularly over time, and depending on whether or not social impacts are considered, which are understood to trail economic benefits (Stokowski 1993). The Atlantic City case offers a prime example.
There is no shortage of studies of the impacts of casinos in Atlantic City and the success of the industry as a redevelopment tool (e.g., Sternleib and Hughs 1983; Walkoff
1993; Warker 1988). Those studies have shown that casinos have for the most part thrived, jobs have been created, and tax revenues have at the least covered the costs of regulating the industry. Yet, it is left to question whether or not a net benefit has been achieved over the industry’s life-course in Atlantic City as retail businesses have declined and surged again, casinos have opened and gone bankrupt, personal taxes have gone up as have expenditures associated with dealing with increased social discord (e.g., Diamond
1994). As a result, many claim that the overall outcome is insignificant from the standpoint of economic development. Many share the opinion that the mass of casino revenues filtered through the economy over the years by way of government and private business has done little to improve the lives of Atlantic City residents (e.g., Oddo 1997;
Teske and Sur 1991).
92 Further, the future vitality of the industry has been questioned by similar issues noted under the domino and market saturation hypotheses in terms of regulation and competition combined with obsolescence (Vignola 1992). With respect to the latter,
Atlantic City as a tourist destination has run its course given its uniqueness of place and the age/dilapidation of casinos, hotels, and other area attractions over time.
4.2.2.4 THE ACCOUNTING OR SUBSIDY HYPOTHESIS
Typically, it is understood that tax revenues are returned or distributed to residents in the form of utility derived from the use of goods, purchased by the government through investment in infrastructure and public services. In other words, the increase in tax revenue stemming from casinos is understood as the portion of economic development captured by residents through government (Grinols 2001). Along those lines, the majority of impact studies count that lump-sum expenditure as a benefit to the residents of the host community. Thus, the accounting framework generally used assumes that casino tax revenues result in increases in the quantity, quality, and/or access to public goods and services, while failing to subtract the resource costs associated with negative externalities from that assumed net benefit to area residents. Those externalities, or costs borne by society, might include increased expenditures for law enforcement and judicial services that come about in concert with rising crime rates, investment in counseling services and treatment centers for pathological gamblers, or regulatory and infrastructure costs associated with attracting and maintaining the casinos (Grinols 1996;
Grinols and Mustard 2001).
93 In that respect, it is hypothesized that residents subsidize the activities of casinos, either directly or indirectly (e.g., Barton 1992). In one study that attempted to estimate subsidy costs across the nation (Kindt 1995), it was determined that it costs taxpayers three dollars for every one dollar contributed to government coffers by gambling interests, while others have come up with even higher estimates (Better Government
Association 1992; Florida Office 1994). In addition, problem gamblers and the poor have been shown to contribute a disproportionately higher percentage of their income to gambling profits compared to other population groups (Lesieur 1998; Volberg et al.
2001). Therefore, gambling tax revenue is often referred to as a regressive tax, whereby the industry is in essence further subsidized by the most vulnerable populations in society.
The relevance of these issues, however, is highly disputed in the literature.
Opponents claim, for instance, that although there is a cost to the consumer, gambling revenues more than cover costs such that a net service benefit is achieved and that said costs are not in excess of those incurred with the introduction of any other new industry, particularly tourist related (Arthur Anderson 1996). In reference to the poor, it is argued that although they spend a greater portion of their wealth on gambling, their total spending represents a small amount of casino revenues relative to other population groups and has little to do with why they are poor in the first place (Gabrielle and
Brenner 1997).
94 4.2.2.5 THE BENEFICIARY HYPOTHESIS
Proponents of gambling policy often link the issue to other societal concerns that may be addressed through increased tax revenues (e.g., funds for education, support for elders, and services for the poor) in order to win over its passage to a potential host community (e.g., Rolling the Dice 1994). In that way, the industry is legitimized as an acceptable form of economic development. This is particularly powerful in an economically distressed place, where gambling might be viewed as the last ounce of hope
(e.g., Gambling as Salvation 1993), as was described in the case of Tunica. In such instances, it is purported that local elites, the common citizen, as well as vulnerable groups, will derive mutual benefit from the adoption of a casino-based economic development strategy. However, that outcome can be very different depending on whether and to what extent casino tax revenue is earmarked for specific programs/groups or if the revenue flows directly into general funds that are then redistributed by those in a position of power.
The literature suggests that where the potential disconnect in funding, that is, the difference between what is promised and what actually happens, is greatest in education.
There are reports that school populations and schools experience few positive gains, that alleged budget increases for education add up to nil when translated into real dollars, that funding from other sources is uniformly decreased, and that as a result, there is often a net negative fiscal impact on education (Better Government Association 1992; Blevins and Jensen 1998; Clotfelter and Cook 1989; Oddo 1997). Such situations are sometimes posed as evidence of conflicting objectives among policy constituents and the resultant policy outcome as codification of the wishes of the most powerful stakeholders, “seeking
95 to maximize their self-interest” (Lindaman 2002: 46). They are also framed as the mismanagement of a potential miracle by state and local governments through their failure to capitalize on the social and economic development opportunities afforded by casino gaming revenue that could well serve the needs of the poverty population (e.g.,
Pollock 1987).
However, socio-economic parameters rather than policy, in terms of who possesses the necessary resources for development in the first place and therefore the ability to capitalize on that development, can also be due to an imbalance of benefits derived among stakeholders. According to industry reports (e.g., Harrah’s 1994; Promus
1994b), casinos have a positive impact on property values, which can be thought of as either a cost or a benefit depending on the stakeholder group under consideration.
Property owners may profit based on the opportunity to sell or rent at a higher rate and local government may receive more funds through property taxes. At the same time, the associated cost for some may be that businesses and residents become financially stressed or displaced by those inflated prices. Such circumstances potentially have social outcomes that may result in a reduction rather than increase in welfare for segments of the host community population.
4.2.3 SOCIAL WELFARE
Grinols (2001) argued that there are nine distinct types of costs associated with gambling that might impact social welfare. Most of those costs relate to problem gambling, directly or indirectly, and many of which have already been touched upon in
96 this chapter in conjunction with job creation and tax revenue. Altogether, they include
(13):
1. Crime (apprehension, adjudication, incarceration, and police costs); 2. Business and employment costs (lost productivity on the job, lost employment time, other costs to firms); 3. Bankruptcy (lawsuits and legal costs, bill collection costs); 4. Suicide; 5. Illness (costs associated with depression, stress-related illness, anxiety, cognitive distortions, cardio-vascular disorders, chronic or severe headaches among others); 6. Social service costs (treatment/therapy costs, welfare, food stamps, costs associated with unemployment); 7. Government direct regulatory costs; 8. Family costs (costs associated with divorce, separation, spousal abuse, child neglect); and 9. Abused dollars (resources acquired from family, friends, [and] employers under false pretenses).
The measurement of these factors and their attribution to gaming development is a contentious topic. Many argue that attempts to analyze such effects are error-prone because the nature of social impacts does not produce credible and verifiable data and causal connections are often based on anecdotal evidence (e.g., Arthur Anderson 1996).
With these considerations in mind, in the remainder of this section I present an overview of the social issues most frequently associated with gambling, including concerns around distribution, crime and addiction, and moral compromise.
4.2.3.1 THE DISORDERED GAMBLING HYPOTHESIS
The disordered gambling hypothesis suggests that there is a correlation between crime and gaming activity, particularly where crimes are committed to feed gambling addiction (Smith and Wynne 1999). Yet, a causal connection between crime and gambling has not been established due to the lack of data-related evidence. Law
97 enforcement agencies do not keep records of criminal activity that are detailed enough to tell whether or not crimes are in any way attributable to gambling. Similarly, there is a lack of hard data on associated costs of the crime, judicial expenditures, incarceration, insurance rate increases, and preventative measures (Henriksson and Lipsey 1999). In addition, the gestation period for disordered gambling can be up to ten years (Miller and
Schwartz 1998). Thus, criminal behavior may be an emergent impact of casino development in the long run (Friedman et al. 1989), which may be why the majority of impact studies give little weight to the problem (Blaszcynski and Silove 1996).
Most research on crime associated with gambling has centered on Atlantic City, and more recently on Biloxi and Gulfport Mississippi, including within-city crime patterns, regional spillover, crimes committed in the casinos, and the affect on real estate
(e.g., values and trespassing) (e.g., Albanese 1985; Buck and Hakim 1989; Buck et al.
1991). These studies suggest that both economic (e.g., robbery and fraud) and public
(e.g., disorderly conduct and aggravated assault) crime increases as casinos are introduced into a community (e.g. Giacopassi and Stitt 1993). However, it is also argued that in considering the influence of casinos on gambling-related crime it should be noted that the crimes committed are primarily casino, not community-based, that crime tends to increase with tourism growth in general, and that increases in crime in casino communities are typically not even remotely proportional to the increase in the number of visitors (e.g., Casino/Street 1993; Chiricos 1994; Curran and Scarpitti 1991).
Yet, the demographics and consequences of the addiction aspect of disordered gambling are vast and widely documented. For instance, Wynne et al. (1996) found that
2 to 5 percent of the adult population and 6 to 8 percent of youths have a gambling
98 problem. While these numbers may not seem significant in the aggregate, others have found that compulsive gambling and the demand on support services (e.g., counseling help and treatment centers) increases after casinos are introduced into a community
(Volberg 1997). Therefore, problem gambling tends to be localized and concentrated among resident populations of host communities. Further, the costs of addiction are believed to ripple through society.
These impacts are presented in the literature in two general research areas. The first, and most controversial, are the potential costs associated with individual addiction and the families of those individuals. For example, gambling stress has been found to increase rates of divorce, family violence, child neglect, bankruptcy, substance abuse, suicide, and poor health, particularly for lower-income groups (e.g., Goss 2004; Health
Services 2002; Smith and Azmier 1997). The second area of research involves the greater public costs. The most talked about are the institutional costs, in the form of increased public expenditures on law enforcement, the treatment and prevention of addiction, and other public health and welfare issues (Lesieur and Rosenthal 1991).
Other societal costs often cited are those borne by businesses in association with increased rates of absenteeism, tardiness, theft, low productivity, and crimes against the employer as well as against other employees (e.g., embezzlement, forgery, fraud, and theft) (Kindt 1998; Lesieur 1998).
99 4.2.3.1 THE DOWNTRODDEN HYPOTHESIS
According to the downtrodden hypothesis, gambling costs manifest as a regressive tax that falls disproportionately on society’s most disadvantaged populations and deepens pre-existing social welfare problems (Broad Coalition 2002). This is thought to be particularly true for the poor and less educated, who gamble comparatively larger amounts of their overall income on gambling activities than do middle- and upper- income groups (Clotfelter and Cook 1989; Gabrielle and Brenner 1997; O’Brien 1998).
Explanations for these differential effects based on income include the notion that society’s economically downtrodden are prone to illusory dreams of winning big, which may act as a form of social empowerment that distracts them from feelings of alienation and helps to foster their hopes and aspirations for a better life (Kaplan 1984). In that respect, gambling is viewed as exploitive of the poor, who are thought to gamble not only in search of economic fortune, but also for momentary feelings of invincibility and liberation from their lot in life, including a feeling of control over their life course (Abt and McGurrin 1992; Brunk 1981; Sprott et al. 2001).
Other vulnerable groups include African Americans and Hispanics, who gamble at a significantly higher rate than does the general population (Clofelter and Cook 1989;
Simurda 1999) and younger cohorts more so than older as gambling activity tends to decline with age (Mok and Hraba 1991). Another factor is place of residence. Research has shown substantial differences in rates of gambling activity and addiction associated with geographic location (James 1999). Further, when it comes to casino gaming as an economic development strategy, the literature suggests that even success is tainted for the disadvantaged. For example, it has been reported that casino development in Atlantic
100 City has resulted in the creation of approximately forty thousand jobs, but that is coupled with a largely unemployed minority workforce who live in a city of mostly boarded-up buildings (Eadington 1995). At the same time, it has also been noted that casinos are making a concerted effort to hire more from minority populations and that this effort is greater than that put forth by most other industries (Palermo 1993).
4.2.3.1 THE MORAL COMPROMISE HYPOTHESIS
A number of ethical and value-ladden problem areas uncovered in the literature on casino development suggest that individual and community morals are compromised by the developmental process and existence of casino gaming in a given society (e.g.,
Evans and Hance 1998; Preston et al. 1998). The most studied area involves political discretions and corruption associated with public policy (e.g., Cabbot 1994; Dixon 1991;
Greene and Shugarman 1997; Smith and Wynne 1999). Louisiana stands as the most notorious case involving questionable behavior on the part of government officials (e.g.,
Koselka 1993). Some examples are findings of coercive behavior aimed at influencing
Gaming Commission rulings, the exertion of political pressure in decisions over what individuals or companies receive the most lucrative gaming contracts, and regulatory officials being captured by the gaming industry through campaign contributions and aggressive lobbying that results in the adoption of policy that may benefit a select few to the detriment of society at large (Henriksson and Lipsey 1999; Kindt 1998; Smith and
Wynne 1999).
With regard to the latter, some researchers hint about a monetary payoff to those officials who are “friendly” toward the industry. In a study on casino gaming in Ontario,
101 Canada, Donovan (1997) found that five senior government officials who had helped set the policy agenda on casinos were later employed by the companies that benefitted the most from that agenda. In another instance, this one in Florida, the gaming industry was instrumental in drafting a state constitutional referendum that if adopted would have mandated the introduction of casinos into communities that had voted them out
(Dyckman 1994). On other occassions, casinos, once established, put undue pressure on host communities to rewrite the rules and regulations in favor of the casinos (Sylvester
1992). While these examples are not illegal, per se, they suggest that there has been an inequity in resources or lack of political balance among stakeholders to the point that the constituencies have allowed the industry to dictate public policy on gambling.
However, the acceptance of casino gaming as an economic development strategy has not been entirely political nor has participation in gambling activities been fostered solely by individual economic considerations and psychological tendencies, such as the desire to win money and being prone to addictive behavior (Rosecrance 1986, 1988).
The idea that gambling is sociologically acceptable has been promoted by the industry and accessibility to gaming opportunity has proliferated with its beneficial claims in aid of distressed areas (Clotfelter and Cook 1989; Davidson 1996; Goodman 1994). In fact, the National Gaming Impact Study Commission (NGISC 1999) found that the industry is prone to aggressive advertising strategies that target those living in impoverished neighborhoods. The problem presents itself as an ideological conflict between those who view the legalization and spread of gambling as economical and those who view it as immoral (Weatherson et al. 1996). Opponents to gambling claim that the propaganda of government and industry has blinded citizens into accepting gambling into their
102 communities (e.g., Deitch 1997). This in turn has led to the capitulation of immoral behavior, noting increases in crime, gambling addiction, out-of-wedlock childbearing, drug use, prostitution, and other illicit activities (e.g., Dobson 2004; Weissman 1996).
There are also claims that gambling leads to reductions in religiosity and a variety of socio-cultural activities that are believed to serve as buffers against social ills such as substance abuse and as a protector of social goods that include family values (e.g.,
Amoateng and Bahr 1986; Thompson et al. 1996). The act of gambling itself is considered an act of immorality (e.g., Burger 1995). In citizen surveys in Arkansas
(Mapping Public Opinion 1999), Las Vegas (Diaz 2000), and Iowa (Hraba and Lee 1995) it was concluded that there is a correlation between lack of religious participation and support of gambling. Similarly, using a national sample, Hoffman (2000) found that the social integration associated with religious attendance had the greatest effect in reducing factors of problem gambling.
Other research suggests that many believe that gambling goes against the
Protestant work ethic because it discourages honest labor and, by definition, promotes the gain of something for nothing through risky undertakings (Luger 1998; Mudrack 1997).
Further, its presence in society is thought to endorse greed and discontent by inducing people to covet the money of others and to lust for material wealth while engaging in pleasure-seeking recklessness and abrogating the need for education (Better Government
Association 1992; Clotfelter and Cook 1989). Thus, even working in the gaming industry is seen by some as an illegitimate means of making money. That is, casinos may create jobs, but working in the gaming industry is not respectable, as noted by one individual after a gaming project was proposed in Chicago (Quinn 1992: 16): “Ten
103 thousand construction jobs are supposed to be created by this project. This may very well be true. However, we could create plenty of construction jobs by building brothels and opium dens.”
That comment also points to the observance that business development around casinos is often related to other “vices.” That is, cluster services associated with gambling, and often those that cater to a potentially addicted market segment, tend to locate in close proximity to gaming establishments. These businesses typically include pawn shops, liquor stores, and “men’s” clubs. On the other hand, traditional community service-oriented and retail sales businesses avoid those areas because of the aforementioned costs and the stigma of the market. This is thought to be in part the reason why Windsor, a city that draws more than 80 percent of its patrons from outside the community and is considered a primary example of casino development success, is described as “forlorn,” lacking major retail and other business and community activity
(Horn 2005).
4.2.3.4 THE CONFLICTED HYPOTHESIS
Residents’ perceptions of potential and actual impacts of casino development offer comparable findings with regard to positive economic impacts. They equally point to discrepancies associated with the distribution of the benefits derived as well as negative social consequences that may ultimately negate positive outcomes. This is captured in studies of residents’ opinions of gaming development and their perceptions of the effect of that development on themselves and their community, which make up a substantial portion of the literature on casino gaming, particularly within the realm of
104 industry-funded research (e.g., AGA 2004). That work tends to focus on residents’ predicted impacts of casino development as an economic development strategy prior to implementation and their perceptions of the realized benefits and costs post implementation (e.g., Hsu 2000a; Turner et al. 1999).
Reported economic impacts are for the most part positive and support the notion that casinos bring jobs and revenues to communities. However, it is questionable whether those factors are indicators of improved well-being (Courant 1994). That uncertainty is supported in part by Giacopassi et al. (1999), who conducted interviews with community leaders and public service workers in seven communities that were new casino jurisdictions. They found that the majority believed that the casinos had enhanced the quality of life in their community; a larger percent felt that there had been a positive effect on the economy. Yet, when it comes to individual impacts, there is evidence that although residents may perceive casinos as bringing economic benefits to the community, they do not necessarily view those changes as directly benefiting them personally (Perdue et al. 1995). Evidence of personal benefits includes individual employment and income levels within the industry.
Time has also been shown to contribute to people’s perceptions of casino impacts.
In a survey of adults in Niagara Falls (Room et al. 1999), prior to casino openings, there was an expectation that positive impacts would be associated with increased jobs and tourism. One year later, respondents expressed recognition that anticipated economic impacts were realized, but that they were negated by negative economic and social impacts, such as increased demands on municipal expenditures and a rise in self-reported gambling problems. In another study, Hsu (2000a) found that residents’ support of
105 gaming in Iowa and Illinois riverboat casino communities wavered over a five-year period and that factors associated with crime and community amenities were significant predictors of their opinions. More controversial and difficult to capture than residents’ opinions of economic impacts are social impacts (USGAO 2000), particularly those associated with issues of morality and their ties to indicators of quality of life and subjective well-being.
Opinion studies offer subjective support that new casino communities are adversely impacted in the ways suggested, or will be in the case of proposed sites. For example, in one survey of residents of new casino communities it was found that perceptions of the prevalence of pathological gambling produced negative impacts that were more than three times the estimates using objective measures (Stitt et al. 2000).
Yet, overall, people are seemingly conflicted when attempting a moral balance between economic and social impacts (e.g., NORC 1999). In a national sample, Gallup (1993) found that the majority of respondents were not morally opposed to casino gambling, but few wanted them located in their community. This “not in my backyard” (NIMBY) attitude was also found in a number of community studies where casinos were proposed or had already been located (e.g., Thompson et al. 1993). For instance, while residents of two potential casino communities in Massachusetts thought that the casinos would bring jobs, they expressed considerable concern over negative social impacts, such as beliefs that the casinos would lead to increases in prostitution, illegal drug use, and crime (Pizam and Pokela 1985). In surveys in Colorado and South Dakota, where casinos had already been located (Long 1996; Kang et al.1996), there was agreement that anticipated
106 economic benefits had been recognized, but the presence of intangible social costs, such as a decreased sense of community, were evident in the residents’ responses.
4.2.3.4.1 WHAT ABOUT THE POOR?
An area of opinion research that has been neglected is the study of perceived impacts on the poverty population. That is, while some research differentiates between impacts on specific groups of residents (e.g., Canedy and Zeiger 1991; Hsu 2000b; Wicks and Norman 1996), there is a lack of empirical analysis on the perceptions of the poverty population in communities where casinos were adopted for the sake of alleviating economic distress. There are a number of potential reasons for this research gap. One is that it may be difficult to ascertain input from this subset of the population for reasons of limited access (e.g., cultural barriers) or resource constraints (e.g., research funding).
Another is that the value of the opinions of the poor may be deemed inferior to that of the larger population or its subset of community leaders because the poor are less likely to be in a position to determine the future of casinos or influence the decisions made on behalf of society at large (Giacopassi, et al. 1999). Regardless, it is unrealistic to consider an assessment of the impacts of casino development on a distressed community as complete without gaining an understanding of what that development has meant/will mean for the resident poverty population.
Given the limits of prior research, there is a lack of consensus on what those impacts might be, but some existing work gives a sense of expected outcomes. The literature on gambling addiction touches upon impacts to the poor, particularly children of parental gambling, who have been shown to experience pervasive loss , which refers to
107 not only financial loss, but also loss of family and security and trust (Darbyshire et al.
2001). Also, as noted previously, it is often argued that gambling costs serve as a regressive tax that falls disproportionately on society’s disadvantaged, particularly the poor. According to resident surveys, comparison against Nevada counties and among counties with and without casinos, and gambling experience to income, this problem is thought to be the most pervasive in Mississippi (Rivenbark 1997; Rivenbark and
Rounsaville 1996). Rivenbark (1998) used data from telephone interviews and log-linear regression analysis to show that Mississippi’s poor, who are among the poorest in the nation, have greater access to casinos than most other populations and are paying a larger percentage of the taxes associated with casino revenues.
Taking these factors together with those highlighted under the downtrodden hypothesis and elsewhere, the literature suggests a positive relationship between gambling’s costs and economically distressed places with a high percentage of poor minority residents, based on racial/ethnic groups. Thus, one might conclude that the poor are made worse off by the location of casinos in their communities. Yet, when individuals are asked to assess net impacts given the multiple dimensions of casino development (i.e., economic and social factors) their expressed opinions reflect conflict with regard to perceptions of well-being, both their own and those of the community.
Further, existing research offers little insight into perceptions of well-being of the poor and its relationship to subjective assessments of the success of casino gaming as an economic development strategy for distressed communities. This void reflects the problems associated with standard approaches to casino impact analysis and the
108 methodological challenges presented when trying to improve upon those analyses. This brings me to the final section of this chapter.
4.4 CHALLENGES OF CASINO IMPACT ANALYSIS
Notwithstanding that over the last decade gambling has been studied exceedingly more so than in the past, there is little hard evidence to support or refute the assertion that gambling is efficacious in economic development terms in general or with respect to helping to alleviate poverty conditions in distressed areas. Comprehensive studies, such as that of the National Gambling Impact Study Commission (NGISC) established by
President Clinton in 1996 to “conduct a comprehensive study of the social and economic impacts of gambling in the United States” (1999: 8), demonstrate the need for more rigorous and critical evaluations of the costs and benefits of gaming to society. The
NGISC set an agenda for developing a factual base of casino impacts from which to make recommendations for state and local decision makers. In attempting to do so, the
Commission inevitably accepted “the inherent limitations of research in answering broad cause and effect questions” and resolved that the evaluation of “a phenomenon as complex and emergent as gambling” must include an assessment of effects on both people and places (1). Thus, a multi-faceted methodological framework was called for in assessing casino gaming impacts, and thereby the effectiveness of casino gaming as an economic development strategy targeted at distressed communities. This includes a methodology that can capture the broader economic changes resulting from the expansion of gaming in society as well as the social-psychological effects of gaming on individuals and select population groups.
109 However, meeting that need is challenging on a number of fronts, including that associated with assessing economic vs. social impacts, private vs. social costs and benefits, societal vs. private impacts, and poverty vs. well-being. The majority of economic impacts are tangible and easily quantifiable while social impacts are not. New roads, new jobs, and new buildings are easily identified, but their impacts on the lived experience of individuals in a community are for the most part illusive. Further, it is difficult to quantify the costs and benefits that arise at different points in time, the distribution of those impacts across income classes, racial groups, economic sectors, and locations, and their intangible outcomes, such as moral concerns. A great deal of debate has taken place on the rigorousness of methodologies used in determining the net impacts of casinos on society, and in conjunction, how differences between private and social costs and benefits should be determined and measured (e.g., Horn 1997; McGowan
1999a; Walker and Barnett 1999).
Such debate was in full force at the Whistler Symposium, which brought together researchers and public policy makers from around the world to discuss the perspectives, definitions, and methods for gambling impact assessment. The overall objective was to derive best practice guidelines for the sake of future impact analysis. This did not materialize, however, due to the limited consensus on a number of key issues, including:
The most salient philosophical perspective that should underpin research on both social and economic impacts; Defining private versus social costs and their attribution to gambling; Exactly what costs and benefits should be included in impact analyses; and, What the best methods are for measuring those costs and benefits.
Essentially, the conclusion was similar to that of the NGISC—there is a need for impact analysis that renders a much deeper and accurate understanding of gambling’s impact on
110 society, and this must include not only economic, but also anthropological, sociological, geographical, and other contextual factors.
Moving in that direction, from a conceptual standpoint, there is at least some agreement that a social impact represents either a significant improvement or deterioration in well-being given casino development, and that social costs represent the burden that individuals who gamble impose on those who do not (Dietz 1987; Thompson and Gazel 1998). However, as discussed in this chapter and elsewhere, those costs (and benefits) have been found to vary based on the macro-economic climate, the gambling format in place, the scale of development, and other contextual factors, such as the political, economic, and social history of the casino location (Gazel 1998; Stokowski
1999). Another complicating matter is the meaning of well-being, which may differ over time, across places, among population groups, and according to whether or not it is provided in reference to individuals or society as a whole. With respect to the latter,
McGowan (1997) argued that the major controversy over casino impacts resonates with the ideological differences between those who advocate for the rights of the individual and those who advocate for societal good .
The operational imperative of assessing impacts under those terms is captured best in a report that appeared in the Chicago Sun-Times (1993) shortly after the beginning of the casino gaming boom. The author concluded that weighing the costs and benefits of casino development is essentially a subjective and moral decision, noting that, for example (14): “How does one weigh a shattered life of a pathological gambler against new jobs for people whose only hope had been welfare?” From this perspective, the issue of determining the most appropriate conceptual and operational framework for
111 conducting comprehensive casino impact analyses is objectively un-resolvable. Yet, the intangibles ( e.g., quality of life, well-being, happiness, perception of place) are fundamentally meaningful, so despite the difficulty of measurement, they should not be discounted when assessing the net impacts of casino development on individuals and the communities in which they reside. Nor should context be ignored:
Many of the most important issues facing the poor—their identities, perceptions, and beliefs, for example—cannot be meaningfully reduced to mere numbers or adequately understood without reference to the immediate context in which they live. (Rao and Woolcock 2001: 7-2)
Unfortunately, this neglect of the aforementioned factors is often the case, as the most common problems with existing impact analyses are that (Rao 2003):
Ground-level realities are ignored—hypotheses are drawn from a read of secondary literature; They represent relatively stagnant representations of human behavior; There is a disconnect between analyzer and analyst via the widespread use of secondary data; There is a lack of consideration for context; and By failing to consider context there is a tendency to replicate existing stereotypes.
The latter is likely due to the fact that industry-led studies dominate and have been shown to contain a high level of bias (Rose and Assoc. 1998). At the same time, studies of specific stakeholder groups are rare, but where done are targeted mainly toward community leaders (e.g., business owners, politicians, landed elite). Thus, the same perspectives are generated time and again. Considering that and the existing lack of understanding of the impacts of casino gaming as an economic development strategy in distressed areas on the resident poor, for this study, the decision was made to focus on the distributional impacts of casino development with respect to the poverty population, both objectively and subjectively.
112 4.6 CHAPTER SUMMARY
In this chapter I discussed the manner in which casino impacts are typically understood from an economic development standpoint and the general issues that arise when undertaking such an assessment with respect to the host community, and more specifically the poverty population within that community. In so doing, summary hypotheses for three key impact areas (i.e., job creation, tax revenue, and social welfare) were abstracted from existing literature on the topic. Those general hypotheses reflect the multiplicity of attributes and relationships that potentially exist in a place in association with gaming industry development and the difficulty that presents when seeking to measure its costs and benefits. Thus, the discussion in this chapter also made clear the problems associated with using standard measurements of the success of an economic development strategy in the context of gaming and the methodological challenges that exist when trying to improve upon such analyses.
These findings are in sync with the realist perspective that the causal powers of the mechanisms that underpin society can only be actualized with respect to contingent conditions. That is, in the case of casinos, their effect is mediated by regulatory structure, interest in gaming as a form of entertainment, and the existence of surplus labor, for example. Further, it is impossible to know the nature and form of these contingencies in advance given that they vary with time and place. Therefore, the relation between causal mechanisms, processes, and empirical events as presented in this chapter as ‘hypotheses,’ which implies generalizability and testing on a theoretical basis, can only be treated as
113 ‘tendencies,’ thereby denying the possibility of empirical regularities (Chouinard et al.
1984; Sayer 1992). 12
This suggests the need for intensive research in order to establish a measure of impact; the causal properties of casino gaming as an economic development strategy can only be identified “in the particular contexts that are relevant to them,” which “provides a better basis than extensive studies for recommending polices that have a ‘causal grip’ on the agents of change” (Sayer 1992: 154). Thus, the next step was to set up an empirical example to meet the challenges of explanation head-on. Thus, chapter 5 begins the case study by illuminating the processes that led to persistent poverty and economic underdevelopment in Tunica, Mississippi. This is followed by a chronicling of the incision of gaming into the area, which serves as a means for teasing out the complex interactions and necessary relations that account for the changes in Tunica since the early
1990s (chapter 6).
4.7 CHAPTER REFERENCES
Aasved, M. and J. Laundergan. 1993. Gambling and Its Impacts in a Northeastern Minnesota Community: An Exploratory Study. Journal of Gambling Studies. 9(4): 301-319.
Abt, V. and M. McGurrin. 1992. Commercial Gambling and Values in American Society: The Social Construction of Risk. Journal of Gambling Studies. 8(4): 413-420.
Albanese, J. 1985. The Effect of Casino Gambling on Crime. Federal Probation. 49(June): 39-44.
12 This represents a major distinction between positivists and realists. The former seeks to identify laws of general applicability while the latter denies the possibility of doing so. For discussion see Sayer (1979), for example.
114 American Gaming Association (AGA). 2004. 2004 State of the States: The AGA Survey of Casino Entertainment. American Gaming Association. Available online at
Amoateng, A. and S. Bahr. 1986. Religion, Family, and Adolescent Drug Abuse. Sociological Perspectives. 29(1): 53-76.
Anderson, E. and A. Charles. 1995 November 23.. New Orleans, State Study Options for Dealing with Harrrah’s. The New Orleans Times-Picayune. Pg. 8.
Arthur Anderson. 1996. Economic Impacts of Casino Gaming in the United States. Vol. 1: Macro Study. Prepared for the American Gaming Association. Las Vegas: Arthur Anderson, LLP.
Barrow, C. 2000. Social Impact Assessment: An Introduction. London: Arnold.
Barton, B. 1992. Legal and Tax Incidents of Compulsive Behavior: Lessons from Zarin. Tax Lawyer. 45: 749-782.
Better Government Association. 1992. Casino Gambling in Chicago. Staff White Paper. Chicago: Better Government Association.
Blaszaczynski, A.., & Silove, D. (1996). Pathological gambling: Forensic issues. Australian and New Zealand Journal of Psychiatry , 30, 358-369.
Blevins, A. and K. Jensen. 1998a. Gambling as a Community Development Quick Fix. Annals of the American Academy of Political and Social Science. 556(March): 109-123.
Blevins, A. and K. Jensen. 1998b. The Last Gamble: Betting on the Future in Four Rocky Mountain Towns. Tucson: University of Arizona Press.
Bordon, G., et al. 1996. Economic Resource and Fiscal Impacts of Visitors on Washoe County, Nevada. Journal of Travel Research. 34(3): 75-80.
Broad Coalition on Religious Leaders Unite Against Gambling. 2002. Focus on the Family Press Room. 6 May. Available online at
Browne, M. and N. Kubasek. 1997. Should We Encourage Expansion of the Casino Gambling Industry? Review of Business. 18(3): 9-13.
Brunk, G. 1981. A Test of the Friedman-Savage Gambling Model. Quarterly Journal of Economics. 96(2): 341-348.
Buck, A. and S. Hakim. 1989. Does Crime Affect Property Values? The Canadian Appraiser. 33(Winter): 23-27.
115
Buck, A. et al. 1991. Casinos, Crime, and Real Estate Values: Do they Relate? Journal of Research in Crime and Delinquency. 28(August): 288-303.
Burger, T. 1995. “Churches Fight Gambling Plan”: That Front-Page Headline in the Parkersburg Sentinel Gave Notice of “A Battle Royal” in West Virginia. Christian Social Action. 8: 25-27.
Bush, S., M. Devitt, S. Krasnoff, and T.Tyrell. 1994. The Local Impacts of Foxwoods 1992-1994: Economic and Social Costs. New England Journal of Travel and Tourism. 11-22.
Cabot, A. 1994. Avoiding the Impact of Scandal. Casino Journal. 7(May): 12.
Canedy, L. and J. Zeiger. 1991. The Social, Economic, and Environmental Costs of Tourism to a Gaming Community as Perceived by its Residents. Journal of Travel Research. 30(2): 45-49.
Casino/Street Crime Connection . 1993 January 1. Memphis: Promus Companies.
Chacko, J. 1995. One Year Review of Casino Windsor. Toronto: KPMG Management Consulting.
Chadbourne, C., P. Walker, and M. Wolfe. 1997. Gambling, Economic Development, and Historic Preservation. Chicago: American Planning Association.
Chicago Sun-Times. 1993. Studies of Gambling Deal Few Answers—Conclusions Elusive on Social, Economic Impacts of Casinos. June 1: 14.
Chiricos, T. 1994. Casinos and Crime: An Assessment of the Evidence . Las Vegas: University of Nevada.
Christiansen, E. 1998. Gambling and the American Economy. Annals of the American Academy of Political and Social Science. 556(March): 36-52.
Chouinard, V., R. Fincher, and M. Webber. 1984. Empirical Research in Scientific Human Geography. Progress in Human Geography. 8: 347-380.
Clotfelter, C. and P. Cook. 1989. Selling Hope: State Lotteries in America. Cambridge: Harvard University Press.
Courant, P. 1994. How Would You Know a Good Economic Development Policy if You Tripped Over One? Hint: Don’t Just Count Jobs. National Tax Journal. 47(4): 863-881.
116 Curran, D. and F. Scarpitti. 1991. Crime in Atlantic City: Do Casinos Make a Difference? Deviant Behavior: An Interdisciplinary Journal. 12: 431-449.
Darbyshire, P., C. Oster, and H. Carrig. 2001. The Experience of Pervasive Loss: Children and Young People Living in a Family Where Parental Gambling is a Problem. Journal of Gambling Studies. 17: 23-45.
Davidson, D. 1996. Selling Sin the Marketing of Socially Unacceptable Products. Westport CT: Quorum.
Deitch, L. 1997. Rolling the Dice in Detroit: How a Land-Based Casino Referendum Beat the Odds Thanks to a Skillful Campaign. Campaigns and Elections. 18: 31- 33.
Diamond, R. 1994. Atlantic City Seeks Life Beyond Gambling. Christian Science Monitor. 86: 8.
Diaz, J. 2000. Religion and Gambling in Sin-City: A Statistical Analysis of the Relationship Between Religion and Gambling Patterns in Las Vegas Residents. The Social Science Journal. 37(3): 453-458.
Dietz, T. 1987. Theory and Method in Social Impact Assessment. Sociological Inquiry. 57(1): 54-69.
Distressed Cities Increasingly Bank on Casino Gambling. 1993. National Civic Review. Summer: 303.
Dixon, D. 1991. From prohibition to regulation: Anti-gambling and the law. Oxford, UK: Claredon.
Dobson, J. 2004. Focus on the Family Position Statement on Gambling. CitizenLink: Focus on Social Issues. 12 March. Available online at
Donovan, K. 1997 December. How Insiders rolled the dice on casinos. Toronto Star.
Dyckman, M. 1994. Misleading the Public. St. Petersburg Times. November 1, p. A1 3.
Eadington, W. 1995a. The Emergence of Casino Gaming as a Major Factor in Tourism Markets: Policy Issues and Considerations. In R. Butler and D. Pearce, eds. Change in Tourism: People, Places, Processes. London: Routledge Kegan Paul.
Eadington, W. 1995b. Economic Development and the Introduction of Casinos: Myths and Realities. Journal of Economic Development Review. 13(4): 51-54.
117 Eadington, W. 1998. Casino Gaming—Origins, Trends, and Impacts. In K. Meyer- Arendt and R. Hartmann, eds. Casino Gambling in America: Origins, Trends, and Impacts. New York: Cognizant Communication Corporation.
Eadington, W. 1999. The Spread of Casinos and Their Role in Tourism Development. In D. Pearce and R. Butler, eds. Contemporary Issues in Tourism Development. New York: Routledge.
Eadington, W. R. 1996. The legalization of casinos: Policy objectives, regulatory alternatives and cost/benefit considerations. Journal of Travel Research. 34: 3-8. Economic Impact of Casino Gambling in Louisiana. 1999.
Evans, R. and M. Hance, eds. 1998. Legalized Gambling For and Against. Chicago: Open Court.
Felsenstein, D., L. Littlepage, and D. Klacik. 1999. Casino Gambling as Local Growth Generation: Playing the Economic Development Game in Reverse? Journal of Urban Affairs. 21(4): 409-421.
Field, S. 2000. Career Opportunities in Casinos and Casino Hotels. New York: Checkmark Books.
Florida Office of Planning and Budgeting. 1994. Casinos in Florida: An Analysis of the Economic and Social Impacts.
Friedman, J., Hakim, S., & Weinblatt, J. 1989. Casino gambling as a “growth pole” strategy and its effect on crime. Journal of Regional Science . 29(4): 615-623.
Gabrielle, A. and R. Brenner. 1997. Gambling: Shaping an Opinion. In W. Eadington and J. Cornelius, eds. Gambling: Public Policies and the Social Sciences. Reno: Institute for the Study of Gambling and Commercial Gaming, University of Nevada, Reno. P. 493.
Gallup Poll 1993. Cited in St. Louis Post-Dispatch. 10 October: 1E.
Gambling as Salvation: Glad to Get It. 1993 November 20. Economist , 28.
Gazel, R. 1998. The Economic Impacts of Casino Gambling at the State and Local Levels. Annals of the American Academy of Political and Social Sciences. 556: 66-84.
Giacopassi, D., M. Nichols, and B. Stitt. 1999. Attitudes of Community Leaders in New Casino Jurisdictions Regarding Casino Gambling’s Effects on Crime and Quality of Life. Journal of Gambling Studies. 15(2): 123-147.
118 Giacopassi, D. and B. Stitt. 1993. Assessing the Impact of Casino Gambling on Crime in Mississippi. American Journal of Criminal Justice. 18: 117-131.
Going for Broke on Casino Gambling. 1995. The Washington Post National Weekly Edition. 28 August – 3 September: 33.
Gold, S. 1994. It’s Not a Miracle, It’s a Mirage. State Legislatures. February: 28.
Goodman, R. 1994, ed. Legalized Gambling as a Strategy for Economic Development. Northampton MA: U.S. Gambling Study.
Goodman, R. 1995. The Luck Business: The Devastating Consequences and Broken Promises of America’s Gambling Explosion. New York: Free Press.
Goss, E. 2004. The Impact of Casino Gambling on Bankruptcy Rates: A County Level Analysis. Creighton University. Available online at
Green, I., & Shugarman, D. 1997 Honest politics: Seeking integrity in Canadian public life. Toronto, ON: James Lorimer & Company.
Grinols, E. 1994. Bluff or Winning Hand? Riverboat Gambling and Regional Employment and Unemployment. Illinois Business Review. 51: 8-11.
Grinols, E. 1996. Incentives Explain Gambling’s Growth. Forum for Applied Research and Public Policy. 11(2): 119-124.
Grinols, E. 21 December 2001. Cutting the Cards and Craps: Right Thinking About Gambling Economics.
Grinols, E. and D. Mustard. 2001. Business Profitability versus Social Profitability: Evaluating Industries with Externalities—The Case of Casinos. Managerial and Decision Economics. 22(1-3): 143.
Grinols, E. and J. Omorov. 1996. Development or Dreamfield Delusions?: Assessing Casino Gambling’s Costs and Benefits. The Journal of Law and Commerce. 16(1): 49-87.
Gross, M. 1998. Legal Gambling as a Strategy for Economic Development. Economic Development Quarterly. 12(3): 203-213.
Hamer, T. 1995. Economic Impact of the New Jersey Casino Industry. Rowan College NJ: The Management Institute.
Harrah’s Casinos. 1994. Harrah’s Survey of U.S. Casino Entertainment. Memphis, TN.
119 Harrison, K. 1992. Economic Effects of Commercial Gaming in New Jersey. In. W. Eadington and J. Cornelius, eds. Gambling and Commercial Gaming: Essays in Business Economics, Philosophy, and Science. Reno: Institute for the Study of Gambling and Commerical Gambling. Pp. 105-115.
Health Services Policy Research Group. 2002. The Costs and Consequences of Gambling in the State of Delaware. School of Urban Affairs and Public Policy: University of Delaware.
Henriksson, L. and R. Lipsey. 1999. Should provinces expand gambling? Canadian Public Policy. 25(2): 259-275.
Hoffman, J. 2000. Religion and Problem Gambling in the US. Review of Religious Research. 41(4): 488-509.
Horn, B. 1997. The Courage to be Counted. Journal of Gambling Studies. 13(4): 301- 307.
Horn, D. 2005. Hopes Stall in Motor City. The Enquirer, Cincinnati. April 13. Available online at
Hraba, J. and G. Lee. 1995. Problem Gambling and Policy Advice: The Mutability and Relative Effects of Structural, Associational, and Attitudinal Variables. Journal of Gambling Studies. 11(2): 105-121.
Hsu, C., ed. 1999. Legalized Casino Gaming in the United States: The Economic and Social Impact. New York: The Hawthorn Press.
Hsu, C. 2000a. Residents’ Support for Legalized Gaming and Perceived Impacts of Riverboat Casinos: Changes in Five Years. Journal of Travel Research. 38(4): 390-395.
Hsu, C. 2000b. Riverboat Casinos’ Impact on Host Communities: Comments from business Owners and Residents. Asia Pacific Journal of Tourism Research. 5(1): 8-15.
James, D. 1999. Alberta Profile, Social and Health Indicators of Addiction. 5 th edition. Edmonton: Alberta Alcohol and Drug Abuse Commission.
Kang, Y., P. Long, and R. Perdue. 1996. Resident Attitudes Toward Legal Gambling. Annals of Tourism Research. 23(1): 71-85.
Kaplan, H. 1984. The Social and Economic Impacts of State Lotteries. Annals of the American Academy of Political and Social Sciences . 474: 91-106.
120 Kindt, J. 1998. Follow the Money: Gambling,Ethics, and Subpoenas. Annals of the American Academy of Political and Social Science. 556: 85-97.
Kindt, J. 1995. Legalized Gambling Activities as Subsidized by Taxpayers. Arkansas Law Review. 48: 889-931.
Koselka, R. 1993 March 1. Fantasyland. Forbes. 151: 62-63, 65.
Lesieur, H. 1998. Costs and Treatment of Pathological Gambling. The Annals of the American Academy of Political and Social Science. 556: 153-171.
Lesieur, H. and R. Rosenthal. 1991. Pathological Gambling: A Review of the Literature. Journal of Gambling Studies. 7: 5-39.
Lindaman, K. 2002. Turning the Token: The Local Politics of Gambling. Published Dissertation. Department of Political Science, University of Kansas.
Long, P. 1996. Early Impacts of Limited Stakes Casino Gambling on Rural Community Life. Tourism Management. 17(5): 341-353.
Lottery Official Blaming Sinking Revenues on Riverboat Gambling. Chicago Tribune , 8 February 1994, p. 2.
Luger, R. 1998. Gambling Weakens the Work Ethic and the Family. In R. Evans and M. Hance, eds. Legalized Gambling For and Against. Chicago: Open Court. Pp. 219-223.
MacIsaac, M. 1994. Winners take nothing. Canadian Business , May, 36-42.
Mapping Public Opinion: The Arkansas Poll. 1999. Politics and Policy. Fall. Center for the Study of Representation: University of Arkansas. Available online at
Marshall, K. 2000. Update on gambling. Perspective, Ottawa: Statistics Canada, Service Industries Division.
McGowan, R. 1997. The Ethics of Gambling Research: An Agenda for Mature Analysis. Journal of Gambling Studies. 13(4): 279-289.
McGowan, R. 1999a. A Comment on Walker and Barnett’s “The Social Costs of Gambling: An Economic Perspective.” Journal of Gambling Studies. 15(3): 213- 215.
McMillen, J. 1991. The Impact of Casinos in Australian Cities. In W. Eadington and J. Cornelius, eds. Gambling and Public Policy. Institute for the Study of Gambling and Commercial Gaming, University of Nevada. P. 89.
121
Meyer-Arendt, K. 1995. Casino Gambling in Mississippi: Location, Location, Location. Economic Development Review. 13(4): 74-87.
Miller, W. and M. Schwartz. 1998. Casino Gambling and Street Crime. Annals of the American Academy of Political and Social Science. 556: 124-137.
Mississippi Employment Security Commission (MESC). 2000. Labor Market Information. Occupational Employment and Wage Data.
Mok, W. and J. Hraba. 1991. Age and Gambling Behavior: A Declining and Shifting Pattern of Participation. Journal of Gambling Studies. 7: 313-335.
Mooney, B. 1992. Racing & Casinos in New Jersey. Blood-Horse. 118: 5529-5534.
Mudrack, P. 1997. Protestant Work-Ethic Dimensions and Work Orientations. Personality and Individual Differences. 23(2): 217-225.
National Coalition Against Legalized Gambling (NCALG). 2001. Speakers Warn Government Addicted to Gambling Taxes. October 14.
National Gambling Impact Study Commission (NGISC). 1999. Report Recommendations. Washington DC: National Gambling Impact Study Commission. Available online at
National Opinion Research Center (NORC). 1999. Overview of National Survey and Community Database Research on Gambling Behavior. Chicago: University of Chicago.
Oakland Econometrics. 1996. The Significance of Louisiana Riverboat Casinos for the Louisiana Economy.
O’Brien, T. 1998. Bad Bet: The Inside Story of the Glamour, Glitz, and Danger of America’s Gambling Industry. New York: Random House.
Oddo, A. 1997. The economics and ethics of casino gambling. Review of Business , 18(3): 4-8.
Palermo, D. 1993. Gaming’s Expansion Aiding Minority Job Seekers. Las Vegas Review-Journal. November 21: E15.
Perdue, R., P. Long, and Y. Kang. 1995. Resident Support for Gambling as a Development Strategy. Journal of Travel Research. 34(2): 3-11.
122 Perniciaro, R. 1995. Casino gambling in Atlantic City: Lessons for economic developers. Economic Development Review , 13(4): 47-50.
Persky, J. 1995. Opportunity Costs and Displacement in Casino Impact Studies. Journal of Gambling Studies. 11(4): 349-360.
Pizam, A. and J. Pokela. 1985. The Perceived Impacts of Casino Gambling on a Community. Annals of Tourism Research. 12(2): 147-165.
Pollock, M. 1987. Hostage of Fortune: Atlantic City and Casino Gambling. Princeton NJ: Center for Analysis of Public Issues.
Preston, F., B. Bernhard, R. Hunter, and S. Bybee. 1998. Gambling as Stigmatized Behavior: Regional Relabeling and the Law. The Annals of the American Academy of Political and Social Science. 556: 186-196.
Promus Companies, Inc. 1994a. The Do’s and Don’t of Casino Legislation: Lesson from the Field. Memphis, TN.
Promus Companies, Inc. 1994b. An Overview of Riverboat Gaming in the United States. Memphis, TN.
Przybylski, M., et al. 1998. Does Gambling Complement the Tourist Industry: Some Evidence of Import Substitution and Demand Displacement. Tourism Economics. 4(3): 213-231.
Quinn, M. 1992. Social Costs of Casino Proposal Are Too High. Chicago Sun-Times. 4. April, Forum: 16.
Rao, V. 2003. Experiments with “Participatory Econometrics” in India: Can Conversation Take the Con Out of Econometrics. In R. Kanbur, ed. Q-Squared: Qualitative and Quantitative Methods of Poverty Appraisal. Delhi: Permanent Black. Pp. 103-113.
Rao, V. and M. Woolcock. 2001. Integrating Qualitative and Quantitative Approaches in Program Evaluation. Ch 7 in tool-kit.
Rich, W. 1990. The Politics of Casino Gambling: Detroit Style. Urban Affairs Review. 26(2): 274-298.
Rivenbark, W. 1997. Taxation and Revenue Generation. Public Administration Quarterly. 24(2): 267.
Rivenbark, W. 1998. The Tax Incentive of Casino Gaming in Mississippi. Public Finance Quarterly. 26(6): 583-598.
123 Rivenbark, W. and B. Rounsaville. 1996. The Incidence of Casino Gaming Taxes in Mississippi: Setting the Stage. Public Administration Quarterly. 20: 129-142.
Rolling the Dice on the Delta: Mississippi Betting on Gambling as its Economic Saviour. 1994 January 7. From the State Capitals: The Outlook. 48: 1-4.
Room, R., N. Turner, and A. Ialomiteanu. 1999. Community Effects of the Opening of the Niagara Casino. Addiction. 94(10): 1449-1466.
Rose and Associates. 1998 November 5. The Regional Impacts of Casino Gambling: Assessment of the Literature and Establishment of a Research Agenda. Prepared for the National Gambling Impact Study Commission, Washington DC.
Rose, N. 1995. Gambling and the Law: Endless Fields of Dreams. In R. Tannenwald, ed. Casino Development: How Would Casinos Affect New England’s Economy? Special report no. 2, symposium proceedings. Federal Reserve Bank of Boston. Pp. 18-46.
Rosecrance, J. 1986. The Sociology of Casino Gamblers. Nevada Public Affairs Review. 2: 27-31.
Rosecrance, J. 1988. Gambling Without Guilt: The Legitimation of an American Pastime. Pacific Grove CA: Brooks/Cole Publishing Company.
Rothschild, S. 2002. Gaming Legislation Under New Scrutiny in Wake of State’s Financial Crunch. Lawrence Journal World. 25 February: B1, 3B.
Ryan, T. and J. Speyrer. 1999 April. Gambling in Louisiana: A Cost/Benefit Analysis. Prepared for the Louisiana Gaming Control Board. New Orleans: University of New Orleans.
Samuelson, P. 1976. Economics. 10 th ed. Englewood Cliffs: Prentice-Hall.
Sayer, A. 1979. Epistemology and Conceptions of People and Nature in Geography. Geoforum. 10: 19-44.
Sayer, A. 1985. Realism and Geography. In RJ Johnston, ed. The Future of Geography. London: Methuen. Pp. 159-173.
Sayer, A. 1992. Method in Social Science: A Realist Approach. 2 nd ed. London: Routledge.
Simurda, S. 1999. A Bad Gamble. The Nation. 268(24): 8.
Smith, D. 1987. Geography, Inequality, and Society . Cambridge, Cambridge University Press.
124 Smith, B. 1998. The Postmodern South: Racial Transformations and the Global Economy. In C. Hill and P. Beaver, eds. Cultural Diversity in the US South: Anthropological Contributions to a Region in Transition. Athens: The University of Georgia Press. Pp. 164-178.
Smith, G. and J. Azmier. 1997. Gambling and the Public Interest? Calgary: Canada West Foundations.
Smith, G. and H. Wynne. 1999. Gambling and Crime in Western Canada: Myth and Reality. Calgary: Canada West Foundations.
South Dakota Legislative Research Council. 1998. Economic and Fiscal Impacts of the South Dakota Gaming Industry. December 8: 1-145.
Sprott, D., A. Brumbaugh, and A. Miyazaki. 2001. Motivation and Ability as Predictors of Play Behavior in State Sponsored Lotteries: An Empirical Assessment of Psychological Control. Psychology and Marketing. 18(9): 973-983.
Stedham, Y., & Mitchell, M.C. 1996. Voluntary turnover among non-supervisory casino employees. Journal of Gambling Studies , 12(3): 269-290.
Sternleib, G. and J. Hughes. 1983. The Atlantic City Gamble. Cambridge: Harvard University Press.
Stitt, B., M. Nichols, and D. Giacopassi. 2000. Perceptions of the Extent of Problem Gambling Within New Casino Communities. Journal of Gambling Studies. 16(4): 433-451.
Stokowski, P. 1999. Social Impacts of Riverboat and Land-Based Non-Native American Casino Gaming. In C. Hsu, ed. Legalized Casino Gaming in the United States: The Economic and Social Impact. New York: The Haworth Hospitality Press. Pp. 233-251.
Stokowski, P. 1993. Undesirable Lag Effects in Tourist Destination Development: A Colorado Case Study. Journal of Travel Research. 32: 35-41.
Sylvester, K. 1992. Jackpot Fever. Governing. December: 23.
Teske, P., & Sur, B. 1991. Winners and losers: Politics, casino gambling, and development in Atlantic City. Policy Studies Review , 10(2/3): 130-137.
Thompson, W. and R. Gazel. 1998. Social Costs of Gambling: A Comparative Study of Nutmeg and Cheese State Gamblers. Paper prepared fro the 12 th National Conference on Problem Gambling. Las Vegas. 18 June.
125 Thompson, W., R. Gazel, and D. Rickman. 1996. The Social Costs of Gambling. In Wisconsin Policy Research Institute Report. July.
Thompson, W., R. Schwer, K. Hoyt, and D. Brosnan. 1993. Not in My Backyard: Las Vegas Residents Protest Casinos. Journal of Gambling Studies. 9: 47-62.
Tiebot, C. 1956. A Pure Theory of Local Expenditures. Journal of Political Economy. 64: 416-424.
Turner, N., A. Lalomiteanu, and R. Room. 1999. Checkered Expectations: Predictors of Approval of Opening a Casino in the Niagara Community. Journal of Gambling Studies. 15(1): 45-70.
Turner, W. 1994 November 5. Mississippi at the Breaking Point: Is Mississippi the Correct Model for the Gaming Industry in the 1990s? International Gaming and Wagering Business. 15: 32-33.
US General Accounting Office (USGAO). 2000. Impact of Gambling: Economic Effect More Measurable than Social Effects. USGAO: Washington DC.
Vand der Slik, J. 1990. Legalized gambling: Predatory policy, Illinois Issues, 10.
Vignola, M. 1992. Atlantic City: Challenge Prompts Change. New York: Salomon Brothers.
Volberg, R. 1997. Gambling and Problem Gambling in Colorado . Report to the Colorado Department of Revenue. Roaring Spring PA: Gemini Research.
Volberg, R., D. Gerstein, E. Christiansen, and J. Baldridge. 2001. Assessing Self- Reported Expenditures on Gambling. Managerial and Decision Economics. 22(1-3): 77-96.
Walker, D. 1998. Sin and Growth: The Effects of Legalized Gambling on State Economic Development. Published Dissertation. Auburn University.
Walker, D. and A. Barnett. 1999. The Social Costs of Gambling: An Economic Perspective. Journal of Gambling Studies. 15(3): 181-212.
Walker, D. and J. Jackson. 1998. New Goods and Economic Growth: Evidence from Legalized Gambling. Review of Regional Studies. 28(2): 47-69.
Walkoff, N. 1993. The Impact of Legalized Casino Gambling on Regional Economic Development: The Case of Atlantic City. Published Master’s Thesis. University of Nevada, Las Vegas.
126 Warker, K. 1988. Casino Gambling as Urban Development: A Case Study of the Political Economy of Atlantic City, New Jersey. Published Dissertation. University of Delaware.
Weatherson, M., T. Harte, H. Bochin, and J. Low. 1996. High Rollers vs. Holy Rollers: An Uncompromising Clash of Values Over Riverboat Gambling on the Mississippi. Paper prepared for the Speech Communication Association. San Diego. 24 November.
WEFA Group. 1994. The Effects of Casino Gaming on Consumer Spending. Bala Cynwyd PA: The WEFA Group.
Weissman, R. 1996. A Bad Bet: Casino Economics and the Politics of Gambling. Multinational Monitor. 17: 10-13.
Wicks, B. and K. Norman. 1996. Urban Riverboat Casino Planning: Including the African American Perspective. Journal of Travel Research. 34(3): 17-23.
Wynne, H., G. Smith, and D. Jacobs. 1996. Adolescent Gambling and Problem Gambling in Alberta. A report prepared for the Alberta Alcohol and Drug Abuse Commission. Edmonton, Alberta: Wynne Resources, Ltd.
127 CHAPTER 5
HISTORICAL FRAMEWORK
[History]… The importance of the task should not be undervalued, however, for its consequences are far reaching. Practically, it will enable us to work with a more realistic picture of geographical knowledge as a cultural product and a political resource… (Livingstone 1992: 3)
The process of and rationale for the “Tunica Miracle,” with casino development as the precursor for change, originated in the history of the region and the geography of place in Tunica County. The two provided the orientation and conditions that structured the possibilities for gambling and its subsequent development. However, the process and outcomes of that development have significantly been influenced by the economic, political, and social context of the local culture. The first part of this case study, therefore, is arranged around those themes, placing the development of the casino gaming industry within the broader framework of the area’s history. The remainder of this chapter offers a regional history of economy and poverty as it relates to Tunica County, including a discussion of key factors, such as those that fall under the auspices of race relations. In chapter 6, I go into greater detail about the growth of the gaming industry in
Tunica County, situating it within national, regional, and local politics.
5.1 THE PRE-CASINO SETTING 13
Tunica County represents the tradition of the rural South with its cotton belt heritage, yet it is in many ways much like other areas where natural resources have historically served as the means for making an economic livelihood. It is a place where
128 communities emerged to service those making use of the natural resource and in turn, whose social, economic, and demographic destiny was for the most part determined by the fate of the natural resource economy on which they so depended (Albrecht 1995;
Luloff and Swanson 1990).
A large body of research suggests that this dependence presents a consistent trajectory of decline, particularly with regard to lower levels of community stability relative to population trends, institutional structure, social conflict, and levels of well- being (Albrecht 1993; Beale 1974; Johansen and Fuguitt 1984; Krannich and Greider
1984; Machlis and Force 1988). Explanations for such instability are found in the lack of control over biological processes, depletion of the resource, technological change, and susceptibility to turns in national and international markets with respect to the resource on which they are dependent (Bernardi and Geisler 1984). Subsequently, it is understood that natural resource communities are imminently in decline.
Yet, it is also recognized that the intertwining of those natural, social, and economic processes is not altogether a matter of fate, but largely conditioned and manipulated by the political sphere, both formal and informal. While the literature on the former, such as federal policy initiatives, is diverse and extensive, there is a substantial gap in research on the latter, which would include power structures like that of the land- holding elite and the association with racial dynamics and industry investment
(Tomaskovic-Devey and Roscigno 1997).
Certainly, historical perspectives have done well to capture the relationship between natural resource ownership and the shaping of the economic environment as well
13 Pre-casino means prior to 1992. Thus, in order to keep the focus on the situation before casinos arrived, statistical information presented does not go beyond that date and in many cases only goes up to 1990
129 as the politics of race and class in conjunction (e.g., Billings 1979; Cobb 1993; Colclough
1988; Key 1950; Vance 1932). However, where this literature fails most is in projecting the inter-connectivity of those factors into the future (O’Connor 1992). History is not only a matter of history. The social, economic, and political processes that emerged around natural resource development and its control not only persist, but remain an influential force as those communities transition to other spheres of economic growth at present. As Gaventa noted in his study of Appalachia (1980):
In the contemporary situation, the local elite continue to play multiple roles, e.g. as brokers of political resources such as jobs or votes, as mediators of values and policies, and as 'gatekeepers' of information between the ‘inside’ and ‘outside’ worlds (259).
And if, within or beyond Appalachia, power relationships do impede challenge to social and economic inequalities, then theorists and practitioners of democracy should turn their energies to considering how the power relationships of contemporary society are to be altered if the social and economic deprivations of the people within it are to be overcome (261).
Thus, in this and the following chapter I lay out the groundwork for my argument that
Tunica County represents the critical case of the ‘contemporary situation’ defined by
Gaventa. I do so first with regard to historical context and then in relation to the recent growth in the gaming industry.
5.1.1 POPULATION TRENDS AND AGRICULTURAL TRANSFORMATION
Like that in other resource-dependent areas, the general population trend in
Tunica County has been one of decline. In fact, in 1990 the county population, which stood at just over 8,000, was nearly one-third of what it was in the 1950s. Such decline is
given census data. A comparison of figures ‘before’ and ‘after’ are presented in a later chapter.
130 typically viewed as evidence of the workings of the basic tenet of human ecology, which maintains that through fertility, mortality, and migration, the population will redistribute itself so as to achieve equilibrium between population size and life chances (Frisbie and
Poston 1975; 1978; Sly 1972). This explanation is used most when referring to the massive population movement that began at the tail of the Great Depression, when the development of labor-saving technologies significantly reduced human labor requirements in natural resource and other industries (Albrecht 1986; Dix 1988).
From 1940 to 1970 this trend was fairly widespread across non-metropolitan areas of the US, although more typically where natural resource based economies dominated
(Beale 1988; Frisbie and Poston 1975), and more so in the South (Lemann 1991; Marks
1989). Further, the loss of population from out-migration in natural resource-dependent areas made the potential for life chances in those communities more severe. The decline in the workforce meant lower levels of tax revenues and demand for services, resulting in the closure of businesses and a lack of investment in community infrastructure from social to physical capital (Bastow-Shoop et al. 1995). In turn, there is a strong association between population decline in natural resource economies and low levels of economic diversity and investment in human capital, such as by way of education. It is understood that the chance for prolonged economic instability is to a large extent manifested in place for natural resource based communities (Stokowski 1992).
However, it was not until after the 1970s, when a turnaround in non-metropolitan population change took place (Beale 1975; Fuguitt 1985; Stack 1996), that the stratification of non-metro counties became more prominent. Those least likely to achieve population growth were those areas where natural resource economies continued
131 to dominate. Among them, areas with major farming industries and high proportions of the workforce historically engaged in agriculture were the most likely to continue to experience population decline (Albrecht 1986; Albrecht and Murdock 1990; Beale 1988;
Bender et al. 1985). This trend in agricultural areas persisted through the 1980s in conjunction with the national farm crisis (Albrecht 1993; Albrecht et al. 1988; Beale and
Fuguit 1990; Johnson 1989; Richter 1985).
In Tunica, as elsewhere across the agricultural landscape, continuous out- migration was in a large part due to the modernization of agriculture, which took place in three stages in the alluvial Mississippi Valley 14 : the development and adaptation of tractors (1935-1946), mechanical cotton pickers (1948-1956), and herbicides (1955-1964)
(Aiken 1998). Modernization resulted in the undermining of traditional patterns of agricultural life and induced a concentration in southern landholding, as viewed by
Crawford (1994:103):
The main catalyst of change was the federal government, which through innovative policies… all but destroyed the farm tenure system that had evolved in the wake of the Civil War and whose most distinctive feature, sharecropping, had proved remarkably impervious to the momentous changes that were transforming rural society elsewhere in the United States. Those southern farmers able to take advantage of price supports and other New Deal programs belatedly discovered that the way to increased efficiency was through greater mechanization. As the cost of credit continued to decline, large landowners gradually abandoned the old labor-intensive methods and with them the sharecroppers and tenants upon whom they had traditionally relied. While the transition to capital-
14 The Mississippi Valley Alluvial Plain covers the entire western edge of the state of Mississippi, with Tunica County in the northernmost section of the state. It consists of the fertile lowlands that form a large part of the Alluvial Plain of the Mississippi River and is generally referred to as the “Delta.” The counties in this land region represent a subset of those designated as the Lower Mississippi River Delta by the federal government, also commonly known as the “Delta.” In this study I make no specific claim about what is legitimately the “Delta” and what is not. However, where policy and regional economic conditions are considered, I use the federal definition.
132 intensive farming was slow and uneven, it was inexorable…
This process of industry transformation was in many ways rooted in Tunica and neighboring Coahoma County where the area’s large landowners were among the innovators and initial users of tractors and mechanical cotton pickers (Aiken 1998; TCM
2003). The impact of this mechanization on population in those two counties is made clear in Figure 5.1, which shows a significant percentage decrease in population from
1950 to 1970 in absolute and cumulative terms. In fact, “between 1960 and 1970, Tunica
County suffered the largest population loss in the State of Mississippi—29.5% of its people” (TCM 2003 n.p.).
Figure 5.1. Population; Absolute and Cumulative Percent Change; United States, Mississippi, Coahoma County (MS), and Tunica County (MS), 1900-1990
Absolute Percent Change Cumulative Percent Change 40% 60%
30% 40% 20% 20% 10%
0% 0% 00-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 -10% -20% United States -20% United States Mississippi Mississippi -40% -30% Coahoma County Coahoma County Tunica County Tunica County -40% -60%
Data Source: US Bureau of the Census
In comparison, Table 5.1 gives unemployment rates for 1960 to 1990 census years. When stacked up against all counties in the nation and the Delta as well as neighboring Coahoma County, these figures suggest that the impact of agricultural transformation was gravest for Tunica County with respect to both mechanization (1960
133 to 1970 change) and farm crisis impacts (1980 to 1990 change). More specifically, from
1970 to 1980 and from 1980 to 1990, the county witnessed a farm employment decrease of 36.5 and 47.1 percent, respectively (US BEA 2002).
Despite the out-migration of those seeking employment elsewhere as a result, particularly the poor (Cloke 1992), individual poverty rates remained high ( see Table
5.2). By 1990 the ability of Tunica County households to obtain a sustainable earned income was significantly low, even by Mississippi standards ( see Table 5.3). For instance, according to 1990 Census Bureau estimates, the median household income in the state of Mississippi was $20,136 while in Tunica County it was just over half that, at
$10,965.
Table 5.1 Unemployment Rate; United States County Mean, Delta County Mean, Coahoma County (MS), and Tunica County (MS), 1960-1990 Year 1960 1970 1980 1990 US County Mean 5.18 4.52 7.4 6.19 Delta County Mean 6.08 6.18 9.23 8.36 Coahoma County 7.04 7.68 8.47 11.5 Tunica County 4.91 10.32 9.55 13.44 Data Source: US Bureau of the Census
Table 5.2. Percent of Persons Below Poverty; United States County Mean, Delta County Mean, Coahoma County (MS), and Tunica County (MS), 1960-1990
Year 1960 1970 1980 1990 US County Mean 34.37 21.01 15.83 16.74 Delta County Mean 52.35 34.19 23.36 25.54 Coahoma County 64.93 54.68 40.64 45.45 Tunica County 78.03 66.4 52.94 56.84 Data Source: US Bureau of the Census
134
Table 5.3 Percent Households by Income Type; Mississippi and Tunica County (MS), 1990 Income Type, Households... Mississippi Tunica County With earnings 76.0% 59.1% With wage or salary income 73.1% 57.6% With nonfarm self-employment income 9.8% 8.5% With farm self-employment income 2.5% 2.9% With interest, dividend, or net rental income 24.9% 7.1% With Social Security income 29.6% 40.3% With public assistance income 13.0% 40.0% With retirement income 12.8% 9.1% With other income 10.6% 17.4% Data Source: US Bureau of the Census Note: Percentages do not sum to 100 because of multiple income types per household.
Given the sharecropping heritage of the Delta and its transformation—which is
argued to have run counter to the interests of the poor, particularly with regard to the
consolidation of white land-holding power via manipulation of federal intervention and
the resultant marginalization of black farmers (Daniel 1972)—the employment and
income crisis that plagued Tunica County was mainly a condition of the black
community, which made up 74.5 percent of the population in Tunica County in 1990,
compared to 35.4 percent for the state of Mississippi (US Census 1990). The number of
unemployed blacks in 1990, male and female, was more than ten times that of whites ( see
Table 5.4). Further, income levels for black households loomed despairingly low ( see
Table 5.5), as the highest percentage of households fell into an income range well below
the 1990 federal poverty threshold for a family of two (i.e., $8,509; US Census 2002).
135 Table 5.4 Percent Race by Sex by Employment Status; Persons 16+ Years Old; Tunica County (MS), 1990 Employment Status Employed Unemployed Not in Labor Force White Male 66.8% 0.9% 32.2% White Female 42.9% 1.3% 55.8% Black Male 43.4% 10.9% 45.6% Black Female 35.2% 13.1% 51.6% Data Source: US Bureau of the Census
Table 5.5 Percent Race of Householder by Household Income; Black and White Population; Tunica County (MS),1990 Income Range White Black Less than $5,000 8.2% 23.7% $5,000 to $9,999 11.3% 20.9% $10,000 to $14,999 10.8% 14.6% $15,000 to $24,999 19.9% 19.3% $25,000 to $34,999 16.7% 10.6% $35,000 to $49,999 16.7% 7.0% $50,000 to $74,999 11.3% 3.0% $75,000 to $99,999 2.8% 0.5% $100,000 or more 2.3% 0.3% Data Source: US Bureau of the Census
However, by 1990 the prospects for sustained economic health in Tunica County were not very promising for even the landed-elite, that is, the planters, the predominantly white segment of the county population who had been the beneficiaries of mechanization.
Looking for ways to remain competitive in an increasingly global industry, many Tunica
County planters had invested heavily in the growth of soybeans, a crop that had always been present in the Delta, but mainly for secondary rather than profitable use (e.g., crop rotation). Increased demand for soybeans around the world and modernization of the industry since the 1960s allowed for the adoption of the highly mechanized methods necessary to make soybeans a major crop for the area.
Despite such maneuvering, among other things, rapid increases in land prices, machinery investment, and debt in the 1970s set the course for the inevitable crash in the
136 agricultural market in the 1980s ( Policy Matters 1999). That downturn hit the Delta as it did the rest of the nation. In Tunica, it was intensified by the bottoming out in soybean prices and tumbling land values (Barkema 1999). Tunica landowners tried to recover, in part, by expanding in other areas, such as in catfish and rice production, but the situation at the start of the 1990s was rather bleak for all in the county. As one former planter recalled:
…. prior to the casinos even the big landholders were in trouble, agriculture was real bad, a lot had sunk money into soybeans and that market went sour, add that to the problems of agriculture around the nation, things weren’t good. When the casinos came in those landholders were able to profit in a big way, it really saved them. If the casinos hadn’t come who knows what would’ve happened, Tunica probably would have been worse off than ever today. (Field Notes A/B 2003) 15
5.1.1.1 SECTION SUMMARY
The aforementioned comments of the Tunica County resident as well as the general discussion in this section speak to a basic tenet of globalization. That is, as natural resource-based commodities become entrenched in the global market (Albrecht
1995) and as the rural South increasingly becomes a part of the mainstream of national and international structures (Hill 1998), creating cross-currents of opportunity and dispossession (Smith 1998), the risk of economic instability of Delta communities intensifies. As such, in order to guard against that likelihood, those communities must
15 The majority of my interviewees requested to remain anonymous, and therefore, refused to consent to the use of their name in any form in the written representation of my research—in fact, there was a unitary outward expression of distrust, particularly of the written media. As such, in order to make use of the rich information that those individuals provided, I use the documentation field notes to represent those individuals whom I interviewed. For the benefit of the reader, I categorize that documentation in the following way: A = land owner, B = county or town official, C = community advocate, D = other (e.g. county resident not one of the former). Also, I conducted my research over the course of four years, consisting of five field visits, therefore, the year of the visit is also given in the citation.
137 find the ways and means to diversify and strengthen the structure of their economy.
However, the implications of such transformation, as rooted in agrarian political economy and the rural restructuring thesis (Marsden et al. 1990), are that uneven development will persist and poverty will become more deeply engrained in society
(Lobao and Schulman 1991; O’Hare 1988).
The direct effects of agriculture’s incorporation into late capitalism are impacts to farm structure and economic well-being (Buttel et al. 1988; Flora and Flora 1988; Skees and Swanson 1988). Indirectly, there are impacts to local aspects of socio-economic well-being, such as the balance between social relations and economic structure (Falk and
Lyson 1988; Lobao 1990; Tomaskovic-Devey 1988, 1987). Where “late and early capitalism meet… the human consequence can be profound economic insecurity and a reduced standard of living” (Smith 1998: 170-171). In sum, the search for solutions moves beyond the economic base, transforming economic contradictions into crises within the political and cultural spheres of society (Habermas 1975).
Up to this point, only one side of that coin has been considered, farm structure and economic well-being, which only gets us part of the way toward understanding the conditions that prevailed in Tunica County when the opportunity for casino development arrived. More specifically, the discussion thus far helps us to understand the regional, and to some extent local, economic situation and its links to poverty, but it does not fully explain Tunica County’s position as the sickest within the region. Therefore, in the next section I attempt to capture the more complex historical associations between social relations (i.e., race and class relations) and economic structure, both regionally and locally.
138 5.1.2 SOCIAL RELATIONS AND ECONOMIC STRUCTURE
Social relations in the Delta have historically been tied to economic structure, with the distinctiveness of the region encapsulated in its agricultural economy, class structure, and the divisiveness of race (Cobb 1992; Stokes and Halpern 1994). This is thought to be particularly true of Mississippi, where the element of race is believed to have stunted economic development, lending to its history as one of the poorest states in the nation. Beginning with institutionalized slavery, racist ideologies grew and remain embedded in the social and economic fabric of the Mississippi Delta (Fields 1982;
Williamson 1984). Among white southerners, whiteness , above all else, has historically been regarded as a measure of an individual’s self-worth and entitlement to a certain level of well-being (Feagin 1989). These ethnocentric and stereotypical attitudes toward blacks emerged in the paternalistic behaviors that help define the history of southern culture: “Beneath the rot of prejudice—ethnocentrism, racism, and even class elitism— from which such stigmas fester, has always been cultural difference, real and perceived”
(Davis 2001: 4).
While white southerners are defensive and impatient with that which continues to damn southern race relations (Davis 2001), evidence suggests that blacks are still regarded as second-class citizens by the quality and quantity of both educational and occupational opportunities made available to them in relation to those more accessible by whites. For instance, in 1985 in Tunica, although the US District Court dismissed the charges, the state NAACP filed suit against Tunica County Schools citing discrimination and constitutional rights violations (TCM 2003). Admittedly, such conditions did and continue to exist, as the situation regarding civil rights and education reads in the Tunica
139 County Museum (2003) with respect to the limited education options for area-wide residents of the county’s only municipality:
Not every white family could afford TIL’s tuition [Tunica’s private school]. Some attended public schools in Tate and DeSoto Counties, others enrolled at the Sacred Heart Mission Catholic School of Walls, MS, and several white families chose to move out of Tunica County. Judge Keady’s famous order to desegregate (Dec. 1969) produced the opposite effect of its intention. It brought about a total resegregation that still exists.
By 1994, the Tunica Institute of Learning (TIL) had 241 students in 12 grades with 20 teachers. The public schools, where the majority of black students were enrolled, were huge. Rosa Fort had a total of 1993 students, only 21 of them white, and 110 teachers.
However, that is not enough to understand the extent of educational deprivation for blacks in Tunica County and its historical relationship to economic structure. It is also important to begin to note the issue of planter persistence and white elitism at its core (Stokes and Halpern 1994), that is, the manner in which planters have retained their elitist position by maintaining economic and political control over societal outcomes
(Billings 1979; Wiener 1978; Williamson 1984).
… it has always been and is still about control, control of the land and the labor force that goes along with it. Each of the little towns (enclaves) around the county, including the Town of Tunica, began as the center of a landholding… where the workers (slaves, sharecroppers, hired laborers, etc.), lived, where the commissary was that they bought their goods (owned by the landholder), where the school was—also owned and run by the landholder, whom only educated them up to the 8 th grade at the most. (Field Notes A/B 2003)
In the 1960s they centralized the schools and got rid of most of the independent schools by the 1980s, so that took care of that, but the education was still poor and still is—
140 Tunica schools were on probation, taken over by the state, who couldn’t do anything to fix the problem, so they lowered the standards in order to get the school district off of probation. (Field Notes A/B 2003)
Thus, from the standpoint of formal education, reasonable investment in human capital has continuously been lacking in Tunica. Where resources were scarce, the choice of who would derive the benefit, no matter how limited, was clearly set along racial lines. Further, the more recent legitimization of a low-quality education for blacks in Tunica by the state of Mississippi has absolved all but the poor themselves of responsibility for the outcome.
In terms of economic development, this suggests little chance that the area’s labor force would be competitive in the global market, even where low-skilled labor is in demand. The educational level of the majority of the population in Tunica County in
1990 was exceptionally low; the educational attainment of the county’s black population
25 years and older stood at 59.6 percent with less than a 9th grade education (US Census
1990). Because of this and similar situations elsewhere in the Delta, for many southern blacks, impoverishment was and still is an unavoidable state (Davis 2001). However, ironically, it was mainly during the Civil Rights era that the persistently poor conditions of the South were set in place.
5.1.2.1 CIVIL RIGHTS AND ECONOMIC DEVELOPMENT
During the 1950s and 1960s the South desperately sought economic development and affluence in line with that being experienced in other regions of the nation (Gray-Ray
1992). Yet, the intensified and embattled social situation of the Civil Rights movement raised the stakes and incited a forceful response on a number of levels, including
141 political, economic, legal, and extra-legal (Ward 1994). On the economic front, this blocked multiple facets of growth, particularly in rural areas of the Delta, thereby putting the region even further behind all others. For instance, although southern states had begun to realize and engage in industrial recruitment (Wright 1986), the mounting of
Civil Rights tensions and their worldwide attraction via the media led to a shying away of industry from the South. Cobb (1993: 122-123) documented this situation in detail:
… in 1955, there were ominous reports that industrialists were reconsidering their plans to open new plants in Dixie. A large manufacturer of electrical equipment refused to construct a new facility in Georgia… a spokesman explained, “They all have families and while they like the area, they didn’t want to move into a mess about schools, social segregation, etc.” Explaining that they could not expect employees to accept Kentucky’s racial customs, executives of a business machines firm decided to put its new plant in New York instead… Fantus Factory Locating Service reported in May, 1956, that at least twenty major factory moving projects were being “seriously reconsidered in light of the situation in the South.”
By the 1960s the situation had in many instances only changed for the worse. In
1962, outrage over the admittance of a black student to the University of Mississippi led to the urging of the governor for whites to stand up against the federal government.
Added to that was the occasional violence. In toto, all of this reinforced images of
Mississippi as “the most savage and backward of the southern states” and further
“seemed certain to undermine the state’s efforts to attract industry” (Cobb 1992: 134).
Evidence to support this position is also presented by Cobb, and found in executive statements like: “We won’t consider expanding in Mississippi again until the state and its people join the Union again” (135); and in reports of double-digit firm loss in 1964 alone,
142 including one firm that moved just over the Louisiana state line to avoid a Mississippi address.
In essence, much of the South lost out on industrial development during the Civil
Rights era, but the Mississippi Delta, especially the state of Mississippi, stood out as the best example of resistance to social change and that which paid the greatest price economically (Gray-Ray 1992). This situation persisted even after the social stigma had begun to lift in the eyes of industry in the 1970s because the lack of investment in the prior two decades set a course that rendered the prospects for future economic development unlikely. As former Mississippi Governor Winter saw it in 1985:
There remains the other South [the Delta], largely rural, undereducated, and under-productive and underpaid, that threatens to become a permanent shadow of distress and deprivation in a region that less than a decade ago had promised it better days. (in Rosenfeld 1988 n.p.)
That promise of better days included the opening up of employment opportunities for blacks from a legal perspective (Gray-Ray 1992), but while Civil Rights laws may have banned public discrimination, southern blacks continued to suffer economically at the hands of industry, local elites, unions, and the government (Cobb 1993; Edds 1987;
Payne 1991; Williams 1991; Wood 1987). Federal anti-discrimination policies such as affirmative action were meaningless because they provided assistance to the black middle class, which was virtually absent from the rural Mississippi Delta, and intervention on behalf of blacks by unions was nonsensical as they contended with their own form of racism (Feagin 1989; Turner et al. 1984).
In addition, the implementation of Civil Rights in government agencies, such as the USDA (within the context of the Farmers Home Administration—FmHA), further
143 reinforced the power of the white elite through the old boy bureaucracy (Sinclair 1987a;
1987b). Contrasting the similarity of such reports to the US Commission on Civil Rights since 1965 (e.g., USCCR 1965), in a recent report it was written:
For more than 100 years—and particularly during the past 30 years—the US Department of Agriculture has administered federally funded programs designed to improve almost every aspect of the lives of low-income farm and rural families… As the group most depressed economically, most deprived educationally, and most oppressed socially, Negroes have been consistently denied access to many [agricultural] services, provided with inferior services when served, and segregated in federally financed agricultural programs whose very task was to raise their standard of living. (USCCR 2001: 18)
At the local level, following the Civil Rights era, in the Delta such exploitation, corruption, and racism remained paramount. The veracity of the situation in Tunica is best described by the story of a black farmer who sought to grow rice in Tunica in 1977 and found himself encompassed “in a network of racism” (Daniel 1994: 100):
Woodard went to the county agent to get advice. “And they told me: ‘Can’t no nigger grow no rice, Henry.’” Woodard persisted, so the county agent suggested he talk to the owner of the grain elevator. “And I went and talked with him. He told me, ‘Naw, I ain’t got no room for your rice.’” Again Woodard persisted. Finally the grain elevator owner told him, “Go on and plant it but when I get through docking you, you’ll hate you ever saw rice.” The next year he planted rice and contracted to have a crop duster apply chemicals. A friend who worked at the flying service told him “you ain’t getting your chemicals. They’re flying over you, but it’s not in there.” In 1982, his rice well burned, but the interview ended before he could explain the circumstances… At the time of the interview Woodard owed FmHA $228,000. (101) 16
16 Interview with Henry Woodard, Tunica, MS, 5 October 1987, by L. Jones, Oral History of Southern Agriculture, NMAH, as it appears in Daniel 1994.
144 5.1.2.1.1 INDUSTRY CHANGE
With respect to industry other than agriculture, new and expanding firms tended to locate in southern places with low percentages of blacks for reasons of racial divide as well as labor force skill levels, thereby eliminating prospects for most communities in
Mississippi (Rosenfeld et al. 1985; Swanson 1988; Timberlake et al. 1991; Walker 1977).
This created a situation that reinforced the racialized political economy that was in part spurred by New Deal farm policy, as Smith (1998: 168-169) explains:
Industrial employment opportunities, above all in textiles, left the power relations of race undisturbed—indeed, reinforced—by providing economic alternatives to impoverished white farmers while denying them to their rural black neighbors. It is not surprising that this route of economic development did not alter the South’s status as the poorest region of the United States, for it was based on maintaining the relative impoverishment of the southern working class.
Despite those circumstances, Tunica County was able to diversify its economy in a fashion that would bring it on par with the rest of the nation by 1986. This is evident when considering a standard diversity index taken as a measure of farm employment and employment in private industry (e.g. manufacturing, construction, etc.); where higher values reflect higher degrees of economic diversity ( see Figure 5.2, Diversity Index
Values). However, those figures can be misleading without taking into account the fact that diversification was largely within the natural resource-based domain. Where Tunica was able to diversify was in growth in the catfish industry, as heavily supported by the federal government (Lord 1990; Pfeffer and Gilbert 1989) and mainly characterized by seasonal employees who receive little to no benefits or profits (Gillette 1998; Jones
1996).
145 Figure 5.2 Comparative Diversity Index Values and Location Quotients; Tunica County (MS), 1969-1989
Diversity Index Values Location Quotients 90 14.00
12.00 85
10.00
80 8.00 LQ Farm Employment Tunica Co./ US 6.00 75 LQ Ag, Fishing, & Forestry Svcs Employment Tunica Co. / US United States Delta Co. Mean 4.00 70 Mississippi Tunica County 2.00
65 0.00
1970 1971 1972 1973 1974 1978 1979 1984 1985 1986 1987 1988 1989 69 73 75 79 81 87 89 19 1971 19 19 1977 19 19 1983 1985 19 19
Data Source: Bureau of Economic Analysis
With that in mind, despite its own losses in farm employment (i.e., a 92.5% cumulative loss in farm employment from 1969 to 1990), Tunica was able to maintain its stronghold as one of the nation’s most concentrated areas of agricultural employment.
This is shown alongside the diversity index, as measured by employment based location quotient values greater than ~1.25 ( see Figure 5.2). In contrast, on an annual basis,
Tunica County had a cumulative loss in full- and part-time employment of 38.4 percent from 1969 to 1990, and where reasonable gains were had in private industry (e.g. 53.8% increase in manufacturing), they were matched by equally devastating losses (e.g., 65.1% reduction in services) (US BEA 2001).
Thus, the structure of Tunica’s economy had changed little from the Civil Rights era to the time casinos entered as a potential means for diversification. This was in part controlled by the traditional white elites who opposed the recruitment of businesses that were viewed as a threat to the status quo. This included not only competition for pre- existing establishments, but also by way of improvement to the circumstances faced by
146 the black population (Cobb 1984; James 1988; Lichter 1988; Rungeling et al 1977;
Wright 1986). As was similarly noted in a report published in conjunction with the US
Commission on Civil Rights (2001: 11):
… some prosperous white Deltans have no desire to see their black neighbors improve their economic circumstances, the seemingly insoluble and intractable poverty, the region’s historic discrimination, and its nearly total economic and social separation of citizens along racial lines—all of which have contributed to the current economic condition of black Deltan residents….
Given that and all that has been presented thus far, a Tunica County resident does well to sum up the situation at the start of the 1990s (Field Notes B 2003):
The middle class that did exist first moved out during the great migration that followed the flood in the 1920’s in combination with the depression. Later, during the 1950s and 1960s white middle class fled because of the education/segregation situation. Those that remained were either wealthy (and white) or poor (and black). The mechanization of farming at the same time elevated the situation, more of the working class whites left and the poor blacks remained with little to no work. Manufacturing had failed to develop as an industry largely because of the control of the landholders who didn’t want the competition for labor and who wanted things their way. So there were no jobs in Tunica, virtually none from the 1960s until the casinos in the early 1990s.
This situation facilitated the introduction of new disparities between the southern rich and poor, urban and rural (Beaulieu 1988; Lyson 1989). In that respect, Applebome
(1995) found that even in economically stable and racially mixed southern towns, where there was a concentration of the black population, they were predominantly poor. He likened these places to a new kind of rural ghetto, that which “incorporates the racism of the old South in a new form that employs economic deprivation rather than Jim Crow
147 laws” (Hill 1998: 5). Aiken (1990, 1998) found this to be similarly true of Tunica, where local elite control over development extended to the residential sphere.
5.1.2.2 RESIDENTIAL PATTERNS, CONDITIONS, AND POLITICS
Nucleation of the black population in Tunica County followed two paths of development, both having to do with agricultural transformation. The first was centered on the plantation as it progressed into sharecropping and tenant farming. Thus, in the early 1960s, aside from a few family farms, the only residential concentrations in the northern part of the county were on the modern plantations (e.g., Kirby, Abby-
Leatherman, and Bowdre) and in the unincorporated village of Robinsonville, later to become the site of casino development. Most of the housing structures were tenant/sharecropper homes, some of which remain today near Bowdre farms, which is one of the few former plantations still in operation (Field Notes D 2001).
Relocation of the black population of Tunica came with the demise of labor- intensive agriculture and took place not only in the form of migration, but also by the redefining of residential space within the county (Aiken 1985). By the mid-1960s hamlets began to emerge along the boundaries of the plantations, largely centered around the extended black family, aside from the Rainbow Subdivision that was developed for black occupancy by a white individual (Aiken 1998). Thus, despite the fact that few employment opportunities in the county served as the alternative to the dwindling prospects for work on the farms, for the most part, people (i.e., the black population) remained in place. As noted by one Tunica County resident:
…the groupings of houses remained and nobody had anywhere else to go even after there was no more work on
148 the farm. So to this day, those enclaves of poverty exist… Robinsonville, Hollywood, etc., it’s just what remains of the agricultural system along with the mindset—which is for the landowners to maintain control. (Field Notes A 2003)
The second path of residential development, which is related to the first but of a somewhat different form, had to do with the displacement of black farmers (e.g., due to foreclosures) and laborers following mechanization and changes in FmHA funding, and the need to provide them with alternative living spaces in addition to work arrangements
(Brown et al. 1994; USCCR 1982). As the black farmer quoted previously recalled:
The peak years, he remembered, were during the civil rights movement: “that’s when they went tearing the houses down and moving us off the farm.” At the time of the interview in 1987, only fifteen black farmers were left in the county. In earlier years, FmHA “was doing the furnishing,” but “to my knowledge, hasn’t furnished any black farmer in Tunica this year.” (Daniel 1994: 100)
The majority of the houses torn down were abandoned and/or in disrepair. A number of them remained in occupancy, despite their condition, by housing day laborers and machine operators whose wages were barely at the subsistence level (Aiken 1998). As the push out of the cotton fields continued many moved to FmHA-sponsored housing.
An example of that housing is the 180-house development known as White Oak, which was built in the late 1970s to harbor the blacks as they exited the farms, and by 1990 would come to house one-seventh of the county’s black population (Aiken 1998).
Ironically, and quite purposely (Field Notes C 2002), White Oak was built three miles outside the town of Tunica, isolated from the town by fields of cotton, rice, and soybeans—both then and now, save a few nearby catfish ponds.
149 Still, others moved to the fringe of the town, some bringing their shacks with them to join older black neighborhoods, such as Sugar Ditch, and other adjoining enclaves in North Tunica (Field Notes C 2002). The concentration of black population in
North Tunica, a census-designated place, sits just outside municipal boundaries and represents what Aiken (1987; 1998) refers to as municipal underbounding . “Blacks in the suburban fringes seek annexation only to be resisted by white-controlled governments” (Aiken 1998: 321). In a study of that phenomenon in the southern plantation region, Aiken (1987) found that Tunica represented the quintessential case of discrimination against blacks involving municipal underbounding.
5.1.2.2.1 SUGAR DITCH AND RACIAL DISPARITIES
Sugar Ditch, as noted previously, was a black residential area in which the living conditions of the poor were akin to the poverty of developing nations. Their plight was given national attention when Jesse Jackson headed-up a documentary of Tunica in 1985.
As a result of the attention brought to Sugar Ditch by the broadcast, the town of Tunica acquired the property, set the residents in temporary housing facilities (trailers), tore down the houses, and lined the ditch with cement and enclosed it with a chain-link fence and barbed wire (TCM 2003). That was followed by the construction of a 48-unit development for the elderly and disabled in Sugar Ditch’s place. Of those 70 or so residents who were displaced in the process, many were relocated over the next several years, largely by way of state and federal assistance. By 1990 about sixteen former Sugar
Ditch families remained in condemned shacks (Christion 1991).
150 What happened in the Sugar Ditch case scenario stands as evidence of the lack of commitment to assisting in improving the long-term living standards of blacks by county and town officials and other local elites. “At best, they did what they did to save face and went only as far as they had to go” (Field Notes C 2003). In fact, in an exhibit in the
Tunica County Museum that recalls the incident, the level of accountability is transferred first to the property owners with respect to the reason for conditions being as they were, in language such as “despite the availability of town water and sewer lines… landlords had not connected to these available city utilities” (2003; my emphasis). Then there is the hint of exaggeration, unfairness, and even exploitation of the media in reporting the circumstances, such as: “The documentary startled the nation and electrified Tunica with its vivid language, tough interviews with unsuspecting local citizens, and shots of shacks with roach infested rooms.”
Finally, there is the apparent lack of accountability on the part of Rev. Jackson, which is not being debated here. Rather, it is interesting to note as a focal point in the representation of Tunica County history, as written and advanced in the public domain by a predominantly white group of museum officials, many of whom were former or current landowners.
Rev. Jesse Jackson made two walks the length of Sugar Ditch, trailed by numerous reporters, TV cameras, and crowds of supporters. At a pep rally held at the Rosa Fort gymnasium and attended by hundreds, a collection of some $3,700 was made. “Then Rev. Jackson and his entourage got in their cars and drove away. Neither Rev. Jackson nor the money was seen again in Tunica,” according to Clifford Granberry, former head of Tunica County School Board.
The point here is not to wholly criticize, but to emphasize the extreme sensitivity within Tunica County, particularly among the whites, to what is perceived as the self-
151 righteousness of outsiders. Further, interventions by outsiders (e.g., federal investigators, researchers, evangelists, etc.) are typically viewed as an assault on the community. This predilection is best stated by Davis (2001: 17), in reference to his research in Natchez, where he found similar expressions of defensiveness, both subtle and overt:
It was not surprising to learn that white Mississippians often exhibit a defensive side to their personality. They still see their state as the “whipping boy” of a duplicitous nation unable to solve its own race problem. In some ways their observation is justified (though behavior of the past certainly is not)… But from the standpoint of the white southerner, the defensive personality is shielding those closest to it from gratuitous vilification: distortions, exaggeration, innuendoes, bald-faced lies, or anything else that might unfairly sully a personal reputation, a family name, or the regional image. In Mississippi, the defensive personality most often arises when dealing with the state’s record on race. 17
Despite the location of responsibility for Sugar Ditch or similar cases, it cannot be denied that by 1990 the differential circumstances within the county remained extreme, that is, between the predominantly white town of Tunica and black residential enclaves throughout the county. Given data limitations, it is difficult to obtain a measure of this difference other than between North Tunica and the town of Tunica. 18 Table 5.6 provides some summary statistics for comparison. It is clear, for example, that a substantial percentage of the county’s black population was concentrated in North Tunica. North
Tunica was almost wholly composed of that population group, 72 percent of whom were poor. A large majority of black households had an income level below 50 percent of the
17 Over the course of my research in Tunica County the issue of white defensiveness was quite apparent in the nature of interviews of community leaders, their willingness to share information; and the selection and presentation of that information. Further, once I stepped outside that circle in attempting to gain alternative perspectives, those doors closed, that is, access to what was previously made available to me in terms of people and data became problematic. In addition, I received direct communication from one person in a position of power warning me of the tendency for those outside the community to misrepresent the situation and expressing concern that I might do the same.
152 poverty level of income (39%). Further, the living arrangement of many North Tunica residents could be defined by overcrowded housing with few amenities, considering the number of persons per household and housing value, and the condition of the housing stock for the black population. It was generally known to be worse off than that of their white counterparts (Field Notes C 2002; McCray 1990).
Table 5.6 Select Individual- and Household-level Statistics for Comparison; North Tunica CDP (MS) and Town of Tunica (MS), 1990
1990 N. Tunica CDP Town of Tunica Population Black: Percent of County 19.5% 5.1% Percent of Place 90.2% 26.1% Persons Below Poverty: Total Population 68.6% 28.6% Black Persons 72.0% 77.3% White Persons 6.1% 10.4% Income: Households w/Income Below .50 Poverty 39.0% 16.6% Population w/Income less than $5000 40.3% 6.0% Median Household Income $7,507 $18,843 Housing: Housing Value less than $15,000 20.1% 1.2% 7 or More Persons per Household 12.6% 2.4% Unemployed: Black & White Persons 15.2% 4.3% Black Persons 16.3% 13.9% White Persons 0.0% 1.6% Educational Attainment Age 25+ Less Than 9th Grade: Black & White Persons 32.0% 16.4% Black Persons 34.0% 42.1% White Persons 0.0% 10.3% Educational Attainment Age 25+ 9th-12th, No Diploma: Black & White Persons 26.5% 14.7% Black Persons 28.1% 26.2% White Persons 0.0% 12.0% Data Source: US Bureau of the Census
18 Place-level census data are only available for North Tunica (CDP) and the town of Tunica for 1990.
153 The black population in the town of Tunica did not fare much better, but overall income circumstances were not nearly as grave. For instance, the black poverty rate may have been higher in the town, yet fewer had exceptionally low income levels in comparison to North Tunica residents. Still, there is an obvious split between levels of well-being between blacks and whites in the town of Tunica in 1990. The racial disparity among poverty, income, unemployment, and education rates suggest that low levels of attainment were distinctly a black, not a white, problem for the town.
Additionally, looking at unemployment for all between the two places, the propensity for townspeople to be unemployed was less than a third of what it was for those in North Tunica. In relation, the life chances of the majority residing in North
Tunica in obtaining employment that would provide a sustainable income were not promising––58.5 percent of the total population and 62.1 percent of the black population with an education level below a high school degree.
5.2 CHAPTER SUMMARY
Numerous studies reveal that the Delta has always been the poorest region of the
South, if not the poorest in the United States. The prevalence of the situation has largely been due to its peripheral position in regional, national, and international economies
(Hyland and Timberlake 1993; Kodras 1997). Within that context the landholding elite have minimized human capital investments and constrained industry development opportunities in order to maintain control over economic and political forces that might otherwise improve the conditions of the largely black poverty population (Johnson 1994;
Swanson 1988).
154 In this chapter, I laid out the region’s path within the broader economy and touched upon those factors of underdevelopment, inequality, and racism that left the region, and more specifically Tunica County, with limited economic resources, insufficient employment opportunities, inadequate housing, and poor quality education, at the time of pre-casino development. In so doing, I have highlighted the debilitating legacy of sharecropping that set the course for the economic, political, and residential disenfranchisement of blacks, only to contribute to the concentration of wealth and power in the hands of the minority white population.
Given that historical progression, the power of the landed elite, via various avenues of planter persistence such as racial exclusion and class politics, has been the most significant factor in determining the present economic position of the Delta. More definitively, Dill and Williams (1992: 104) purported that the Delta economy is “the conscious construction of the rural White elite,” whom “accumulate large profits that are then invested in small amounts in their own communities.” In the case of Tunica, it is important to tease out the inherent controversies of such forms of nonrepresentational politics in the growth of the gaming industry, its distributional outcomes, and the prospects for future development.
Discussion of the latter two points is for the most part reserved for later chapters.
The former is presented in the next chapter in line with the incision of gaming into the
Tunica County economy. However, obtaining an understanding of the local dynamics necessitates consideration of other contingent factors, such as industry-wide trends, geographic context, and state and national politics. Therefore, chapter 6 provides an overview of the conditions that set forth the opportunity for casino gaming in Tunica
155 County, the manner in which that opportunity was seized, and the developmental outcome with respect to the local embeddedness of the industry.
5.3 CHAPTER REFERENCES
Aiken, C. 1985. New Settlement Patterns of Rural Blacks in the American South. Geographical Review. 75(4): 383-404.
Aiken, C. 1987. Race as a Factor of Municipal Underbounding. Annals of the Association of American Geographers. 77(4): 564-579.
Aiken, C. 1990. A New Type of Black Ghetto in the Plantation South. Annals of the Association of American Geographers. 80(2): 223-246.
Aiken, C. 1998. The Cotton Plantation South Since the Civil War. Baltimore: The Johns Hopkins University Press.
Albrecht, D. 1986. Agriculture Dependence and the Population Turnaround: Evidence from the Great Plains. Journal of the Community Development Society. 17(1): 1- 15.
Albrecht, D. 1993. The Renewal of Population Loss in the Nonmetropolitan Great Plains. Rural Sociology. 58(2): 233-246.
Albrecht, D. 1995. Population Trends in Resource-Dependent Counties. Journal of the Community Development Society. 26(2): 155-168.
Albrecht, D. and S. Murdock. 1990. The Sociology of US Agriculture: An Ecological Perspective. Ames IA: Iowa State University Press.
Albrecht, D., S. Murdock, K. Schiflett, R. Hamm, F. Leistritz, and B. Eckstrom. 1988. The Consequences of the Farm Crisis for Rural Communities. Journal of Community Development Society. 19(2): 119-135.
Applebome, P. 1995. Deep South and Down Home, But It’s a Ghetto All the Same. New York Times. August 20: 1, 6.
Barkema, A. 1999 November. Sizing Up the Farm Downtown. The Main Street Economist Commentary on the Rural Economy. Center for the Study of Rural American, Federal Reserve Bank of Kansas City.
156 Baruffalo, R. 2000. Local Politics/Outside Interests: An Analysis of Gambling Proposals, Referendums, and Economic Development in Three Mississippi Counties. Published dissertation, University of Kentucky. Lexington, Kentucky.
Bastow-Shoop, H., F. Leistritz, L. Jolly, R. Kean, L. Gaskill, C. Jasper, and B. Sternquist. 1995. Factors Affecting the Financial Viability of Rural Retail Businesses. Journal of Community Development Society. 26(2): 169-188.
Beale, C. 1974. Rural Development: Population and Settlement Prospects. Journal of Soil and Water Conservation. 29(January-February): 23-27.
Beale, C. 1975. The Revival of Population Growth in Nonmetropolitan America. Economic Research Service, ERS-605. Washington DC: US Department of Agriculture.
Beale, C. 1988. Americans Heading for the Cities Once Again. Rural Development Perspectives. 4(4): 4-8.
Beale, C. and G. Fuguitt. 1990. Decade of Pessimistic Nonmetropolitan Population Trends Ends on an Optimistic Note. Rural Development Perspectives. 6: 14-18.
Beaulieu, L., ed. 1988. The Rural South in Crisis: Challenges for the Future. Boulder: Westview Press.
Bender, L., B. Green, T. Hady, J. Kuchn, M. Nelson, L. Perkinson, and P. Ross. 1985. The Diverse Social and Economic Structure of Nonmetropolitan America. Economic Research Service, Rural Development Research Report Number 49. Washington DC: US Department of Agriculture.
Bernardi, G. and C. Geisler. 1984. The Social Consequences and Challenges of New Agricultural Technologies. Boulder: Westview Press.
Billings, D. 1979. Planters and the Making of the ‘New South’; Class, Politics, and Development in North Carolina, 1865-1900. Chapel Hill: University of North Carolina.
Brown, A., R. Christy, and T. Gebremedhin. 1994. Structural Changes in US Agriculture: Implications for African American Farmers. The Review of Black Political Economy. Spring: 52.
Buttel, F., M. Lancelle, and D. Lee. 1988. Farm Structure and Rural Communities in the Northeast. In L. Swanson, ed. Agriculture and Community Change in the US: The Congressional Research Reports. Boulder: Westview Press. Pp. 181-237.
Christion, C. 1991. Tunica’s Sugar Ditch Fades Into the Past. The Commercial Appeal. 8 March: B1.
157
Cloke, P. 1992. Rural Poverty: Some Initial Thoughts on Culture and the Underclass. In I. Bowler, C. Bryant, and M. Nellis, eds. Contemporary Rural Systems in Transition, Volume 2, Economy and Society. London: CAB International. Pp. 29-45.
Cobb, J. 1984. Industrialization and Southern Society, 1877-1984. Lexington: University Press of Kentucky.
Cobb, J. 1992. The Most Southern Place on Earth: The Mississippi Delta and the Roots of Regional Identity. New York: Oxford University Press.
Cobb, J. 1993. The Selling of the South: The Southern Crusade for Industrial Development 1936-1990. Chicago: University of Illinois Press.
Colclough, G. 1988. Uneven Development and Racial Composition in the Deep South 1970-1980. Rural Sociology. 53: 73-86.
Crawford, M. 1994. The Legal System and Sharecropping: An Opposing View. In M. Stokes and R. Halpern, eds. Race and Class in the American South Since 1890. Pp. 103-110.
Daniel, P. 1972. The Shadow of Slavery, Peonage in the South, 1910-1969. Urbana: University of Chicago Press.
Daniel, P. 1994. The Legal Basis of Agrarian Capitalism: The South Since 1933. In M. Stokes and R. Halpern, eds. Race and Class in the American South Since 1890. Oxford: Berg. Pp. 79-110.
Davis, J. 2001. Race Against Time: Culture and Separation in Natchez Since 1930. Baton Rouge: Louisiana State University Press.
Dill, B. and B. Williams. 1992. Race, Gender, and Poverty in the Rural South: African- American Single Mothers. In. C. Duncan, ed. Rural Poverty in America. New York: Auburn House. Pp. 97-109.
Dix, K. 1988. What’s a Coal Miner to Do? The Mechanization of Coal Mining. Pittsburgh: University of Pittsburgh Press.
Edds, M. 1987. Free at Last: What Really Happened When Civil Rights Came to Southern Politics. Bethseda: Alder and Alder.
Falk, W. and T. Lyson. 1988. High Tech, Low Tech, No Tech: Recent Industrial and Occupational Change in the South. Albany NY: State University of New York Press.
158 Feagin, J. 1989. Racial and Ethnic Relations. 3rd Edition. New Jersey: Prentice Hall.
Fields, B. 1982. Ideology and Race in American History. In J. Kousser and J. McPherson, eds. Region, Race, and Reconstruction: Essays in Honor of C. Vann Woodward. New York: M.E. Sharpe. Pp. 143-177.
Flora, C. and J. Flora. 1988. Public Policy, Farm Size, and Community Well-Being in Farming Dependent Counties of the Plains. In L. Swanson, ed. Agriculture and Community Change in the US: The Congressional Research Reports. Boulder: Westview Press. Pp. 76-129.
Frisbie, P. and D. Poston. 1975. Components of Sustenance Organization and Nonmetropolitan Population Change: A Human Ecological Investigation. American Sociological Review. 40(December): 773-784.
Frisbie, P. and D. Poston. 1978. Sustenance Differentiation and Population Redistribution. Social Forces. 57(1): 42-56.
Fuguitt, G. 1985. The Nonmetropolitan Population Turnaround. Annual Review of Sociology. 11: 259-280.
Gaventa, J. 1980. Power and Powerlessness: Quiescence and Rebellion in an Appalachian Valley. Chicago: University of Illinois Press.
Gillette, B. 1998. Land of Cotton and Catfish Seeking Healthy Diversity From Other Types of Development. Mississippi Business Journal. 20(20): 1.
Gray-Ray, P. 1992 December. Race Relations in the Delta. In A. Cosby, M. Brackin, T. Mason, and E. McCulloch, eds. A Social and Economic Portrait of the Mississippi Delta. Mississippi State University.
Habermas, J. 1975. Legitimation Crisis. Boston: Beacon Press.
Hill, C. 1998. Contemporary Issues in Anthropological Studies of the American South. In C. Hill and P. Beaver, eds. Cultural Diversity in the South: Anthropological Contributions to a Region in Transition. Southern Anthropological Society Proceedings, No. 31. Athens: University of Georgia Press.
Hyland, S. and M. Timberlake. 1993. The Mississippi Delta: Change or Continued Trouble. In T. Lyson and W. Falk, eds. Forgotten Places: Uneven Development in Rural America. Kansas City: University Press of Kansas. Pp. 76-101.
James, D. 1988. The Transformation of the Southern Racial State: Class and Race Determinants of Local State Structure. American Sociological Review. 53(2): 191-208.
159 Johansen, H. and G. Fuguitt. 1984. The Changing Rural Village in America: Demographic and Economic Trends Since 1950. Cambridge: Ballinger Publishing Co.
Johnson, K. 1989. Recent Population Redistribution Trends in Nonmetropolitan America. Rural Sociology. 54(3): 301-326.
Johnson, M. 1994. Public Policy and Industrial Location in the Mississippi Delta in an Era of Restructuring. Southeastern Geographer. 24: 17-39.
Jones, J. 1996. The Late Twentieth-Century War on the Poor: A View From Distressed Communities Throughout the Nation. Boston College Third World Law Journal. 16(Winter): 6.
Key, V. 1950. Southern Politics in State and Nation. New York: Knopf.
Kodras, J. 1997. The Changing Map of American Poverty is an Era of Economic Restructuring and Political Realignment. Economic Geography. 73(1): 67-93.
Krannich, R. and T. Greider. 1984. Personal Well-Being in Rapid Growth and Stable Communities: Multiple Indicators and Contrasting Results. Rural Sociology. 49(Winter): 541-552.
Lemann, N. 1991. The Promised Land: The Great Migration and How it Changed America. New York: Knopf.
Lichter, D. 1988. Race and Underemployment: Black Employment Hardship in the Rural South. In L. Beaulieu, ed. The Rural South in Crisis. Boulder: Westview Press.
Livingstone, D. 1992. The Geographical Tradition. Oxford: Blackwell.
Lobao, L. 1990. Locality and Inequality: Farm and Industry Structure and Socioeconomic Conditions. Albany NY: State University of New York Press.
Lobao, L. and M. Schulman. 1991. Farming Patterns, Rural Restructuring, and Poverty: A Comparative Regional Analysis. Rural Sociology. 56(4): 565-602.
Lord, L. 1990. Pulling Together to Save the Delta. US News and World Report. 23 July, 29.
Luloff, A. and L. Swanson, eds. 1990. American Rural Communities. Boulder: Westview Press.
Lyson, T. 1989. Two Sides of the Sunbelt: The Growing Divergence Between the Rural and Urban South. New York: Praeger.
160
Machlis, G. and J. Force. 1988. Community Stability and Timber-Dependent Communities. Rural Sociology. 53(2): 221-234.
Marks, C. 1989. Farewell—We’re Good and Gone: The Great Black Migration. Bloomington: Indiana University Press.
Marsden, T., P. Lowe, and S. Whatmore. 1990. Introduction: Questions of Rurality. In T. Marsden, P. Lowe, and S. Whatmore, eds. Rural Restructuring: Global Processes and Their Responses. London: David Fulton Publishers.
McCray, J. 1990. Housing Problems and Solutions in the Lower Mississippi Delta. Report to the Lower Mississippi Delta Commission No. DC-00111. Pine Bluff: University of Arkansas.
O’Connor, A. 1992. Modernization and the Rural Poor: Some Lessons from History. In C. Duncan, ed. Rural Poverty in America. New York: Auburn House. Pp. 215- 233.
O’Hare, W. 1988. The Rise of Poverty in Rural America. Occasional Paper No. 15, July. Washington DC: The Population Bureau.
Payne, W. 1991. Institutional Discrimination in Agricultural Programs. The Rural Sociologist. 11: 16-17.
Pfeffer, M. and J. Gilbert. 1989. Federal Farm Programs and Structural Change in the 1980s: A Comparison of the Cornbelt and the Mississippi Delta. Rural Sociology. 54(4): 550-567.
Policy Matters. 1999 October. Agricultural Policy Questions: Why Have Grain Prices Fallen So Low? Newsletter of the Agricultural Policy Analysis Center. 4(5).
Richter, K. 1985. Nonmetropolitan Growth in the Later 1970s: The End of the Turnaround? Demography. 22: 245-262.
Rosenfeld, S. 1988. The Tale of Two Souths. In L. Beaulieu, ed, The Rural South in Crisis: Challenges for the Future. Boulder: West View Press.
Rosenfeld, S., E. Bergmon, and S. Rubin. 1985. After the Factories: Changing Employment Patterns in the Rural South. Raleigh: Southern Growth Policies Board.
Rungeling, B., L. Smith, V. Briggs, and J. Adams. 1977. Employment, Income, and Welfare in the Rural South. New York: Praeger Publishing.
161 Sinclair, W. 1987a. Lying Laid Down the Law, but is the USDA Enforcing it? Washington Post. 21 Sept: A13.
Sinclair, W. 1987b. Old-Boy Network Still Haunts Agriculture’s Problem Child. Washington Post. 21 Sept: A13.
Skees, J. and L. Swanson. 1988. Farm Structure and Rural Well-Being in the South. In. L. Swanson, ed. Agriculture and Community Change in the US: The Congressional Research Reports. Boulder: Westview Press.
Sly, D. 1972. Migration and the Ecological Complex. American Sociological Review. 37(5): 615-628.
Smith, B. 1998. The Postmodern South: Racial Transformations and the Global Economy. In C. Hill and P. Beaver, eds. Cultural Diversity in the US South: Anthropological Contributions to a Region in Transition. Athens: The University of Georgia Press. Pp. 164-178.
Stack, C. 1996. Call to Home: African Americans Reclaim the Rural South. New York: Basic Books.
Stokes, M. and R. Halpern, eds. 1994. Race and Class in the American South Since 1890. Oxford: Berg.
Stokowski, P. 1992. The Colorado Gambling Boom: An Experiment in Rural Community Development. Small Town. 22(May-June): 12-19.
Swanson, L. 1988. The Human Dimensions of the Rural South in Crisis. In L. Beaulieu, ed. The Rural South in Crisis. Boulder: West View Press. Pp. 92-98.
Timberlake, M., B. Williams, B. Dill, and D. Tukufu. 1991 . Race and Economic Development in the Lower Mississippi Delta. Working Paper. Memphis: Center for Research on Women.
Tomaskovic-Devey, D. 1987. Labor Markets, Industrial Structure, and Poverty: A Theoretical Discussion and Empirical Example. Rural Sociology . 52(1): 56-74.
Tomaskovic-Devey, D. 1988. Industrial Structure, Relative Labor Power, and Poverty Rates. In D. Tomaskovic-Devey, ed. Poverty and Social Welfare in the United States. Boulder: Westview Press. Pp. 104-129.
Tomaskovic-Devey, D. and V. Roscigno. 1997. Uneven Development and Local Inequality in the US South: The Role of Outside Investment, Landed Elites, and Racial Dynamics. Sociological Forum. 12(4): 565-597.
162 Tunica County Museum (TCM). 2003 March. Civil Rights in Tunica, Education in Tunica County, The Story of the Tunica County Casinos, and Sugar Ditch. Permanent exhibits. Tunica County, Mississippi.
Turner, J, J. Singleton, and D. Musick. 1984. Oppression. Chicago: Nelson-Hall.
US Bureau of Economic Analysis (US BEA). 2002. U.S. Department of Commerce. Regional Accounts Data.
US Census Bureau. 1990. Census of Population and Housing. Washington DC: U.S. Government Printing Office.
US Census Bureau. 2002 September. Historical Poverty Tables. Weighted Average Poverty Thresholds for Families of Specified Size 1959-2001. Accessed 04/03/03.
US Commission on Civil Rights (USCCR). 1965. Equal Opportunity in Farm Programs: An Appraisal of Services Rendered by Agencies of the United States Department of Agriculture. Washington DC: USCCR.
US Commission on Civil Rights (USCCR). 1982. The Decline of Black Farming in America. Washington DC: USCCR.
US Commission on Civil Rights (USCCR). 2001. Racial and Ethnic Tensions in American Communities: Poverty, Inequality, and Discrimination—Volume VII: The Mississippi Delta Report. Accessed 02/0202.
Vance, R. 1932. Human Geography of the South: A Study in Regional Resources and Human Adequacy. Chapel Hill: University of North Carolina Press.
Walker, J. 1977. Economic Development and Black Employment in the Non- metropolitan South. Austin: Center for the Study of Human Resources, The University of Texas.
Ward, B. 1994. Racial Politics, Culture and the Cole Incident of 1956. In M. Stokes and R. Halpern, eds. Race and Class in the American South Since 1890. Pp. 181-208.
Wiener, J. 1978. Social Origins of the New South: Alabama 1860-1895. Baton Rouge: University of Louisiana.
Williams, P. 1991. The Alchemy of Race and Rights. Cambridge: Harvard University Press.
Williamson, J. 1984. The Crucible of Race, Black-White Relations in the American South Since Emancipation. New York: M.E. Sharpe.
163
Wood, G. 1987. The Economic Revolution in the American South. Economic Perspectives. 1: 161-178.
Wright, G. 1986. Old South New South: Revolutions in the Southern Economy Since the Civil War. New York: Basic Books.
164 CHAPTER 6
GROWTH OF GAMING
“Can you believe this?” one woman asks another, as they shuffle forward, waiting at midnight for a table in a casino restaurant. “Right in the middle of the cotton fields,” she marvels. (Schwarz and Schwarz 1999)
Tunica gleaned fame from its 60 Minutes episode, becoming a symbol of poverty within the United States (Saul 1997). In a county where more than half of the residents survived on food stamps, where illiteracy was widespread, and infrastructure was so poor that no tax incentive could draw industry to the area, there was little hope of change
(Schwarz and Schwarz 1999). Certainly, it hardly appeared to be a likely candidate for the location of a new industry that in ten years’ time would bring in more than $4 billion in capital investments, 15 million tourists annually, and twice as many jobs as people in the county (TCVB 2002).
That is indeed the case for Tunica. Sorting out how such a magnitude of growth transpired, and in a relatively short period of time, requires examination of the broader economic, political, and cultural manifestations of casino gaming. This chapter begins with a brief history of gambling in the United States, including its relationship to globalization, culture, and the construction of place, focusing on the manner in which casino industry development surfaced as a means of economic opportunity across the nation. Then the political course by which that opportunity was filtered through the state of Mississippi to Delta and Gulf Coast counties is considered, honing in on the development of the industry in Tunica County and the role played by various stakeholders in that process.
165 6.1 HISTORY OF GAMING IN THE US
Legalized gambling in the US has been accompanied by a rise in services, particularly entertainment and hospitality sectors constructed around the increasing demand for and consumption of leisure activity. However, gaming has largely been promoted by government officials as a means of fostering employment growth and generating tax revenue (Abt 1996; Corditz 1990; McGowan 2001), especially in distressed areas (e.g., Jensen and Blevins 1998; Stokowski 1996). Thus gaming, particularly casino gambling, has become a lifeline in terms of economic development
(Goodman 1994). This interest in gaming as a means of raising revenue and providing jobs and subsequently economic relief for distressed areas is hardly new.
McGowan (1999b) documented four waves of state-sponsored gambling activity in the United States. The first wave came in the form of state-sanctioned lotteries for a period that spanned from the early 1600s to the 1840s. During that time a handful of lotteries were sponsored by states to help finance their armies, but after the Declaration of
Independence the majority were used to fund larger projects such as colleges, local school systems, churches, hospitals, or capital improvements (Ezell 1960). Yet, by the
1800s states began to turn to more reliable tax-raising systems and moral opposition began to mount toward all forms of gambling, in part due to scandal and proof of corruption and the desire to “protect the poor from the machinations of others” (Munting
1996: 36). By the 1840s all but a few states had banned the lotteries.
At the close of the Civil War in 1865, with the need for reconstruction, southern legislatures allowed private operators to conduct lotteries to finance roads, bridges, school buildings, and various other social capital projects. This second wave was
166 different than the first in that sales were confined to local regions, while the post-Civil
War lotteries of the South took on a national scope. Once again moral opposition began to grow. Fueled by controversy over the national draw of southern lotteries, particularly that of Louisiana, all lottery activity was curbed by congressional legislation by 1895.
Similarly, casino gaming was banned in all states by 1911 and illegal “games of numbers” or “policy games” were attacked based on the “moral concern that the poor were throwing away their money at such ventures” (Munting 1996: 36).
The third wave, which consisted of state-operated lotteries, began in the 1920s when a number of states (e.g., Florida, Rhode Island, Connecticut, Delaware, and
Nevada) began to permit pari-mutuel betting on jai-alai, horse races, and dog races. In addition, Nevada legalized casino gambling in the 1930s, and a string of illegal casinos was known to be operating at Miami Beach and on boats floating off the California coast
(Longstreet 1977). Yet gambling was generally a socially unacceptable activity from
1900 to the mid-1960s, largely due to its real and perceived association with organized crime. Then, in 1964, the fourth wave began when New Hampshire voters approved a lottery sweepstakes, with the justification that its legalization was wholly economic. It was intended to serve as a means of salvation for the educational system while escaping the need to enact a state sales or income tax (Sternlieb and Hughes 1983).
The New Hampshire lottery was an enormous success, “with 90 percent of the lottery tickets being bought by out-of-state residents” (McGowan 1999b: 15). Witnessing this, over the next ten years every state in the Northeast approved a lottery. Miers and
Dixon (1979) referred to this period as “a quiet revolution” in government attitudes toward gambling. Pennsylvania’s lottery was begun in 1971 with its proceeds tagged for
167 property tax relief for the elderly (Blakely 1984). However, justifications for the adoption of gaming in Pennsylvania and elsewhere extended beyond tax revenue for distinctly public venues, like that of New Hampshire, to more of a competitive rationale, as explained by McGowan (1999b): 1) People are going to gamble, so why shouldn’t the state profit from this activity?; and 2) The neighboring state is reaping benefits from our constituents, so we need to institute a lottery to keep the money home .
Thus, in this fourth wave, the lotteries were owned and operated by state agencies.
Between 1980 and 1990 twenty-five states approved not only lotteries, but other forms of gambling, such as off-track betting, keno, and video poker machines, all devised to supplement the revenue capabilities of lotteries. In fact, by 1993, the liberalization of gambling had been embraced by all but two states—Hawaii and Utah, Neither had a form of legalized gambling. Further, by 1987 forty-three states allowed betting on bingo for charitable purposes (Munting 1996). As such, during the fourth wave, gaming had gained a social acceptance and legitimization among American people that had not existed previously (Corditz 1990).
Further, such legitimization extended to the service industry, such as through the acceptance of hotel and hospitality firms as a respectable means of business (Dixon
1998). This followed the lifting of restrictions on corporate casino ownership in 1969 and the clearing of Nevada casinos from criminal backing in the mid-1970s (Commission on the Review of the National Policy Toward Gambling 1976; Munting 1996). When casinos were introduced in Atlantic City in 1978 as an urban revitalization project (Vogel
1990), creditable firms, such as the Hilton and the Hyatt, made their entry into the industry (Eadington 1984; Eadington and Cornelius 1992). In addition to those and
168 others was the entrance into the market of the Holiday Inn, which had made its prior success by projecting itself as a family place to stay.
6.1.1 THE GLOBAL CULTURE OF INDUSTRY GROWTH
In the late twentieth century the existing gambling network became consolidated and institutionalized through a process referred to as the “commodification of chance,” something that is sold by businesses and purchased by the consumer (Reith 1999: 89). It is a process that set to absolve gambling of condemnation by bringing it into the spectrum of legitimate business. Having been suppressed for much of the time since the 19 th century, while still retaining some objection; by 1990 gambling had shed its immoral stigma and had become wholly incorporated into the capitalist economy as just one more form of commercial enterprise (Preston et al. 1998). According to the dynamics of entrepreneurialism its legalization spread rapidly, becoming almost ubiquitous throughout the world (Eadington 1999; Reith 1999; Thompson 1998).
Many have written on this capitalist embrace of gambling (e.g ., Abt et al. 1985;
Caldwell et al. 1985; Eadington 1988; McMillen 1996; Munting 1996), expressing casino life in terms like casino capitalism and global casino (Reith 1999). Most refer to its proliferation around the globe since the 1970s with the development of mass tourism and leisure industries, growth of international financial markets, the movement of gamblers across increasingly fluid national boundaries, its incorporation into state fiscal policy, and technological advances (Martins 2002).
Technological innovation, the emergence of international financial markets, and growth in mass tourism and leisure industries have all contributed to the development of new, transnational forms of gambling and the commercialization
169 of existing gambling traditions. Business and political leaders in all parts of the globe are embracing gambling policies which would have been anathema to governments and the community alike a decade ago. (McMillen 1996: 263)
In the meantime, gambling behavior has become somewhat homogenous. That is, in earlier waves there was stratification in the gambling economy. Gaming in the casino and at the racetrack was the prerogative of the well-to-do, the gentry planters , while lotteries and other numbers games were patronized mainly by the poor (Breen 1977;
Munting 1996; Reith 1999). More recently, the middle classes, traditionally opposed to all forms of gambling, became incorporated into the consumer pool as influenced by the increasing commercialization and embeddedness of industry in the capitalist economy
(AGA 2001). Hence, gambling simply became one more form of recreational commodity and consequentially homogenized “once disparate areas of gambling activity and to the inclusion of all classes into their fold” (Reith 1999: 92).
The pinnacle of the advance of gambling in the United States, however, was the differentiation of the gambling economy into distinctive gambling sites, each with its own rules, governed by its own dynamic, giving off its own experience of play (Reith
1999). The spatial organization of a gambling site refers to the concentration or diffusion of the gambling environment, whereby concentrated sites present intense, localized activity such as a racetrack, while diffuse sites are disseminated over a wide area (e.g., lotteries and Internet gambling). Relating those differences in the spatial organization of a gambling site to its embeddedness in place, Reith (1999: 97) stated:
Such spatial organization is related to the social separation or incorporation of sites into the larger social fabric, with concentrated sites tending to exist out with the local
170 environment in their own separate spheres and diffuse ones tending to be incorporated into the routine of daily life.
The casino is an example of a concentrated site, self-contained, enclosed, demographically separated, and physically separated from its surroundings in its own exclusive place . It is a place that is packaged as a commodity and sold to investors as well as consumers (Philo and Kearns 1992).
Thus, the industry exhibits strong localization economies, as casinos tend to cluster in an attempt to create destination resorts or exotic casino locations that have greater revenue potential than casinos of convenience , which only accommodate the local market. In this process of agglomeration, their presence around the world has increasingly become dominated by publicly traded corporations (Faragher 1995; MGC
2002). Yet, since government regulations at the national and sub-national levels have fostered gaming as a means for economic development and increased competitiveness in tourism (Eadington and Cornelius 1997), in many places control over the legalization and spread of gaming has been localized (Frey 1998).
6.1.2 SECTION SUMMARY
The discussion of the public acceptance of legalized gambling and its process of growth as it relates to economic development has thus far been set in the context of its abstract spatial and temporal diffusion. In order to understand its incision into
Mississippi, into the Bible Belt , a deeper examination of the related social, economic, political, and cultural transformational shifts is required. As such, the remainder of this chapter consists of a brief introduction to contemporary casino gaming in the United
States. This is followed by the dynamics of riverboat gaming development, first by
171 entertaining the theoretical constructs of competitiveness and then by way of an in-depth description of the growth of riverboat gaming in the Tunica case.
6.2 CASINO GAMING IN THE CONTEMPORARY US
The initial growth in gaming during the fourth wave, as centered on lotteries, can be traced to competition between neighboring states in the 1960s and 1970s. The basis of that competition was for revenues to offset fiscal crises prompted by capital flight and deindustrialization and the onset of economic recession (Bluestone and Harrison 1982;
Clark 1989; Dixon 1998; Peet 1983; Storper and Walker 1989). Yet, not all were supportive of legalized gambling as evidenced by the fact that public acceptance and development of land-based gaming sites other than those on Native American reservations has been slow. Examples of established casino firms’ failure to obtain approval in the 1980s are documented in a number of tourist-based economies, such as in the Pocono and Catskill Mountains, Miami Beach, and Hot Springs, Arkansas (Dombrink and Thompson 1989; Fischer 1985).
A few political successes relating to commercial developments occurred in former resource-dependent economies in South Dakota and Colorado, but their social and economic outcomes remain questionable and thereby have served as a caution to those interested in following suit. More recently, major land-based projects, initiated mainly for the sake of urban redevelopment, can be found in New Orleans and Detroit, with the former having been subject to much scrutiny (Bridges 2001). Aside from those and expanses in prior gaming developments in Reno and Las Vegas, Nevada, most of the
172 growth in casino gaming in the US has been in the form of riverboat gambling following the passage of the Indian Gaming Regulatory Act of 1988 (Roush 1993).
6.2.1 THE DYNAMICS OF RIVERBOAT GAMING DEVELOPMENT
Voters in Iowa were the first to approve casino gaming via a statewide referendum that legalized riverboat casinos, with the intention of capitalizing on the historic image of the Mississippi River. The legislation mandated that the new boats resemble those of the last century, with a maximum of 30 percent of the floor space to be used for limited low-stakes gambling, which could not take place unless the boats were in cruising mode, promoting a family-oriented tourist environment (Goodman 1995).
Within a year of the passing of Iowa’s legislation, Illinois and Mississippi also legalized restrictive gambling, but with far fewer restrictions in the case of the latter. As a result, just fourteen months after the opening of Iowa’s first riverboat casino, the boat set sail for
Mississippi.
In order to remain competitive, both Iowa and Illinois would later reduce restrictions in their gaming regulations. Eventually, betting and loss limits were lifted in both states. In Iowa, the cruising requirement was also lifted, which included giving over to Mississippi’s condition of allowing dockside gambling on a 24-hour basis. Yet, that did not sully the fact that within two years of legalization, the state of Mississippi boasted more square footage of casino space than had been constructed in Atlantic City in sixteen years of casino development (Goodman 1995). By 1997 casino gaming in Mississippi had become a $1.9 billion industry in terms of annual revenues (Myerson 1996). Within ten years, Tunica County ousted Reno/Tahoe from its position as the nation’s third most
173 sought-after casino tourist destination and stood as the largest agglomeration of casinos situated between Las Vegas and Atlantic City.
As noted earlier, the possibility of this outcome is quite perplexing given Tunica’s seeming lack of competitive potential as identified in the last chapter. However, an understanding of the county’s surge of gaming industry development and its success can be attained by situating it in the framework of Porter’s (1980) Competitive Strategy:
Techniques for Analyzing Industries and Competitors. Therefore, the next portion of this discussion is centered on the theoretical constructs of competitive dynamics, followed by its application to the Tunica case.
6.2.1.1 COMPETITIVE DYNAMICS
According to Porter (1990), most explanations of successful competitiveness rest on Ricardian theories of comparative advantage, which is based on the notion that all nations have equivalent technology. But, the ability to capitalize on that technology is mitigated by differences in factor endowments, such as land, labor, natural resources, and financial capital. Comparative advantage fails to explain why some nations are competitive despite the absence of those endowments. It also fails to explain how Tunica
County, an area ill-suited for most any industry development, could obtain such success.
Competitive advantage, on the other hand, centers on the complex interaction of a host of characteristics that allow an area’s firms to generate and maintain leadership within particular fields (Porter 1990). Porter’s model consists of five categories or components that impact the competitiveness of a specific industry: suppliers, industry rivalry, substitute products, new entrants, and customers, while also recognizing the
174 barriers to entry and exit. The fundamental force operating among those components is that of power relationships, that is, where power rests at a given point in time and the manner in which it may or may not shift over time, making it a seemingly logical theoretical framework in which to ground the Tunica case.
However, Porter’s analysis is limited by usually taking place within the constructs of the product market and technology arena at the national scale (e.g., Glowacka 1996;
Rugman 1991; Yla-Antilla 1994). He does offer a similar framework for the analysis of inner-city economic development (Porter 1995), allowing its application at a more localized level (e.g., Healey and Dunham 1994; Sabety and Griffin 1996). Still, what is missing from the Porter model is the non-market sources of change that impact the dynamics of competitiveness and industry relationships, such as government influence and the socio-cultural imperative of gambling (e.g., religious beliefs and planter persistence).
With respect to government, although not presented as a primary component,
Porter implies that it is an important factor of competitive advantage by enacting and enforcing anti-trust regulation, by restricting or encouraging competition, and by providing subsidies or infrastructure (Wallace 1998). Therefore, it is understood that government does not stand as a separate component interacting with the other five, but rather as an umbrella that ultimately may influence the entire competitive system. In order to extend the Porter model to deal with those factors of influence from the political arena as well as those pertaining to socio-cultural issues, Mahon and McGowan (1996) offered a complimentary social and political (S&P) model ( see Figure 6.1). The
175 fundamental approach of the S&P model is the same as Porter’s, but with three additional critical assumptions (McGowan 2001), all of which are captured in Table 6.1.
Figure 6.1 Porter’s Model of Industry Competitive Dynamics and Mahon and McGowan’s Social and Political Model of Industry Competitive Political Dynamics
Porter Mahon & McGowan barriers barriers new entrants stakeholders to entry to entry
industry industry (including (including nature suppliers nature of customers issues &events audience of competitive & competitive political rivalry rivalry)
substitute barriers substitute issues barriers products to exit or events to exit
Source: Adapted from McGowan 2001, pp. 78 and 81.
Table 6.1 Assumptions of the Porter and S&P Models of Competitive Dynamics Porter S&P Product: Goods and/or Services Issues/Ideas or Events Theater of Transaction: The "Marketplace" A Chosen Arena Unit of Currency/Exchange: Money Influence Source: Adapted from McGowan 2001, p. 81
The product in the Porter model is straightforward as it applies to something produced in the form of a good or service, depending on the industry identified. In the
S&P model there are also issues, ideas, and events that in the broadest sense are inputs being supplied to the firm or industry (e.g., intermediate goods) as well as the output created for the customer (e.g., goods and services). In addition, there are input supplied to external groups that can impact on the competitive dynamics of the industry.
176 Examples include disagreements regarding industry regulation, the means for resolution to a given problem, or over the values of a certain situation. The latter could include people’s belief system regarding the right and wrong of gambling as an economic development strategy or the casino as a place of work. In any case, the issue, idea, or event is what provokes the industry to act or react.
The marketplace is where goods or services are exchanged and can be at any geographic scale (i.e., local, state, national, and international). Just as those goods and services can be put up for sale in the marketplace, an issue, idea, or event can be put up for discussion in a variety of arenas—public or private, formal or informal—depending on the target audience. This might include, but is not limited to, various forms of media, such as the local newspaper or national news broadcast, public discussion at a community meeting, mediation or in government quarters with respect to regulatory or legislative action, or an executive board meeting of a particular firm.
In the product market, the unit of currency is usually money, but can be some other form of financial capital. In the S&P realm the unit of currency or exchange is influence, which can also be money or some other traded favor, such as information or services rendered or withheld. In other words, influence can generally be thought of as whatever is held of value that merits a response. In that respect, discourses and rhetoric are forms of currency or exchange and in the form of cultural politics can be used to persuade communities of the appropriateness of casinos as an economic development strategy (Dixon 1998: 170):
Residents must be persuaded that a particular type of development is the only one that will secure their own economic future as well as that of the town or city. As Roberts and Schein (1993) note, this rhetoric may take the
177 form of an appeal to civic pride. It may also, however, take the form of a “desperate” plea that this development is the only hope for the community, and as such must be fought for tooth and nail.
Additionally, as with barriers to entry or exit in the product market, such as money or technology, barriers in the political and social realm are related to access and legitimacy. Access is that which allows for the exercise of influence and legitimacy is recognition by other stakeholders that a particular individual or group has reason to be involved and that the form of involvement is acceptable. Stakeholders, therefore, are defined as “those individuals, groups, and firms” that can (McGowan 2001: 85-86):
Alter the definition of an issue; Impact on the power relationships among players involved in the issue at hand; and, Influence the target audience and the resolution of the issue and/or the implementation of the resolution.
This brings us to industry rivalry, which in the product market impacts the dynamics of the situation, but in potentially different ways––its impact is not necessarily equal or uniform across the industry. The same is true for the social and political arena.
For example, in the case of regulations imposed on riverboat casinos in Iowa versus
Mississippi, restrictions in Iowa were based on an understanding of the industry as a somewhat benign tourist industry development (Goodman 1995). In Mississippi, casinos were viewed as potentially having profound economic impacts on the state and therefore a more open regulatory framework was adopted. In doing so, however, Mississippi legislators significantly altered the playing field of the riverboat casino industry on a national scale.
The last point also pulls in the notion of substitute issues, where the focus of discussion may change and have implications for the industry. The focus in Iowa,
178 although in need of economic relief, was largely casino gaming as a complement to other forms of tourism. As such, the implication for the industry in Iowa was that of strict regulation, while in Mississippi the focus was on economic health with casinos as an opportunity to relieve widespread distress. Therefore, tourism growth through gaming substituted for other forms of policy intervention, changing the patterns of stakeholder involvement and arena of policy resolution to include all that pertains to the commercial casino industry. In turn, the industry was impacted by greater opportunity for development, and advanced by loose regulatory practices that would not exist if
Mississippi’s arena for resolution were not embedded in the casino.
Finally, we come to the audience. In Porter’s model the audience includes the customers who assert influence over the industry through their purchasing power and decisions. Such feedback mechanisms help to determine the strength and longevity of firms and transformations within the industry. The audience in the political and social arena similarly determines the fate of the industry by deciding whose camp they wish to support and for what reason. In the next portion of this chapter I will argue that the opportunity for casino industry development in Tunica was in part contingent upon
DeSoto County’s decision whether or not to legalize gaming within that county. Further, similarities between the two counties with respect to the issue existed in terms of the widespread disapproval of gambling based on religious doctrine. In the case of DeSoto
County, the economic situation was such that they could afford to disapprove. On the flip side, the cost of being so pious was significantly greater for Tunica County residents.
Thus, their decision was based on need rather than want. In either case, the audience represents the individuals or groups that exercise control over the solution to the issue.
179 In the remainder of this chapter I demonstrate the application of the S&P model to the Tunica case. I do not make direct comparisons with each model component in a structured fashion, as much would be lost in capturing the complexity of the case by doing so. The intention is not to make a one-to-one corollary in support of the theoretical model, but to use it as an advanced organizer . That is, the goal is to use the model to raise awareness of the need for an intimate examination of political and social processes in relation to casino industry growth and to aid in understanding those processes as they pertained to casino industry development in Tunica County, Mississippi.
6.2.2 RIVERBOAT GAMING IN MISSISSIPPI
Just as gambling for economic development was not new to the US in the 1990s, neither were casinos in the Delta nor riverboat gaming in Mississippi (Kelley 1992a).
Crude casinos existed in Louisiana during the first wave. It is reported that by the 1820s
New Orleans hosted the first of what would later become known as Las Vegas style casinos––ornate and open around the clock (Asbury 1938). As greater restrictions were imposed on gambling in the city, casinos diffused “northward along the Mississippi River and eastward along the Gulf Coast toward Mobile… [and] sprouted in Mississippi River towns such as Natchez and Vicksburg” (Meyer-Arendt 1998: 151). In fact, Louisiana was the purveyor of illegal gambling that spread everywhere along the Delta, mainly on the floating casinos of the Mississippi (Munting 1996). With riverboats operating out of
New Orleans, it is estimated that by the mid-1830s, “six to eight hundred gamblers regularly worked the steamboats that traveled the Mississippi River between New
Orleans and St. Louis” (Bridges 2001: 8).
180 As policing of land-based gambling activities elevated, during the second wave cunning entrepreneurs wholeheartedly instituted riverboat and offshore gambling, most notably in Biloxi (Sullivan et al. 1985). Another surge of illegal gambling growth along the Mississippi coastline ensued following World War II. By the early 1960s, just prior to the start of the fourth wave, the activities had all but seized under government crackdown. That did not deter Mississippians, who proceeded to build and run what were perceived as legal offshore casino boats into the late 1980s. However, the livelihood of those boats was cut short by enforcement of the federal Gaming Ship Act of 1948 (Morris
1989). Yet, interestingly, by that time, with the state nearing fiscal bankruptcy,
Mississippi legislators had begun giving serious consideration to the legalization of riverboat gambling.
The potential revenue generation of casinos was appealing, but the state legislature was apprehensive about the public acceptance of legalized gambling in
Mississippi. Despite the aforementioned history with gambling, the majority of the state’s residents remained opposed to gambling of any form given their strong religious convictions, “dominated by temperance-minded Southern Baptists” (Meyer-Arendt 1998:
152). After significant debate and in the face of record high levels of statewide unemployment and overall economic hardship, the Mississippi Legislature did eventually pass a casino bill in March 1990. This came as a shock for many Mississippi residents as a statewide lottery had repeatedly been rejected. Even bingo as a form of revenue generation for churches had recently come under harsh scrutiny.
The legislation made gambling legal under very specific conditions, and was meant to conform best to what/where they perceived it would be most socially acceptable
181 and economically helpful and successful. That is, no gambling was to take place on anything but a floating vessel, which was to be permanently docked along the shore of a navigable water body, yet restricted to counties along the Mississippi River and Gulf
Coast, and only where the majority of residents so approved. The bill further stipulated that residential approval was to be based on a local veto option (Markon 1990), which followed the process set forth by Iowa and Illinois.
This meant that a state representative would introduce a bill to allow riverboat casinos in his/her district in order to enhance the attraction of visitors to augment pre- existing heritage tourism (e.g., Civil War sites). If successful, others would argue for inclusion. Once accepted, in order for a given county to turn down a bid for casino development, an intricate process of political red tape ensued. A casino developer would first have to file plans with the Mississippi Gaming Commission (MGC) and run a notice of intent in a county newspaper for three consecutive weeks. Citizens who objected were required to respond to that notice by gathering 1,500 signatures or 20 percent of registered voters (whichever was less) (Branson 1990a). The signatures needed to be certified by the county clerk within thirty days of the date of the last day that the notice of intent had appeared in the newspaper. Then within sixty days the county had to set up a referendum to vote on the issue (Bayne 1990a). If the vote were not defeated or if no petition was filed in opposition of the casinos in the first place, the Board of Supervisors for that county would adopt the resolution and the casinos would be legalized. If the vote were defeated, the casinos would be deemed illegal, but only for the time being, as the matter would be left open for reconsideration after a year’s passing.
182 If residents did not organize and obtain enough support to vote down the casino and the proposed location did not conflict with zoning regulations, there were just a few steps remaining for the developer. US Army Corps of Engineers permits had to be obtained because of the fact that all sites were to be on navigable waters and with consideration of wetland disturbance. Then, the final site had to be granted approval by
MGC. This end process proved to be somewhat problematic in Delta counties because having scouted out potential sites along the Mississippi River, it was decided that casinos would be restricted to sites west of US Highway 61 (Howard 1993). That meant all casinos would be riverside of the natural bluffs or behind the artificial protection levees
(Field Notes B 2002).
As such, the primary target for development from the perspective of the industry was DeSoto County, just north of Tunica County and adjacent to Tennessee. DeSoto
County hosts a clustering of suburban bedroom communities near the Memphis metro area, making it a suitable urban hinterland location. As one prospective investor stated,
“the demographics of the area, the proximity to Memphis, Little Rock, and St. Louis would make DeSoto County the plum of the riverboat operations” (Lehmberg quoted in
Bayne 1990b: A1). Yet, DeSoto County was the only eligible Delta County to soundly reject the legalization of casino gaming (Kifner 1996). It did not do so wholly on its own accord, as will be discussed with respect to casino development in Tunica County.
Notably, other river counties approved of the casinos (e.g., Adams, Hancock, Claiborne, and Issaquena) and a number of sites were developed, one of which is in Coahoma
County which borders Tunica to the south.
183 None of the other river counties that adopted casino gaming nor has the development along the Gulf Coast seen the success experienced by Tunica.
Understanding the reasons requires an appreciation for the various causal factors and contingent effects that led to the agglomeration of casinos in Tunica and its ability to establish itself as a resort destination. Within that framework, as demonstrated by the
S&P model, and as pointed out by Baruffalo (2000: 51):
There is a need also for an explicit recognition of the different expectations and possibilities that various regions and localities, or more precisely, their citizens , might pursue (or find acceptable) in terms of maintaining or enhancing quality of life… for example, in the case of Tunica County, where there exists an elitist mode of political representation very much of the traditional sort. An emphasis on social relations generally, and on the sociological and psychological attitudes in particular, is needed to tease out the inherent controversies that surround casino gambling and especially the political activism that surrounds such controversy.
Thus, I proceed with a detailed account of how the adoption, development, and growth of riverboat gambling unfolded in Tunica County.
6.2.2.1 TUNICA’S “CASINO” STORY
On September 13, 1990, Tunica County residents were exposed to their first notice of intent in the Tunica Times-Democrat, to be followed by dozens more. Unlike that in DeSoto County, citizen reaction was slow and almost unnoticeable in comparison.
Some resistance was expressed by church leaders, particularly in the white community, but there was not enough opposition to mount a successful petition drive (Branson
1990b). In other counties where notices of intent appeared (e.g., DeSoto, Washington,
184 Wayne), church leaders and their followers who had moral objection, used all the clout they could muster to defeat the legalization of riverboat casinos (Branson 1990b).
Opponents in DeSoto County were backed by the Christian Action Committee, the political arm of the state’s Southern Baptist Church, which distributed petitions to more than fifty churches in the county to help the area’s churches educate the population on the gambling issue (Bayne 1990b). In Warren County, church leaders united and divided the Vicksburg telephone book and canvassed nearly every home in the county, and then used church vans to get voters to the polls (Branson 1990a). Still, even in those counties, it was recognized that there was ambivalence in the black church community.
One Washington County reverend was quoted as saying, “a lot of (black) people look at it as being a white issue” (Branson 1990b: A1).
In Tunica County the issue was not so much one that focused on ethnicity or moral repulsion for gambling, but one due to unfamiliarity with the process, political powerlessness, and the underlying need for any form of economic reprieve. The level of illiteracy within the black community was a major obstacle. Many couldn’t read the notice of intent or debates taking place via the newspaper, or for that matter, the scant number of petitions that were circulated (Field Notes C 2002). In fact, gambling opponents contended that the public notice in newspapers was discriminatory, charging that it violated equal protection by serving as a sort of literacy test for a majority black population—“a significant portion of the population in Tunica… is illiterate or undereducated to read the notice much less act on it” (Coleman in Branson 1991a: A1).
Further, within the black churches, many had pastoral council every couple of weeks, on a visiting basis, and therefore lacked the leadership to mount a serious
185 campaign (Baruffalo 2000; Wallace 1998). Even so, as one resident explained, “if petitions were circulated in the black churches in Tunica, it might have been to support gambling to provide jobs” (Bailey in Baruffalo 2000: 78). That sentiment was echoed by at least one black deacon in the county (Hudson in Kelley 1992b: A1): “I believe it’ll be a help to the county and community. They’ve [casinos] given lots of people jobs out there.
I’m proud of that.” In fact, most of the reports coming from the black population were positive as a result of a realistic understanding of need and belief that the benefits would trickle down to all via either jobs or community benefits. As one elderly black woman stated, “I don’t see no bad… If it helps my county, I feel it will help me” (Curry in Kelley
1992b: A1). Still, the sinfulness of the matter was ever present, as evidenced in these comments of the black farmer as quoted in the last chapter:
I don’t think it’ll hurt anything. People already are gamblin’ anyway… Seems to me, people’s minds are just turned that way. ‘Course, they’re not serving the Lord no way. (Woodard in Kelley 1992b: A1)
Inevitably, the situation was such that legalization of riverboat gaming went uncontested (technically) in Tunica County (Branson 1991b). As a result, on November
5, 1990, the Tunica County Board of Supervisors adopted a resolution which stated that if someone were willing to invest in a port, then gambling would be legal (Branson 1990b;
Real 1990). 19 At that time none of the casinos were soundly seeking to operate in the county, as they awaited the outcome of future referendums in DeSoto, but the message was clear. As indicated by the then Tunica Board of Supervisors President: “It’s not the best industry, but it’s the only one we can get… We welcome the casino boats and I want the world to know it” (Battle in Garlington 1991: A1). Later, reflecting on the manner in
19 In Mississippi, at the county level, all political power resides with the board of supervisors.
186 which things transpired, similar sentiment was expressed by another county official
(Murphree in Baruffalo 2000: 126):
I don’t think it just slipped through without anybody noticing it. I think in Tunica County you had a situation where statistically it had the lowest per capita income in the United States. So I don’t think Tunica County was any smarter than anybody else by allowing the gambling in this community, they were more desperate. The people in this community were willing to take the risks involved by inviting this industry into their midst because they were that desperate for the potential economic development. DeSoto County was prospering, doing well, and didn’t need to take that risk, because they had their whole focus on the family.
Indeed, the fact that Tunica County was able to lure casinos to the area at all was dependent on their nonavailability in DeSoto County and, in relation, the difference in perspective in terms of being treated as a moral or economic issue. However, that taken together with liberal gaming regulations, “looser licensing restrictions and relatively low gaming taxes” (Wallace 1998: 41), and better, yet still problematic, riverboat access sites than DeSoto were not enough. The publicly owned commercial gaming institutions, those that operated top shelf casinos in places like Las Vegas, were not convinced that
Tunica County provided a sound investment (Hirschman 1991). Their hesitance left the first entrepreneurial move in the hands of local landowners who unbeknownst to them would set the precedent that allowed the type of riverboat casino development that exists in Tunica today and which is to a large extent responsible for its growth.
187 6.2.2.1.1 SPLASH AND THE LOCATIONAL TUG-O-WAR
It’s kind of ironic that Tunica would revive something [riverboat gambling] that was so reminiscent of the imagery of the really wealthy, high-living planter, when Tunica’s reputation is that of a region or a county that was really very much victimized by its plantation leadership. (Cobb in Kelley 1992a: A1).
The political power of the planters in Tunica County was unyielding at the time that Mississippi introduced riverboat gambling as an economic development opportunity.
Many had or currently resided on the Tunica County Board of Supervisors, which controls almost everything in the county. 20 However, the planters did not have to be elected officials to set the course for development nor does that development have to center around agriculture. Two of the most influential in casino development were Dutch
Parker and Richard Flowers. The former stood to benefit most as one of the handful who owned thousands of acres of river-front property in northern Tunica County (Hirschman
1991). Parker and Flowers proposed and subsequently opened the first of Tunica’s casinos (fall of 1992), Splash Casino, located on Mhoon Landing, approximately thirty- six miles from Memphis.
Mhoon Landing was a former steamship-landing site that had some assemblage of development. Given the natural landscape of the county, potential casino sites were generally restricted to old oxbow lakes (cutoffs) and sloughs on old point bars with limited road access. In Tunica County only two public roads diverged from US Highway
61, then two lanes, to the river––one in Robinsonville and one in the town of Tunica, the latter a state highway (US 4) paved out to the levee at Tunica Cut-Off. The town, which
20 The most well-known is Paul Battle III, a planter who has been successful in the catfish industry and who has been on the board for nearly forty years.
188 wished to reap as much of the benefit from the casinos as possible, fully supported the
Mhoon Landing location, which is set just a few miles west of town.
A gravel road led to the casino site from town. Patrons had to traverse this road after having traveled along Route 61 from Memphis to Tunica, with scarcely a gas station available for services, just to wait in line for hours to board the casino. While the casinos later developed in Tunica County can hardly be considered boats, Splash was an actual barge, formerly operated as a dancing/dining cruise ship, which was transformed into a casino and permanently moored in a slip that had been dredged out to accommodate the boat. During its first month of business about 80,000 people paid the ten-dollar cover charge to board the 1,800-capacity casino. It had been shut down for two days due to an investigation of violations of state gaming laws related to internal financial controls
(Kelley 1992c,d).
The patronage of Splash far outweighed that projected by the casino industry and demonstrated a latent customer base (Baruffalo 2000), an economic inefficiency that had been severely underestimated (Wallace 1998). This recognition produced a surge of licensing applications, in a manner that has been referred to as a gold rush mentality . By late 1993 three other casinos had opened at the Mhoon Landing site. However, casino development was slow, due in part to an absence of infrastructure (Kelley 1992a).
Splash, having had a significant jump start, enjoyed a virtual monopoly for nearly a year, collecting more than $5 million in that time (MGC 2004). The owners retained 4 percent of Splash’s net revenue and further capitalized on property negotiations for additional developments.
189 However, the timing of Splash’s opening and the risk absorbed by the planters by being the first in the county to invest in a casino were not exactly operands of the free market. Intervening opportunity helped fuel the initial success of Splash, but also later led to the demise of Mhoon Landing as the agglomeration site of Tunica County casinos, leaving it to rest as a casino ghost town (Meyer-Arendt 1998). 21 That opportunity was constructed internally in a struggle between town and county political regimes and externally through the somewhat underhanded means of intervention in DeSoto County affairs.
At the same time that the proposal for Splash was in the works (late summer
1991), another plan to build a casino on Buck Lake, in northern Tunica County, was released by the Hardie Financial Group (Huston 1991). The Mississippi Gaming
Commission withheld approval of the Buck Lake site awaiting proof that the Mississippi
River actually flows into the lake (Taylor 1992). In the meantime, Tunica Town officials took action to block the development. In a resolution signed by the mayor and the Board of Alderman and printed in the local newspaper, among other things, it was declared that the Buck Lake location would provide ( Tunica Times-Democrat 1991) :
… no benefit to the economic development of the Town of Tunica and will be a substantial detriment since the likelihood of other casino development in Tunica County will be eliminated.
In that resolution the detriment to development at Mhoon Landing and another potential site at Tunica Cut-Off were mentioned specifically. In so doing, it was further resolved:
That the State Tax Commission of the State of Mississippi, the Gaming Commission of the State of Mississippi, the Planning Commission of Tunica County, Mississippi, and the Board of Supervisors of Tunica County, are hereby
21 Mhoon landing is currently (2004) undergoing redevelopment as a major casino site.
190 requested to deny any action which would further or aid the development of casino gambling on Buck Lake in Tunica County, Mississippi.
Essentially, the local casino developers and their supporters tried to strong-arm all involved into forcing the location of casinos as near the town of Tunica as possible, persuading townspeople that the benefit would be lost if casinos located in the northern part of the county. At the same time, the Board of Supervisors and the Planning
Commission were being pressured by landowners in the north (Buck Lake) and residents nearest other proposed sites at Tunica Cut-Off and Bordeaux Point.
By the start of 1992 an environmental coalition had been organized in opposition to all potential casino sites west of the levee. The formation of the Mississippi River
Coalition was prompted by fishermen who successfully challenged the development at
Tunica Cut-Off due to their concern about environmental impacts. The coalition consisted mainly of members from the Sierra Club as well as other activists based in
Memphis who condemned the US Army Corps of Engineers for failing to give adequate consideration to the environmental impacts of casino sites in the north Delta region. This incited a response from the Tunica County Board of Supervisors who, fearing the loss of opportunity altogether (Field Notes 2002 B), drafted the following resolution as it appeared in the Tunica Times-Democrat on April 23, 1992:
Resolutions of the Board of Supervisors of Tunica County, Mississippi, Endorsing the Buck Lake Casino Project
WHEREAS, it appearing unto the Board that Tunica County is in dire need of any and all industries that will provide jobs and additional revenue for the County; and
WHEREAS, it appears that the Mississippi Grand Resort Casino (Buck Lake Project) will provide numerous jobs
191 and approximately $1,400,000 of additional revenue to the County; and
WHEREAS, it appears that certain environmental groups are attempting to deny the County of these much needed jobs and revenue
NOW THEREFORE BE IT RESOLVED, that the undersigned Board does hereby vigorously endorse and support the aforesaid Mississippi Grand Resort Casino (Buck Lake Project) and directs the Clerk of this Board to submit copies of these resolutions to the US Army Corps of Engineers, the Department of Environmental Quality, and cause same to be published in the local newspaper.
With this decree of endorsement developers increased the number of proposed sites as near as possible to Memphis. Sites included the aforementioned Buck Lake, which is an oxbow lake abreast the DeSoto county-line, and others at old Commerce
Landing in Robinsonville. From late 1993 through 1994, casino development erupted in the northernmost part of the county. A cluster of four corporate casinos opened at
Commerce Landing and another cluster of three at Buck Lake, referred to as Casino Strip and Casino Center , respectively. Later, in 1996, the Grand Casino Resort opened (an expanse of earlier Hardie Financial Group investments in Tunica), literally just over the
Tunica county-line. Despite other spatial rearrangements, including openings and closings as start-up casinos gave way to corporate casinos, the Grand marked the last of the major casino construction site during the boom.
In the process, Mhoon Landing became relatively less competitive as “strong rivalry forces the competitors to continually innovate and improve” (Wallace 1998: 47).
This was done both in terms of location and amenities on the part of the new casinos to the north by taking full advantage of the Mississippi Legislature’s failure to resolve what
192 it meant by a navigable waterway and by capitalizing on the precedent set by Parker and
Flowers in their interpretation of the law. With the uncontested allowance of a slip in the case of Splash, the riverboat (barge) was not technically docked , but rather was enclosed .
As such, the capital-rich corporate casinos were able to manipulate the law and the environment to their own advantage, destroying wetlands for waterfront development
(Walters 1994; Williamson 1994), in a manner best described by Meyer-Arendt (1998:
160):
The preparation of potential sites for casino “vessel” emplacement entailed great modification in many cases, including deepening access approaches and introducing fill to raise the grade of the parking areas and support infrastructure above potential 100-year flood levels. For each casino site, several acres of batture (seasonally flooded but forested) land were cleared and raised 12 or more feet in elevation. In some cases, ring levees were constructed around the casino property. Such extensive filling and site modification resulted in the disturbance and destruction of vegetation identified as wetlands. Although wetland modification could legally be “mitigated” by agreements with the US Army Corps of Engineers and the US Fish and Wildlife Service, reports of unauthorized wetlands destruction led to periodic investigations. Also, the casino was required to float in water linked to the Mississippi River, and this legal requirement was met by placing a small-diameter connecting pipe [to the casino barge] which would allow water exchange during flood events.
One by one, the casinos nearest the town of Tunica began to disappear. Two, including Splash, filed for bankruptcy in 1995, Bally’s relocated to a site at Buck Lake adjacent to the others at Casino Center, and the fourth, a fully operable paddle wheeler, simply steamed down river to a new location. Further, Parker and Flowers had leases on four additional parcels of land for casinos and plans for support facilities in the Mhoon
Landing vicinity (e.g., RV park, grocery store, employee housing), all of which never
193 materialized. The demise of Mhoon Landing was slowed by the delay of casino openings in the north from the April 1992 resolution through 1993. The delay was due to a number of human resource factors in addition to those already mentioned (e.g., cultural politics, physical resources, and infrastructure conditions).
6.2.2.1.2 IMPEDIMENTS TO GROWTH
In 1992 (as well as in later years), DeSoto County was still able to approve the resolution for riverboat gambling. Many developers who had hopes for a DeSoto location, with Tunica in mind as a back-up plan, awaited the second-time referendum outcome in early November 1992 before moving forward in Tunica. This time around the debate in DeSoto was more heated and fueled not only by local politicians and residents and statewide church leaders, but also by players in the casino industry, serving in both opposing and supportive positions. All were backed by a substantial amount of capital in what was dubbed the county’s most expensive political campaign (Bayne
1992a). The major contributors were Promus and Belz Enterprises, Memphis based companies that were pursuing a license to operate on Horn Lake in DeSoto County, and the Hardie Financial Group, who were already operating in Tunica County.
It was believed that opposition groups were being funded with money run through
Hardie, owner of one of the nation’s largest gambling operations in Los Angeles and principal owner of Mississippi Grand Casinos, in order to protect the gaming interests in
Tunica County. This was alleged by Promus Companies Chairman (Mike Rose):
“We believe this entire scheme of opposition has been orchestrated by (George) Hardie and his partners… to deceive DeSoto county voters as to the true nature of the opposition.” Rose said Hardie told Promus officials early
194 in the referendum campaign that “he would strongly resist efforts on our part to secure a license to operate in DeSoto County… I feel sorry for Jim Brown (Chairman of the Coalition of Citizens for Quality Life),” Rose said. “… he was duped by the gambling interests of Hardie and his partners to protect their gambling interests in Tunica County.” (Bayne 1992b: A1).
Those interests not only included the Grand, but also Splash and other potential casino operators at both Mhoon Landing and Buck Lake because their interests were one and the same with regard to establishing a successful casino environment. Their goal was to construct a destination place rather than offer casinos of convenience.
The Coalition of Citizens for Quality Life claimed to have seized the issue and therefore the financial support, “through altruistic motives of protecting the public morality and the quality of life of the community” (Bayne 1992a: A1). Efforts included resident mailings, newspaper, television, and radio ads, and were rumored to have extended to coercing DeSoto residents who worked at the Tunica casinos to post derogatory statements about gambling on their properties (Baruffalo 2000; Bayne 1992a;
Field Notes C 2002). Such activities reflect what Kindt (1998) stated about the American gaming industry on the whole: it is “prepared to spin any moral debate either way to fulfill industry agendas” (93), with the philosophy that “everyone and everything has a price” (87). In this case their spinning paid off, as the second attempt to allow riverboat gambling in DeSoto County was voted down (Bayne 1992c), opening the floodgates for
Tunica.
Once the mad rush to Tunica ensued, the process by which developers were to announce their proposal and apply for the needed approval slowed the process for all. By
April 1993 the number of notices of intent had escalated to twenty. Many of the
195 proposals hinged on requests to rezone properties from agricultural to commercial.
County officials simply couldn’t keep up with that level of demand. Also, the planters who owned that land, which went from virtually worthless to approximately $5,000 an acre in 1992 to $100,000 an acre in 1993 (Field Notes A 2003), were reluctant to sell.
Instead, the landholders forced perspective casino operators into lease deals, many in exchange for revenue sharing (Field Notes A 2003). Securing property took longer than expected as corporate casino operators preferred to own rather than lease and the negotiations that took place over the matter deterred some from locating in Tunica altogether (Field Notes B 2002).
Further, there was a shortage of both construction workers/contractors and, most of all, of suitable permanent casino employees. As noted previously, a large percentage of the population was poorly educated and few had experience in the sales and service occupations that made up more than 85 percent of the casinos’ employment needs (Hill
1994). This was not simply an issue of occupational skills, but one of social skills and basic labor practices, as noted in Walsh (1999): “of every seven casino-job applicants from Tunica only one is deemed fit to join the work force… the other six lack even the basic habits necessary to hold down almost any job.” The then county director of human services explained further that, “if you’re twenty-six or twenty-seven and never had a job… nothing has taught you how to work” (Crawford in Schwarz and Schwarz 1999:
112). Many of the potential employees had been employed in agriculture, and for many that meant as day laborers rather than permanent employees. This situation produced an altogether different work culture, as expressed by one casino manager (Mezzetta in
Baruffalo 2000: 181-182):
196 …this guy, working building maintenance… didn’t show up for three nights. So he was fired, and when he came in to work and was told that he was fired, … he came into the office and sat down and told me that he “didn’t understand.” I told him, “Well, you were on the schedule to work and you did not show up for three days, so you were terminated.” And he said, “Well, I understand that, but when I came in this morning, the floor was dirty and it needed sweeping, so why didn’t you put me back to work?”
Because, you see, they had two major sources of labor in the Delta here, either you worked in agriculture, or you worked in one of these factories that made toys or mattresses or that kind of thing. And the standard procedure was that the foreman would walk out on the loading dock, and there would be two or three hundred people and he would say, I need you and you and you and you. And if that person on the line didn’t show up the next day, it didn’t make any difference, there was somebody there to take their place. It was the same way in agriculture. So it was a way of life for them.
Given the situation in Tunica, the casinos were forced to turn to Memphis to fill labor needs by offering competitive wages and benefits to lure in commuters. This course of action put a crunch on the Memphis labor market, particularly within the hospitality industry (Campbell 1996; Hayes 1995). In some cases, casinos even offered the means of transportation. As one Route 61 billboard read, “casino staffing: full-time and part-time positions available immediately, round trip transportation furnished from
Memphis” (Field Observation 2001). Still, as the number of gambling establishments grew so did competition for employees. In fact, one casino manager reported that its competitors were “stealing our employees, they’re actually recruiting them right off the floor (Catolo in Sullivan 1993: A1).
Further impeding full employment at the casinos was the poor and somewhat dangerous road system that commuters had to travel to get to work. This issue was
197 presented earlier in the case of Splash, but it remained a problem even with the new casino location nearer the major thoroughfare, US 61, which was set to be widened to four lanes by the state but was not expected to be completed until late 1996 (Meyer-
Arendt 1998). Thus, the journey to work was hindered by bumper-to-bumper casino customers along with slow-moving construction vehicles and the ever-present farm equipment, making the route accident-prone, which further imposed delays (Field observation 1996). 22
Also, eliminating the trip from Memphis via migration was not an option for many, both literally and conceptually. Due to the housing shortage amenities were limited and costs were high, reflecting demand. Few hotel rooms existed at the time to serve as temporary housing. To accommodate this demand, several trailer villages were set up, such as Mhoon Landing Mobile Homes, which still exists. Added to that was the lack of basic community services, such as places to shop, and the notably poor education system, piled on top of the poverty reputation set forth by the Sugar Ditch notoriety of the prior decade. Few were willing to relocate to Tunica County. One long-time resident likened the situation to Cobb’s (1992) description of the Delta as the most southern place on earth (Field Notes A 2003):
Tunica is the most southern, southern place on earth… we are still going through reconstruction and to understand anything about Tunica you have to recognize that. What exists in other places of the country that people take for granted didn’t exist here before the casinos and much of it still doesn’t exist here—especially things like good schools and services like grocery stores, and so on. There’s the problem with getting people to move in… you can’t get an educated resident population to move in without it and you
22 Although my research in Tunica County did not officially begin until 2001, I visited the county in prior years and have some first-hand knowledge of the conditions/processes of the earlier stages of casino development in the county.
198 can’t get it without them, their demand to make things happen, their demand for a quality education… There was no middle class in Tunica prior to the casinos and still isn’t.
6.3 CHAPTER SUMMARY
The power elite, particularly the Board of Supervisors which was composed of and represented the interests of the white landholder, maintained a position of control.
Enveloped in the rhetoric of the Southern culture , and despite the odds, they sought to and successfully commanded the incision of gaming in Tunica County as well as its growth trajectory. In so doing, they projected the gaming industry as an instrument for the greater good. Whether sincere or not, their argument was most forceful with respect to the plight of the black poverty population.
On the point of sincerity, it is not my position to judge, but throughout the process those who had no stake in the outcome exerted influence on the issue of Southern white defensiveness . For instance, a respected journalist, in conveying local opinion, reported that (Kelley 1992b: A1):
There is a residue of anger here among some whites who felt the press misrepresented the town by taking Sugar Ditch out of the context of the rural South and the Mississippi Delta. They vow never again to be portrayed like they were then.
For black Tunica residents, many felt attention finally was being given to the needs long ignored in an agricultural community dependent upon perpetuating a ready pool of unskilled, seasonal black workers. They wanted new opportunities, and that means jobs.
With that in mind, we can see how the interests of both black and white residents of
Tunica County could possibly come together in support of an issue so seemingly in opposition to their cultural identity.
199 Such an understanding is particularly salient with respect to religion, which otherwise would have been thought to reject such an economic imperative as gambling.
Typically a highly religious state, Mississippi had in the past rejected gambling, even for charitable purposes, due to the perceived sinfulness of the activity. In the case of Tunica, a dire economic state seemingly outweighed that long-lived moral concern. Framing the issue in economic terms opened the door for oversight by many citizens with respect to the issues of the immorality of gambling from a religious perspective, but this did not negate the fact that those moral objections remained and could influence the development and distributive outcome.
There is little doubt that the outcome has been anything less than positive from an economic standpoint. For instance, in celebrating the 10-year anniversary of casino gaming development in Tunica, the Tunica Convention and Visitor’s Bureau (2002) documented more than $4 billion in total capital investments, a county-wide drop in unemployment from 26 percent in 1992 to 5 percent in 2001, and a per-capita income increase from $9,000 in 1991 to over $20,000 in 2001. Also, in terms of tax revenue from 1991 to 2001, the state gleaned $521 million, of which $215.4 million went to the county. Of that $215.4 million, the town of Tunica was given $13.2 million and Tunica
County schools received $27.3 million. Yet, what is left to question most, however, is the distributive nature of that outcome with regard to the majority black poverty population. The discussion thus far hints at the least benefit having been derived by the most in need from the perspective of jobs. This matter will be taken up in the next several chapters (7-9), as well as the outstanding issue of religion and its influence on economic outcomes for the poor (chapter 10).
200 6.4 CHAPTER REFERENCES
Abt, V. 1996. The Role of the State in the Expansion of Commercial Gambling in the United States. In J. McMillen, ed. Gambling Cultures: Studies in History and Interpretation. New York: Routledge. Pp. 179-198.
Abt, V., J. Smith, and E. Christiansen. 1985. The Business of Risk: Commercial Gambling in Mainstream America. Kansas City: University Press of Kansas.
American Gaming Association (AGA). 2001. 2001 State of the States: The AGA Survey of Casino Entertainment. American Gaming Association. Available online at
Asbury, H. 1938. Sucker’s Progress. New York: Dodd, Mead, & Co.
Bayne, W. 1990a. Riverboat Gambling Foes Face Deadline for Petition. The Commercial Appeal. 29 November: S1.
Bayne, W. 1990b. Gambling Awareness Tops Foes’ Agenda: Education Valued Over Signatures. The Commercial Appeal. 13 December: S1.
Bayne, W. 1992a. Gambling Allies, Foes May Spend $1 Million, Two Sides Pour Funds, Claims Into DeSoto Campaign. The Commercial Appeal. 2 November: A1.
Bayne, W. 1992b. Rose Says Rival Casino Backs Foes in DeSoto. The Commercial Appeal. 1 November: A1.
Bayne, W. 1992c. DeSoto Casino Loses; Miss. Lottery Ahead, Big DeSoto Question Comes Up ‘No’ Again. The Commercial Appeal. 4 November: A1.
Blakely, R. 1984. Legal Regulation of Gambling Since 1950. The Annals of The American Academy of Political and Social Sciences. 474: 12-22.
Bluestone, B. and B. Harrison. 1982. The Deindustrialization of America: Plant Closings, Community Abandonment, and the Dismantling of Basic Industry. New York: Basic Books.
Branson, R. 1990a. All Bets Off as Vicksburg Defeats Gambling. The Commercial Appeal. 12 December: A8.
Branson, R. 1990b. Casino Backers Appeal to Economic Upswing. The Commercial Appeal. 18 November: A1.
Branson, R. 1991a. Miss. Clergy Claim Racial Bias in Law, Sue to Sink Casinos. The Commercial Appeal. 30 March: A1.
201
Branson, R. 1991b. Opinion on Casino Location Blasted. The Commercial Appeal. 10 January: B1.
Breen, T. 1977. Horses and Gentlemen: The Cultural Significance of Gambling Among the Gentry of Virginia. William and Mary Quarterly. 34: 239-257.
Bridges, T. 2001. Bad Bet on the Bayou: The Rise of Gambling in Louisiana and the Fall of Governor Edwin Edwards. New York: Farrar, Straus and Giroux.
Caldwell, G., B. Haig, M. Dickerson, and L. Sylvan (eds). 1985. Gambling in Australia. Sydney: Croom Helm.
Campbell, L. 1996. Casinos Offer Perks to Lure Skilled Staff. The Commercial Appeal. 10 March: C1, C5.
Clark, G. 1989. Unions and Communities Under Siege. Cambridge UK: Cambridge University Press.
Cobb, J. 1992. The Most Southern Place on Earth: The Mississippi Delta and the Roots of Regional Identity. New York: Oxford University Press.
Commission on the Review of the National Policy Toward Gambling. 1976. Gambling in America: Final Report. Washington DC: US Government Printing Office.
Comprehensive Plan, Tunica County, Mississippi. 2002 October. Tunica: Allen and Hoshall.
Corditz, D. 1990. Beting the Country. Financial World. February 20: 23-26.
Dixon, D. 1998. The Only Game in Town: The Cultural Politics of Riverboat Gambling in Cape Girardeau and Scott City, MO. In K. Meyer-Arendt and R. Hartmann, eds. Casino Gambling in America: Origins, Trends, and Impacts. New York: Cognizant Communication Corporation. Pp. 168-179.
Dombrink, J. and W. Thompson. 1989. The Last Resort: Success and Failure in Campaigns for Casinos. Reno: University of Nevada Press.
Eadington, W. 1984. The Casino Gaming Industry. The Annals of the American Academy of Political and Social Sciences. 474: 23-35.
Eadington, W. 1988. Gambling Research: Proceedings of the Seventh International Conference on Gambling and Risk-Taking. Volumes 1-3. Reno: University of Nevada.
202 Eadington, W. 1999. The Spread of Casinos and Their Role in Tourism Development. In D. Pearce and R. Butler, eds. Contemporary Issues in Tourism Development. New York: Routledge.
Eadington, W. and J. Cornelius, eds. 1992. Gambling and Commercial Gaming: Essays in Business, Economics, Philosophy, and Science. Reno: University of Nevada.
Eadington, W. and J. Cornelius, eds. 1997. Gambling: Public Policies and the Social Sciences. Reno: Institute for the Study of Gambling and Commercial Gaming, University of Nevada.
Ezell, J. 1960. Fortune’s Merry Wheel: The Lottery in America. Cambridge: Harvard University Press.
Faragher, S. 1995. The Complete Guide to Riverboat Gambling: Its History and How to Play, Win, and Have Fun. New York: Citadel Press.
Fischer, T. 1985. Watch Where the Next Casino Cities Will Grow. Successful Meetings. November: 75-81.
Frey, J. 1998. Federal Involvement in U.S. Gambling Regulation. The Annals of the American Academy of Political and Social Science. 556: 138-153.
Garlington, L. 1991. Business Press Bids for Casinos in Tunica. The Commercial Appeal. 13 September: A1.
Glowacka, A. 1996. Governments and Competitiveness in Central and Eastern Europe. Competitiveness Review. 6(2): 27-30.
Goodman, R. 1994, ed. Legalized Gambling as a Strategy for Economic Development. Northampton MA: U.S. Gambling Study.
Goodman, R. 1995. The Luck Business: The Devastating Consequences and Broken Promises of America’s Gambling Explosion. New York: Free Press.
Hayes, J. 1995. Casino-Labor Game Leaves Winners, Losers Behind. Nation’s Restaurant News. 13 March: 11.
Healey, M. and P. Dunham. 1994. Changing Competitive Advantage in a Local Economy: The Case of Coventry, 1971-1990. Urban Studies. 31(8): 1279-1301.
Hill, M. 1994. Labor Market Effects of Gaming in Mississippi. Mississippi Economic Review and Outlook. December: 10-18.
Hirschman, D. 1991. Casino Defeat in DeSoto Called Jackpot for Tunica. The Commercial Appeal. 21 February: B1.
203
Howard, J. 1993. Opinion Attempts to Define ‘Navigable.’ Jackson Clarion-Ledger. 16 July.
Huston, J. 1991. California Firm Might Float $20 Million Mississippi Casino. The Commercial Appeal. 30 August.
Jensen, K. and A. Blevins. 1998. The Last Gamble: Betting on the Future in Four Rocky Mountain Mining Towns. Tucson: University of Arizona Press.
Kelley, R. 1992a. Gaming Off Delta Shores Grew Wild and Woolly. The Commercial Appeal. 28 December: A1.
Kelley, R. 1992b. Gambling Puts Tunica on Path for Change. The Commercial Appeal. 18 October: A1.
Kelley, R. 1992c. Casino, County Hit Jackpot 1 st Month. The Commercial Appeal. 9 December: A1.
Kelley, R. 1992d. Gamblers Jam Splash Casino After 2-Day Shutdown. The Commercial Appeal. 10 November: A9.
Kifner, J. 1996 October 4.. An Oasis of Casinos Lifts a Poor Mississippi County. High Rolling on the River, A Special Report. New York Times. A1-2.
Kindt, J. 1998. Follow the Money: Gambling, Ethics, and Subpoenas. Annals of the American Academy of Political and Social Science. 556: 85-97.
Longstreet, S. 1977. Win of Lose: A Social History of Gambling in America. Indianapolis: Bobs Merrill.
Mahon, J. and R. McGowan. 1996. Defining the Competitive Environment: Industry as a Player in the Political and Social Environment. Westport CT: Greenwood Press.
Markon, J. 1990. DeSoto Petitions Bring Gambling Vote Nearer. The Commercial Appeal. 20 December: B1.
Martins, L. 2002. Industry Insights—Casinos. TB Taglich Brothers. Analyst Insights.
McGowan, R. 1999b. Legalized Gambling: A History. In M. Williams, ed. Legalized Gambling: Contemporary Issues. San Diego: Greenhaven Press. Pp. 13-22.
McGowan, R. 2001. Government and the Transformation of the Gaming Industry. Northampton MA: Edward Elger.
204
McMillen, J., ed. 1996. Gambling Cultures: Studies in History and Interpretation. London: Routledge.
Meyer-Arendt, K. 1998. From the River to the Sea: Casino Gambling in Mississippi. In K. Meyer-Arendt and R. Hartmann, eds. Casino Gambling in America: Origins, Trends, and Impacts. New York: Cognizant Communication Corporation.
Miers, D. and D. Dixon. 1979. The National Bet: The Re-emergence of the Public Lottery. Public Law. 372-403.
Mississippi Gaming Commission (MGC). 2004. Reports.
Mississippi Gaming Commission (MGC). 2002. Reports. Directory of Current Operators.
Morris, R. 1989. Pride of Mississippi Plagued by Problems. Jackson Clarion-Ledger. 1 October.
Munting, R. 1996. An Economic and Social History of Gambling in Britain and the USA. Manchester: Manchester University Press.
Myerson, A. 1996. A Wave of Casinos Hits Mississippi’s Gulf Coast. The New York Times. 9 July.
Peet, R. 1983. The Geography of Class Struggle and the Relocation of United States Manufacturing. Economic Geography. 59: 112-143.
Philo, C. and G. Kearns, eds. 1992. Selling Places: The City as Cultural Capital, past and present. Oxford: Pergamon Press.
Porter, M. 1980. Competitive Strategy: Techniques for Analyzing Industries and Competitors. New York: The Free Press.
Porter, M. 1990. The Competitive Advantage of Nations. New York: The Free Press.
Porter, M. 1995. The Competitive Advantage of the Inner City. Harvard Business Review. 73(3)
Preston, F., et al. 1998. Gambling as Stigmatized Behavior: Regional Relabeling and the Law. Annals of the American Academy of Political and Social Science. 556(March): 186-196.
Real, G. 1990. DeSoto Will Vote Feb. 19 on Gambling. The Commercial Appeal. 28 December: B1.
205
Reith, G. 1999. The Age of Chance: Gambling in Western Culture. London: Routledge.
Roush, C. 1993. So Much for the Puritan Heritage. Business Week. 18 October: 82.
Rugman, A. 1991. Diamond in the Rough: Business Theory of Michael Porter, Canada’s International Competitiveness. Business Quarterly. 55(3)
Sabety, J. and J. Griffin. 1996. Pro-Competitive Alliances: New Vehicles for Regional, State, and Community Based Economic Development. Economic Development Quarterly. 14(2): 2-6.
Saul, S. 1997. Rural Renewal: But Poverty Persists as Casinos Thrive in Mississippi County. In J. Vogel, ed. Crapped Out: How Gambling Runs the Economy and Destroys Lives. Monroe ME: Common Courage Press. Pp. 47-57.
Schwarz, B. and C. Schwarz. 1999. Mississippi Monte Carlo: Gambling and Race Relations in Tunica County. In M. Williams, ed. Legalized Gambling: Contemporary Issues. San Diego: Greenhaven Press. Pp. 111-121.
Sternleib, G. and J. Hughes. 1983. The Atlantic City Gamble. Cambridge: Harvard University Press.
Stokowski, P. 1996. Riches and Regrets: Betting on Gambling in Tow Colorado Mountain Towns. Boulder: University of Colorado Press.
Storper, M. and R. Walker. 1989. The Capitalist Imperative. London: Blackwell.
Sullivan, B. 1993. Casinos Leaving Workers Flush, Jobs Multiply: “Everything’s Better.” The Commercial Appeal. November 29: A1.
Sullivan, C., L. Powell, and N. Harvey. 1985. The Mississippi Gulf Coast: Portrait of a People. Northridge CA: Windsor Publications Inc.
Taylor, B. 1992. Gaming Commission Upholds Buck Lake Site Approval. Tunica Times-Democrat. 5 March.
Thompson, W. 1998. Casinos de Juegos del Mundo: A Survey of World Gambling. Annals of the American Academy of Political and Social Science. 556(March): 11-21.
Tunica Convention and Visitor’s Bureau (TCVB). 2002. Tunica Mississippi10 Years: The Tunica Miracle, The Economic Impact of Gaming and Tourism 1992-2002. Tunica MS: Tunica Convention and Visitor’s Bureau.
206 Tunica Times-Democrat. 1991. Resolutions of the Mayor and Board of Alderman of the Town of Tunica, Mississippi Regarding the Location of Riverboat Gambling in Tunica County. 7 September.
Vogel, H. 1990. Entertainment Industry Economics. Cambridge: Cambridge University Press.
Wallace, J. 1998. The Casino Gambling Industry: A Case Study of Tunica, Mississippi. Published Dissertation. The University of Memphis.
Walsh, M. 1999 October. Gambling Pays Off for County—but Not for Many Inhabitants. Los Angeles Times.
Walters, L. 1994. A Mississippi County Grows Casinos Instead of Cotton. Christian Science Monitor. 86: 10.
Williamson, L. 1994. A Dicey Development. Outdoor Life. 193(April): 44,46.
Yla-Antilla, P. 1994. Industrial Clusters—A Key to New Industrialization? Economic Review. 1(March 22)
207 CHAPTER 7
CONTROVERSIES AND CONTRADICTIONS OF THE MIRACLE
All empirical studies, including those offering elaborate models of less developed economies, suffer from the inadequacy of historical data, as well as from unresolved problems in definition, methodology, and measurement. (Gagliani 1987: 313)
This chapter begins the first of three chapters on the impact analysis step of PSIA.
In this chapter, I further unearth some of the controversies relating to and contradictions about what is touted as the Tunica Miracle. I first provide objective measures of impacts at the national, state, regional, and county levels and link them to economic and fiscal growth and related outcomes. In so doing, I use standard indicators and traditional forms of analysis (e.g., shift-share, input-output, and location quotients). Then I turn to an assessment of the distributional effects of those impacts with respect to the poverty population by supplementing analysis of objective measures with subjective and other contextual data gleaned from the participatory econometric approach. Throughout the impact chapters, I demonstrate the value of taking on alternative perspectives with regard to geographic scale and methods of measurement when trying to understand economic development impacts. As I drill down through those scales, I extend those perspectives to different stakeholder groups (e.g., county officials and the poverty population) in order to illustrate underlying issues of intent, access, and behavioral responses to change.
208 7.1 MACRO PROFILE OF INDUSTRY GROWTH
Industry experts at Global Betting report that despite increased competition abroad, since the early 1990s the United States has had the fastest growing gaming market. That market consists of charitable gaming, pari-mutuel wagering, state lotteries, commercial casinos, and tribal casinos, which together brought in $68.7 billion in gross gaming revenue (GGR) in 2002 compared to $30.4 billion in 1992 (AGA 2004). 23 Each segment of the market contributed to that growth, which reflects a compound annual growth rate of 8.4 percent from 1992 to 2002. However, growth in the commercial casino segment of the gaming industry has been most vigorous ( see Figure 7.1).
Goss (2002) stated that casino revenues grew from $8.3 billion in 1990 to $25.7 billion in 2001, which represents a growth rate more than five times that of inflation and nearly three times the growth rate of the U.S. economy on the whole. Further, in 2002 casinos commanded 59.8 percent of the total U.S. gaming market with 38.7 percent of
GGR going to commercial casinos (AGA 2003). In addition, in recent years much of that growth occurred in riverboat casinos (including dockside casinos like those found in
Tunica). For example, from 1997 to 2002 alone, the gross gaming revenue of riverboat casinos grew by 64.1 percent, which represents 37.1 percent of total gross gaming revenues for casinos in 2002 ( see Table 7.1). Those figures reflect the fact that nine states other than Nevada and New Jersey legalized commercial casinos over the decade following the passage of the federal Indian Gaming Regulatory Act (IGRA) in 1988 ( see
Table 7.2) .
23 Gross gaming revenue represents gross gaming receipts, which include the winnings paid to the bettor. Adjusted gross revenues are gross gaming receipts minus the winnings paid to the bettor. Both measures are used in this study; the choice of the measure reflects the manner in which the data are published by the
209 Figure 7.1 Cumulative Change in Gross Gaming Revenue; All Gaming and Commercial Casino Gaming, 1993-2003
100% 90% 80% 70% 60% 50% 40% 30% 20% Cummulative Change 10% 0% 1993- 1994- 1995- 1996- 1997- 1998- 1999- 2000- 2001- 2002- 94 95 96 97 98 99 00 01 02 03 Year All Gaming Commercial Casinos
Source: AGA 2004
Table 7.1 Gross Gaming Revenues by Casino Type, 1997 and 2002
Gross Gaming Revenues Growth Percent Total Casino Type 1997* 2002*Rate** 1997 2002 Nevada/New Jersey $11,524.4 $13,631.6 6.7% 56.1% 48.4% Deepwater Cruise Ships $244.1 $294.4 9.2% 1.2% 1.0% Cruises-to-Nowhere $219.6 $385.1 68.1% 1.1% 1.4% Riverboats $6,170.5 $10,437.9 61.4% 30.1% 37.1% Other Land-based Casinos $474.5 $1,911.2 312.6% 2.3% 6.8% Other Commercial Gambling $157.5 $162.6 -9.5% 0.8% 0.6% Non-casino Devices $1,737.0 $1,320.9 -38.7% 8.5% 4.7% Total $20,527.6 $28,143.7 26.9% 100.0% 100.0% *Millions of dollars **Adjusted for inflation using 2005 CPI conversion factors Sources: Christiansen Capital LLC 2004 and International Gaming & Wagering Business 1998 (August).
industry or reported to the government (e.g., state gaming commissions), which may vary due to the regulatory framework of each state.
210 Table 7.2 Commercial Casino Legalization and Opening Dates, Number in Operation, and Gross Gaming Revenues by State, 2002
Year Year 1st Casino Casinos in Gross Gaming Revenue 2002 State Legalized Opened Operation 2002 Total* Mean* Colorado 1990 1991 42 $719.7 $17.1 Illinois 1990 1991 9 $1,800.0 $200.0 Indiana 1993 1995 10 $2,100.0 $210.0 Iowa 1989 1991 13 $972.3 $74.8 Louisiana 1990 1993 16 $2,000.0 $125.0 Michigan 1996 1999 3 $1,100.0 $366.7 Mississippi 1990 1992 29 $2,700.0 $93.1 Missouri 1993 1994 11 $1,300.0 $118.2 Nevada 1931 N/A 249 $9,400.0 $37.8 New Jersey 1976 1978 12 $4,400.0 $366.7 South Dakota 1989 1989 38 $66.3 $1.7
*Millions of dollars Source: AGA 2004
In association with the growth in the number of states with commercial casinos, the number of casino visits went from 46 million in 1990 to 310 million in 2003. The latter number includes 53.4 million patrons or approximately one-fourth of the U.S. adult population and an average of 5.8 trips per gambler (AGA 2004; Harrah’s 1997). The majority of those visitors (38%) came from the West, while the least came from the
Northeast (18%) and the South (20%) (AGA 2004). Among the eleven commercial casino states (excluding Nevada), Mississippi had the most admissions in 2003 ( see Table
7.3). Based on those visits, casinos have become the second most popular form of gaming in the United States, followed only by lotteries. This growth is reflected in consumer spending on commercial casino gaming, which went from $11.2 billion in 1993 to $27.0 billion in 2003 ( see Figure 7.2). Those figures represent a growth rate of 141 percent in current dollars and 89 percent in real (2005) dollars.
211 Table 7.3 Commercial Casinos; Number Employees, Employee Wages, Gross Gaming Revenue, and Admissions by State, 2003.
Employees State GGR** Tax Revenue* Admissions*** Number Wages* Colorado 7,364 $207.1 $0.698 $95.6 N/A Illinois 9,101 $376.4 $1.709 $719.9 16.6 Indiana 16,555 $589.5 $2.229 $702.7 25.4 Iowa 8,764 $278.5 $1.024 $209.7 19.3 Louisiana 20,775 $452.7 $2.017 $448.9 37.5 Michigan 8,087 $368.0 $1.130 $250.2 N/A Mississippi 30,377 $1,028.0 $2.700 $325.0 54.0 Missouri 10,700 $310.0 $1.330 $369.0 51.2 Nevada 1 192,812 $6,954.0 $9.625 $776.5 48.6 New Jersey 46,159 $1,239.0 $4.490 $414.5 32.2 2 South Dakota 1,734 $34.9 $0.074 $11.3 N/A
*Millions of dollars, wages include benefits and tips **Billions of dollars ***Millions of patrons 1Statistics include only locations with GGR of at least $1 million; admissions reflect visitor volume 2Employment data are for 2002 Sources: State Gaming Regulatory Agencies
Figure 7.2 Consumer Spending on Commercial Casino Gaming; U.S., 1993-2003*
$30.0
$25.0
$20.0
$15.0 Current $ Real $ $ Billions $10.0
$5.0
$0.0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
Year
*Real dollars are current dollars adjusted to 2005 values using CPI conversion factors Sources: Christianson Capital Advisors 1993-1999 and State Gaming Regulatory Agencies 2000-2003
212 As a result of the aforementioned activity, commercial casinos generated $27 billion in GGR in 2003, $4.32 billion of which went to state and local governments through direct taxes, representing an overall effective tax rate of 16 percent (AGA
2004). 24 Considering those figures on a per admission basis, GGR and tax revenue for the state of Mississippi was $6 and $50 in 2003, which was well below respective state averages of $15 and $79 for states where data on this variable were available ( see Figure
7.3). Those low figures for Mississippi, in comparison to those of other commercial casino states, are likely due in part to differences in gaming tax rates, which are relatively modest compared to most other states that legalized casinos since 1988 ( see Table 7.4).
Figure 7.3 Per Admission Tax Revenue and Gross Gaming Revenue; State and State Average, 2003
$250
$200
$150
$100
$ Per Admission $50
$0 IL IN IA LA MS MO NV NJ AVG State
Tax Revenue GGR
Source: Derived from Table 7.3
24 These figures include only direct commercial casino tax revenue. That is, they do not include tax revenue generated by state compacts with Native American casinos or other forms of gaming. Nor do they
213 Table 7.4 Range of Statutory Gaming Tax Rates by State
State Tax Rate Admission Tax Wager Tax Colorado Graduated None .25%-20% depending on million in AGP* Illinois Graduated $3-$5 per person depending on 15%-70% depending on million in number of persons admitted AGR** Indiana Graduated $3-$4 per person depending on 15%-35% depending on million in number of persons admitted AGR Iowa Graduated variable depending on number of 5%-20% depending on million in persons embarking an excursion AGR; annual $5/person riverboat capacity Louisiana Fixed & Graduated None for land-based casinos; 18.5%-21.5% depending on million variable based on riverboat in AGR and location; $60 headcount million/yr New Orleans Michigan Fixed None 18% on AGR; yearly state services fee no greater than 1/3 total annual assessment; 1.25% municipal services fee Mississippi Graduated None 4%-8% depending on monthly GGR***; .4%-.8% local tax depending on monthly GGR; 3.2% county tax depending on location
Missouri Fixed $2 per person 20% depending on monthly AGR Nevada Graduated None 3%-6.25% depending on monthly GGR; $250 annual per slot machine; annual and quarterly license fees on number of slot machines and table games
New Jersey Fixed None 8% GGR; 1.25% quarterly community investment tax or 2.5% annual tax on GGR South Dakota Fixed None 8% GGR; $2000 annual device fee for number of slot machines and table games
Sources: AGA 2004 and Center 2004 *Adjusted Gross Proceeds **Adjusted Gross Revenue ***Gross Gaming Revenue
include other revenues that stem from casino operations, such as income, sales, or rooms and meals taxes.
214 In terms of jobs, in 2003 the commercial casino industry directly employed
352,428 persons and paid more than $11.8 billion in wages ( see Table 7.3 for individual state figures), including benefits and tips (AGA 2004). That translates into 13 jobs on average per state and 11 jobs for the state of Mississippi for every $1 million in GGR ( see
Figure 7.4). Table 7.5 shows that those jobs spanned 443 casinos, which employed an average of 796 persons each, and represented more than half of all gaming industry employment. The lowest of those workforce shares at the state level are found in South
Dakota, while the highest are found in Nevada and New Jersey, followed by Mississippi.
Given the latter, it is clear that casinos play a more important employment role in
Mississippi than in any of the other states (10) that adopted commercial casinos since the
1988 legislation.
Figure 7.4 Number of Jobs per Million Dollars of Gross Gaming Revenue by Commercial Casino State, 2003
23
20
13 11 11 10 10 9 8 7 7 5
CO IL IN IA LA MI MS MO NV NJ SD AVG
Source: Derived from Table 7.3
215 Table 7.5 Casino Employment Comparisons by Number of Casinos per State, 11-State Casino Workforce, State Workforce, and Gaming Industry Workforce, 2003
Number Employed in Casinos as… Number of % 11-State % Gaming State Average Per State % State Casinos Casino Industry** Casino Workforce* Workforce Workforce CO 44 167 2.1% 0.3% 1.1% IL 9 1011 2.6% 0.2% 1.4% IN 10 1656 4.7% 0.6% 2.5% IA 13 674 2.5% 0.6% 1.3% LA 18 1154 5.9% 1.1% 3.1% MI 3 2696 2.3% 0.2% 1.2% MS 29 1047 8.6% 2.8% 4.5% MO 11 973 3.0% 0.4% 1.6% NV 256 753 54.7% 18.1% 28.7% NJ 12 3847 13.1% 1.2% 6.9% SD 38 46 0.5% 0.5% 0.3% 11-State 443 796 100.0% 1.3% 52.5%
*Based on employment in all occupations as of May 2003 **Gaming industry workforce defined here by SIC-701/709 employment Sources: AGA 2004, Bureau of Labor Statistics 2003, and PricewaterhouseCoopers 2003
Clearly, growth in the casino gaming industry has been phenomenal since 1988.
Despite recent recession and typical fluctuations in the business cycle, most experts expect that growth to continue. Further, it is believed that the Mississippi casino industry has yet to reach its peak. However, those predictions are based on recent industry trends that were witnessed during an extended and unprecedented time of general economic health and expansion across the nation. Therefore, it is important to understand and account for differences in positive economic impacts derived from industry growth and those stemming from macro-economic conditions, as well as that which defines the industry locally, such as location and regulatory and market structure.
216 7.2 DETERMINANTS OF INDUSTRY GROWTH IN MISSISSIPPI
One cannot logically separate the economic activity from the environment and historical context in which it occurs. There are, however, various statistical techniques that can provide partial answers to this question. (von Herrman et al. 2000: 21)
Fifty-seven counties in the United States have commercial casinos, seven of which are in Mississippi. Mississippi casinos, like most commercial casinos in the U.S., are located near a river or a body of water, in this case the Mississippi River or the Gulf of Mexico. As explained in chapter 5, this location pattern in Mississippi is due to legislative law and manipulation of that law by local elites and the casino industry.
However, the specific casino sites are in no way different than those in other states where commercial casino locations were strategically selected in advance or in response to gambling pressures from neighboring counties or states. For example, eleven of Iowa’s thirteen casinos are situated no more than three miles from the state’s borders with
Nebraska and Illinois (Goss 2002). This situation, referred to as border competition
(Vervilos 1998), is similarly the case in Mississippi, but more so by county. For instance,
Tunica’s Grand Casino Resort begins just a few feet away from the Desoto County line to the North and runs the length of that line east to west between Highway 61 and the
Mississippi River, which is as close at it can get physically to Tunica’s feeder market—
Memphis, Tennessee.
Those locational aspects are a large part of the reason why industry growth has continuously been achieved in Mississippi. Yet, there is also a difference within the state in that the agglomeration of Mississippi River casinos in the Tunica area are somewhat distanced from competitors compared to those along the Gulf and the southern portion of
217 the river. That is, Tunica casinos are at the center of a 150-mile area comprised of nearly three and a half million residents who lack an alternative casino gaming venue, while in the southern and coastal portions of the state there is direct competition from neighboring
Louisiana casinos for local residential draw as well as the potential draw from Arkansas.
Understanding the extent of growth and impact of casino gaming in Mississippi at the county level, however, is made difficult by the reporting and disclosure practices of the state. For instance, casino revenues by county are not published. Instead, such information is typically given on a regional basis, divided among Gulf Coast casinos,
North River casinos, and South River casinos ( see Figure 7.5). There are five counties in the Coast (3) and South River (2) regions, which are historic tourist areas. Thus, unlike the North River region, a tourist infrastructure existed prior to casino development. For instance, the Coast alone had about 6,400 hotel rooms before casinos while the North
River had only 20.
The North River consists of two counties, Tunica and Coahoma. There is just one small casino in Coahoma County, near the southwestern Tunica County line (i.e., in
Lula). As such, references to the North River region are best understood as equivalent to
Tunica County, which currently has ten casinos ( see Table 7.6). In addition, the majority of the county’s population, the casinos, and related developments (e.g., public services, housing, restaurants and hotels, retail, etc.) fall within a thirty-mile radius of the county’s one and only municipality. Therefore, references to county-wide economic activity, demographic make-up, and so forth typically reflect the North River casino region.
However, the economic trade area extends north through DeSoto County (MS) to the
Memphis metropolitan statistical area (Memphis MSA TN-AR-MS).
218 Figure 7.5 Mississippi Delta Casino Counties and Mississippi Casino Regions
Sources: Farrigan 2004 and Williams 2001
Like other metropolitan areas, the Memphis economy is diverse and complex.
The absence of a commercial casino industry is due to the fact that casinos have repeatedly failed to be legalized in Tennessee. Further, the economic relationship of the broader geographic area to the North River casino region is mainly limited to labor supply and casino patronage at a scale that has been found to have little effect on the
MSA (e.g., Redding and Schenk 2000; Walker 1998). Hence, given that, and the micro- rather than macro-focus of casino impacts of this study (i.e., Tunica County and its resident poverty population), the economic area used for analysis of the North River
219 region only extends to the MSA where the aforementioned factors are concerned. 25
However, in the interest of further situating Tunica County casino development within national and state-wide industry growth, where relevant, in the remainder of this chapter I offer comparative statistics and analysis across commercial casino counties in Mississippi and elsewhere as well as among Mississippi’s casino regions.
Table 7.6 Casino Operating History; North River Casino Region, MS, August 2004
Name Location Opened Closed / Relocated Bally's Saloon & Gambling Hall Tunica 12/3/1993 2/9/1995 Bally's Saloon & Gambling Hall (Olympia) Robinsonville 12/18/1995 current operator Fitzgeralds Casino Robinsonville 6/6/1994 current operator Gold Strike Casino Resort* Robinsonville 8/29/1994 current operator Grand Casino-Tunica Robinsonville 6/24/1996 current operator Harrah's-Tunica Robinsonville 11/29/1993 5/19/1997 Harrah's Tunica Mardi Gras Robinsonville 4/8/1996 current operator Hollywood Casino-Tunica Robinsonville 8/8/1994 current operator Horseshoe Casino & Hotel Robinsonville 2/13/1995 current operator Isle of Capri-Lula** Lula 6/27/1994 current operator Isle of Capri-Tunica Robinsonville 7/26/1999 10/8/2002 Lady Luck Tunica Inc Tunica 9/18/1993 4/24/1994 Old River Development Tunica Licensed 03/17/94 never opened President Casino Tunica 12/6/1993 7/8/1994 Sam's Town Hotel & Gambling Hall Robinsonville 5/25/1994 current operator Sheraton Casino Robinsonville 8/1/1994 current operator Southern Belle Casino Robinsonville 2/19/1994 8/31/1994 Splash Casino Tunica 10/19/1992 5/24/1995 Treasure Bay Casino-Tunica Robinsonville 5/9/1994 5/31/1995
*Formerly Circus Circus **Formerly Lady Luck Rhythm & Blues Casino Source: Mississippi Gaming Commission 2004
25 Robison and Miller (1988) warned that regional analysis techniques such as Input/Output models should not be applied to any single community or county or aggregation of counties that are not a functional economic area because economic relationships will not be accurately modeled. That warning is noted, yet in this case it is believed that to include the full functional economic area (i.e., the Memphis MSA) would not be a fair representation of the Tunica County economy and would skew analytical/statistical results in a way that would render them incomprehensible and irrelevant to the study area.
220 One important area of comparison is industry regulation and market structure.
Unlike most commercial casino states, Mississippi has a free-market casino gaming regulatory structure with no limits on the number of casino licenses granted or on credit, wagering, and loss amounts for casino patrons ( see Table 7.7). This regulatory structure, as well as the market structure, of the casino industry in Mississippi is much like
Nevada’s. This is particularly true of the North River region, which is dominated by top shelf casinos. That is, those owned directly or through subsidiaries of major corporations, which command control of the industry on national and global scales. For instance, Caesars Entertainment (formerly Park Place Entertainment) has twenty-eight properties in five countries, spanning four continents. Three of those properties are in
Tunica County −−Bally’s, Grand, and Sheraton.
Table 7.7 Casino Credit, Wager, and Loss Limits by State
State Credit Allowed Wager Limits Loss Limits Colorado no yes no Illinois yes no no Indiana yes no no Iowa no no no Louisiana yes no no Michigan yes no no Mississippi yes no no Missouri no no yes Nevada yes no no New Jersey yes no no South Dakota no yes no Source: Eadington (1999)
221 Of those three, the Grand is of resort magnitude, with three hotels, an RV park, golf course, convention center, and the most gaming footage and number of games of
Tunica’s casino establishments ( see Table 7.8). Yet, all of the casinos in Tunica have a full range of amenities on site. Each contains lodging, dining, parking, and entertainment facilities while many offer a number of additional non-gaming activities, such as pools, spas, and fitness centers, theaters, museums, shopping, arcades, and children’s play centers ( see Table 7.9). Further, like Nevada-style casinos, each has a theme, with architecture conjuring up cowboys in the old West and the luck of the Irish in a grand castle to name a few, so that visitors feel that they are somewhere else other than among the poor of the Mississippi Delta (Kifner 1996).
Table 7.8 Casino Number of Employees, Square Footage, and Number of Games; Mississippi Casino Gaming Regions, 2004
Number Gaming Sq. Other Sq, Number Casinos / Region Employees Footage Footage Games* North River Region 12,305 573,452 3,163,862 16,284 (1) Bally's Saloon & Gambling Hall 719 46,536 149,358 1,355 (2) Fitzgeralds Casino 930 36,000 525,000 1,367 (3) Gold Strike Casino Resort 1,381 50,486 1,347,597 1,480 (4) Grand Casino-Tunica 2,296 117,920 222,080 2,634 (5) Harrah's Tunica Mardi Gras 811 35,000 151,924 1,201 (6) Hollywood Casino-Tunica 925 54,000 337,613 1,654 (7) Horseshoe Casino & Hotel 2,465 63,000 222,500 2,201 (8) Isle of Capri-Lula 804 63,500 85,000 1,543 (9) Sam's Town Hotel & Gambling Hall 1,183 74,210 21,790 1,400 (10) Sheraton Casino 791 32,800 121,000 1,449 Gulf Coast Region (12 casinos) 13,886 681,583 3,633,961 18,141 South River Region (7 casinos) 3,143 178,662 283,481 6,206 State Total 29,334 1,433,697 7,081,304 40,631
*Includes number of slot machines, table games, and poker tables Source: Mississippi Gaming Commission (2004)
222 Table 7.9 Amenities/Activities in Addition to Gaming; Tunica Co.Casinos, MS, 2004
RV Entertain- Other Tunica County Casinos Hotel Dining Golf Arcade Park ment* ** Bally's Saloon & Gambling Hall x x x Fitzgeralds Casino x x x Gold Strike Casino Resort x x x x x Grand Casino-Tunica x x x x x x x Harrah's Tunica Mardi Gras x x x x Hollywood Casino-Tunica x x x x x Horseshoe Casino & Hotel x x x x Sam's Town Hotel & Gambling Hall x x x x Sheraton Casino x x x
*Includes live entertainment, theater and/or ballroom on site **Other here includes only clay shooting, tournaments, museums, Kid’s Quest, Western Emporium, convention/meeting space, which does not represent the full extent of casino or casino hotel amenities. Source: Mississippi Gaming Commission (2004)
These factors, together with the establishment of an intense marketing and growth scheme (Field Notes A/B 2002), have helped the region establish itself as a resort destination. This is evidenced by the highest number of admissions among the post-1988 casino counties ( see Table 7.10), the majority of visitors coming from outside the state
(see Table 7.11), and a top ten ranking for gross gaming revenue among all commercial casino markets ( see Table 7.12). Further, both Gulf Coast and North River casino clientele are characterized by: females, those without children (below age 18), a median age of 49 years, those employed full-time or retired, first-time visitors to the area or returning casino visitors, a higher education level than in most other casino markets, and with a median income between $30,000 and $39,999 (von Herrman 2000). This means that the industry is primarily supported by dollars from outside the local area. This also suggests that displacement is due to import substitution, not to local demand for pre- existing entertainment and leisure activities.
223 Table 7.10 Top Five Region/County by Admissions; Adjusted Gross Revenue and AGR per Visitor; Post-1988 Casino Counties,2001
Region / County Admissions AGR** AGR / Visitor Mississippi River Region, MS* 32,188,332 $1,549.6 $48 Gulf Coast Region, MS 24,134,276 $1,151.1 $48 Lake, Indiana 17,607,238 $732.6 $42 St. Louis, Missouri 14,935,909 $345.4 $23 Jackson, Missouri 12,823,057 $284.0 $22 *Includes both North and South River casinos **Millions of dollars Source: State Gaming Boards (2001)
Table 7.11 State Residence of Casino Visitors by Mississippi Casino Region, 2000
Residence North River South River Gulf Coast Alabama 11% 2% 14% Arkansas 5% 2% 14% Florida <2% <1% 14% Georgia 2% 1% 4% Illinois 2% 1% <1% Louisiana <1% 11% 15% Missouri 5% 0% <1% Mississippi 22% 77% 39% Tennessee 32% 0% <1% All Others 15% 3% 9% Source: von Herrman et al. (2000)
Table 7.12 Top Ten Casino Markets Ranked by Gross Gaming Revenue, 2002
Rank Casino Market GGR 1 Las Vegas (Strip) $4.7 billion 2 Atlantic City, NJ $4.4 billion 3 Chicagoland (IL, IN) $2.3 billion 4 Connecticut (Indian) $2.0 billion 5 Detroit $1.1 billion 6 Tunica, MS $1.1 billion 7 Reno/Sparks, NV $916.8 million 8 Biloxi, MS $878.8 million 9 Southeast Indiana $841.7 million 10 Shreveport, LA $823.5 million Source: American Gaming Association (2004)
224 All in all, these elements lend support to claims that Tunica County has been one of the fastest growing tourist destination economies in the nation. Marked changes in the local economy, such as the employment growth shown in Figure 7.6, are the result.
Given the economic history of Tunica County prior to the casinos, it would be illogical to think that employment growth was due to anything other than casino industry growth.
However, it is useful to systematically sort out that which is attributable to national, local, and industrial components of change, and to do so in comparison to other counties. Table
7.13 presents the top ten results of a shift-share analysis used to decompose employment growth for the life of the casino industry in each of the 57 counties. 26 In this table, the national growth effect represents the amount of employment growth that can be attributed to nationwide employment growth. The industry mix effect is the amount of change that would be achieved by growth in the local industry at the rate of national growth less the national growth effect. The competitive effect is actual growth less that expected based on the industry mix effect. The total is the sum (growth and losses) for all three types of effects.
Those figures suggest that Tunica County was the second highest among casino counties in gains from casino development with more than 100% of per year net growth
(217.9% competitive effect / 217.7% total) attributable to the casinos. Hancock and
Harrison Counties, which are in the Gulf Coast casino region, fall into the list at numbers five and ten with competitive effects of 12 percent and 7 percent, respectively. Looking at the differences from the top of the list to the bottom, it is clear that casino development and operation in Tunica County has generated a significant amount of employment in comparison to that of other casino counties. This employment is attributable to growth in
26 The start date used for Nevada and New Jersey casino counties was 1978.
225 the national economy. Likewise, taking all 57 counties together, employment growth in casino counties has been found to be largely due to expansion in the national economy, reflecting 97.8 percent of the jobs generated by the casinos. Thus, Tunica is truly an anomaly in this regard from a national industry perspective.
Figure 7.6 Total Full- and Part-Time Employment; Tunica County, MS, 1990-2000
25,000
20,000
15,000
10,000
5,000
0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Year
Source: REIS (2003)
Table 7.13 Yearly Employment Growth Rate and Impact of Casinos; Top Ten Growth Counties out of Total Casino Counties in the U.S.
National Growth Industry Mix Competitive State County Total Effect Effect Effect CO Gilpin 1.4% -0.6% 344.1% 344.9% MS Tunica 2.8% -3.1% 217.9% 217.6% IN Ohio 2.6% 2.6% 84.6% 89.8% CO Teller 1.1% -1.2% 29.8% 29.7% MS Hancock 2.5% -0.3% 12.0% 14.2% NV Pershing 1.1% -2.1% 11.8% 10.8% LA Bossier 2.8% -0.8% 8.5% 10.5% IN Dearborn 2.6% -1.8% 8.1% 8.9% IL Massac 2.8% -2.4% 7.7% 8.1% MS Harrison 2.5% -0.2% 7.0% 9.3%
Source: Shift Share Analysis, Adopted from Center (2004), pp. 25-26.
226 7.3 CHAPTER SUMMARY
In order to situate the impact analysis of casino gaming in Tunica County in relation to that of the nation and the state of Mississippi, I began with a macro profile of casino industry growth in the United States. This included summary statistics of that growth at the state and county levels along with some general impact indicators (e.g., employment and tax revenue). Then I turned to a brief discussion of the determinants of industry growth in Mississippi. In the next chapter I present a more detailed analysis of that growth and its impacts in Tunica County. In completing that task, I focus on the direct economic effects associated with employment and tax revenue growth and the manner in which that growth ripples through the economy and is filtered through various transmission channels to impact upon the poor.
7.4 CHAPTER REFERENCES
American Gaming Association (AGA). 2004. 2004 State of the States: The AGA Survey of Casino Entertainment. American Gaming Association. Available online at
American Gaming Association (AGA). 2003. 2003 State of the States: The AGA Survey of Casino Entertainment. American Gaming Association. Available online at
Gagliani, G. 1987. Income Inequality and Economic Development. Annual Review of Sociology. 13: 313-334.
Goss, E. 2002 December 4. The Economic Impact of An Omaha, Nebraska Casino. Omaha: Goss & Associates—Economic Solutions.
Harrah’s Casinos. 1997. Harrah’s Survey of U.S. Casino Entertainment. Memphis, TN.
Kifner, J. 1996 October 4.. An Oasis of Casinos Lifts a Poor Mississippi County. High Rolling on the River, A Special Report. New York Times. A1-2.
227 Redding, S. and S. Schenk. 2000 October. The Migration of People and Their Incomes in the Memphis MSA: 1992 to 1997. Memphis: Regional Economic Development Center, The University of Memphis.
Robison, M. and J. Miller. 1988. Cross-hauling and Nonsurvey Input-Output Models: Some Lessons from Small-area Timber Economies. Environment and Planning A. 20: 1523-1530.
Vervilos, A. 1998. Public Policy and the New Casino Gaming Markets. Published thesis. University of Nevada, Reno. von Herrman, D., R. Ingram, and W. Smith. 2000 June. Gaming in the Mississippi Economy: A Marketing, Tourism, and Economic Perspective. The University of Southern Mississippi .
Wagner, J., et al. 1992. Estimating Economic Impacts Using Industry and Household Expenditures. Journal of the Community Development Society. 23(2): 79-102.
Walker, D. 1998. Sin and Growth: The Effects of Legalized Gambling on State Economic Development. Published Dissertation. Auburn University.
228 CHAPTER 8
IMPACTS OF GROWTH IN TUNICA
Economic growth without social progress lets the great majority of people remain in poverty, while a privileged few reap the benefits of rising abundance. ~John F. Kennedy
The previous chapter provided an overview of the growth and characteristics of growth of casino development across the U.S., in Mississippi, and among casino counties and Mississippi casino regions. That overview provides an initial look at the impacts.
When economic development produces change as growth, growth as measured should not be understood as a one-to-one corollary of the impacts of economic change. Impacts represent the effects of the interaction between growth (or decline or whatever the change may be) and the study community on specific elements of that community, such as differential effects across socioeconomic groups, industry sectors, and locations (e.g., neighborhoods) (Shaffer 1989). Therefore, impact analysis must not just consider what types of change take place initially or as a direct result of the economic development, but must also include an assessment of relational changes, whether economic, physical, demographic, fiscal, social, cultural, or political. Since the most obvious and deliberate changes related to the establishment of a casino industry in Tunica County are economic and fiscal (i.e., employment and tax revenue) at the county level, that is the most logical place to start the impact analysis.
229 8.1 ECONOMIC IIMPACTS
Economic impacts can be defined in a number of ways. The way most congruent with the objective of this study is to define economic impacts as the effective changes in casino industry growth on the level and distribution of employment and income with respect to the county’s poverty population. However, before getting to that level of detail, economic impacts should be defined in a more generalizable manner. The standard practice is to do so in terms of the output, employment, and labor or personal income generated by the development and to decompose total impacts into direct, indirect, and induced categories. For this study, the following definitions apply:
Output is the value of goods and services produced by the casino industry and other industry sectors of the Tunica County economy; Employment is the number of people employed, including wage and salary employees and self-employed persons; Personal income is the wages, benefits, and other income (including profit-related income like dividends) derived from employment; Direct impacts are the on-site economic activities carried out that are an immediate consequence of casino operations and that would not have occurred in the absence of the industry’s development; Indirect impacts are multiplier effects derived primarily from off-site economic activities that are attributable to the development, and that which occurs mainly as a result of non-payroll expenditures related to casino operations (e.g., supplies and support services) that take place within the study area; and Induced impacts are the multiplier effects of the direct and indirect impacts that are attributable to the economic activity created by successive rounds of spending by employees and proprietors.
One of the most popular approaches for assessing economic impacts following a particular event or policy change and for doing so with respect to the aforementioned impact categories is input-output modeling (I-O). I-O is traditionally used to derive economic multipliers as well as to provide descriptive accounts of the structure of an economy of interest. It has been used in this way in the assessment of casino gaming impacts (Rose and Associates 1998; Rose and Miernyk 1989; Wagner et al. 1992).
230 Similarly, an input-output model was developed for Tunica County for the years 1990 and 1999 using IMPLAN data and software (MIG 1999).
According to the model, nearly $1294 million in goods and services were produced in Tunica County in 1999, with local industry supporting more than 19,778 jobs generating $477 million in employee compensation. In comparison, in 1990 the respective values were $126 million in output, 2,539 jobs, and $28 million for employee compensation. That represents a difference of $769 million in total value added in current dollars or a 197 percent increase between 1990 and 1999 given real dollars
(2005). That difference is almost entirely due to growth in the service industry, which replaced agriculture as the county’s key industry, with more than 80 percent of industry output and employment in 1999 compared to approximately 7 and 13 percent in 1990, respectively. This change is illustrated in Figures 8.1 and 8.2, where values greater than one demonstrate the importance of the industry to the economic viability of the county from an employment perspective (i.e., utilizing employment location quotients). Census
Bureau reports show a similar trend for the state, where impressive gains in service sector employment and income took place for the period since casino industry development started.
231
Figure 8.1 Employment Location Quotients; Farming and Agriculture, Fishing, and Forestry (AFF) Service Sectors; Tunica County, MS, 1990-1999
12.00 10.00
8.00
6.00 LQ 4.00
2.00
0.00 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Year
Farming AFF Service
Source: Location Quotient Analysis, 1990-1999 REIS data
Figure 8.2 Employment Location Quotients; Service and All Other Industry Sectors;* Tunica County, MS, 1990-1999
3.00
2.50
2.00
1.50 LQ
1.00
0.50
0.00 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Year
All Other Industries* Service
*Excludes Farming and Agriculture, Fishing, and Farming Services Source: Location Quotient Analysis, 1990-1999 REIS data
232 Growth rates for aggregate industry base data for Tunica, which provide a snapshot of the local economy for the comparison years, are displayed in Table 8.1.
Those figures demonstrate the tremendous growth in the service industry across output, employment, and income streams, which can easily be attributed to the operation of casino industry establishments. For instance, Table 8.2 shows similar data for casino sectors, all of which fall under the larger service sector category given in Table 8.1.
Table 8.3 provides those values relative to one another (i.e., the casino industry as a percentage share of the service sector). Given that those estimates are around 98 percent, it is clear that the service sector in Tunica County is almost wholly comprised of economic activity related to the casino industry.
Table 8.1 Growth Rates in Aggregate Industry Base Data; Tunica County IMPLAN Model, 1990-1999
Other Indirect Total Industry Base Industry Employ- Employee Proprietor Property Business Value Year 1999 Output* ment Compensation* Income* Income* Tax* Added*
Agriculture -11% 12% -50% -18% 138% 553% -2% Mining -100% 0% -100% -100% -100% -100% -100% Construction 510% 344% 809% 681% 708% 418% 759% Manufacturing 98% 62% 66% -228% 39% 324% 58% TCPU -36% -28% -13% -71% -8% -27% -18% Trade 53% 46% 24% -1% 410% 5% 39% FIRE 46% 91% -1% 32% 40% -18% 23% Services 9319% 4959% 11049% 811% 114740% 59627% 10640% Government 636% 632% 728% 0% -7599% 0% 862% Other -192% -54% -3% 0% -60241% 0% -192% Totals 700% 679% 1227% 132% 1166% 1026% 965% *Based on millions of real dollars; adjusted for inflation using 2005 CPI conversion factors Source : IMPLAN, 1990 and 1999 data from Minnesota IMPLAN Group, Inc.
233 Table 8.2 Growth Rate in Casino Sector Base Data; Tunica County IMPLAN Model, 1990-1999
Industry Output* Employment Total Value Added* Casino Sector 1990 1999 GR** 1990 1999 GR 1990 1999 GR** Hotels & Lodging $0 $820,369 413857865% 6 10,994 183133% $133 $556,800 418119% Places Amusement & Recreation $0 $367,438 36744% 0 4,748 474800% $1 $257,309 25731% Services, N.E.C.
Membership Sports & $129 $2,190 1602% 8 39 388% $52 $1,398 2601% Recreation Clubs
Total $129 $1,189,998 923120% 14 15,781 112621% $186 $815,508 438554% *Thousands of dollars **Values adjusted for inflation using 2005 CPI conversion factors Source : IMPLAN, 1990 and 1999 IMPLAN data from Minnesota IMPLAN Group, Inc.
Table 8.3 Casino Sector Percentage of Total Service Industry; Tunica County IMPLAN Model; Base Data, 1999
Value Casino Sector Output Employment Added Hotels and Lodging Places 67.8% 68.1% 67.3% Amusement and Recreation Services, N.E.C. 30.4% 29.4% 31.1% Membership Sports and Recreation Clubs 0.2% 0.2% 0.2% Total 98.4% 97.8% 98.6% Source : IMPLAN, 1999 data from Minnesota IMPLAN Group, Inc
The estimated direct, indirect, and induced effects from all Tunica County industries are presented in the form of employment and income multipliers in Table 8.4.
A multiplier represents the system of transactions that follow a disturbance (positive or negative) in an economy, such as a tourist dollar spent at a casino. Therefore, for example, the total income multiplier for services represents the income impacts that result from the production of every dollar of casino industry revenue injected into the economy.
These values are rather low in comparison to multipliers for most other industries and for that reflective of the casino industry in Mississippi and the United States on the whole.
234 von Herrman et al. (2000: 14) cited sources that offer state and national multipliers for gaming employment and hotels and amusement that are 1.45 and 1.88, respectively. Clearly there is tremendous variability in the multiplier estimates depending on how the industry is defined, what type of multiplier is computed, and differences in computational methods used. However, it is to be expected that the multipliers for Tunica would be low given that the main factors affecting the multipliers are intra-regional linkages (interdependence). Thus, a more expansive and sophisticated economy (e.g., diversified) would have larger multipliers. In the case of Tunica, even with the growth in the gaming industry, the county economy remains limited as is illustrated in the following discussion.
Table 8.4 Employment and Income Multipliers; Aggregate Industries; Tunica County IMPLAN Model, 1999
Employment Income Industry Direct Indirect Induced Direct Indirect Induced Total Total Effects Effects Effects Effects Effects Effects AG 0.0295 3.9020 0.3262 4.2577 0.2609 0.0819 0.0585 0.4013 Mining 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 Const 0.5773 5.5756 0.7513 6.9041 0.3545 0.1279 0.0441 0.5265 MFG 0.7391 5.7095 0.1650 4.6137 0.1727 0.1312 0.0300 0.3340 TCPU 0.6156 2.7344 0.9817 2.3318 0.2497 0.0723 0.0518 0.3738 Trade 0.4047 2.7846 0.5764 0.7657 0.4334 0.0703 0.0670 0.5707 FIRE 0.6976 2.5335 0.1419 1.3730 0.0900 0.0693 0.0567 0.2161 Services 0.4995 3.2485 0.1913 0.9392 0.4198 0.0839 0.0567 0.5604 Gov't 0.5551 0.7747 0.9791 2.3088 0.8041 0.0222 0.0497 0.8761 Other 0.3497 0.0000 0.0066 5.3431 -1.0500 0.0000 0.0575 -0.9925
Source : IMPLAN, 1999 data from Minnesota IMPLAN Group, Inc
That lack of multiplicative effect in terms of output is demonstrated in Figure 8.3, a ripple effect model, which provides an illustration of the manner in which baseline service industry output for 1999 would ripple through the Tunica County economy, like a
235 drop of water in a still pond. 27 The model asks, what are the outputs required of each producer or service provider in the county to produce what is purchased in each round of economic activity stemming from the initial activity?28 In this case, the starting point is
$1041.13 million in casino industry (i.e., services) output in round zero, which after nine rounds results in an additional $243.76 million, which represents a multiplier of 1.234.
Despite that increase, it is clear that the local economy is rather leaky , as suggested by how quickly circulation falls off after round one.
That leakage, as represented by this example, does not denote how much casino revenue escapes during each round of spending, but rather how little of the initial dollars spent to produce casino-related goods and services translates into indirect rounds of spending and the dispersal of that spending across other industries through additional output demands. Evidence of other forms of leakage exists in Table 8.4 where multiplier values are negative. Negative values can mean a number of things. For instance, where output represents net income from foreign sources a negative multiplier value would reflect net outflow or where inventory valuation is concerned it would represent a net loss in value of inventory from one year to the next (Olson 2005). In the case of Tunica we can speculate that negative income multipliers reflect the effects of an economy that is highly dependent on a non-resident labor force. That issue is discussed in detail in the next section of this chapter, which deals directly with employment.
27 This is done by building a direct impact vector from the IMPLAN model regional absorption table and setting the iterative process in motion through an Excel spreadsheet. 28 This assumes that Tunica County’s production function is the same as the industry average. No adjustments are made to regional purchase coefficients (RPC),
236 Figure 8.3 Ripple Effect of Service Industry Output; Tunica County, 1999
Source : Derived from IMPLAN service industry output base data for 1999
The leakage situation reflected in Figure 8.3 can be explained in part by two specific factors in the context of the Tunica County economy and the casino industry.
The first has to do with what the casino industry demands in support of its operations.
For instance, Mississippi Gaming Commission reports show that a significant portion of casino expenditures goes toward the purchase of equipment and that licensed manufacturers and distributors of that equipment are limited in Mississippi. That relates to the second factor, which is the availability of goods and services directly and indirectly
237 demanded by the industry given the scale and diversity, or lack there of, of the Tunica
County economy on the whole. Those limitations can be understood in part by considering the sectoral make-up of the economy.
IMPLAN allows for up to 528 industry sectors for base data at the most disaggregated level of a county’s economy. The Tunica County economy was comprised of just sixty-eight of those sectors in 1990 and eighty in 1999. The difference between the structures of the economy for the model years reflects both sector gains (22) and losses (10). Losses were mostly suffered by non-profit organizations (e.g., labor, civic, and non-profit) and manufacturing (e.g., wood pallets and skids), while sector gains as shown in Table 8.5 reflects the growth of the gaming industry and related support and infrastructure development sectors. Still, those interviewed through the regional business organization reported that while some local businesses have relationships with the casinos, most of the casinos’ needs cannot be met locally due to a limited quantity or absence of suppliers of the products/services demanded (Field Notes B 2002).
Of the sixty-eight sectors present in 1990 and remaining in 1999 (58), excluding casino industry categories (2), thirty-six showed growth in output. Those sectors are listed in Table 8.6 and reflect the growth in the catfish industry noted in chapter 4. They also reveal growth in sectors complementary to the casino industry, and more extensively, infrastructure development. The characteristics of the latter, including the beneficiaries, are discussed in more detail later in this chapter along with tax revenues.
238 Table 8.5 Economic Diversification by Industry Sectors Gained, 1990-1999; Number Employed and Output by Sector, 1999; Tunica County, MS
1999 Industry Sector* # Employed Output** Amusement and Recreation Services, N.E.C. 4,748 316.364 Detective and Protective Services 46 0.803 Nursing and Protective Care 22 0.602 Social Services, N.E.C. 21 1.267 Local, Interurban Passenger Transit 19 0.964 Fabricated Structural Metal 14 2.733 Theatrical Producers, Bands Etc. 12 0.893 Equipment Rental and Leasing 11 1.531 Management and Consulting Services 10 0.606 Photofinishing, Commercial Photography 9 0.768 Water Supply and Sewerage Systems 8 0.85 Newspapers 8 0.64 Business Associations 7 0.521 Computer and Data Processing Services 6 0.322 Advertising 6 0.314 Services To Buildings 6 0.253 Signs and Advertising Displays 3 0.292 *Excludes government and agricultural sectors (5) **Millions of Dollars Source : IMPLAN, 1990 and 1999 data from Minnesota IMPLAN Group, Inc
In terms of who has lost and who has benefited from a business perspective, a concrete measure is difficult to ascertain. For instance, identifying which and how many of those sectors experiencing growth/loss are localized as locally owned businesses and/or pre-casino establishments, and which changes are due to casino development, is difficult to accomplish explicitly. That is, other studies that have attempted this have done so on a larger geographic scale (e.g., metro area or statewide) using data pertaining to ownership, numbers of establishments, and levels of economic activity, employment, and payroll (e.g., Hashimoto and Fenich 2004; Wallace 1998). The data that would make similar analysis possible at the scale of Tunica’s economy either do not exist publicly or are subject to disclosure issues or cannot be pooled together (e.g., County Business
239 Patterns and county tax rolls). However, I was able to get a sense for this by conducting a current business inventory, comparing it to the data that do exist, and talking with people about the business-related changes that have taken place.
Table 8.6 Industry Growth Sectors by Differential Growth Rate in Output; Tunica County, MS, 1990-1999
Output Output Idustry Sector* Idustry Sector* DGR DGR Prepared Fresh/Frozen Fish/Seafood 2282% Food Grains 161% New Government Facilities 2107% Agricultural, Forestry, Fishery Services 160% New Highways and Streets 1370% Funeral Service and Crematories 153% Maintenance and Repair, Residential 1318% Ranch Fed Cattle 151% Child Day Care Services 1020% Federal Government - Military 131% Maintenance and Repair Other Facilities 752% Automotive Dealers & Service Stations 120% New Mineral Extraction Facilities 733% Feed Grains 109% New Residential Structures 593% Personnel Supply Services 107% New Industrial & Commercial Buildings 510% Housefurnishings, N.E.C 96% Eating & Drinking 449% Food Stores 76% Credit Agencies 416% Owner-occupied Dwellings 47% Apparel & Accessory Stores 352% Wholesale Trade 40% Real Estate 325% Legal Services 38% Beauty and Barber Shops 297% Miscellaneous Retail 36% Banking 201% Cotton 35% Communications, Except Radio and TV 181% Domestic Services 31% New Utility Structures 174% Accounting, Auditing and Bookkeeping 12% Laundry, Cleaning and Shoe Repair 164% Furniture & Home Furnishings Stores 8%
Source : IMPLAN, 1990 and 1999 data from Minnesota IMPLAN Group, Inc
My findings are, first and foremost, that it is impossible to grow or cannibalize something that does not exist in the first place. As noted previously, beyond agriculture, economic activity in Tunica prior to the casinos was nearly at ground zero. The number of private non-farm business establishments for the entire county was 127 in 1990. In
1995 that number was 146 and in 1998 it was 175, which represents a 37.8 percent change from 1990 to 1998. The limited number of private service-oriented and retail
240 sales businesses that did exist within the vicinity of the casinos in 1990 were characterized by few employees, low levels of output, and local ownership, and were mainly located in/nearby the town of Tunica, serving its residents, enclaves, and passers- by. Despite reports in the popular media to the contrary, this characterization still holds.
For the most part, longstanding businesses are still standing and serving the same clientele in the same capacity. That is, few new businesses have developed that serve basic resident needs despite the promise that such development would occur. For instance, plans for a new grocery store near the town never materialized. Alternatively, a string of service stations has been built nearer the casinos, along with liquor stores, pawn shops, tobacco outlets and other businesses meant to serve gaming industry patrons.
It is true that some businesses have come and gone, as supported by a -3.5 percent change in private non-farm establishments for 2000-2001 alone. Yet, according to that reported to me by those within the business community (Field Notes B 2002; D 2003), their failure has largely been of their own accord. Factors include poor location and product choices or poor business management, such as overextension in anticipation of a larger capture of the casino-tourist market than was realistic. Many naively expected or hoped for a mass new tourist base from which to glean profits (Field Notes 2002 B).
While local businesses have seen increased activity alongside an increase in tourist traffic, despite aggressive marketing, only a small percentage of casino visitors make it the ten miles down Highway 61 to the town of Tunica. Further, business development resulted in increased competition for discretionary income, but really only with respect to restaurants. There was little local opportunity for entertainment or retail expenditures
241 (e.g., clothing stores) prior to the casinos. That competition, however, is not exactly tied to the casinos as is typically understood.
The food service industry has diversified not only through the opening of casino restaurants, but also by the development of fast food chain stores along Highway 61 in
Robinsonville and the town of Tunica. 29 Those in the town directly compete with local businesses for residential patrons as well as for tourists, and some restaurants (there are only a handful) have reported losses due to this competition. The casino restaurants serve both client bases, but their draw from the resident population as a substitute for patronage in local food establishments is for the most part a fallacy, at least in terms of revenue generation. One local restaurant owner verbalized that the casinos were stealing his customers by giving away meal vouchers (Field Notes D 2002), which is a typical promotional tactic of casinos in order to draw people in to gamble. However, those interviewed among the resident population said that they rarely went out to eat prior to the casinos because they could not afford to do so and that they only go out to eat now because they can eat for free at the casino restaurants and possibly even have free drinks and live entertainment in the process. So in essence, the casino restaurants are not stealing customers, but rather, are offering a different commodity (in the form of free food) for a clientele that does not, nor did ever, really exist for local restaurant operators.
The point to be made is that the magnitude and character of the economic changes taking place in Tunica County, as demonstrated here, are likely more complex than is discernable from the I-O model itself. The economic context is a spatial context, which is for the most part “ignored in the mechanistic application” of the model. Therefore, it is
242 understood that as with any form of regional analysis, “technique should never be a substitute for thought” (Robison and Miller 1988: 1529). That thought needs to include the fact that economic changes can affect people and businesses in a community very differently (Shaffer 1989), and potentially do so not only objectively, but also subjectively in terms of their perceptions and resultant behaviors. This should be kept in mind while proceeding through the remainder of the impact study as presented in this and the next chapter.
8.2 EMPLOYMENT
The absolute change in employment from pre- to post-casino development has been noted. However, there are a number of ways to look at changes in employment and, therefore, employment impacts (i.e., total effects). One perspective is job quality in terms of what jobs are available, how much they pay, and who gets them. However, noting what types of jobs in a meaningful way is difficult given that a multitude of jobs exist in the casino industry. The U.S. Department of Labor, Bureau of Labor Statistics, lists 136 occupations for gambling industries for 2003. This does not include those within casino hotels. Still, by placing those occupations into major occupational categories we can gain some understanding of differences in job quality from the perspective of how much they pay and who gets them in the aggregate.
The occupational breakdown used here is shown in Table 8.7, which classifies casino jobs into nine occupational categories and offers employment comparisons in those occupations based on the national workforce, the total workforce of the 11
29 While a comprehensive business location map is not available for the entire study region along Highway 61, a number of maps are provided in Appendix A that give a sense for the density and location of businesses in relation to the casinos and the Town of Tunica.
243 commercial casino states, the broader gaming industry workforce, and from those working in the casinos. 30
Table 8.7 Casino Employment by Occupation Comparisons; Casino Workforce, Gaming Industry Workforce, 11-State Casino Workforce, and National Workforce, 2003
Occupation Casinos Gaming Industry* 11-State National Officials and Managers 9.1% 9.8% 10.9% 10.8% Professionals 2.9% 2.8% 15.9% 16.5% Technicians 2.4% 1.7% 5.8% 6.1% Sales Workers 4.4% 4.7% 11.8% 12.1% Office and Clerical 9.6% 10.4% 13.3% 14.3% Craft Workers (Skilled) 8.3% 5.4% 7.9% 7.8% Operatives (Semi-skilled) 4.3% 3.6% 14.1% 13.0% Laborers (Unskilled) 2.7% 3.7% 8.0% 7.7% Service Workers 56.4% 57.9% 12.3% 11.7% Totals 100% 100% 100% 100%
*Gaming industry workforce defined here by SIC-701/709 employment Sources: Adopted from PricewaterhouseCoopers (2003), p. 7-9.
One way to judge the value of that employment is by comparing wage and salary levels to those in other industries. Historically, casino workers have been paid less than those in other industries, but have been paid slightly higher than those within other sectors of the arts, recreation, and entertainment industry, of which casinos are a part.
For instance, according to U.S. County Business Patterns statistics for 2000, those working in casinos had an average salary of $22,691. In comparison, those within the arts, recreation, and entertainment industry on the whole earned and average $21,018 while across all industries the average was significantly higher, at $33,524. The latter suggests that casino workers in the United States in 2000 earned on average $11,000 less
30 Employment by occupation figures for those among the casino workforce is based on a sample from participants in a survey conducted by PricewaterhouseCoopers (2003). This sample is not representative of the entire casino workforce population.
244 for the year than did those working across all industries. The scenario was slightly worse for those working in Mississippi casinos, where the average annual salary for workers in
Mississippi’s 29 commercial casinos was $20,500 in 2000 (von Herrman et al. 2000), a rate $13,000 less than those working in all industries across the nation.
These facts are not surprising, however, given that the majority of those that work in casino jobs and related occupations do so in the area of services, which despite variability in wages depending on the type of job and geography is the lowest paying of occupational categories for gambling industries. There are not only locational and occupational wage differences, however, but racial differences as well. For instance, a comparison of Tables 8.8 and 8.9 reveals that the lowest paying jobs go disproportionately to the black population.
Table 8.8 Casino Employment by Occupation Comparisons; Casino Workforce, Gaming Industry Workforce, 11-State Casino Workforce, and National Workforce; White Workforce Population Only, 2003
Occupation Casinos Gaming Industry* 11-State National Officials and Managers 12.8% 14.1% 12.9% 13.1% Professionals 3.4% 4.0% 17.8% 18.8% Technicians 3.2% 2.3% 6.2% 6.5% Sales Workers 4.5% 5.8% 12.5% 12.6% Office and Clerical 10.9% 11.6% 13.3% 14.0% Craft Workers (Skilled) 10.1% 6.5% 8.6% 8.5% Operatives (Semi-skilled) 4.4% 3.4% 13.3% 11.9% Laborers (Unskilled) 1.9% 3.1% 6.2% 5.7% Service Workers 48.9% 49.0% 9.3% 8.9% Totals 100% 100% 100% 100%
*Gaming industry workforce defined here by SIC-701/709 employment Sources: Adopted from PricewaterhouseCoopers (2003), pp. 7-9.
245 Table 8.9 Casino Employment by Occupation Comparisons; Casino Workforce, Gaming Industry Workforce, 11-State Casino Workforce, and National Workforce; Black Workforce Population Only, 2003
Occupation Casinos Gaming Industry* 11-State National Officials and Managers 6.2% 5.7% 5.1% 5.0% Professionals 2.3% 1.5% 7.7% 8.2% Technicians 2.5% 1.6% 4.9% 5.2% Sales Workers 5.0% 3.5% 11.3% 11.6% Office and Clerical 11.1% 11.9% 16.2% 17.7% Craft Workers (Skilled) 5.9% 3.7% 5.6% 5.4% Operatives (Semi-skilled) 6.1% 4.0% 17.3% 16.2% Laborers (Unskilled) 4.2% 3.8% 10.9% 10.5% Service Workers 56.7% 64.3% 21.0% 20.2% Totals 100% 100% 100% 100%
*Gaming industry workforce defined here by SIC-701/709 employment Sources: Adopted from PricewaterhouseCoopers (2003), pp. 7-9.
An indication of similar distributional patterns in Tunica County resonates in the perspective of one longtime resident with respect to employment outcomes of casino development and the conditioning factors for those outcomes (Field Notes A 2003):
There’s the uneducated poor people, mostly black, whose education level is so bad that they can’t get casino jobs, except maybe in housekeeping or the like. And their parents and those before them are even worse given the education related to the cotton farming—most dropped out of school to work and the landowners encouraged them to do so. When the casinos came in few among the 5500 or so of working age population were qualified to work in the casinos… around 15,000 are currently employed there and Tunica residents hold few of those jobs and of those jobs they are the lowest paying.
The truth of that sentiment is difficult to ascertain given the lack of availability of public data from which to establish appropriate indicators. That is, the Mississippi
Gaming Commission (MGC) does not maintain sub-population (e.g., race, gender, and class) data for casino jobs by occupation, salary, and skill level. In fact, even though
MGC is the regulatory law enforcement body, the Commission does not collect data on
246 equal opportunity in casinos nor is there a requirement that such information be tracked by the state gambling commission. However, at the state and federal levels, the
Mississippi Department of Employment Security, the US Census Bureau, and the Equal
Employment Opportunity Commission (EEOC) collect data that are helpful in establishing occupation, race, and income class indicators in the aggregate.
8.2.1 SELECT LABOR FORCE STATISTICS
The Tunica County labor force grew by more than 67% from 1990 to 2000, coupled with an equally significant drop in the unemployment rate, to bring Tunica
County on par with the state by 2001 with a rate of 5.5 percent ( see Figures 8.4 and
8.5)—a difference of 20.7 percent from 1992. The black population made up 63 percent of that labor force, but while the county-level unemployment rate had reached a low of
6.8 by 2000, the unemployment rate for blacks was nearly double that amount at 12.2 percent. This reflects, in part, the fact that 2.8 percent of blacks in the labor force who were unemployed in 2000 had been steadily without work since 1995, which was at end of the casino construction period in Tunica. Those who were working were concentrated in low-level jobs, with 43 percent working as laborers/helpers or service workers. That group represented 70.4 percent of all those employed in the county and 71.4 percent of the resident labor force. (Comparatively, blacks made up 70.2% of the county population in 2000.)
247 Figure 8.4 Cumulative Percent Change in Labor Force; Tunica County and State of Mississippi, 1990-2001
100% 80% 60% 40%
%Change 20% 0%
1 2 3 4 5 6 7 8 9 0 1 -9 -9 -9 -9 -9 -9 -9 -9 -9 -0 -0 90 91 92 93 94 95 96 97 98 99 00 19 19 19 19 19 19 19 19 19 19 20 Year
Tunica Co. MS
Source: BLS (2003)
Figure 8.5 Unemployment Rate; Not Seasonally Adjusted; Tunica County (MS) and State of Mississippi, 1990-2001
20.0
15.0
10.0
5.0 Unemployment Rate 0.0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 Year
Tunica County State of Mississippi
Source: BLS (2003)
248
Thus, given the availability of jobs, it is likely that the employed black population in Tunica in 2000 was representative of those working in entry-level positions in the casinos. This assumption is supported by community survey respondents, who when asked about the occupations of community residents who worked in casinos, they indicated that the majority worked in housekeeping (38.8%) and food services, as a cook or a waiter (22.1%). In comparison, managerial and professional positions were reportedly held predominantly by the white labor force population of Tunica County
(Field Notes B 2003). According to BLS, the industry-wide mean hourly and annual wage levels for those occupations are: $10.06/$20,920 for housekeeping, $9.90/$21,450 for food preparation and serving, and $34.21/$71,170 for hotel management and
$31.67/$65,870 for casino management.
Those figures are typically even lower for housekeeping and food services in
Tunica because they are generally hourly rather than salary-based and depend on highly volatile visitor levels, whereas management positions do not. For instance, visitor levels for casino hotels not only vary seasonally, but also by event. That is, the number of other events going on in the county (e.g., at the agricultural arena, which was funded by casino tax revenue) or at the casinos would increase visits. As such, in order to avoid the cost of temporary lay-offs or of maintaining a full housekeeping staff, many casino hotels put their housekeeping staff on a room-by-room wage rate, which in most cases is $5 per room. The result is that although there may be increased income potential during high visitation periods, housekeeping and other hourly support staff have a low level of income stability.
249 The impact of this psychologically is evident in survey responses. The majority of those who reported working in the casino service industry also reported thinking about their future finances constantly or often and feeling like they were no better off financially now than they had been in the past. One might find such sentiment unreasonable when looking at changes in aggregate income measures, such as growth in per-capita income. However, the discrepancy of who is benefiting most from casino jobs and who is not becomes clear when considering that same measure from the standpoint of race, as shown in Table 8.10. Similarly, although average earnings per job in Tunica
County in 2000 ($25,513) were only slightly lower than the state average ($26,513), 22.8 percent of black households in Tunica had an annual income of less than $10,000. Yet another way of viewing this is through distributional differences in median household income, which went from $10,965 for the county in 1989 to $23,270 in 1999. For instance, of the different geographic scales given in Table 8.11, households in N. Tunica
CDP had significantly lower income levels.
Table 8.10 Per Capita Income by Race/Ethnicity; Tunica Co., Mississippi, US, 2000
Tunica United Population Group Mississippi County States Total Population $11,978 $15,853 $21,587 White $22,715 $19,387 $23,918 Black or African American $7,929 $10,042 $14,437 Native American $13,821 $11,726 $12,893 Asian $20,328 $17,504 $21,823 Native Hawaiian / Pacific Islander N/A $19,794 $15,054 Hispanic or Latino $9,446 $12,549 $12,111
Source: US Census Bureau (2000)
250 Table 8.11 Select Distributional Characteristics of Median Household Income and Earnings; Mississippi, Tunica County, North Tunica CDP, and the Town of Tunica, 1989
Greater FT FT Ratio of Median Less Than Area Name Than Earnings Earnings Female to HH Income $25,000 $100,000 Males Females Male Mississippi $31,330 40.7% 6.0% $30,549 $21,554 0.71 Tunica County $23,270 52.4% 3.6% $25,244 $18,104 0.72 North Tunica CDP $14,891 71.0% 1.3% $16,250 $16,985 1.05 Tunica Town $26,607 48.3% 5.2% $30,208 $22,250 0.74
Source: US Census Bureau (2000)
Given those statistics, it is likely that the employment and income benefit of casino development has been limited for the black population in Tunica County, which was for the most part synonymous with the poverty population in the past and at present—40.6 percent of the black population remained in poverty in 1999, while that number was 33.1 percent for the total county population. There are a number of reasons why this may be the case, many of which have been talked about previously in this study.
For instance, poverty researchers suggest that persistent rural poverty is due to a combination of variables, including below-average education levels and limited job skills for individuals, which are confounded by low family income, physical isolation, inadequate infrastructure, and limited institutional resources and social support services.
All of these factors existed prior to casino development and have since remained, but to a lesser degree for some than others.
Most of those issues will be taken up in the next section, but some are important to note here, such as the issue of infrastructure as it relates to physical isolation and access to jobs. The county road system was abysmal up until late 1996 when at least
Highway 61 was made into four lanes. However, this did not detract from the fact that
251 most among the poverty population had little to no means to traverse the ten miles or so to the casino establishments. There is still no public transportation system in the area and private service is limited to casino shuttle buses (i.e., between casinos and casino hotels), a locally owned taxi business, and some limited busing services provided by Catholic
Social Services, which is mainly for the elderly. Early on many gave in to walking the entire distance, which is on average 19.7 minutes by car. Some still walk, which despite road improvements is a dangerous feat as accidental death rates due to motor vehicle accidents have risen significantly since the casino industry’s arrival (MSDH 2003).
However, the new income for the persistent few has afforded increased employment opportunity for others. That is, a number of the poor have since purchased vehicles and in most instances this has meant one new car for use in carpooling or in trading off with other members of the household, who often work different or partially overlapping shifts. This has allowed for increased participation in casino industry employment, and therefore lifted total household income, but there have also been social consequences. For instance, some among the non-poor population fail to recognize the immediate importance of owning a vehicle and further criticize the poverty population on their value-system (Field Notes A/B 2003). That is, they deride the placement of material possessions above what they perceive as more salient needs and thereby lending credence to the culture of poverty theorem. Most importantly, from the standpoint of the poor themselves, there are reports of family disruption (Field Notes C/D 2003). The impacts of transitioning into the modern economy mean that multiple income earners are the household norm. As a result, family unity and stability often suffer. This has begun to
252 alter the familial culture of the population and to do so in a negative way (Field Notes C
2003).
Other issues to be discussed are centered on migration and commuting.
According to Mississippi Vital Statistics, Tunica County’s population increased by 13 percent from 1990 to 2000 (net births and deaths), including an 8.3 percent increase in the non-white population and a 27.6 percent increase in the white population. The majority of those individuals came from a state other than Mississippi, mainly Shelby
County, TN, which represents Memphis, and neighboring counties DeSoto and Coahoma
(see Table 8.12). The same geography was relevant for out-flows, while the trade-off within that decade was seemingly for the better from an income perspective. For example, from 1999 to 2000 the average median adjusted gross income was $18,028 for those coming in and $15,019 for those going out. Those with highest income came from
DeSoto County ($20,416).
Table 8.12 County to County Migration Patterns; In-Flow and Out-Flow for Tunica County, 1990-2000
County / State In-Flow Out-Flow Shelby, TN 18.3% 21.6% Clark, NV 2.4% 0.0% Philips, AZ 0.5% 0.0% Coahoma, MS 9.3% 8.3% De Soto, MS 9.2% 16.9% Panola, MS 3.2% 3.8% Quitman, MS 2.6% 1.9% Tate, MS 2.8% 6.5% Same State 15.1% 14.4% Different State 36.7% 26.7% Total 2316 2511
Source: County to County Migration Patterns, 2002
253 The influx of a population with a higher income as such, and the loss of more poor than are coming in, can distort or create fallacies in social welfare measures in terms of what gains (or losses) have actually occurred for the resident pre-casino population.
As Shaffer (1989) explained, there are three types of income change:
• Extensive income change occurs when more people are attracted to the community; • Intensive income change represents increases in per capita income of existing residents, occurring without any change in community population; and • Combined has both extensive and intensive income growth, that is, more people and more income per person.
Tunica has experienced combined income change. Without explicit statistics to make the necessary linkages, it is difficult to determine, for instance, how much of the decrease in the poverty rate is due to actual income growth in the pre-casino resident population and how much of that decrease is due to migration and related income flows that dilute the population base to make it appear as though people are better off. Survey responses from the poverty population can give us a sense for this. For example, 63 percent reported being currently unemployed, 39 percent did not feel financially independent, and 45 percent considered themselves poor, with poor being defined as a lack of money. Yet, in trying to get an even better handle on this, it helps to know why people are moving (or not), and whether or not the move is attached to income and other measures of increased well-being.
There is an amalgamation of motives for migration, but in this case the reason is purely economic. Many resist moving to Tunica County based on the loss of the advantages of an urban and suburban lifestyle afforded by Memphis and DeSoto County.
Beyond what existed previously, the most basic community services (e.g., protective services), and opportunities for discretionary spending other than the casinos have yet to
254 develop. In addition, there are issues centered on the social-psychological motivation to relocate that are clearly distinguishable from economic reasons in the Tunica case. There are reports that people from Memphis and surrounding counties in Mississippi, from which the casinos draw labor, remain averse to taking up residence in the county due to its former reputation as the Ethiopia of America and their lack of desire not to be counted as one of those Ethiopians (Field Notes A/D 2003). Stated more bluntly, the remnants of racial discrimination and segregation of the past in Tunica County are giving rise to class discrimination and segregation in the present. This is a common, although subtle theme, throughout this analysis.
The alternative to migrating is commuting. Of the 14,006 persons employed in
Tunica County in 2000, only 22.5 percent were residents of the county. The high commuter rate seems logical given that the county labor force made up less than one- third of the number employed in 2000. The majority of those who commute to Tunica do so from Memphis (Shelby Co., TN) and DeSoto County to the north and Coahoma
County to the south. The growth in the number of commuters from those counties as well as current service industry worker and wage data are given in Table 8.13.
Table 8.13 Commuters from Coahoma, DeSoto, and Shelby Counties to Tunica; Total 1970-2000; Average Wage and Workers by Service Industry
Total Number of Commuters County of Service Industry 2000 to Tunica Residence 1970 1980 1990 2000 Workers Average Wage Coahoma, MS 38 16 29 1348 1075 $21,645 DeSoto, MS 0 17 183 3830 3380 $38,537 Shelby, TN 32 93 162 2749 2250 $26,865
Source: BEA 2003
255 In terms of the locally based labor pool, education and skill levels remain as an obstacle. In 2000, a large chunk of the total county, and specifically the black population, still had less than a high school diploma −−30.2 percent and 22.6 percent, respectively. Yet, although education may have caused problems on the onset, the ability for the population to obtain the skills necessary to work in the casino industry has since been hindered by the structure of Mississippi gaming law. The legislation was carefully crafted with the sins of gambling in mind, with the placement of state restrictions on the teaching of casino-related content in public job training and college environments in order to ensure that the act of gambling is not taught and reinforced.
One final factor to be noted, which will be revisited in the next chapter with respect to religion, is the issue of labor force participation. According to Census Bureau and state labor market estimates, approximately 42 percent of the black, working-age population was not in the labor force in 2000. This is in part due to high disability rates within that population, particularly for older cohorts who in many cases were given disability status in years past as a means for obtaining federal and state financial assistance where other means were lacking (Field Notes 2002 C). Those numbers have since dropped, likely with the aging of that population. Still, that dependency remains an economic, social, and poignantly psychological barrier for many (Field Notes 2003 D).
8.3 TAX REVENUE
In each commercial casino state the manner in which casino tax revenues are distributed and spent is variable. In most states casino tax revenues go into a general fund with portions allocated to education and some form of economic or community development. Likewise, in Mississippi all gaming revenues go directly into a state
256 general fund except for a percentage that is designated for a bond sinking and highway fund and for transfer to local governments. Through redistribution of those funds, most revenues have gone toward housing, transportation, health care services, youth counseling programs, and, more recently, education.
Thus, the state of Mississippi in many ways has the casino industry to thank as its savoir as well, with more than $2965.7 billion in gaming tax revenue since 1993, when the state was near bankruptcy. That amount reflects steady growth to its present annual collection of approximately $330 billion (up from $44 billion in 1993). Since 1995, the state has transferred approximately 33 percent of the annual amount to local governments
(see Figure 8.6). Over the first 10 years of gaming in Tunica County, 1991 to 2001, the state gleaned $521 million in tax revenue from the North River region, $215.4 million of which went to Tunica County (i.e., 4% of the state’s 12% gaming tax). Of that $215.4 million, the town of Tunica was given $13.2 million and Tunica County schools received
$27.3 million, while the remainder went to the levee board and general fund ( see Figure
8.7) for annual percentage distribution).
Figure 8.6 Mississippi Tax Revenue from Gaming; State Allocation and Local Government Transfers, 1993-2004
$350 $300 $250 $200 $150 $100 $ Billions $ $50 $0 1993 1995 1997 1999 2001 2003 Year
Mississippi Local Government
Source: Mississippi Gaming Commission (2004)
257 Figure 8.7 Percentage Distribution of Tunica County Gaming Tax Revenue
4% 4% 2%
Town of Tunica Tunica County Schools Levee Board General Fund
90%
Source: Tunica County Chamber of Commerce (2002)
However, the direct revenue benefits of casino development do not stop with gaming taxes. They come in a number of other forms, such as through rooms and meals taxes generated through patronage at casino hotels and restaurants, retail sales taxes collected at casino stores, and property taxes. The actual amounts attributable to gaming, however, are difficult to ascertain given the inability to identify and extract the amount attributable to casino-related tourism and recreation activities from each major category.
However, in the case of Tunica, given that casinos own and operate approximately 90 percent of all hotels and restaurants in the county, one can fairly view all rooms and meals tax revenue as casino-related (von Herrman et al. 2000). As such, it is easy to see how local and state governments can easily become dependent on gaming taxes to support fiscal spending. In fact, the state of Mississippi has the highest level of gaming industry dependency among all commercial casino states except for Nevada.
258 Such dependency is risky. Casino revenues can fluctuate due to a number of factors that are both predictable and unpredictable. For instance, as previously noted, casinos are subject to vagaries in the business cycle and operate on a tight profit margin.
They are also footloose and have a propensity to pick up and leave in a heartbeat if the corporation no longer finds the site viable. Tunica County witnessed this when the Isle of
Capri closed down shortly after preparations for a $14 million entertainment complex.
Thus, governments should be warned about committing those revenues to standard expenditure streams. Officials in Tunica County have avoided that tendency for the most part, but not altogether. For example, in the town of Tunica, property taxes were first cut in half and then eliminated completely. However, as explained to me, the loss of that revenue stream was meaningless given the amount of funds it generated in comparison to what is received from the casinos, which is so much money that they cannot invest or spend it fast enough (Field Notes 2003 B).
At the county level, that spending has gone mainly toward the expansion of
Highway 61, a new elementary school, and the development of non-gaming activities, such as an arena and exposition center, a river park landing and museum, public golf and tennis facilities, and, more recently, airport expansion. ( See Table 8.14 for major spending categories and percentages of total tax revenue.) With those expenditures in mind, we should pause and ask: what does this spending mean in terms of social welfare, particularly given that the justification for welcoming the casinos was tied to providing jobs and other forms of assistance to the resident poverty population?
259 Table 8.14 Allocation of Gaming Revenue; Tunica County Expenditures, 1992-2001
Allocation of Gaming Revenue Education 15.7% Water & Sewer / Utilities 8.7% Youth & Family Recreation 3.7% Protective Services 3.1% Housing 1.6% Arena & Exposition Center 15.2% History Museum 1.0% Library Expansion 0.8% Tunica Lake Restoration 0.8% River Park Landing & Museum 10.5% Highways & Roadways 26.2% Public Golf & Tennis Facility 6.3% Airport 6.3% Total $Million 190.6
Source: Tunica County Chamber of Commerce (2002)
One might think that it would be logical to invest in training and education for the adult population, but this role has been played by the Casinos themselves, such as through the Grand Casino’s adopt-a-town program. This brings us back to the questions that I raised at the close of chapter 6 with respect to the sincerity of the white planter class and their underlying intentions. Sowell (1994: 98) provided some food for thought in terms of how to go about understanding those intentions:
The government’s economic impact on particular groups is not simply a question of what specific policies it follows, but also—and perhaps more important—whether it follows any policy at all.
In other words, the role that the government (and those in a position to influence the government) chooses to play in directing the use of gaming funds can have an important economic impact and other effects on the poor. Yet, in its absence as a regulating force or as a representation of historical racial and class antagonisms, discrimination in the
260 distribution of gaming benefits can be difficult to detect or estimate. Accordingly, I begin the next discussion by clarifying the role of the power elite and the direction of tax revenue spending from an institutional perspective. In so doing, I identify and speak to some of the controversial investment areas with respect to how/why the poor may or may not be impacted positively by those developments and show where there are hints of the aforementioned historical racial and class antagonisms.
8.4 CHAPTER REFERENCES
Hashimoto, K. and G. Fenich. 2004. Does Casino Development Destroy Local Food and Beverage Operations?: Development of Casinos in Mississippi. Gaming Law Review. 7(2): 101-109.
Minnesota IMPLAN Group (MIG). 1999. IMPLAN Pro Technical Manual. Stillwater MN: MIG.
Mississippi State Department of Health (MSDH). 2003. Tunica County Health Profile. Jackson, MS: Office of Science. Olson, D. 2005 March 29. E-mail communication. MIG Technical Support.
Robison, M. and J. Miller. 1988. Cross-hauling and Nonsurvey Input-Output Models: Some Lessons from Small-area Timber Economies. Environment and Planning A. 20: 1523-1530.
Rose and Associates. 1998 November 5. The Regional Impacts of Casino Gambling: Assessment of the Literature and Establishment of a Research Agenda. Prepared for the National Gambling Impact Study Commission, Washington DC.
Rose, A. and W. Miernyk. 1989. Input-Output Analysis: The First Fifty Years. Economic Systems Research. 1(2): 229-271.
Shaffer, R. 1989. Community Economics: Economic Structure and Change in Smaller Communities. Ames IA: Iowa State University Press.
Sowell, T. 1994. Race and Culture: A World View. New York: Basic Books. von Herrman, D., R. Ingram, and W. Smith. 2000 June. Gaming in the Mississippi Economy: A Marketing, Tourism, and Economic Perspective. The University of Southern Mississippi .
261
Wagner, J., et al. 1992. Estimating Economic Impacts Using Industry and Household Expenditures. Journal of the Community Development Society. 23(2): 79-102.
Wallace, J. 1998. The Casino Gambling Industry: A Case Study of Tunica, Mississippi. Published Dissertation. The University of Memphis.
262 CHAPTER 9 BENEFICIARIES
Poverty in America exists due to misallocation, maldistribution, and waste of resources and income, and the closely related fact of the elevation of corporate profit and growth over the elevation of human need. There can be no other rationalizations, justifications, or excuses. (Anderson and Gibson 1978: 37)
Realist geographers (e.g., Marxists) look to the conflict between classes in capitalist society and the distribution of power as a means to explain how resources are allocated in that society (Eyles 1974), pointing out that uneven development is a necessary condition of capital accumulation (Smith 1986). This inherently leads to inequalities in the distribution of assets within a capitalist society. One way to begin to look at the distributional outcomes of casino industry growth in Tunica County is to accept similar rationalizations or justifications for social and economic investments.
For example, when looking at public investment in economic development, infrastructure can be divided into two categories: economic overhead capital (EOC) and social overhead capital (SOC). The former refers to direct support of productive activities and consists mainly of public works projects, while the latter is geared toward the enhancement of human capital through social service investment, such as education
(Eberts 1990). Tunica County officials were keen enough to recognize that the ability to invest in SOC was contingent upon the speed and intensity with which they would be able to invest in EOC. In other words, observing the deplorable infrastructure conditions under which Splash casino operators had to work and its patrons had to withstand, which stemmed from prolonged dis-investment in the region (as discussed in chapter 6)—the need was made very clear, and the need was grave (Field Notes B 2001).
263 9.1 ECONOMIC OVERHEAD
In the eyes of the County Board of Supervisors investing in Tunica first meant investing in infrastructure that would help attract and keep both casinos and patrons. It also meant investing in the county’s image by putting forth a concerted effort to transform the Ethiopia of America into the Diamond of the Delta , even if only on the surface for a time (Field Notes B 2001). This meant that wide-scale; yet very basic infrastructure development would have to be completed with alacrity if the casinos were to come in the first place. Then, attention would need to be turned toward the drivers of destination tourism because, once more, it was realized that to achieve success meant achieving scale (Field Notes B 2001). Those drivers include the availability of lodging, air transportation, dining and retail opportunity of a particular quality/quantity, non- gaming leisure activities and entertainment, and sizeable convention facilities, the development of which was laid out in a comprehensive plan for the county that has been followed steadfastly.
While this market-oriented approach has been met with great success in Tunica, it has also been met with extensive criticism from those who see it as a ways to alternative means (Field Notes 2001 C). It is perceived by some as the hand with which to further subjugate the poor, rather than lift them into prosperity, or at the least, to improve their level of well-being. An example is found in investments in infrastructure, namely roads.
That is, once Highway 61reached completion, the county turned its attention to other roadway improvements. This began with a concerted effort to not only build and expand the roads nearest the casinos, but to beautify them to resort standards. At the same time, dirt roads, or more appropriately defined, tractor paths running through the fields began
264 to be paved. Even more odd to a passer by, were the fire hydrants that appeared to blossom with the cotton. It was clear that they were planting the seeds for the next phase of development, but what was not clear to an outsider such as myself was: on who’s land and at who’s expense was this investment in infrastructure taking place or for what reason was a particular plot of land receiving attention?
While investigating these activities, I received at least two very different answers.
The first response was from a business leader who was also on the planning board and quite proud of Tunica’s success and that which was on the drawing table for the future.
This person clearly identified the property as owned by one of the county’s landed-elite and revealed plans for a golf course on that site. Another individual of a similar stature corroborated the story and explained that even though the handful of landowners in northern Tunica County were not elected officials, they had to be included in the establishment of development plans for the region, because despite what was written on paper, nothing would be done according to that plan unless so desired by those landowners.
Hence, in many ways the planning process and the final development plans came down to identifying who among them was going to profit most and in what way. During the conversation in which this was revealed, I was repeatedly asked if I was hiding a tape recorder or if I was going to use the person’s name in any way—clearly, this was a very sensitive issue that was not to be publicized. That summation was validated when I next spoke with yet another county official −−this one in a more marketing-oriented position. I asked probing questions of this person for which I already knew the answers (i.e., with respect to the planned development of the land and who owned it) and I was blatantly lied
265 to in every respect—this individual had no idea that I had just seen the plans and the property tax maps and county tax rolls firsthand. The best explanation that I can find for this behavior, once again, is Southern white defensiveness because besides their official positions, the characteristic of each respondent that stood out the most was that the first two were new to the area, brought in with the casinos, while the third was a life-long resident.
Still, no matter which aspects of this development process seem culturally and politically tied to the history of the region, the manner in which investments were decided upon, along with whom would reap the greatest rewards, is not unique to Tunica. On the contrary, it is quite representative of that experienced in other persistently poor regions in developing countries where economic change has taken place and the process recorded using PSIA. For instance, Ihsan and Wodon (2002: 160) explained that when conducting benefit incidence analysis they found a threshold effect with certain types of developments, “whereby the poor gain in access only once the non-poor already have fairly high access.” 31 As Lanjouw and Ravallion explained further (1998):
… current distributional impacts of change in provisioning will depend on how well positioned different socio- economic groups are to gain from marginal expansions, given the history of past allocations… Suppose that the non-poor were able to capture the bulk of the gain when the program was first introduced, but are now virtually satiated at the margin. Then the poor will gain a large share of the marginal benefits … even though their share of average benefits is low…. The timing of program capture by different income groups could well be critical to the policy conclusions drawn about the incidence of gains and losses from public spending reforms (3).
31 Benefit incidence analysis (BIA) is a term used widely in reference to the distributional impacts of public spending. The actual methods for conducting BIA are therefore nearly as diverse as PSIA itself.
266 We can formalize these arguments in a simple political- economy model of the capture of an anti-poverty by the non-poor. The model assumes that the government wants to reduce poverty with the program, but that it faces a political-economy constraint… the non-poor have political influence over program placement which they use to obtain compensatory benefits. (5)
That extended quote well reflects what I had recently begun to observe in Tunica.
Continuing with the example of roadway improvements, it was only on my last visit that I witnessed construction on the largely dirt and gravel roads that line the poverty neighborhoods. Thus, although the landed-elite may have manipulated gaming tax expenditures to their advantage, their first gain may not mean that the poor will not achieve access to gaming’s benefits to some degree at some point. It may just mean that such gains will go in favor of the poor through the age-old adage of trickle down , once the needs and desires of the non-poor are satiated. In the meantime, we shall continue with the situation at present.
9.2 EDUCATION
In his book, Race and Culture , Sowell (1994: 98) noted that:
One of the crucial areas of discrimination by government has been in the quantity and quality of education made available to different groups, for this can have lasting effects on their productivity and career potential in the private sector as well.
This certainly rings true in the case of Tunica, where historically the majority of the county’s white children have attended well-funded private schools, while black children enrolled in the public school system, which has had a notoriously low academic record, chronic debt, and low levels of service given the number of students. While it seems logical that those in Tunica County might wish to change this situation, if only for
267 the sake of improving the county’s image by shedding that notoriety, this has not been the case, at least not for everyone. That is, although it was eventually agreed that a proportion of gaming tax revenue would be allocated toward education, the Board of
Supervisors made it quite clear that they had no intention of turning over those funds to the public schools. In fact, many within their cohort felt that the problems of the almost entirely black public school system had little to do with a lack of funding (Field Notes
A/C 2003).
As such, in order to guarantee that gaming revenues were used to address the schools’ problems, the Concerned Citizens for a Better Tunica County (formed in 1993) successfully negotiated a 20 percent tax revenue allocation for public schools. As a result, the school system’s debt was eliminated in a matter of six months (Higgins-Null
2004). However, renovations to school facilities were delayed and poor performance remained an issue that resulted in a move by the Mississippi Department of Education to assume direct control over the operation of the school district in 1997. These factors were tied to developers’ interest in building a new school in conjunction with new housing near the casinos, virtually inaccessible to the majority black resident population given distance and income. This was attempted by pitting the Tunica County School
District against the coalition in a motion to modify the district’s desegregation plan, which the school district entered into in 1970 (USDOJ 2003: 1-2).
On September 16, 1999, the District filed a Motion to Terminate Supervision, or, Alternatively, to Modify Desegregation Plan, in which it sought a declaration of unitary status and termination of federal court supervision, or, in the alternative, approval to build a new elementary school in Robinsonville (“the Robinsonville site”) and to modify elementary-school attendance zone lines…
268 … the United States argued, among other things, that the District had not met its burden of proving either that it had achieved unitary status or that its proposed new school comports with its affirmative obligation under federal law and the 1970 Order…
This Court’s 1970 Order requires that “[a]ll school construction, school consolidation, and site selection… in the system shall be done in a manner which will prevent the recurrence of the dual school structure…
Thus, although area students remain unofficially segregated through the private/public school systems, it was feared that the economic exclusion in education of the past would be reproduced and reinforced with the control of new funds for education in the hands of the elite. The battle ensued and in the end, a new school was built at an alternative site in the district’s motion, two miles closer to the black population than originally planned.
Finally, renovations to existing schools slowly took place.
9.3 HOUSING
The amount of new housing construction in a region is typically considered a strong indicator of economic growth. In Tunica County there were a total of 2,990 housing units in 1990, 3,705 in 2000, and 4,171 in 2002. This represents an increase of
23.9 percent from 1990 to 2000, and another 12.6 percent increase from 2000 to 2002. In comparison, state growth in number of housing units in 2000-2002 was just 2.9 percent.
Those numbers reflect the fact that the number of authorized new private housing permits alone in 2002 was nearly eight and half times what it was in 1990 ( see Table 9.1).
Despite the growth in housing, vacancy rates for 2000 were not very high ( see Table 9.2), which is not surprising given that there was a shortage of housing prior to the arrival of the casinos and the population has since grown by 13 percent (1990-2000).
269
Table 9.1 New Private Housing Units; Tunica County, MS, 1990, 1997, and 2002
New Private Housing Units… 1990 1997 2002 Authorized by Building Permits 7 22 59 Value $279,000 $1,888,000 $4,413,000 Per Unit $39,857 $85,818 $74,797
Source: US Census Bureau (2004)
Table 9.2 Select Housing Statistics; Tunica County, MS, 2000
Tunica County 2000 # Housing Units 3,705 % Occupied 87.9% % Owner Occupied 51.7% % Renter Occupied 48.3% Homeowner Vacancy Rate 1.3% Renter Vacancy Rate 5.8% Housing Density (sq mile) 8.1 Average HH Size Owner Occupied 2.97 Average HH Size Renter Occupied 2.62 Median Housing Value $56,800 % Housing Value Less Than $50,000 40.4% % Housing Value Greater Than $200,000 4.1%
Source: US Census Bureau (2000)
According to Weber et al. (1993: 21), “place of residence has a direct bearing on an individual’s quality of life” and “in addition to economic well-being, housing and neighborhood factors weigh heavily in an overall assessment of quality.” Those participating in focus groups expressed a similar sentiment with respect to the poverty population’s desire to improve their living situation by taking advantage of the investments in new residential housing which, according to baseline data from IMPLAN, was $9.179 million in 1999 compared to $1.327 million in 1990. However, the poor have had a difficult time accessing this housing despite increased employment and income
270 levels. One issue that contributes to this is their attachment to place—most would prefer to remain in their own neighborhood and make improvements from within, rather than moving even just a short distance away. Yet, almost all of the new housing that has been and will be built is out in the county, nearest Robinsonville and closer to the DeSoto
County line than the town of Tunica. This reflects what one community advocate was quoted as saying (Cox in Mississippi Monte Carlo 1996: 17): “This county is so dollar- signs-in-the-eyes that they’re not looking at the small community—the citizens that are already here… They’re concentrating on how to bring people in.”
Another part of the problem is that conventional lending mechanisms have failed to materialize for the poverty population. This is often the situation in the Delta. Even where income levels are on the rise and the economy appears healthy, levels of perceived risk in serving such a population have prevented private lending institutions from providing financing to those living in distressed places ( Key Challenges 2001). However, those among the poverty population in Tunica and their advocates suggested that their inability to obtain the financial means to either purchase new homes or repair their existing residences goes beyond what would be considered sound business practice.
They point to existing power structures, comprised mostly of the planter elite, in preventing them from improving their living conditions.
For instance, they note that the Town’s power brokers not only lack the desire to annex North Tunica, or the sub as it is referred to locally, but also wish to drive them out by facilitating bank foreclosure or condemnation of their homes. They also struggle with political disenfranchisement when attempting to access housing grants made available to those in the county through casino revenues. Though a non-competitive selection process
271 supposedly exists, poor individuals are forced to compete for those funds with those who are in a privileged social position relative to themselves. That includes not only those of other races or economic classes, but also those within their own community. Simply put, as explained to me, you get your name on the list and when you get to the top of the list, you get the money. The problem is, unless you know someone, you never get to the top of the list, as expressed by one frustrated resident (Field Notes D 2002):
I’m fixin’ to do my house, if I could, they won’t give me no money, I been askin’ for years, gots my name on the list, and it keep movin’ down ‘cause I don’t know no one.
That is, every poor person in Tunica is not equal politically. Some are more connected than others to those who are in a position of power, formally or informally.
Such relationships are often historical in the sense that a former tenant farmer may receive special consideration from the landowner whose land they worked and who may be in a position to influence distributive decisions. This type of relationship is reflected in one elderly black woman’s reply. When asked whether or not she felt discriminated against, she appeared confused by the question and responded by saying, “no, my white folks takes good care o’ me” (Field Notes D). The result of these forces, in the case of housing, is that North Tunica and other poverty enclaves in the casino region are still predominantly comprised of what are commonly called shacks (short for the former sharecropper shack)—paper-thin wood for walls, broken windows and doors, detached porches set upon cinder blocks, rusted tin roofs ( see Table 9.3 for geographic variations in housing value). Yet, dotted among them are freshly painted homes with new roofs and an appearance of hope like that of the resident previously quoted who, when I last visited
Tunica (August 2004), had yet to receive the funds to repair her home.
272
Table 9.3 Geographic Variations in Median Housing Values; County and Place; Tunica County and Mississippi, 2000
Median Value Less Value Greater Area Name Housing Than $50,000 Than $200,000 Value Mississippi $71,400 28.6% 5.7% Tunica County $56,800 40.4% 4.1% North Tunica CDP $38,000 60.6% 0.0% Tunica Town $83,900 14.0% 3.9% County Mean $61,739 38.0% 4.0% County Median $57,200 42.0% 3.0% Place Mean $59,438 42.0% 2.0% Place Median $55,400 43.0% 1.0%
Source: US Census Bureau (2000)
9.4 HEALTHCARE
According to the US Department of Health and Human Services (2003), Tunica
County represents a healthcare shortage area. This designation is defined as a geographic area with at least 3,500 persons per primary care physician within thirty minutes’ travel time. In 2002, Tunica County had just five primary care physicians and one dentist available to serve a total population of 9,227, including 2,164 persons with a disability
(MSDH 2003). In addition, just two small healthcare facilities are available to residents −−one in the town of Tunica and another in Robinsonville, placed there mainly to serve casino visitors and new residents (Field Notes C 2002). Although this represents improvement over that which existed in the past, it is the case that:
[Only] a few organizations in Tunica address the immediate health care needs of the community, and even fewer are addressing the broader issues associated with poverty… In addition, many people lack transportation and are unable to reach health care providers for treatment. (CDC 2001)
273 Focus groups revealed that those broader issues include not only the inability to access healthcare services due to lack of transportation, but also the lack of insurance, trust, and the desire among the poor to not feel dependent on others (particularly with respect to a history of forced dependency on the white and elitist populations). The extent of those issues was investigated through the community survey. Thirty one percent reported having no insurance whatsoever (including life, medical, etc.), 52 percent said they worried about their health constantly or often, and 31.5 percent reported not receiving help when recently in need of health care or medical advice for a combination of personal and service oriented reasons. Levels of trust were extremely low where those who might be considered officials or authorities are concerned. These issues are particularly troubling with respect to motherhood among the poverty population.
9.4.1 UNWED MOTHERS AND TEENAGE CHILD BIRTHS
The percent of total live births to unmarried mothers in Tunica County by race in
2001 was 33.3 percent for whites (state, 22.4%) and 86.6 percent for non-whites (state,
74.3%) (MSDH 2004). This represents an increase for the county over the last decade
(MSDH 1993, 2001). The life chances for such children, in terms of living healthy lives and getting out of poverty, are rather grim. For instance, research has shown that children born to unwed mothers are less likely to graduate from high school and more likely to grow up under lower standards of living than those of married mothers (Coontz and Folbre 2002; Wu and Wolfe 2001).
The aforementioned growth was within the white population, where growth occurred most for non-whites with respect to infant mortality. The infant mortality rate
274 for non-white infants—the proportion of deaths in the first year of life in every 1,000 live births—went from 11.2 percent between 1987 and 1991 to 22.2 percent between 1997 and 2001 (MSDH 2004). This is attributed to a number of factors, including the mother being too old or too young, having poor health or having children too close together, chemical use (e.g., tobacco, alcohol, drugs), and poor infant nutrition and hygiene or disease. Worse yet, post-neonatal mortality (infants 28 days to one year old) for non- white infants during the same time periods went from 5 percent to 15.2 percent. The
Mississippi State Department of Health estimates that nearly half of those deaths could have been prevented by parental education and health care interventions.
Improvement has occurred among births to teenage mothers. However, there was little room to grow in this area given that during the 1987 −1991 period births to teenage mothers represented 92.9 percent of all live births in Tunica County. That number has since dropped to 30.8 percent, but that is still far from the statewide percentage of 17.8 percent, in a state that has the highest teen birth rate in the nation. The majority of those teenage mothers were from a family with an income below the poverty level, most of whom have or will drop out of school, require long-term financial support, and be involved in child abuse (Field Notes C 2002; MSDH 2004). This puts those children at risk above and beyond that presented to them by factors previously mentioned.
275 9.5 MORAL COMPROMISE
Figure 9.1 Illustrations of Crime, Addiction, and Sexuality Associated with the Casino Industry; Tunica County, MS Billboards, 2004
Source: Farrigan and Katz (2004)
As Figure 9.1 illustrates, whether or not one can statistically measure issues of moral compromise or make a causal link of those measures to gaming, the message sent out to the community is clear. So too are the temporal aspects of these factors as noted in chapter 4, where through personal observation in 1996 and each year from 2001 to 2004,
I can attest to the fact that these types of messages have only just appeared in the last year or so. Also over the course of that time, it was only on that last visit that evidence of crime or at least the concern for crime became apparent. For instance, one casino hotel that had previously had an open and welcoming environment had over the last year installed elevator locks and placed locked gates around outdoor recreational areas. Data to support crimes related to these observations are lacking, but as with all else there is somewhat anecdotal evidence of negative impacts. For example, there have been newspaper reports of casino-related crimes, such as one about an elderly couple being murdered in a casino elevator.
Some crime data are available from the Federal Bureau of Investigations (FBI), but this data is not altogether reliable in the case of Tunica because it is based on estimates. That is, the FBI gets its data from state and local law enforcement agencies
276 who are not required to report to the FBI and no numbers were available that indicated that Tunica County officials had done any reporting as of late. Still, Table 9.4 consists of estimated percentages of offenses and arrests in Tunica in 2000. Those figures suggest that crime patterns, given types of illegal activities, are similar to other destination casino resorts, such as a high incidence of drunken driving and illicit drug use. With respect to the latter, without meaning to make generalizations, when survey respondents were asked to identify their occupation, a number replied husslin’ , which is a local term for drug dealer. I was later told by that same population that husslin’ had become a more lucrative business over the last few years than it had been in the past (Field Notes D
2003).
Another moral issue that surfaced in the public eye in Tunica more recently is problem gambling. Yet once more, analysis of the extent and distributional characteristics of this issue is hindered by a lack of data. Thus, I turn once more to that which is not wholly representative of the situation in Tunica. For example, in 1996 the
Mississippi Council for Problem and Compulsive Gambling, along with Mississippi State
University, conducted the first comprehensive study of the impact of problem gamblers in Mississippi and the added impact of the establishment of casinos in the state on that population. The study characterized 5 percent of Mississippi residents as problem gamblers. Of those, 2 percent were deemed probable pathological gamblers based on the severity of their addiction (e.g., spending levels). Those numbers were relatively low compared to national and state estimates, including those without casinos. Since that time, estimates have risen to closer to 7 percent, which puts Mississippi near the top for the nation (estimates range from 1.7 to 7.3%; Lesieur 1998) and suggests that a negative
277 impact in the three casino regions is likely taking place. However, there is no benchmark for Mississippi that would allow for an assessment of whether or not those numbers are high in comparison to what they were for Mississippi prior to the legalizations of the casinos.
Table 9.4 Types of Crime and Percentages of Total Arrests; Tunica County, MS, 2000
Estimated Percentage Type of Crime of Total Arrests Murder 0.3% Rape 0.3% Robbery 0.3% Aggravated Assault 2.6% Burglary 3.7% Larceny-Theft 3.4% Motor Vehicle Thefts 0.3% Arson 0.0% Other Assaults 9.1% Forgery and Counterfeiting 1.1% Fraud 2.0% Embezzlement 0.6% Have Stolen Property 0.9% Vandalism 0.3% Weapons Violations 0.6% Prostitution and Commercial Vice 0.0% Sex Offenses 0.6% Total Drug Violations 12.8% Gambling 0.9% Offenses Against Family and Child 5.4% Driving Under the Influence 13.4% Liquor Law Violations 2.0% Drunkenness 7.4% Disorderly Conduct 4.5% Vagrancy 0.3% All Other Offences Except Traffic 27.0% Total Offender Population 9227 Total Offenses 352
Source: FBI, National Archive of Criminal Justice Data, 2004
278 That same study suggests that problem gamblers in Mississippi are younger and more racially diverse than non-problem gamblers and that they tend to be divorced or single. Yet, that is not necessarily a reasonable characterization when dropping down to a regional scale because, for instance, regional demographic profiles are variable across the state, as are residential visitation patterns. For example, in their survey von Herrman et al. (2000) found that the likelihood for South River residents to gamble (73.8%) was much greater than that for residents in both the North River (11.5%) and Gulf Coast
(39.4%) regions. This plays directly into problem and pathological gambling rates, as the more visits the greater the likelihood of addiction, and with it associated problems such as criminal behavior and bankruptcy.
Thus, while on the whole Mississippi residents, who visit Mississippi casinos more than non-residents, are at greater risk for problem gambling, that same logic suggests that it is less likely the scenario in the North Casino region based on the estimates produced by the von Herrman study. However, some clues hint otherwise. For instance, Milloy (1998) reported that while few among those with gambling problems typically seek treatment, Gamblers Anonymous meetings near Tunica went from two meetings a week with about seven attendees in 1995 to somewhere in the vicinity of eight meetings a week attended by approximately twenty people in 1998. Additionally, in conducting my own research, a number of survey participants, who were paid $5 for their time, commented that they planned to go directly to the casinos and play that $5 in the slots. This is by no means a measure of addiction, but it does point out that to suggest that there is no gambling problem among the resident population, or at least the potential for a problem for the poor due to the lack of hard evidence, would be naïve and
279 misleading. Still, that gambling behavior as a form of entertainment was found to be unacceptable by nearly 67 percent of survey respondents, which was also found to be associated with measures of religiosity.
9.6 CHAPTER SUMMARY
Development must be inegalitarian since “it does not start in every part of the economy at the same time.” (Lewis 1976 in Gagliani 1987: 313)
I began the impact analysis in chapter 7 by documenting the rapid growth in casinos and casino revenues stemming from the widespread rush of casino openings since
1988. Of the 11 states and 57 counties with commercial casinos today, Tunica County has shown the most in combined growth in admissions, gross gaming revenues, and casino-related employment. As a result, it is ranked third among the nation’s top casino tourist destinations. However, it is recognized that evaluating the effects of that growth is an inexact science. Research problems can be traced to a number of measurement difficulties, such as factors associated with history, scale, time, and perception, to name a few. Thus, in this chapter I tried to engage as many of those perspectives as reasonably possible in order to further demonstrate the controversies and contradictions that arise with respect to understanding the overall and distributive impacts of casino gaming as an economic development strategy. A number of very basic conclusions can be drawn from that assessment with respect to the ‘tendencies’ (i.e., summary hypotheses) highlighted in chapter 4:
• The casinos have created an enormous amount of tax revenue and jobs in terms of direct effects, but the multiplier effects of that activity are limited;
280 • The casinos have not crowded out or cannibalized local businesses and they are exporters of services, but this is likely due to the limited economic structure to begin with; • The industry has generated a lot of new income through job creation, but it has not significantly raised the personal income levels of the resident population, particularly those who are black; • The industry can be characterized as both an economic island and a toll house; • The state and the county are overly dependent on the North River casino region; • The Tunica County gaming industry has as yet to be negatively impacted by the domino effect or market saturation; • Time has yet to be a factor in terms of the industry reaching its peak, but it has recently become a factor with regard to encroaching negative social impacts; • The county has highly subsidized casino industry growth, but it has done so with revenues from the industry −−there is little evidence to support the idea that those revenues are subsidized by the resident poverty population; • The immediate beneficiaries of casino development have been the casinos themselves, north Tunica landowners, state and local government, and the low- skill labor force from the surrounding area −−the benefits to the resident poverty population have been limited thus far, but it appears that they will increase significantly with time; and • Social costs are apparent, but they also appear to be limited thus far and are difficult to measure with any certainty.
To add anything more to those points would require revisiting the details in the impact chapters. However, this analysis has produced three interrelated findings that can be said with clarity and conciseness:
1. In this context, understanding economic incentives is imperative to understanding economic results and in determining what impacts can be attributed to the casino industry directly and what impacts can not; 2. The power of the planter elite has not been reduced in some egalitarian fashion, on the contrary, it has been restored; and 3. The discriminatory attitudes and behaviors of the past have not been done away with −−at best they have been tempered by the concerted effort to construct a new social and economic reality.
It is in relation to number three that I begin the next chapter. Picking up where I left off, with moral compromise, I further explore measures of subjective well-being and the association of casino impacts on well-being to the issue of culture, economics, and
281 religion. The focus on religion is supported by conflicting views of behavioral responses to change that emerged throughout the research process. Explicitly, that certain behavioral change was expected of the poor, particularly in association with employment.
Where that behavioral change has been found absent, those individuals have been criticized and further stigmatized in a negative light that is akin to the stereotypes and discriminatory attitudes of the past.
9.7 CHAPTER REFERENCES
Anderson, C. and J. Gibson. 1978. Toward a New Sociology. 3 rd ed. Homewood ILL: Dorsey Press.
Coontz, S. and N. Folbre. 2002. Marriage, Poverty, and Public Policy: A Discussion Paper from the Council on Contemporary Families. Paper prepared for the 5 th Annual CCF Conference, April 26.
Eberts, R. 1990. Public Infrastructure and Regional Economic Development. Economic Review: Federal Reserve Bank of Cleveland. Pp. 15-27.
Eyles, J. 1974. Social Theory and Social Geography. In C. Board et al., eds. Progress in Geography 6. London: Edward Arnold. Pp. 27-88.
Gagliani, G. 1987. Income Inequality and Economic Development. Annual Review of Sociology. 13: 313-334.
Higgins-Null, E. 2004. 50 Years After Brown, Parents and Students Fight for Equality in Mississippi’s Delta Schools. Rural Roots. 5(1): 1, 4-8.
Key Challenges to Effective Community Development. 2001. Washington DC: Housing Assistance Council. Available online at
Ihsan, A. and Q. Wodon. 2002. Who Benefits from Increased Access to Public Services at the Local Level? A Marginal Benefit Incidence Analysis for Education and Basic Infrastructure. World Bank Economists’ Forum. 2: 155-175.
Lanjouw, P. and M. Ravallion. 1998 July 15. Benefit Incidence and the Timing of Program Capture. Paper prepared for the World Bank’s 1998 Poverty Assessment for India.
282 Lesieur, H. 1998. Costs and Treatment of Pathological Gambling. The Annals of the American Academy of Political and Social Science. 556: 153-171.
Mississippi Monte Carlo . 1996 January. The Atlantic. Available online at
Mississippi State Department of Health (MSDH). 1993. Mississippi Health Futures County Data Book. Jackson, MS: Office of Science.
Mississippi State Department of Health (MSDH). 2001. Vital Statistics. Jackson, MS: Office of Science.
Mississippi State Department of Health (MSDH). 2003. Tunica County Health Profile. Jackson, MS: Office of Science.
Mississippi State Department of Health (MSDH). 2004. Tunica County Health Profile. Jackson, MS: Office of Science.
Smith, N. 1986. On the Necessity of Uneven Development. International Journal of Urban and Regional Research. 10: 87-104.
Sowell, T. 1994. Race and Culture: A World View. New York: Basic Books.
US Department of Health and Human Services, Health Resources and Services Administration (HRSA). 2003 July. Community Health Status Report: Tunica County, Mississippi.
US Department of Justice (USDOJ). 2003. The United States of America vs. Tunica County School District et al. and the State of Mississippi, the State Board of Education, et al. US District Court for the Northern District of Mississippi Delta Division. Washington DC: US Government Printing Office. von Herrman, D., R. Ingram, and W. Smith. 2000 June. Gaming in the Mississippi Economy: A Marketing, Tourism, and Economic Perspective. The University of Southern Mississippi .
Weber, M., J. McCray, and M. Ha. 1993. Housing Assessment Criteria of Rural Households. Social Indicators Research. 28: 21-43.
Wu, L. and B. Wolfe, eds. 2001. Out of Wedlock: Causes and Consequences of Nonmarital Fertility. New York: Russell Sage Foundation.
283 CHAPTER 10
SIN AND SAVIOR
When talking about the structure of poverty, we are in truth talking about the cultural core of poverty. This cultural core is itself surrounded by a penumbra of secondary cultural elements that are located in the concrete interaction of classes and the reproduction of the social formation as a whole. (Harvey 1993: 27)
The causal mechanisms that underpin social structure can be identified as systems of social practices that include cultural and other systems. In many ways, they are fundamental to the realist account of the world (Williams 1981). The identification of those causal mechanisms and their relations have been the focus of intensive research, which in this study was largely centered on participatory research aimed at obtaining the position of the poverty population in the Delta region. This chapter looks at one facet of necessary relations and contingent conditions that emerged from that research, one that pertains to the association among culture (religion), economy (employment), and poverty
(well-being). First, I begin by situating the discussion in associated empirical regularities, as understood through the extensive research aspect of this study.
Explicitly, research revealed that the spread of casinos is a complex phenomenon that is marked in the United States by a number of highly debated social, economic, cultural, and political factors. The most cited include:
1) The 1988 passing of the Indian Gaming Regulatory Act (IGRA), which opened the floodgates to casino development from the legislative perspective; 2) Increased support of gambling as an acceptable form of entertainment on the part of the American public, particularly among the middle class who had objected most strenuously about gambling in the past; 3) The desire of government officials to adopt economic development strategies that would foster the revitalization of distressed communities and, in conjunction, the
284 attraction of gaming as a substantial source of revenue that would not add to the tax burden of area residents; and 4) Increased competition within the gaming industry, mainly due to technological advances and factors associated with industrial organization.
This chapter examines the second and third factors, which in broader terms represent the conflict between gaming as a moral issue and gaming as an economic issue.
10. 1 MORAL VS. ECONOMIC
Those who view casino gaming as a moral issue typically argue that gaming fosters social ills and preys on the downtrodden, while those who see it as an economic issue tend to equate gaming with the creation of jobs and increased tax revenue that generates economic and community development (as discussed in chapter 4). Yet, morality issues can be perceived in a number of ways (Hunter 1994; Meier 1994;
Tatalovich and Daynes 1988), one of which subsumes the economic aspects under the moral (Studler 2001). For instance, those who support gaming as an economic development strategy in distressed areas may see it as a moral issue in terms of their assumed social responsibility to provide economic salvation and gaming’s potential to serve as the means to that end.
How those perspectives translate into the policy arena can be formally defined in two ways (Mooney 2001): contentious-based morality policy, where there is no consensus on the issue; and consensus-based morality policy, which is non-conflictual in the sense that a majority agrees on policy direction. In other words, consensus-based does not necessarily mean that there is no source of contention. Rather, it means that a majority of citizens, or at least a majority of those in a position of power, find the policy acceptable or objectionable such that there is sound agreement about its adoption or
285 rejection. In fact, Mooney and Lee (2000: 224) stated that “consensus morality policy variation is influenced almost exclusively by the general ideology of political elites.”
Similarly, in the casino examples, case study findings typically suggest that local elites have united with other powerful stakeholders behind the idea that, as an economic development strategy, gaming serves the greater good. With that in mind, they have adopted such a policy despite the expressed moral objections of the citizenry. That objection, quite ironically, resonates most with the poor, who have been shown to be less receptive to gaming than other groups, and among those with a Protestant-based religious background, whose concern is associated with the positioning of their religious faith against the act of gambling (Hutcheson and Taylor 1973; Johnson and Meier 1990;
Mooney and Lee 1995; Morgan and Meier 1980).
In those instances where the host community population is largely composed of the aforementioned individuals, casino gaming typically becomes a reality when broad constituencies composed of actors within and without the local government quickly and forcefully emerge in support of the industry as their savior (Lehne 1986). The coalition building that ensues represents what Wilson (1993) referred to as a moral cloud , where policy is determined by the combination, rather than opposition, of moral (e.g., religion) and economic (e.g., the market) concerns. In other words, if the monetary benefits of casino gaming are earmarked for developmental purposes (e.g., education), referenced in aid of the poor or other vulnerable groups who are in a position of dire need, then the religious and moral concern is alleviated (Pierce and Miller 1999). Meier (1994) referred to this legitimization aspect as redistributive morality policy, distinguishing it from sin policy, which few would be willing to affirm.
286 Hence, when powerful constituencies act in concert, both monetarily and politically, and frame gaming as an economic development issue, they are virtually impossible to defeat (Kindt 1998). The result is that the adoption of casino gaming, the structure of its regulation, and the use of its funds are largely determined by the combination of local and extra-local politics. So too is its measure of success as an economic development strategy, which is thereby seen through the lens of the local elite and casino groups who downplay the negative impacts and advertise the positive
(Felsenstein et al. 1999).
Thus, the incision of the gaming industry and its proliferation in a distressed place can easily occur without majority resident approval, courted by those in a position of power at times of economic stagnation and often representative of existing divisiveness within that community on a number of fronts. Every aspect of the situation just described was found to be true with respect to Tunica, as illustrated by the case study presented in chapters 5-9. Knowing this, however, would not have been possible if it weren’t for the emergent research process—guided by the PSIA framework and a realist philosophy— adopted for this study. That open line of inquiry enabled me to unearth and tease out the complex interactions, necessary relations, and contingent conditions at work in Tunica and elsewhere (e.g., DeSoto County; Massey and Meegan 1985).
10.1.1 THE PROBLEM
The prior discussion suggests that where gaming has been adopted as an economic development strategy, seemingly consensus-based, it would be a mistake to assume a lack of contention or residual discord among the host community population,
287 particularly with respect to the moral legitimacy of the industry. Yet, there is a lack of scientific research on the moral aspects of gambling policy, to the extent that “arguments based on the moral premise are often ignored by gambling proponents and society as a whole” (Lindaman 2002: 39). Therefore, an economistic viewpoint of gaming tends to dominate even where moral objections are clear. This is not only true with respect to local elites and industry proponents selling the industry as economic development, but has become the dominant perspective within American society (e.g., Smith 2000). The same can be said of the distribution of benefits and the success of the endeavor.
The success of casino gaming (i.e., from the perspective of policy rather than that of the industry) is typically measured according to standard aggregate indicators associated with growth in tourism and economic development around those activities.
This reflects the nascent emphasis on service rather than producer goods around the nation and the focus on the maximization of associated profits to the community, to the detriment of moral and social consequence (Deitrick et al. 1999; Fainstein and Gladstone
1999). This is not to suggest that social outcomes associated with moral concerns fail to be considered (e.g., crime and addiction) when weighing the impacts of casino development in a cost/benefit framework. Quite the contrary. My argument here is that moral factors (e.g., religious beliefs) are often viewed as adoption determinants (Mooney and Lee 1995, 2000; Wright et al. 1987), but they fail to be considered as determinants of impacts of casino gaming in a place.
The relevance of moral concerns to residents is for the most part dismissed as a determinant of potential economic change once casino development has taken place. Yet, those values and concerns have not disappeared and in many instances remain strong—
288 “the values of the prevailing religious culture appear quite resistant to any sudden modification from changing economic conditions” (Fairbanks 1977: 417). In that respect, local cultural interests are not given full or adequate consideration in the process of determining gaming impacts (Fainstein and Gladstone 1999). Those perspectives are marginalized further within the policy arena, as is the crucial role they may play in determining outcomes (Moser and McIlwaine 2001). My goal in the remainder of this chapter is to consider cultural factors and the perspective of the poor.
10.2 CULTURE AS A CAUSAL MECHANISM
Culture-type models of poverty (e.g., culture of poverty and urban underclass) inevitably treat the behaviors of the poor as core beliefs that determine the way they view and imbibe the untenable situations in which they find themselves and the manner in which they cope with inhibiting anxieties induced by feelings of helplessness (Devereaux
1949; Reith 1999). While those models contribute something to our understanding of the persistently poor, they provide only piecemeal and stereotypical explanations for actions that inevitably appear as irresponsible or irrational behaviors to those whose life circumstances have not placed them in similar situations. They do not get at the cultural core of poverty, that is, the complex of material and nonmaterial cultural elements that are defined by a constellation of social and political features closely related to economic arrangements (Steward 1955). For many, one of those nonmaterial cultural elements is religion, which is not only impacted by, but impacts upon, economic arrangements at a variety of scales (e.g., individual and society).
289 10.2.1 POVERTY CULTURE VS RELIGIOUS CULTURE
When it is recognized that different groups of people in a society or portions of a group differ culturally to varying degrees, those differences are often referred to as stereotypes or perceptions. Perceptions and stereotypes are ideological words that similarly obscure the behavioral differences among groups and the social and class cleavages that result. Since World War II, these have been found to be increasingly tied to religion (Carmines and Layman 1997). When such differences transcend into economic behavior , they can result in very real costs that do not necessarily entail prejudice or feelings of animosity (Sowell 1994). This interpretation gives value to cultural elements such as religion in and of itself, making it conducive to the study of economics, which is “a study of cause and effect, not intentions and hopes” (Sowell
1994: 114). Thus, unfounded perceptions and stereotypes can be just as damaging as discrimination and segregation and are equally important aspects of social and economic reality for those of certain groups, and therefore should be analyzed as such.
In studying the development of the casino industry in Tunica and its impacts, culture of poverty stereotypes emerged, characterized most by differences in perceptions of the relationships among religious, employment, and educational factors. For instance, a common theme emerged from interviews and purposive conversations with community leaders, which included politicians, business owners, the landed elite, and public service administrators. The theme was this: that the casinos have created so many jobs that anyone who wants a job could have one, but a certain element of the population does not want to work and does not value education, thereby making it difficult to further
290 eradicate poverty in the county (Field Notes A/B/D 2001-2003). Similar sentiment has been captured in the popular media ( Mississippi Monte Carlo 1996: 6):
In the face of persistent unemployment, those who are well- off continue to insist that “there is a job for everyone who wants one”; but their emphasis has begun to fall on the second clause, so that an observation that once seemed to express relief and celebration now suggests exasperation and disgust. One woman we talked to expressed this bluntly, complaining, “You could put a factory in some people’s back yard and they still wouldn’t work.”
Derrick Crawford, the county’s director of human services finds this view unfair. He points out that one kind of employer cannot possibly suit every potential employee, and that for religious reasons alone many of Tunica’s blacks would rather be unemployed than work in a casino. Still, like many others, he ultimately lays the blame on what is most often called the “lack of work ethic”— meaning that many Tunicans make poor employees because they haven’t been conditioned to take a job seriously.
In response, the position expressed by those within the poverty population through focus group participation was that (Field Notes D 2003):
1. Many within the community have strong religious objections to the act of gambling and gambling’s influence on society that have left them unwilling to accept employment within the industry, despite the alternatives (e.g., unemployment).
2. That the majority of those who have sought work in casino establishments (i.e., casino, hotel, or restaurant) have very limited skills and are only able to obtain the lowest paying jobs, most of which are part-time and subject to seasonal fluctuations (e.g., housekeeping, valet).
3. The fact that most of the population has limited skills as well as a low level of education does not reflect a lack of perceived value for those things on the part of the poor, but rather represents broader social ills, such as a lack of investment in the quality of public education, a history of sharecropping and tenant farming that tied people to the land and supported only a low level of education, and a history of racial discrimination that limited educational opportunities for the majority black population.
291 Such claims as expressed by community leaders, however, cannot be ignored based on that response. To automatically accept the opposite a priori; to say that a group or those in a group are not adverse to work or education, and to lay blame for that perception on other stereotypes or perceptions, like that associated with southern white defensiveness or discrimination, would equally be a mistake. Not all adverse characterizations can be condemned just because they are adverse. If facts are not available in support of either/or, then all characterizations remain unfounded. Having said that, it is not my intention to challenge or disprove the existence of that certain element , but rather to give validity to religion as one causal factor for some lumped into that category. This suggests that understanding the economic impacts of casino development for the poverty population requires recognition of and knowledge about intervening socio-cultural factors and the answering of associated questions. For example, what is the relationship between religious or moral objection to casino gaming and the likelihood of employment in the gaming industry?
The problem with answering that question in a credible way is that although many facts have already been presented that lend credence to the perspective articulated by the poor, a causative link to employment has yet to be made. That is, although there is widespread recognition that religion is a major factor in the lives of the poor and that it represents moral conflict for many where the adoption of gaming is concerned; causation and morality are typically treated as separate when assessing impacts. Moral issues, such as those associated with religion, are no longer viewed as relevant causal forces or agents with regard to the direct effects of gaming and are thereby left out of analyses of economic impacts such as employment.
292 This is not to suggest that the issue of morality is lost altogether. For example, there remains recognition that causal relationships likely exist with respect to indirect or induced economic effects, such as the loss of jobs stemming from pathological gambling.
Yet, as noted previously, causation with respect to such assumed relationships is difficult to prove. More relevant to this discussion is that such a scenario has nothing to do with the willingness of those in that group to take a job in the casinos in the first place. What it raises, however, is the difference in the lived experiences of the poor where moral issues associated with gaming are concerned. That difference can be expressed via what is referred to as lived religion (Schweiger in Mathews et al. 1998) . Lived religion, defined in reference to the study context, asks: What are the cognitive structures associated with religion that create tension and conflict with regard to behavioral responses to change, such as the availability of casino jobs? Any attempt to answer this question and to understand how the answer may differ among or within groups in the
Tunica area first requires an understanding of the substance and nature of African
American religious culture in the South.
10.3 RELIGION IN THE SOUTH
Religion and American southern culture go hand in hand (e.g., Boles 1994;
Harvey 1997; Hill 1983, 1999). As one social historian noted (Mathews in Mathews et al. 1998: 147): “religion and the American South belong together—literature, memory, stereotype, and public opinion agree on this much even if historians have not convincingly explained why.” Implicit in that Southernness of religion is the distinct relationship between race and faith. A substantial body of literature is dedicated to
293 understanding the two, particularly as this issue relates to southern African American religion (e.g., Harrell 1971; Levine 1978; Raboteau 1978), which is thought to be rather complex. Historically, the belief was that “God, and Negroes and Jesus and sin and salvation were baled up together” (Smith in Mathews et al. 1998: 163). Boles pointed out
(in Mathews et al. 1998) that this is tied to the notion that God is involved in creating and determining the outcome of dilemma faced by blacks and other disempowered individuals in the South while at the same time offering a sense of empowerment (173):
[Religion] provided a sense of community and an arena for spiritual growth for two large groups otherwise left out of southern institutional and organizational life. To a degree no where else in contemporary society, women and blacks were incorporated into the governance structure of local evangelical congregations and found there a sense of moral worth and empowerment unique in southern society.
Boles went on to note that although poor whites of the South also found a sense of agency and self-worth in the church, religion became a central aspect of black culture because, unlike whites, blacks had little else by way of institutional identification.
The legacy of that culture of religion and associated racial differences is evident in contemporary society by conventional indicators that suggest that blacks are more religious than whites from comparable backgrounds (Levin et al. 1994). Within that population women demonstrate higher levels of religiosity than do men, as do
Southerners and those living in rural areas than elsewhere. Further, religiosity among
African Americans has been found to increase with age (Taylor 1986, 1988). Different dimensions of that religiosity (Levin et al. 1994) have also been shown, including: organizational (e.g., congregational participation), non-organizational (e.g., Bible study), and subjective religiosity (e.g., strength of personal religious identity).
294 More substantively, Ellison and Sherkat (1995) found that the rural southern church serves a central and multifunctional purpose in black communities such that the church becomes a semi-voluntary institution that reflects the behavioral norms and expectations of that community. Those norms and expectations include an emphasis on social network ties and family relationships, personal spiritual concerns, and cultural traditions (Ellison and Sherkat 1990; Mutran 1985), for which African Americans show overwhelming respect (Taylor et al. 1987). Thus, through history, most southern blacks have come to view religion as essential to their social and personal lives (Nelson and
Nelson 1975).
The impact of this thinking comes in the form of social support, status, identity, and self-esteem (Hughes and Demo 1989; Moore 1991). The latter is particularly true where greater levels of deprivation exist and for longer periods of time (Manuel 1988), such as with persistent poverty. Chronic life stressors drain individual psychological and social resources that might otherwise be used to cope (Kessler et al. 1985; Lin and Ensel
1989). In that case, the impact of southern African American religion is largely one of psychological or subjective well-being with respect to feeling a sense of self-worth and the perceived ability to be in control of one’s affairs, both in the present and in the afterlife (Ellison 1993; Ellison and Gay 1990; Krause and Tran 1989).
This discussion suggests that from an analytical perspective southern African
American religion can be distinguished by “culturally produced constitutive rules, the emergently material social relations to which those rules give rise, and the situated behavior and self-understanding of actors operating within those rules and relations”
(Porpora 1993: 213). Put simply, religion shapes both thought and action, but the ability
295 to predict behavior based on the relationship between the two requires an understanding of the context within which an individual is operating. For a religious person, that context may not only include the here and now, but also that which relates to the afterworld. Thus, moving religion into the realm of economics is not straightforward, but it is necessary since it plays an important role in shaping behavior (Rupasingha and
Freshwater 1999).
10.4 ECONOMICS AND RELIGION
The link between religion and economic behavior has only been given serious attention in the economic literature since the 1970s (Hirschleifer 1985). The studies run along three strands of inquiry (Iannaccone 1998): the interpretation of religious behavior from an economic perspective, the economic consequences of religion, and religious economics, which is mainly comprised of evaluations of economic policy from the perspective of religion. The delay in giving adequate attention to those areas in economics can be attributed to a long line of political scientists and philosophers, including Karl Marx and David Hume, who argued that religious behavior was for the most part irrational behavior and therefore not conducive to or worthy of scientific inquiry (Iannaccone 1998).
This line of thinking has more recently been challenged by Iannaccone (1996) and others (i.e., following Adam Smith as explained in Anderson 1988), who view religious behavior as an instance of rational choice in the context of religion as a system of utility- maximizing rules. That is, religion can be defined as a shared set of beliefs or a belief system premised upon faith in supernatural forces that has direct economic implications
(e.g., voluntary community service, financial donations, subsidized education, etc.). In
296 that light, economic models can be extended or modified to address questions about belief systems, such as religion, and by extension, cultural morals, as well as explorations of how religion affects economic attitudes and activities. Most of the researchers who have attempted to do so have followed the work of Becker (1976) and Azzi and
Ehrenberg (1975).
Becker’s (1965) work is the seminal theoretical foundation for most contemporary economic analysis related to behavior (i.e., utility theory). Azzi and Ehrenberg’s (1975) study lays the basis for the interpretation of religious behavior from an economic perspective. These authors do so by elaborating on Becker’s framework in a way that allows for the examination of previously unexplained behavioral variation (Levi et al.
1990)––variation in religious participation by economic agents whose motives are defined as: salvation motive (i.e., afterlife consumption), consumptive motive, and social pressure motive. Their major finding was that all of the motives potentially yield immediate utility, but that the salvation motive was the dominant or primary motive for religious participation. Subsequent work concurs with Azzi and Ehrenberg’s finding that religious activity generates utility, but a mixed bag of motives drive the economic agent to act and they are not limited to the initial three (e.g., Sawkins et al. 1997; Ulbrich and
Wallace 1983).
For example, Iannaccone (1998) pointed out a range of utility pay-offs for religious activity beyond afterlife expectations, such as sense of purpose, moral instruction, group identity, social support, social status, and mutual aid. However, it is still the case that:
Economic models tend to undermine the presumed validity of these interpretations. (1489) ... Research has tended to
297 sidestep questions concerning the substance of religion…. It is not, as yet, clear how these broader conceptions can be captured with formal models. (1491)
Part of the problem is that data on religious participation are scarce, unreliable, and limited in terms of coverage while other aspects of religion are difficult to observe, let alone capture. Of the data that do exist, very little has been collected via government or funded research. Most religious data are collected by religious organizations, typically based on membership lists and their willing participation. In the case of religious data for
Tunica County, there is a comprehensive accounting of congregations and adherents (i.e., membership) based on religious bodies (e.g., Southern Baptist, Presbyterian, Catholic,
Black Baptist, etc.) for 1990 that stems from the Association of Statisticians of American
Religious Bodies. However, in 2000 most of the historically African American religious bodies failed to participate; therefore, no data exist that may be used in a comparative analysis for that population group.
Another issue is the tendency in economics to treat religious groups as homogeneous, while an extensive body of literature suggests clear characteristic differences. Some of those differences have already been noted with respect to race and geographic location. Other socio-demographic examples (e.g., differences based on gender, marital status, etc.) include the fact that in opposition to that commonly assumed, religious belief and activity do not have a tendency to drop off with income and for the most part are positively correlated with a rise in education (e.g., Chiswick 1983).
However, religious orientation varies with income, education, and orientation. There are also differences in participation levels and beliefs with respect to issues of morality and subjective well-being. Johnson and Meier (1990: 587) found that, in relation to
298 gambling, “only conservative ideology and Catholicism have significant impacts”––the former in opposition and the latter in support.
There also remains the issue of religion as a causal agent. Although religious effects have been shown to be sufficiently large and significant, many argue that spurious correlation makes causal impacts unattainable (Freeman 1986; Iannaccone 1998). Still, enough research demonstrates a strong relationship between religion and economic behavior to justify the assumption that religion has an effect on some behavioral outcomes in accordance with what is of optimal utility for the individual, such as earnings, education, and economic attitudes (Young 1997). This stresses the point that what is being measured is subjective rationality . Rationality is defined as (Stark and
Finke 2000: 86):
Within the limits of their [human beings] information and understanding, restricted by available options, guided by their preferences and tastes, humans attempt to make rational choices.
With this in mind, the following is an analysis of the subjective well-being of the poor with respect to the impact of casino gaming development on a number of living environments, with particular attention to the relationship of casino employment to perceptions of morality.
10.4 ANALYSIS OF SUBJECTIVE WELL-BEING
As discussed, extant research stresses the importance of religion for well-being, but suggests that its effects are not the same in all social contexts. That is, both personal characteristics and social factors moderate the relationship between the two and therefore the effects of religion on well-being may differ from one group to the next. This has been
299 shown to be true with regard to race, where blacks are more likely to report greater levels of quality of life in association with religiosity than whites. Further, those whose core belief system is set in spirituality or theodicy have a tendency to devalue the material world. Given that and the fact that perceptions of well-being are based on cognitive assessments of life circumstances rather than affective ones, it is possible that the elements of the material world are neither necessary nor sufficient in achieving subjective well-being, and thereby may be rejected altogether even in the face of poverty.
Yet, at the same time, it has been shown that life stressors, such as the living conditions and psychological aspects of poverty, may make people more vulnerable to temptation, leading them to partake in a world that they are supposed to reject. This sets up the potential for a number of contradictions when attempting to assess the relationship between religion and the impacts of the gaming industry. For instance, an individual may outright reject personal employment in the industry due to religious beliefs, but at the same time express an increase in social well-being due to the many jobs brought by gaming to their community. Likewise, one who has moral objections to gambling may accept a job in the industry, noting that it has led to an increase in personal well-being while also citing its negative impacts on the community and an associated decrease in social well-being.
These contradictions were found to be true in the case of Tunica, where seemingly polar responses were given to similar questions based on whether it was posed in reference to individual well-being or social well-being. In an attempt to impose some structure on those and similar findings, the following analysis employs correlation and multinomial logit regression analyses to the examination of the relationships between
300 moral concerns and perceived impacts of casinos on well-being. Data for this analysis were collected using the community survey discussed in chapter 6, which is available in
Appendix C.
10.4.1 LOGISTIC TRANSFORMATION
As mentioned, a multinomial logit analysis was employed to examine the perceived impacts of casino development on well-being, while considering the relationship of that outcome to the issues that rose around moral compromise, employment, and education. The dependent variable represents the overall conclusions regarding the impacts of gaming development for each subjective domain (i.e., environments). The explanatory variables are grouped into a number of categories: moral, which reflects the responses to questions pertaining to moral attitudes toward gaming and religious participation; economic, which relates to income levels and employment in the casino industry; and demographic (e.g., gender, age, and education level). Thus, the basic empirical model is of the form:
(1) P(Y j) = f ( Xmoral , X economic , X demographic , ε)
where Yj is the response to the question: “Overall, what is your conclusion regarding the impact of the gaming industry on your well being within each of the study environments?” For each environment, j = 0 (worse off), 1 (no different), or 2 (better off).
The moral variables include: a measure of involvement with a religious group, defined as either not involved, recently involved, or long-standing involvement; a dummy variable where 1 represents the respondent’s satisfaction with their level of education;
301 and a set of dummy variables that represent the respondent’s agreement with statements of morality in association with the gaming industry and work within it (i.e., it is an unacceptable industry in which to work, it is immoral but acceptable because it has provided jobs and income to the area, it is immoral and completely unacceptable). The economic variables are comprised of: monthly net income for the household, including that of respondent and other household members; and a dummy variable equal to 1 if the respondent was employed at the time of the survey. The demographic variables consist of: a dummy variable equal to one if the respondent is male; the respondent’s age in years; and the respondent’s level of educational attainment (not past the 8 th grade, some high school, GED, HS graduate, or some college). ε is a stochastic error term.
Following Nichols et al. (2001), equation (2) represents the general form of the multinomial logit model used to estimate equation (1) and equation (3), given the marginal effect or the marginal probability that Y = j, δj.
1 1 β x J β x (2) P(Y ) = ( e j ) / = 0^( e j ), j= 0…. J j t ∑ j t where j is the number of outcomes given in response to the impact questions (dependent variable), βj are the coefficients to be estimated, and X are the characteristics of the survey respondents or independent variables as described previously.
J (3) δj = ∂ Pj / ∂ xi = Pj [ β j - ∑ P k β k ] k =0 where Pj is the probability that Y = j, xi is the ith independent variable, and β j is the coefficient estimate from the multinomial logit model.
The results of the multinomial logit analysis, as presented in the form of equation
(3), are discussed in the next section. However, prior to discussion of those results, descriptive statistics for responses to a subset of the survey questions are given. The
302 selection of descriptives reveals a number of objective and subjective details with regard to the survey population, some of which reinforce the inherent contradictions of the perceived impacts of casino development on the well-being of the poverty population and the conditioning factors of those impacts, as suggested throughout this thesis.
10.4.1.1 DISCUSSION OF RESULTS
Among respondents, 98 percent identified themselves as black or African
American, with an average age of 37 years old. 32 More than one-third had an education level below the 9 th grade and 63 percent were unemployed. In relation to, and seemingly in support of, outsider opinion with regard to a lack of value for education on the part of the study population, among possible determinants for level of educational attainment, personal choice received the highest response rate. However, many elaborated on that fact by stating that their choice was based on the need to leave school to work in support of their family and more than half reported dissatisfaction with their current level of education.
Further, 43 percent felt that gaming was immoral, but okay in comparison to its income and employment benefits to the community. In fact, 25 percent reported a positive community impact specifically in association with jobs. Still, 27 percent felt that gaming was immoral and totally unacceptable. That factor was found to be correlated with unemployment as well as with both long-standing and recent involvement with a religious group. In addition, involvement with a religious group was found to be negatively correlated with work in the casino industry and satisfaction with one’s level of education. This offers some support to the claim that many among the poverty
303 population reject employment in the gaming industry due to religious beliefs and that they do value education, but have found themselves in life situations where they had to put something else first, such as family or income.
With regard to work and the ability to earn a living wage, 34 percent reported agriculture as the type of industry in which they regularly work, but this was also found to be positively correlated with current unemployment. Another 25 percent reported manufacturing as the industry in which they regularly work and 26 percent reported services related to the casino industry. This is supported by reports among the survey population that given their personal knowledge of those in their community who work in the gaming industry, most do so within the realm of housekeeping and food service occupations. Although this offers little by way of concrete evidence that casino jobs do not pay a living wage, it does lend support to the idea that few among the poverty population work in the casino industry. Those who do are in the lowest paying occupations. Further, 60 percent of survey respondents said they were no better off financially now than they had been in the past, 45 percent considered themselves poor and gave a definition of poverty in association with a lack of money, and 84 percent stated that they think about their financial situation constantly or often.
Hence, from the standpoint of the financial and work environments, it appears that casino gaming development has provided the poverty population with limited relief, especially where subjective well-being is concerned. This was similarly indicated with regard to other dimensions of well-being. In terms of the health and nutritional environment, 31 percent had no insurance whatsoever and 52 percent said they worried about their health. With regard to the living environment, 52 percent reported that their
32 See Appendix D for select frequency tables.
304 living conditions had gotten better over the last ten years, yet 82 percent stated that they think about their future living conditions constantly or often. Overall, 37 percent reported a level of personal well-being, most commonly defined by respondents in association with the term happiness, as “not very well off.” Additionally, 35 percent of respondents claimed that the casinos had had no impact on them at all, while at the same time most reported some form of betterment to the community and social environment, although that was ill-defined beyond the notion that casinos had provided jobs for many persons.
The multinomial logit analysis provides further detail on the overall impact of casino development on well-being and the association of that outcome to religion and employment. Tables 10.1 and 10.2 provide descriptives and parameter estimates for the work environment effects model. Table 10.2 can be interpreted as follows:
Where Exp(B) is a measure of relationship (effect size => 1), and Sig. is a measure of significance (<.05), such as with the response “a long-standing association with a religious organization” [CHG5=2], the long-standing association with a religious organization increases the odds that the work environment is somewhat better or significantly better since the incision of the gaming industry into the area.
Further, where Exp(B) is greatest for all significant factors and covariates, the effect is greatest among all variables. Given the parameter estimates, this means that religion
[CHG5A-2] has the greatest effect in determining that the impact of the gaming industry on the work environment is somewhat or significantly better. Religion is followed by being a female [SEX-0] and holding the moral stance that the gaming industry is immoral but acceptable because it has provided jobs and income for the area [MC8F-0].
305 Table 10.1 Descriptives for the Work Environment Effects Model
Marginal Question Response Category N Percentage 8.08: overall conclusion regarding the impact of the gaming industry on your significantly or [WB4=0] 52 24.76 well being within your work somewhat worse environment? no different [WB4=1] 70 33.33 somewhat better or significantly [WB4=2] 88 41.90 better
5.05: Are you/have you been involved not involved [CHG5A=0] 97 46.19 with a religious group? involved [CHG5A=1] 42 20.00 recently involved long [CHG5A=2] 71 33.81 standing 7.03: Are you satisfied with your no [SAT7A=0] 142 67.62 educational level? yes [SAT7A=1] 68 32.38 8.03: How do you feel about the local gaming industry: it is an unacceptable disagree [MC8E=0] 190 90.48 industry in which to work? agree [MC8E=1] 20 9.52 8.03: How do you feel about the local gaming industry: it is immoral, but disagree [MC8F=0] 119 56.67 acceptable because it has provided jobs and income for the area? agree [MC8F=1] 91 43.33 8.03: How do you feel about the local gaming industry: it is immoral and disagree [MC8G=0] 151 71.90 completely unacceptable? agree [MC8G=1] 59 28.10 4.01: Are you currently employed? no [EMP=0] 131 62.38 yes [EMP=1] 79 37.62 1.05: What is your gender? female [SEX=0] 108 51.43 male [SEX=1] 102 48.57 4.13: What is your level of educational not past 8th [EDUC=0] 73 34.76 attainment? grade have GED [EDUC=1] 19 9.05 some hs [EDUC=2] 30 14.29 hs grad [EDUC=3] 69 32.86 some college [EDUC=4] 16 7.62 college degree [EDUC=5] 3 1.43 Valid 210 100.00 Missing 30 Total 240 Subpopulation 209
306 Table 10.2 Parameter Estimates for the Work Environment Effects Model
8.08 overall conclusion regarding the impact of the gaming industry on your well being within your work environment?
somewhat 95% Confidence Interval for Exp(B) better or Exp(B) Sig. significantly Lower Bound Upper Bound better AGE 0.977 0.204 0.943 1.013 THINC 1.000 0.398 1.000 1.001 [CHG5A=0] 0.922 0.110 0.813 5.923 [CHG5A=1] 1.604 0.109 0.807 8.404 [CHG5A=2] 2.604 0.020 0.834 5.923 [SAT7A=0] 0.938 0.000 0.353 2.491 [SAT7A=1] 1.046 0.938 0.243 1.463 [MC8E=0] 0.461 0.238 0.128 1.669 [MC8E=1] 0.061 0.000 0.015 0.255 [MC8F=0] 1.073 0.878 0.437 2.633 [MC8F=1] 1.216 0.007 0.450 3.288 [MC8G=0] 0.061 0.471 0.015 0.255 [MC8G=1] 0.129 0.000 0.045 0.374 [EMP=0] 0.802 0.618 0.338 1.905 [EMP=1] 1.216 0.161 0.450 3.288 [SEX=0] 1.304 0.045 0.587 2.894 [SEX=1] 1.594 0.234 0.740 3.434 [EDUC=0] 0.421 0.570 0.021 8.333 [EDUC=1] 0.505 0.665 0.023 11.069 [EDUC=2] 0.623 0.766 0.028 14.012 [EDUC=3] 0.773 0.865 0.040 14.918 [EDUC=4] 2.408 0.568 0.118 49.222 l [EDUC=5] 2.613 0.522 0.138 49.365
This analysis lends support to previous indications in this study. Those among the poverty population may find themselves in conflict between individual and community assessments of well-being. That assessment is further supported by the fact that agreement with the statements, “the gaming industry is an unacceptable industry in which to work” [MC8E=1] and “the gaming industry is immoral and completely unacceptable”
[MC8G=1]” were found to be significant, but with a minimal effect (.061 and .129, respectively). This indicates that many in the poverty population may abstain from
307 employment in the casino industry based on moral opposition while also espousing the industry’s positive impacts given increased employment opportunities.
10.5 CHAPTER SUMMARY
This analysis supports the notion that moral factors driven by religious beliefs matter in determining the economic and social outcomes of casino development on the study population. This is particularly true in association with jobs, which are believed to be the greatest private benefit derived from casino development, and therefore the most likely to have a positive impact on poverty. Thus, internal validity can be attached to the claim that the moral position of the poor may keep some from seeking employment in the casino industry. It also highlights the conflict presented for those individuals when assessing individual casino impacts versus individual impacts. Overall, this analysis, together with other indicators extracted from the survey data, illustrates the importance of considering (1) the perspective of the poverty population and (2) non-economic factors that may have economic outcomes, when conducting impact analysis.
10.6 CHAPTER REFERENCES
Azzi, C. and R. Ehrenberg. 1975. Household Allocation of Time and Church Attendance. Journal of Political Economy. 83: 27-53.
Becker, G. 1976. The Economic Approach to Human Behavior. Chicago: University of Chicago Press.
Becker, G. 1965. A Theory of Allocation of Time. Economic Journal. 75: 493-517.
Boles, J. 1994. The Irony of Southern Religion. New York: Peter Lang.
308 Carmines, E. and G. Layman. 1997. Issue Evolution in Postwar American Politics: Old Certainties and Fresh Tensions. In B. Shafer, ed. Present Discontents. Chatham: Chatham House. Pp. 64-99.
Chiswick, B. 1983. The Earnings and Human Capital of American Jews. The Journal of Human Resources. 18(3): 313-336.
Deitrick, S., et al. 1999. Riverboat Gambling, Tourism, and Economic Development. In D. Judd and S. Fainstein, eds. The Tourist City. New Haven: Yale University Press. Pp. 233-244.
Devereaux, E. 1949. Gambling and the Social Structure. Unpublished Ph.D. thesis, Harvard University.
Ellison, C. 1993. Religious Involvement and Self-Perceptions Among Black Americans. Social Forces. 71: 1027-1055.
Ellison, C. and D. Gay. 1990. Region, Religious Commitment, and Life Satisfaction Among Black Americans. Sociological Quarterly. 31: 123-147.
Ellison, C. and D. Sherkat. 1990. Patterns of Religious Mobility Among Black Americans. Sociological Quarterly. 31: 551-568.
Ellison, C. and D. Sherkat. 1995. The ‘Semi-Involuntary Institution’ Revisited: Regional Variations in Church Participation Among Black Americans. Social Forces. 73: 1415-1437.
Fainstein, S. and D. Gladstone. 1999. Evaluating Urban Tourism. In D. Judd and S. Fainstein, eds. The Tourist City. New Haven: Yale University Press. Pp. 21-34.
Fairbanks, D. 1977. Religious Forces and ‘Morality’ Policies in the American States. Western Political Quarterly. 30: 411-417.
Felsenstein, D., et al. 1999. Casino Gambling as Local Growth Generation: Playing the Economic Development Game in Reverse. Journal of Urban Affairs. 21(4): 409- 421.
Freeman, R. 1986. Who Escapes? The Relation of Churchgoing and Other Background Factors to the Socioeconomic Performance of Black Male Youths from Inner-City Tracts. In R. Freeman and H. Holzer, eds. The Black Youth Employment Crisis. Chicago: University of Chicago Press. Pp. 353-376.
Harrell, D. 1971. White Sects and Black Men in the Recent South. Nashville: Vanderbilt University Press.
309 Harvey, D. 1993. Potter Addition: Poverty, Family, and Kinship in a Heartland Community. Aldine de Gruyter.
Harvey, P. 1997. Redeeming the South: Religious Cultures and Racial Identities Among Southern Baptists 1865-1925. Chapel Hill: University of North Carolina Press.
Hill, S. 1999. Southern Churches in Crisis Revisited. Tuscaloosa: University of Alabama Press.
Hill, S. 1983. Religion in the Southern States: A Historical Study. Macon: Mercer University Press.
Hirschleifer, J. 1985. The Expanding Domain of Economics. American Economic Review. 75: 53-68.
Hughes, M. and D. Demo. 1989. Self-Perceptions of Black Americans: Self-esteem and Personal Efficacy. American Journal of Sociology. 95: 132-159.
Hunter, J. 1994. Before the Shooting Begins: Searching for Democracy in America’s Culture War. New York: Free Press.
Hutcheson, J. and G. Taylor. 1973. Religious Variables, Political System Characteristics and Policy Outputs in the American States. American Journal of Political Science. 17: 414-421.
Iannaccone, L. 1996. Religion, Values, and Behavioral Constraint . Prepared for the Symposium on the Economic Analysis of Social Behavior. Chicago, December Iannaccone, L. 1996. Religion, Values, and Behavioral Constraint . Prepared for the Symposium on the Economic Analysis of Social Behavior. Chicago, December.
Iannaccone, L. 1998. Introduction to the Economics of Religion. Journal of Economic Literature. 36: 1465-1496.
Johnson, C. and K. Meier. 1990. The Wages of Sin: Taxing America’s Legal Vices. The Western Political Quarterly. 43(3): 577-595.
Kessler, R., R Price, and C. Wortman. 1985. Social Factors in Psychopathology: Stress, Social Support, and Coping Processes. Annual Review of Psychology. 36: 351- 372.
Kindt, J. 1998. Follow the Money: Gambling,Ethics, and Subpoenas. Annals of the American Academy of Political and Social Science. 556: 85-97.
Krause, N. and T. Tran. 1989. Stress and Religious Involvement Among Older Blacks. Journal of Gerontology: Social Sciences. 44: 4-13.
310
Lehne, R. 1986. Casino Policy. New Brunswick: Rutgers University Press.
Levi, M., K. Cook, J. O’Brien, and H. Faye. 1990. Introduction. In. K. Cook and M. Levi, eds. The Limits of Rationality. Chicago: University of Chicago Press. Pp. 1-16.
Levin, J., R. Taylor, and L. Chatters. 1994. Race and Gender Differences in Religiosity Among Older Adults: Findings from Four National Surveys. Journal of Gerontology: Social Sciences. 49.
Levine, L. 1978. Black Culture and Black Consciousness: Afro-American Folk Thought from Slavery to Freedom. New York: Oxford University Press.
Lin, N. and W. Ensel. 1989. Life Stress and Health: Stressors and Resources. American Sociological Review. 54: 382-389.
Lindaman, K. 2002. Turning the Token: The Local Politics of Gambling. Published Dissertation. Department of Political Science, University of Kansas.
Manuel, R. 1988. the Demography of Older Blacks in the United States. In J. Jackson ed. The Black American Elderly: Research on Physical and Psychosocial Health. New York: Springer Publishing Company. Pgs. 25-49.
Massey, D. and R. Meegan. 1985. Introduction: The Debate. In D. Massey and R. Meegan, eds. Politics and Method: Contrasting Studies in Industrial Geography. London: Methuen. Pp. 1-12.
Mathews, D., S. Hill, B. Schweiger, and J. Boles. 1998. Forum: Southern Religion. Religion and American Culture. 8(2): 147-177.
Meier, K. 1994. The Politics of Sin: Drugs, Alcohol, and Public Policy. Armonk NY: M.E. Sharpe, Inc.
Mississippi Monte Carlo . 1996 January. The Atlantic. Available online at
Mooney, C. 2001. The Public Clash of Private Values: The Politics of Morality Policy. In C. Mooney, ed. The Public Clash of Private Values. New York: Chatham House.
Mooney, C. and M. Lee. 1995. Legislative Morality in the American States: The Case of Pre-Roe Abortion Regulation Reform. American Journal of Political Science. 39(3): 599-627.
311 Mooney, C. and M. Lee. 2000. The Influence of Values on Consensus and Contentious Morality Policy: U.S. Death Penalty Reform, 1956-82. The Journal of Politics. 62(1): 223-239.
Moore, T. 1991. The African-American Church: A Source of Empowerment, Mutual Help, and Social Change. Prevention in Human Services. 10: 147-167.
Morgan, D. and K. Meier. 1980. Politics and Morality: The Effect of Religion on Referenda Voting. Social Science Quarterly. 61(1): 144-148.
Moser, C. and M. McIlwaine. 2001. Violence and Social Capital in Poor Urban Communities: Perspectives from Columbia and Guatemala. Journal of International Development. 13: 965-984.
Mutran, E. 1985. Intergenerational Family Support Among Blacks and Whites: Responses to Culture or to Socioeconomic Differences. Journal of Gerontology. 40: 382-389.
Nelson, H. and A. Nelson. 1975. Black Church in the Sixties. Lexington: The University Press of Kentucky.
Pierce, P. and D. Miller. 1999. Variations in the Diffusion of State Lottery Adoptions: How Revenue Dedication Change Morality Politics. Policy Studies Journal. 27(4): 696-706.
Porpora, D. 1993. Cultural Rules and Material Relations. Sociological Theory. 11(2): 212-229.
Raboteau, A. 1978. Slave Religion: The “Invisible Institution” in the Antebellum South. New York: Oxford University Press.
Reith, G. 1999. The Age of Chance: Gambling in Western Culture. London: Routledge.
Rupasingha, A. and D. Freshwater. 1999. Economics of Religious Participation in the Rural South. The Review of Regional Studies. 29(3): 256-271.
Sawkins, J., P. Seaman, H. Williams. 1997. Church Attendance in Great Britain: An Ordered Logit Approach. Applied Economics. 29: 125-134.
Smith, K. 2000 April. Dirty Minds and Muddy Thoughts: The Pathologies of Morality Politics Theory. Paper presented at the annual meeting of the Midwest Political Science Association, Chicago.
Sowell, T. 1994. Race and Culture: A World View. New York: Basic Books.
312 Starke, R. and R. Finke. 2000. Acts of Faith: Explaining the Human Side of Religion. Berkeley: University of California Press.
Steward, J. 1955. Theory and Application in Social Science. Ethnohistory. 2(4): 292- 302.
Studler, D. 2001. What Constitutes Morality Policy: A Cross-National Analysis. In C. Mooney, ed. The Public Clash of Private Values. New York: Chatham House.
Tatalovich, R. and B. Daynes. 1988. Conclusion: Social Regulatory Policymaking. In R. Tatalovich and B. Daynes, ed. Social Regulatory Policymaking—Moral Controversies in American Politics. Boulder: Westview.
Taylor, R. 1986. Religious Participation Among Elderly Blacks. The Gerontologist. 26: 630-636.
Taylor, R. 1988. Structural Determinants of Religious Participation Among Black Americans. Review of Religious Research. 30: 114-125.
Taylor, R., M. Thornton, and L. Chatters. 1987. Black Americans’ Perceptions of the Sociohistorical Role of the Church. Journal of Black Studies. 18: 123-138.
Ulbrich, H. and M. Wallace. 1983. Church Attendance, Age, and Belief in the Afterlife: Some Additional Evidence. Atlantic Economic Journal. 11: 44-51.
Williams, S. 1981. Realism, Marxism and Human Geography. Antipode. 13(2): 31-38.
Wilson, J. 1993. Religion and Revolution in American History. Journal of Interdisciplinary History. 23(3): 597-613.
Wright, G., et al. 1987. Public Opinion and Policy Liberalism in the American States. American Journal of Political Science. 31: 980-1001.
Young, L., ed. 1997. Rational Choice Theory and Religion: Summary and Assessment. New York: Routledge.
313 CHAPTER 11
SUMMARY CONCLUSION
If you must play, decide upon three things at the start: the rules of the game, the stakes, and the quitting time. ~Chinese Proverb
Casino gaming as a means of economic development in distressed areas has been extensive over the last one and one half decades. Its popularity resonates in its promise as a direct source of job creation and tax revenue, in addition to the ripple effect of initial increases in jobs and income to area-wide development. Despite a growing body of literature about its impacts, both positive and negative, prior to this study the distributional impacts of casino gaming as an economic development strategy had yet to be analyzed in a comprehensive manner, particularly with respect to the poverty population. The research described here achieved this by presenting a critical case, that is, an assessment of the effects of an extraordinarily successful casino development initiative from the traditional economic standpoint, on a place with the most extreme poverty conditions in the United States.
In so doing, a methodological framework for the study of distributional impacts stemming from economic and social reform (PSIA) was applied to the United States for the first time. This framework was created by the World Bank after decades of experience in developing nations. This application was founded on the methodological objectives of building on earlier experiences, strengthening analytical capacity, maintaining flexibility and openness with respect to data, tools, and methods, and the associated need to increase transparency in the links among poverty, economy, and policy. Yet, my overarching argument throughout has been geared toward the larger
314 picture of ontological, epistemological, and more critically, methodological understanding.
I believe that looking at ontological and epistemological issues at an abstract level is essential to an understanding of the complex issues behind r esearch strategies.
However, the tendency to get stuck in philosophical debate does not help us to practice social science research. In this dissertation I used my own stance on these issues
(ontology and epistemology) as an example of how realist methodology can be more concretely understood and applied to the practice of social science research within the context of geography. In so doing, I acknowledged that this undoubtedly comes with its own set of difficulties in conducting research, understanding the results, and applying learning to everyday practice.
For example, as a means to avoid methodological foreclosure realist researchers tend to favor an emergent research design such as the adoption of a realist philosophy tied to a research methodology that is an emergent process, such as PSIA. Doing so makes moving from philosophy to practice seem rather complicated and may prevent others from seeking to do the same. It may also suggest to critics of that research that the methodological approach is ‘untidy’ due to a lack of preparation in research design or to a lack of methodological rigor. On the contrary, realist research design emerges from a considerable read of the methodological literature, but the various twists and turns of the research process create difficulty in the reporting of the study (e.g., explanation of the research design and interpretation of findings).
This study takes the reader on a journey of one realist’s experience, step by step, in order to dispel those beliefs regarding preparation and rigor, but more importantly to
315 seek some degree of transparency with respect to the ‘process.’ The first two chapters presented the ontological and epistemological stance, specification of the problem and research questions, the research process in abstract form, and the ultimate research design, including data collection and analysis. The remaining chapters (3–10) were an expression of the intellectual process associated with the emergent research design.
Telling the story, documenting the case study, was not just an exercise in ‘storytelling.’ It was aimed at helping the reader to think more critically about research strategy based on the logic that ‘unpacking’ the depth and scope of causal mechanisms and abstract relations associated with poverty and economic development would demonstrate both the necessity and potential difficulty of doing so. I elaborate further on both that ‘necessity’ and ‘potential difficulty’ in the remainder of this chapter.
11.1 NECESSITY
What did we learn that we didn’t already know (or what did we learn about what we thought we knew based on anecdotal evidence)? In the case of Tunica, did economic growth stemming from casino industry development lead to poverty alleviation? What my research suggests is that the industry alone cannot alleviate poverty. The question posed as ‘cause and effect’ is inappropriate given that the result is the outcome of a process. The industry is a success in terms of an economic development strategy, but the forces that determine the poverty outcome in the Tunica area are less economic than they are political, social, and cultural forces that characterize the place and pre-date casino gaming development. The ways in which these things manifest at present include:
Religious objections to gambling on the part of poor that results in their failure to seek employment in the industry;
316 Persistent racial and increasing class discrimination that emerges in the political sphere in terms of where and how much of gaming industry revenue is invested; The denial that these things still exist according to the local elite and mass media; and The failure of researchers to give consideration to non-economic factors (i.e., that may have economic outcomes) in a meaningful way.
In other words, this study challenges the ‘miracle’ (i.e., understood mainly as economic) by presenting evidence that a history of social, political, cultural, and economic relationships associated with racial discrimination, class elitism, and lack of investment in human capital were the forces that placed Tunica in the position of being the poorest in the US in the first place and are what perpetuates that poverty for many persons today. Specifically, in the moment it appears that the poor are benefiting to some extent from the success of the gaming industry, but in many ways the economic growth and development associated with that development have set the wheels in motion for another round of discrimination, class elitism, and lack of investment in human capital.
Clearly, the gaming industry has served to reinstate the landed elite to the position of power. The elite have not let go of the past where the ‘planter mentality’ is concerned.
It has also introduced a new population into the community (mainly African American, but in the last few years the draw has been Latin American) who discriminate against the pre-casino black residents on the basis of class elitism and cultural differences, and who compete with existing residents for access to the benefits of investments in community development (e.g., new housing, schools, etc.). Given this context, one has to question whether the poor will be better or worse off in the long run: will the cycle of persistent poverty in the Tunica area break or will it continue to be reinforced?
The findings from this research indicate that so far the condition of poverty has for the most part been reinforced. At the same time, there is also significant evidence to
317 suggest that there is hope—with time, the objective circumstances for the next generation of ‘would-be’ poor will be very different. Consider the moral dilemma. Setting the aforementioned issues aside (e.g., class relations), global investments (e.g., infrastructure, training and education, etc.) aimed at maintaining the casino industry and further growing the area as a resort destination may in the end achieve the goals of industry diversification and increased skills within the resident labor force. This would afford those who object to gambling the opportunity to seek employment in an acceptable industry.
My expression of hope for the seemingly hopeless in Tunica is generalizable in that it is inferred from the realist ontology that the nature of real objects in the present moment may constrain and enable what can happen, but they do not determine what will happen. This suggests that powers or forces exist that are in the moment unexercised
(totally or to their fullest). Therefore, what has happened in the present or has been known to happen in the past does not exhaust what could have happened or what will happen in the future (Sayer 2000: 12):
Realist ontology therefore makes it possible to understand how we could be or become many things which currently we are not; the unemployed could become employed, the ignorant could become knowledgeable, and so on.
What does this suggest for policy? Simply put, it affirms what we already know, but seemingly deny—there is no absolute prescription for change, at least not in the case of persistent poverty. You can have an effect on the ‘structure’, but you cannot pre- determine the outcome. Poverty processes do not happen in the abstract. In other words, restating an illustration of this thought process offered by Sayer (1992) to fit the subject matter: economic development has the ( necessary ) causal power to alleviate poverty, yet
318 it does not do so anywhere and everywhere. Whether it does so depends on ( contingent ) circumstances; it depends on the presence of the right conditions for doing so in the context of the place and the larger whole of which that the place is a part (e.g., region).
What does this suggest for those seeking to inform policy? Is our understanding of poverty (i.e., poverty and the means by which to alleviate it) merely a matter of epistemological and methodological debate or are there real-world consequences? I argue yes to the latter by placing that question in the current reference frame. The failure to assess socio-cultural content and to do so in each instance ( context ) increases the potential for error in the measurement of casino development benefits in a place and puts the ability to determine the distribution of those benefits to various groups within the host community population at risk. Reintroducing cultural and other context-based factors as influencing the impacts of casinos makes it necessary to view gaming development outcomes through more than one lens. It necessitates looking beyond the reference frame of the local elite and others seeking to maximize economic growth (e.g., policymakers and players within the industry), to validating belief structures and the overall perception of the poor (i.e., with respect to poverty, well-being, and gambling), making the analysis of gaming impacts on distressed areas a more complex and holistic endeavor than has typically been undertaken.
There is a need for a more open, yet sophisticated approach to understanding poverty and the means to alleviate it given the explicit context in which poverty is situated. The PSIA framework, which consists of a number of core principles for conducting poverty research, offers a means for meeting that need. As applied to the current study, those principles consist of (in no particular order) the following:
319 Devote effort to identifying and understanding the circumstances of marginalized and excluded groups; Stress outcomes for poor people, which can only be understood by working with poor people themselves; Emphasize macro-micro linkages with respect to those outcomes—analysis should be done at a variety of scales; Do not follow PSIA as a “strait-jacket” approach—it should be applied flexibly, ensuring that the right questions are asked in the most appropriate way so as to lead to the most accurate and broad view of poverty and the impacts of growth; Include methods that emerge as most relevant, not that are predetermined to be most relevant; and Begin with a broad understanding of poverty and context, narrowing down, leading to in-depth investigation of critical issues as they are uncovered.
Further, in following these principles it is important to take on alternative perspectives, including social perspectives, economic perspectives, and the combination of the two:
Social perspectives Differences in access, perspective, power, etc., between and across groups. Differences in the value attributed to different measures of well-being and outcomes. The effect of local social organization on well-being. The promotion of needs, views, and participation by the poor and other vulnerable groups.
Economic perspectives To understand the economic environment in which people operate: asset, economic incentive, returns to different strategies, local effects of economic policy, production and consumption decisions, etc. To understand the economic factors behind organizational and institutional behavior.
Analytical overlap Common data collection tools (e.g., surveys and interviews); Similar objectives (e.g., analysis of different types of capital); Shared data requirements (e.g., mix of quantitative and qualitative); and Mutually reinforcing information (e.g., interrelated behaviors and outcomes).
320 11.2 POTENTIAL DIFFICULTY
The methodological overview just presented can be thought to go beyond the boundaries of geography, as its application to the study requires drawing upon theory and method from most, if not all, the social sciences in one form or another—anthropology, economics, psychology, sociology, and political science. This presents a great deal of potential difficulty from the onset given the different research traditions and schools of thought that operate within those disciplines. Each has its own distinctive views about what comprises the social world and how to study that world. In other words:
…the range of traditions which have some kind of interest in [poverty] research do not dovetail neatly into one uniform philosophy or set of methodological principles. (Mason 1996:88)
Yet, what we learn from the World Bank and the empirical study presented here is that central to our understanding of poverty outcomes is a clear focus on the complementary and contradictory aspects of the social world. Thus, it seems appropriate to place poverty research in its contemporary position within the complete spectrum of social science where those complements and contradictions also reside.
What problems or differences might this approach create in practice? The trouble with most impact analyses lies not only with definitional and measurement issues with respect to social and economic costs and benefits, but also with the construction of problem definition strategies in the policy and academic domains. That is, the manner in which one approaches a problem is based on the cultural theory that the person is oriented toward. For example, as Hoppe (2002) explained: hierarchists will impose a structure on any problem no matter what the cost (e.g., assumptions), isolates see social reality as unstable and thereby view any privileged structure as problematic, enclavists
321 look at all policy problems from the standpoint of fairness and distributive justice, while individualists exploit all usable knowledge to improve the situation. Thus, there is a cost or ideological bias embedded in the adoption of any one strategy.
A similar concern was raised here with regard to assessing the impacts of casinos as an economic development strategy. It was suggested that there is a lack of objectivity in adopting a particular conceptual and operational framework for impact analysis that is typically driven by ideological differences associated with perspectives of the individual versus society. This subjectivity in conducting impact analysis is all too often ignored in expressing study limitations and delimitations. Equally ignored within that context is the subjective assessment of the well-being of the poor. In the case study presented here, the position of the poor was privileged in the sense that the research project was structured, conceptually and operationally, to assess the social and poverty impacts of casino development from the perspective of the poor themselves.
However, recognizing the necessity of situating the poor in their broader context, a concerted effort was made to examine the conflicting constructs of success versus failure with regard to casinos as an economic development strategy in economically distressed areas. In so doing, both the economic context and the political, social, cultural, and historical contexts of people and place were considered, and at a number of scales.
The sub-analysis presented in chapter 10 serves as an example of the value of that approach, by illustrating the differences in our understanding of impacts based on the perspective taken. That is, by considering socio-cultural factors such as religion in the interpretation of economic outcomes, the poor have a voice.
322 So what does it take, really? It takes the ability to get to the aforementioned frame of reference based on the adoption of PSIA methodology, thereby demonstrating its value and that of the multidisciplinary, emergent approach embedded within it. That fact supports the need to encourage human geographers to engage in research that is dramatically different from the “norm” across the discipline. This is not only true of methodology in terms of what one might find acceptable given their epistemological stance, but also with respect to methods.
Emergent design (realist or otherwise) requires that one “be able to think and act strategically in ways which combine intellectual, philosophical, technical, and practical concerns rather than compartmentalizing these into separate boxes” (Mason 1996: 2).
This is further complicated by the realist’s focus on process, which itself is an elusive term that does not entail a specified set of procedures and therefore does not translate well into written form. Inevitably, the application of realist methodology is difficult to achieve and communicate in a comprehensive manner.
This is particularly problematic for beginning researchers who may not be conversant with the minefield of methods available to social scientists, let alone the philosophical debates around the issues of epistemology and methodology. Thus, while an emergent design is best left to the experienced researcher in general, this presents a lost opportunity for budding human geographers for whom a more open approach to research may seem appealing. In response to this situation within social science in general, Grix (2002) argued that:
[A] clear and transparent knowledge of the ontological and epistemological assumptions that underpin research is necessary…. (176)
323 This will allow them to defend their own positions, understand other researchers’ positions and fully grasp the directional relationship of key components of the research process. The latter is essential if students are to engage properly in academic debate and produce quality and transparent research projects. (184)
I don’t necessarily believe that I have achieved that final goal myself in terms of transparency of research design and epistemological stance, replicability, interpretation, and conclusions. But just as realist methodology is a work in progress, so too am I with respect to both its application and communication. That is not an excuse for failure if I have failed, but rather an acknowledgment of the need to continue that methodological development process both within as an economic geographer and a social science researcher and without in the broader discipline of geography.
With respect to the latter, my recommendation, my belief, is that with further methodological development, the discipline will be able to garner wider academic acceptance. More importantly, it will be able to contribute further to our understanding and study of the social world. This will be achieved by developing appropriate means for transforming geographers’ dynamic understanding of that world from one of theory to one of practice. Thus, when I think of my audience beyond this dissertation, I think of the students on whom the vitality of the discipline depends and the policymakers and community leaders who might ultimately be informed by their work. I hope that my contribution might be to encourage them to challenge orthodox beliefs about what there is to know and how we might know it—to revisit ‘persistent’ problems and look at them in a new and more informed way.
In order to see, we must look. (Brenneman et al. [1982]: 21)
324 11.3 CHAPTER 11 REFERENCES
Brenneman, W., et al. 1982. The Seeing Eye: Hermeneutical Phenomenology in the Study of Religion. University Park: Pennsylvania State University Press.
Grix, J. 2002. Introducing Students to the Generic Terminology of Social Research. Politics. 22(3): 175-186.
Hoppe, R. 2002. Cultures of Public Policy Problems. Journal of Comparative Policy Analysis. 4(3): 305-326.
Mason, J. 1996. Qualitative Researching. Thousand Oaks: Sage.
Sayer, A. 1992. Method in Social Science: A Realist Approach. 2 nd ed. London: Routledge.
Sayer, A. 2000. Realism and Social Science. Thousand Oaks, CA: Sage Publications.
325
APPENDIX A
MAP COMPENDIUM
326 A1. Mississippi State, County Map
Source: US Census Bureau (2000)
327 A2. Per Capita Transfer Payments by County; Mississippi, 1970-2000
Source: Delta Regional Authority (2005)
328 A3. Per Capita Net Earnings by County; Mississippi, 1970-2000
Source: Delta Regional Authority (2005)
329 A4. Per Capita Unemployment Insurance Benefits by County; Mississippi, 1970-2000
Source: Delta Regional Authority (2005)
330 A5. Per Capita Transfer Payments by County; Mississippi, 1970-2000
Source: Delta Regional Authority (2005)
331 A6. 1990 USGS Topographic Map of the Tunica Area
Source: MapCard (2005)
332 A7. Section of 1990 0USGS Topographic Map of the Tunica Area; Highlighting Highway 61
Source: MapCard (2005)
333 A8. Section of 1990 USGS Topographic Map of the Tunica Area; Highlighting the Town of Tunica and Surrounding Area to the South
Source: MapCard (2005)
334 A9. Tunica County Casino Area Map
*Tunica County casino locations are designated by circles 1 through 9 **Tunica County Hotels/B&Bs are designated by boxes 1 through 20 Source: Tunica Convention and Visitors Bureau (2005)
335 A10. Downtown Tunica Street Map; Highlighting Area Business Locations
*Numbered circles represent business locations Source: Tunica County Chamber of Commerce (2005)
336
APPENDIX B
STAKEHOLDER ANALYSIS
337 B.1 STAKEHOLDER ANALYSIS
Stakeholder analysis is the identification of the stakeholders in a project, program, or reform, an assessment of their interests, and the ways in which these interests affect risk and viability with regard to success. Stakeholder analysis can contribute to the design of the project/program or the selection of the reform strategy as well as our understanding of the processes of that framework ex-post by helping to identify the ways and means of stakeholder participation. Stakeholders include a range of persons, groups or institutions, both winners and losers, and those involved or excluded from decision- making processes. Stakeholders can be further defined as:
Primary stakeholders: those ultimately affected, either positively or negatively; Secondary stakeholders: the intermediaries in the delivery process; Key stakeholders: those who can significantly influence, or are important to the success of the endeavor.
In the case of the adoption of a particular economic development strategy, stakeholder analysis can help policymakers, practitioners, and researchers assess an environment throughout the change process. More specifically, by:
Drawing out the interests of stakeholders in relation to the problems which the strategy seeks to address or the purpose of the strategy in the first place; Identifying conflicts of interests between stakeholders, which will influence the assessment of risk and viability; Helping to identify relations between stakeholders, including coalitions and advocates and related forms of ownership, and cooperation; Helping to assess the type of participation by different stakeholders at successive stages of change.
As such, from a research prospective, stakeholder analysis should be done at the beginning of a study, beginning with writing up a quick and simple list of stakeholders and what the researcher believes their interests to be. Such a list can be used to draw out assumptions and provide guidance for data collection and the overall research design.
338 Once that process is underway, however, it must be understood that stakeholder analysis can include the attainment and processing of sensitive and undiplomatic information, interests of stakeholders may be covert and agendas hidden, and in many situations there may be negative consequences to unearthing and sharing that information. Another factor is that stakeholder analysis can be resource intensive in terms of time and money needed to complete the investigatory steps of the analysis.
The latter is particularly true when the research is conducted over some length of time because as change takes place in the study environment so too do stakeholders and their relationships change—in essence, stakeholder analysis can never really be considered a finished product. Thus, the extent of the analysis should be driven by the type and scale of the research project, the economic development strategy (i.e., project, program, or reform) under study, and the complexity of the issues. However, there is a basic methodology that can be followed, such as that offered by the Overseas
Development Administration (ODA). A-33 The steps in that methodology are summarized here and are elaborated on in the remainder of this section.
I. Draw up a stakeholder table; II. Do an assessment of the importance of each stakeholders to the success of the strategy and their relative power/influence within that context; III. Identify associated risks and assumptions that may affect success, including how success is understood (i.e., perceived, measured, expressed, etc.).
B.1.1 STEP ONE: STAKEHOLDER TABLE
To draw up a stakeholder table:
Identify and list all potential stakeholders;
A-1That which is presented here is directly summarized or paraphrased from the Overseas Development Administration’s Guidance Note on How to Do Stakeholder Analysis of Aid Projects and Programmes , July 1995.
339 Identify their interests (overt and hidden) in relation to the problems being addressed by the economic development strategy and its objectives; Note that each stakeholder may have several interests, list them all; Assess the likely impact of the development on each interest for every stakeholder (positive, negative, or unknown); Indicate the priority given to each stakeholder in meeting their interests in terms of that derived from the policy or the objectives of the development strategy.
Stakeholders can be listed and categorized in a variety of ways. A way to begin is to draw ups a rough list and that list into primary and secondary stakeholders. Once again, primary stakeholders are those people and groups that are ultimately affected by the project, program, or reform. They may include both intended and unintended beneficiaries as well as those negatively affected. This can be accomplished in part by categorizing according to social analysis, that is, by dividing into groups based on gender, social or income classes, occupational or service user groups. Thus, in many instances, primary stakeholders may overlap, such as the case where a black woman is a part of a low-income group.
Secondary stakeholders are intermediaries in the process of facilitating the development, which may include delivering aid to primary stakeholders depending on the goal of the strategy. Example categories are funding, implementing, minority and advocacy organizations, or simply governmental, NGO and private sector organizations.
This may require that key individuals as specific stakeholders relative to those groups are identified (e.g., heads of departments or other agencies, which have personal interests at stake as well as formal institutional objectives). Secondary stakeholders may also included informal political or social groups, such as politicians, local leaders, and respected persons with social or religious influence. A checklist of questions for identifying both secondary and primary stakeholders includes:
340 Have all primary and secondary stakeholders been listed? Have all potential supporters and opponents been identified? Have primary stakeholders been divided into user/occupational, gender, or income groups? Have the interests of vulnerable groups (especially the poor) been identified? Are there any new primary or secondary stakeholders that are likely to emerge as a result of the project?
The resulting list of stakeholders forms the basis of a tabulation of interests for each stakeholder and the likely impact on them. A checklist for drawing out those interests may include answering the following questions:
What are the expectations of the stakeholder with regard to the development? What benefits are there likely to be for the stakeholder? What resources will the stakeholder wish to commit or avoid committing for the sake of the development? What other interests does the stakeholder have which may conflict with the objectives of the development strategy? How does the stakeholder regard the other stakeholders on the list?
In completing this step, note that information on secondary stakeholders should be compiled in the form of institutional analysis. Information on primary stakeholders should be available from social analysis as briefly described previously. In addition, much of the information on primary stakeholders will have to be defined by those individuals themselves or by key informants who have first-hand or on-the-ground knowledge of the development experience and participating parties.
B1.2 STEP 2: INFLUENCE AND IMPORTANCE
Key stakeholders are those which can significantly influence or is important to the success of a development strategy. The term influence is used here to mean how powerful a stakeholder is, while importance refers to those stakeholders whose problems, needs and interests are the priority of the development—in other words, if important stakeholders are note assisted effectively according the objectives of the strategy then the
341 project cannot be deemed a success. Combining influence and importance can be done through the use of a matrix diagram, whereby the stakeholders are classified into different groups, which will help identify assumptions and the risks and their management throughout the development process.
Assessing influence can be difficult as it is broadly defined as power that a stakeholder holds with respect to controlling decisions, facilitation implementation, and exerting influence that may affect the development positively or negatively. Thus, it is best understood as the extent to which people, groups or organizations are able to persuade or coerce others into making decisions, and following certain courses of action .
Accordingly, power may be derived in a number of ways, such as through the nature of the stakeholder’s organization, their political or social position relative to that of another stakeholder, and even their connection to others in particular organization or of a political or social position. Hence, power may be formal or informal. It is also important to consider the manner in which one’s power is influenced, increased or decreased, by different stages and aspects of the development process. For example, a stakeholder with little power on the onset may acquire resources introduced by the development that increase their power along the way.
Importance is an indication of the priority given to satisfying stakeholders’ needs and interests throughout the development process. It assessing importance its distinction from influence must be kept in mind. For instance, their may be stakeholders, such as unorganized primary stakeholders, whom are given great priority with respect to the objectives of the development, but have little capacity to participate in the development
342 and to influence key decisions along the way. A checklist of questions for assessing importance includes:
What problems, affecting which stakeholders, does the development strategy seek to address or alleviate? For which stakeholders does the development place a priority with respect to meeting their needs, interests and expectations? Which stakeholder interests converge most closely with policy and project objectives?
Importance and influence can be combined by using a matrix diagram, which is achieved by positioning primary and secondary stakeholders in a two by two matrix. The exercise of doing so will aid in the identification of relative risks for specific stakeholders and the potential coalition building in support of different aspects of the development.
B.1.3 STEP 3: RISKS AND ASSUMPTIONS
The success of a development depends partly on the validity of the assumptions made about its various stakeholders, and the risks facing the development. Some of these risks will derive from conflicting interests, such as those related to gaming as a moral issue versus gaming as an economic issue in the study at hand. As noted previously, some of those risks can emerge through the completion of the influence and importance matrix diagram. As a general rule, risks will be evident from those stakeholders who have high influence, but interests who are not in line with the objectives of the development strategy—one may assume that these key stakeholders may be able to block or divert the development from its primary goals. As a means for systematically identifying those risks and assumptions, the following checklist of questions may be used:
What is the role or response of the key stakeholder that must be assumed if the development is to be successful?
343 Are these roles plausible and realistic? Are there negative responses which can be expected, given the interests of the stakeholder? If such responses occur, what impact would they have on the development and its targeted beneficiaries? How probable are these negative responses, and are they major risks? Overall, which plausible assumptions about stakeholders offer support for or threats to the success of the development?
B.1.4 UTILIZING STAKEHOLDER ANALYSIS
There are a number of ways that stakeholder analysis can be used for impact study. In its simplest form, it can inform research design in terms of deciding which research methods are most appropriate and it is integral to identifying research participants for participatory methods. Given a more in-depth analysis (completing all steps presented), once the risks and assumptions have been taken into account, stakeholder analysis may be used to glean an understanding of the hierarchy of the explicit and inexplicit (underlying) objectives of participants in the development process.
It terms of reporting, stakeholder analysis can be presented as a formalized product through the sharing of associated tables, matrices, and diagrams. However, formal presentation of stakeholder analysis may be difficult if it was integrated into an extended study, such that tables, matrices, and diagrams would not be static given changes to the relationships examined as the development and research progresses. In that instance, stakeholder analysis is best shared in the research report as a concept rather than as document .
344
APPENDIX C
SURVEY INSTRUMENT
345 IRB #15002—Survey Questionnaire
Tracey L. Farrigan, Researcher Amy K. Glasmeier, Advisor Department of Geography The Pennsylvania State University 302 Walker Building University Park, PA 16802-5022 (814) 865-3433
PART ONE: General Information
1.01 What year were you born? ______
1.02 Which racial category do you belong to? Circle one American Indian Asian Black or African American Native Hawaiian or Pacific Islander White Other______
1.03 Where were you born? Country ______State/province ______County/area______
1.04 What is your present marital status? Circle one Single Married / with Partner Divorced / Separated Widowed Other:______
1.05 What is your gender? Circle one Male Female
PART TWO: Living Environment
2.01 Please give the name of the street of your residence and your zip code, as I would like to see if questions are answered differently by people living in different areas. Your answer will be confidential. Street: ______Zip Code:
2.02 Why do you live in this area? Circle all that apply I like the people To be close to my family I was born here This is where I work This is where I can afford to live I like the housing selection I am forced to live here I like the natural environment I like the social environment Other: ______
346 2.03 What type of housing structure do you live in? Circle one Single-family house Multi-family house Apartment building or condominium Mobile home Other: ______
2.04 Do you own or rent your home? Circle one and answer additional question Own; Did you inherit it, yes or no? Do you own it outright, yes or no? ______Rent; What type of landlord do you have? The landlord is a relative Individual or local company Individual or company outside of area Housing authority Government agency Other: ______
2.05 How many people live with you in your home? Number of adults: ______Number of children:______
2.06 How many rooms are in your home? Total number of rooms: ____ Number of bedrooms: ____ Number of bathrooms: ____
2.07 Do you feel that your home is overcrowded? Circle one— No Yes
2.08 Have you moved within the last ten years? Circle one, if yes answer additional questions No Yes; How many times altogether? ______What was the greatest distance (miles)? _____ What was the shortest distance? ____
2.09 Over the last ten years have your living conditions changed in general? No, they have remained the same Yes, they have gotten better; In what way? ______
Yes, they have gotten worse; In what way? ______
2.10 What services do you use in your community? Do you feel that the services are adequate? Check all that apply and circle yes or no. Educational/Job Training: yes no Protective Services: yes no Recreational Services: yes no Transportation Services: yes no Welfare Services: yes no Health Services: yes no
347 2.11 Have you ever been homeless? No Yes; How many times? ______What was the shortest length of time? ______What was the longest length of time? ______
2.12 Do any of the conditions listed describe your home now or in the past? Check and circle now and/or past depending on what applies to you Inadequate water supply or water supply system—now past Inefficient cooling, heating, or ventilation system—now past Leaky roof or damp walls or ceilings—now past Insect or rodent infestation—now past Windows or doors that do not open/close properly—now past Dangerous or improperly working electrical system—now past Subject to break-ins, vandalism, or other crime—now past High noise level—now past Lacking a refrigerator, stove, or working sink—now past No laundry facilities—now past Other: ______—now past
2.13 How often do you think about your future living conditions? Circle one Constantly Often Sometimes Rarely Never
2.14 Considering everything, how satisfied are you with your current living situation? Please indicate by marking along the scale Not at all 0 1 2 3 4 5 Very satisfied
PART THREE: Financial Environment
3.01 How many people does your household support financially? Include yourself, those living with you, and those living outside of your home Number of adults supported, in full: ______in part:______Number of children supported, in full: ______in part: ______
3.02 What is your monthly net income? $______
3.03 What is the monthly net income of all other household members? $______
3.04 What was the average weekly income over the last ten years for you and all other household members? Your income? $______All other household members? $______
348 3.05 From what sources has your household derived its income over the last year? Check all that apply.
Wages or salaries Farm proprietor’s income Other proprietor income Unemployment insurance Disability payments Social Security payments Welfare payments Veteran’s payments Medical payments Food Stamps Investment profits Rents from assets Annuities or pensions Reparations Other ______
3.06 Would you say you are better off financially now than you have been in the past? Circle one No Yes; why? ______
3.07 How often do you think about your future finances? Circle one Constantly Often Sometimes Rarely Never
3.08 To what extent do you feel financially independent? Please indicate by marking along the scale Not independent 0 1 2 3 4 5 Very independent
3.09 On what does your household spend its money and how much is spent per item each month? Check all that apply and indicate amount. Food…………………………..$______Clothing………………………$______Telephone…………………….$______Heating/cooling………………$______Health/medical……………….$______Rent/mortgage……………….$______Education…………………….$______Transportation………………$______Entertainment……………….$______Debts…………………………$______Savings……………………….$______Other investments…………..$______Other ______$______Other ______$______
3.10 Do you believe that it was harder to make a living ten years ago compared to today? No Yes, why ______
3.11 Over the last twelve months did your total household income fluctuate from month to month? No Yes, why and by how much______
349 PART FOUR: Work Environment
4.01 Are you currently employed? No; How long have you been unemployed? ______mos ______years Yes; How long have you worked at your current Primary job? ______mos ______years; Secondary job? ______mos _____ years
4.02 What type of industry do you regularly work in? Manufacturing Agriculture Transportation Communications Real Estate / Finance Government Services; what type?______Other: ______
4.03 What is your primary occupation? ______
4.04 Please describe your current primary job by checking all that apply: Unemployed Temporary work Full-time work Part-time work Self-employed Seasonal work Work individually Work as a team Physical work Clerical work Managerial work A supervisor Day shift hours worked Night shift hours worked Graveyard shift hours worked Hourly wage $______per hour Salary $______per year
4.05 What other positions have you held in the last ten years? Why did you leave those jobs? Please list and explain ______
4.06 What benefits do you receive at your current jobs, primary and secondary? Please list ______
4.07 What do you like most about your current primary job? ______
4.08 What do you like least about your current primary job? ______
4.09 Would you like to change your current job situation? No Yes; How?______
4.10 How successful do you think you are in your primary job? Please indicate by marking along the scale A Failure 0 1 2 3 4 5 Very Successful
350 4.11 How responsible do you feel in your primary job? Please indicate by marking along the scale Not at all 0 1 2 3 4 5 Very Responsible
4.12 Do you feel that the work that you do is important? Circle one : No Yes
4.13 What is your level of educational attainment? Circle one Did not go past the 8 th grade Some high school High school graduate Have GED Some college College graduate; What degree(s) do you hold? Associate’s degree Bachelor’s degree Master’s degree Doctorate
4.14 What other formal or informal education have you had? Circle all that apply Night or adult school On the job training Taught by a friend or family member Community workshops Other: ______
4.15 Please list the level of education obtained and occupation of your parents and all adult household members, excluding yourself. Person…………….Education Level…………..Occupation Father ______Mother______Spouse______Other______Other______Other______
4.16 Considering everything, how satisfied are you with your current primary job? Please indicate by marking along the scale Not at all 0 1 2 3 4 5 Very Satisfied
4.17 Have you ever been out of work over the last ten years? No Yes; How many times? ______What was the longest period of time you went without work? ____days /weeks What was the shortest period of time you went without work? ____days/weeks
4.18 How do you travel to and from work? Circle all that apply Bicycle Vehicle not shared with other household member Walk Vehicle shared with other household member Ride from someone outside the household, specify: ______Public transportation, specify: ______Other: ______
4.19 What is the distance you travel to work on the average, past and present? Past: ______miles Present: ______miles
4.20 How do you get along with the people at work? Please indicate by marking along the scale Not at all 0 1 2 3 4 5 Very Well
351
PART FIVE: Community & Social Environment
5.01 Does your social life include anyone you have met at work? Circle all that apply No Yes, who? Your boss Your employees Fellow workers People you have met through your job Other:______
5.02 What is the average number of vacation days you have per year? ______days
5.03 What do you do most often during your vacation? Circle one Work at home Stay at home Visit family Go to a resort Outdoor recreation, specify: ______Travel, specify: ______Other: ______
5.04 Do you feel that work interferes with your personal life? No Yes; How so? ______
5.05 What organizations are you involved in and is your involvement only recent or long- standing? Check all that apply and indicate by circling recent or long-standing A religious group—recent long-standing Labor union or political party—recent long-standing A group concerned with public issues (e.g. civil rights)—recent long-standing A self-improvement or self-help group—recent long-standing A group concerned with community betterment—recent long-standing A social or recreational group—recent long-standing A group concerned with or concerning children—recent long-standing Other: ______
5.06 What elections do you generally vote in? Circle one None Only national Only local National and local
5.07 How satisfied are you with the services you receive from these authorities? If you never have contact with these authorities or do not feel influenced by them then write “0,”, otherwise circle number that most applies: 1=Very Satisfied 2=Somewhat Satisfied 3 = Not Satisfied Protective Services: 1 2 3 Local Government: 1 2 3 State Government: 1 2 3 National Government: 1 2 3 Housing Authorities: 1 2 3 Employment Agencies: 1 2 3 Local Welfare Institutions: 1 2 3 Financial Institutions: 1 2 3 Medical Institutions: 1 2 3 Educational Institutions: 1 2 3
352 Utilities Companies: 1 2 3 Insurance Companies: 1 2 3
5.08 How would you describe your main activities in terms of time spent? Check top five that apply to you and give a number rank where “1” is most time spent and “5” is the least time spent. Unemployed _____ Self-employment _____ On a training course _____ Wage or salary employment _____ Looking after children _____ In primary or secondary school _____ Retired _____ Student at college/university _____ Exercising/playing sports _____ Watching TV or playing video games ____ Socializing with family and/or friends _____ Other______
5.09 How much enjoyment do you get from your free time? Circle one A lot Some Not very much
5.10 How often do you have time that you don’t know what to do with? Circle one Never Rarely Sometimes Often Always
5.11 Do you feel that you have enough time to accomplish the things that you want to do? Yes No; Why? Too busy with your job Bothered by family problems Busy working around the house Other: ______
5.12 How well do you trust each of the following in making decisions on your behalf? Please indicate by placing a mark on the scale for each category a. Family members 0 1 2 3 4 5 Not at all Completely b. ‘Good old’ friends 0 1 2 3 4 5 Not at all Completely c. Work companions 0 1 2 3 4 5 Not at all Completely d. Residential neighbors 0 1 2 3 4 5 Not at all Completely e. Local government officials 0 1 2 3 4 5 Not at all Completely f. State government officials 0 1 2 3 4 5 Not at all Completely g. Federal government officials 0 1 2 3 4 5 Not at all Completely
353 h. Yourself 0 1 2 3 4 5 Not at all Completely
5.13 Would you like to be more involved in community activities? No Yes; What kind? ______
PART SIX: Health & Nutritional Environment
6.01 What insurance do you have? Circle all that apply Medical Dental Eye Auto Life Other: ______
6.02 How tall are you? ______ft ______in
6.03 How much do you weigh? ______lbs
6.04 How would you best describe your health? Circle one Poor Fair Good Excellent
6.05 Have you had a need for health care or medical advice in the past 12 months and did not seek it? No Yes; Why? Circle all that apply The health facilities are too far away Services are of poor quality It’s too long to wait for an appointment I can manage without help I couldn’t afford it Other: ______
6.06 Do you worry about your health? No Yes
6.07 Please describe a typical day’s diet: Breakfast: ______Lunch: ______Dinner: ______Snacks: ______
6.08 How often do you exercise? Circle one Never Less than once a month Less than once a week Every day Once or twice a week More than twice a week
6.09 Where do you get exercise? Circle all that apply At a public gym At a private commercial gym At a home gym At work Around the house Around the neighborhood
354 6.10 On average, how often do you consume alcoholic beverages? Circle one Never Less than once a month Less than once a week Every day Once or twice a week More than twice a week
6.11 How often do you purchase food from a restaurant? Circle one Never Less than once a month Less than once a week Every day Once or twice a week More than twice a week
6.12 When you purchase food at the market, what is most important to you in making your selection? Price Quality Personal taste Convenience Other:______
6.13 How often do you go to sleep hungry? Circle one Never Sometimes Often Always
6.14 Considering everything, how satisfied are you with your present diet? Please indicate by marking along the scale Not at all 0 1 2 3 4 5 Very Satisfied
6.15 Have you ever smoked cigarettes, cigars, a pipe, or chewed tobacco? No Yes; For how long? ______years Do you still smoke or chew, yes or no? ______How much per day? ______
6.16 Are you regularly exposed to secondhand smoke? No Yes
6.17 How much sleep do you get each night on the average? ______hours
PART SEVEN: General Attitudes and Beliefs
7.01 Do you feel discriminated against? No Yes; What way, where? Circle all that apply By race or ethnicity By age By gender By sexuality By religion By political orientation At work At school In your home In your community Other: ______
7.02 What determined your level of formal education? Circle all that apply Personal choice Financial cost Time spent Age Location Other: ______
7.03 Are you satisfied with your educational level? No Yes
7.04 Do you feel that you are able to dress properly? Yes No; Why? Circle all that apply
355 It is too warm in the summer It is too cold in the winter My clothes are too worn out My clothes are out of style I do not have enough clothes Other: ______
7.05 Here are some statements about the way people feel and act, circle the ‘T’ if you agree that it is mostly true about you and the ‘F’ if it is mostly false. It often seems that my life has no meaning……………..T…F I look forward to the future with hope………………….T…F I can’t make things better, I might as well give up…….T…F I can’t imagine what my life will be like in 10 years…T…F I expect more good things in life than average………..T…F I never get breaks and don’t expect to in the future…..T…F I expect to be happier in the future than I am now……T…F The future seems uncertain……………………………..T…F I can look forward to more good times than bad………T…F
7.06 What is the most serious problem you have right now? ______
7.07 If you found $50 right now, what would you do with it? ______
7.08 If you found $500 right now, what would you do with it? ______
7.09 If you needed $50 right now, how would you get it? ______
7.10 If you needed $500 right now, how would you get it? ______
7.11 Think of someone who has a good life, what makes their life good? ______
7.12 Think of someone who has a bad life, what makes their life bad? ______
7.13 What kind of life do you have? Circle one Good Average Bad
7.14 Do you consider yourself poor, average, or well off? Circle one Poor Average Well off
356 7.15 Complete the following sentences in 10 words or less.
I fear ______I want ______I hope ______I feel ______I love ______I hate ______I believe in ______I count on ______My future is ______The past was ______The present is ______I can’t imagine ______
7.16 Complete the statement, when I feel angry it’s usually because… Circle one I can’t get what I want from life My family makes me angry My job makes me angry My financial situation makes me angry People don’t respect me Other: ______
7.17 What type of job do you desire for your children? I do not have children I desire ______Do you think that they will get it? Yes No; Why? Circle all that apply They are not good enough They are not rich enough They do not have an equal chance They are not rich enough They are not getting the right education Other: ______
7.18 Do you feel that your children will do better than you? No Yes; In what way?______
357 7.19 Do you feel that you are doing better than your parents? No Yes; In what way? ______
7.20 What is your definition of poverty? ______
7.21 What is your definition of well-being? ______
PART EIGHT: The Gaming Industry
8.01 Do you feel that the gaming industry has helped create jobs for those in your neighborhood? No Yes
8.02 Of the people you personally know who work in the gaming industry, what kind of work do they do? ______
8.03 How do you feel about the local gaming industry in general? Circle all that apply. It creates wealth in the community It is an acceptable form of entertainment It is an unacceptable form of entertainment It is an acceptable industry in which to work It is an unacceptable industry in which to work It is immoral, but is acceptable because it has provided jobs and income to the area It is immoral and completely unacceptable It has helped reduce the level of poverty It has not helped to reduce the level of poverty It has made life worse around here It has made life better around here
8.04 Were you a Tunica or Coahoma County resident before the casinos arrived (prior to 1992) ? If no; what year did you move into the county? ______If yes; did you vote or participate in activities or discussions regarding the development of the casino industry in the area? Please explain. ______
8.05 How has the casino gaming industry in Tunica County impacted you personally? Please explain. ______
358 8.06 How do you see the casino gaming industry’s impact on your community in the long run, say ten years down the road, including additional developments stemming from it, Please explain. ______
8.07 How do you see the future of agriculture in the county considering the changes taking place and how does that potentially affect you? Please explain. ______
8.08 Overall, what is your conclusion regarding the impact of the gaming industry on your well-being within each of the study environments? Circle that which applies for each: 1=significantly worse, 2=somewhat worse, 3=no different, 4=somewhat better, 5=significantly better Living Environment: 1 2 3 4 5 Financial Environment: 1 2 3 4 5 Work Environment: 1 2 3 4 5 Community/Social Env.: 1 2 3 4 5 Health/Nutritional Env.: 1 2 3 4 5 Attitudes/Beliefs: 1 2 3 4 5
PART NINE: Other Questions
9.01 Overall, how would you describe your past level of well-being? Circle one In extreme hardship Not very well off Neither Quite well off Very well off
9.02 Overall, how would you describe your current level of well-being? Circle one In extreme hardship Not very well off Neither Quite well off Very well off
9.03 Are there any major comments, concerns, opinions that you’d like to voice with regard to your own well-being or that of your community or the gaming industry? No Yes; what? ______
359
APENDIX D
SELECT FREQUENCY TABLES
360 1.02: Which racial category do you belong to?
Cumulative Frequency Percent Valid Percent Percent Valid other 4 1.7 1.7 1.7 black or African American 231 96.3 98.3 100.0 Total 235 97.9 100.0 Missing System 5 2.1 Total 240 100.0
1.03: Where were you born?
Cumulative Frequency Percent Valid Percent Percent Valid other county 12 5.0 5.0 5.0 Coahoma County 99 41.3 41.3 46.3 Tunica County 129 53.8 53.8 100.0 Total 240 100.0 100.0
1.04: What is your present marital status?
Cumulative Frequency Percent Valid Percent Percent Valid single 146 60.8 64.6 64.6 married/partnered 37 15.4 16.4 81.0 divoerce/sep 28 11.7 12.4 93.4 widow 15 6.3 6.6 100.0 Total 226 94.2 100.0 Missing System 14 5.8 Total 240 100.0
1.05: What is your gender?
Cumulative Frequency Percent Valid Percent Percent Valid female 121 50.4 51.7 51.7 male 113 47.1 48.3 100.0 Total 234 97.5 100.0 Missing System 6 2.5 Total 240 100.0
361 2.05: How many people live in your home?
Cumulative Frequency Percent Valid Percent Percent Valid 0 1 .4 .5 .5 1 19 7.9 8.8 9.2 2 22 9.2 10.1 19.4 3 28 11.7 12.9 32.3 4 60 25.0 27.6 59.9 5 32 13.3 14.7 74.7 6 25 10.4 11.5 86.2 7 13 5.4 6.0 92.2 8 14 5.8 6.5 98.6 9 2 .8 .9 99.5 10 1 .4 .5 100.0 Total 217 90.4 100.0 Missing System 23 9.6 Total 240 100.0
2.06: How many rooms are in your home?
Cumulative Frequency Percent Valid Percent Percent Valid 1 1 .4 .5 .5 2 3 1.3 1.4 1.8 3 20 8.3 9.1 11.0 4 34 14.2 15.5 26.5 5 61 25.4 27.9 54.3 6 47 19.6 21.5 75.8 7 18 7.5 8.2 84.0 8 25 10.4 11.4 95.4 9 8 3.3 3.7 99.1 10 2 .8 .9 100.0 Total 219 91.3 100.0 Missing System 21 8.8 Total 240 100.0
2.07: Do you feel that your home is overcrowded?
Cumulative Frequency Percent Valid Percent Percent Valid no 176 73.3 80.4 80.4 yes 43 17.9 19.6 100.0 Total 219 91.3 100.0 Missing System 21 8.8 Total 240 100.0
362 2.09: Over the last 10 years have your living conditions changed in general?
Cumulative Frequency Percent Valid Percent Percent Valid no 107 44.6 45.1 45.1 yes-better 124 51.7 52.3 97.5 yes-worse 6 2.5 2.5 100.0 Total 237 98.8 100.0 Missing System 3 1.3 Total 240 100.0
2.10: Do you feel that educational/job training services are adequate?
Cumulative Frequency Percent Valid Percent Percent Valid do not use 106 44.2 44.2 44.2 use, adequate 80 33.3 33.3 77.5 use, not adequate 54 22.5 22.5 100.0 Total 240 100.0 100.0
2.10: Do you feel that protective services are adequate?
Cumulative Frequency Percent Valid Percent Percent Valid do not use 118 49.2 49.2 49.2 use, adequate 52 21.7 21.7 70.8 use, not adequate 70 29.2 29.2 100.0 Total 240 100.0 100.0
2.10: Do you feel that recreational services are adequate?
Cumulative Frequency Percent Valid Percent Percent Valid do not use 106 44.2 44.2 44.2 use, adequate 64 26.7 26.7 70.8 use, not adequate 70 29.2 29.2 100.0 Total 240 100.0 100.0
2.10: Do you feel that transportation services are adequate?
Cumulative Frequency Percent Valid Percent Percent Valid do not use 100 41.7 41.7 41.7 use, adequate 49 20.4 20.4 62.1 use, not adequate 91 37.9 37.9 100.0 Total 240 100.0 100.0
363 2.10: Do you feel that welfare services are adequate?
Cumulative Frequency Percent Valid Percent Percent Valid do not use 113 47.1 47.1 47.1 use, adequate 66 27.5 27.5 74.6 use, not adequate 61 25.4 25.4 100.0 Total 240 100.0 100.0
2.10: Do you feel that health services are adequate?
Cumulative Frequency Percent Valid Percent Percent Valid do not use 91 37.9 37.9 37.9 use, adequate 115 47.9 47.9 85.8 use, not adequate 34 14.2 14.2 100.0 Total 240 100.0 100.0
2.13: How often do you think about your future living conditions
Cumulative Frequency Percent Valid Percent Percent Valid constantly/often 196 81.7 82.0 82.0 sometimes 30 12.5 12.6 94.6 rarely/never 13 5.4 5.4 100.0 Total 239 99.6 100.0 Missing System 1 .4 Total 240 100.0
2.14: Considering everything, how satisfied are you with your current living situation?
Cumulative Frequency Percent Valid Percent Percent Valid 0/1 not satisfied 89 37.1 37.6 37.6 2/3 indifferent/somewhat 93 38.8 39.2 76.8 4/5 satisfied 55 22.9 23.2 100.0 Total 237 98.8 100.0 Missing System 3 1.3 Total 240 100.0
364 3.01: How many people does your household support in full financially?
Cumulative Frequency Percent Valid Percent Percent Valid 1 28 11.7 12.2 12.2 2 28 11.7 12.2 24.3 3 27 11.3 11.7 36.1 4 62 25.8 27.0 63.0 5 32 13.3 13.9 77.0 6 27 11.3 11.7 88.7 7 12 5.0 5.2 93.9 8 8 3.3 3.5 97.4 9 2 .8 .9 98.3 10 2 .8 .9 99.1 11 1 .4 .4 99.6 15 1 .4 .4 100.0 Total 230 95.8 100.0 Missing System 10 4.2 Total 240 100.0
3.06: Whould you say you are better off financially now than you have been in the past?
Cumulative Frequency Percent Valid Percent Percent Valid no 137 57.1 59.8 59.8 yes 49 20.4 21.4 81.2 yes, named assoc 43 17.9 18.8 100.0 w/gambling Total 229 95.4 100.0 Missing System 11 4.6 Total 240 100.0
3.07: How often do you think about your future finances?
Cumulative Frequency Percent Valid Percent Percent Valid constantly/often 190 79.2 84.1 84.1 sometimes 31 12.9 13.7 97.8 rarely/never 5 2.1 2.2 100.0 Total 226 94.2 100.0 Missing System 14 5.8 Total 240 100.0
365 3.08: To what extent do you feel financially independent?
Cumulative Frequency Percent Valid Percent Percent Valid 0/1 not independent 88 36.7 39.1 39.1 2/3 somewhat/indifferent 89 37.1 39.6 78.7 4/5 independent 48 20.0 21.3 100.0 Total 225 93.8 100.0 Missing System 15 6.3 Total 240 100.0
3.10: Do you believe that it was harder to make a living ten years ago compared to today?
Cumulative Frequency Percent Valid Percent Percent Valid no 128 53.3 57.9 57.9 yes 52 21.7 23.5 81.4 yes, named assoc 41 17.1 18.6 100.0 w/gambling Total 221 92.1 100.0 Missing System 19 7.9 Total 240 100.0
4.01: Are you currently employed?
Cumulative Frequency Percent Valid Percent Percent Valid no 150 62.5 63.0 63.0 yes 88 36.7 37.0 100.0 Total 238 99.2 100.0 Missing System 2 .8 Total 240 100.0
4.02: What type of industry do you regularly work in?
Cumulative Frequency Percent Valid Percent Percent Valid man 58 24.2 24.8 24.8 fire 5 2.1 2.1 26.9 ag 79 32.9 33.8 60.7 gov 4 1.7 1.7 62.4 tran 1 .4 .4 62.8 svc 15 6.3 6.4 69.2 com 12 5.0 5.1 74.4 8 60 25.0 25.6 100.0 Total 234 97.5 100.0 Missing System 6 2.5 Total 240 100.0
366 4.10: How successful do you think you are in your primary job?
Cumulative Frequency Percent Valid Percent Percent Valid 0/1 not successful 85 35.4 37.9 37.9 2/3 somewhat/indifferent 73 30.4 32.6 70.5 4/5 successful 66 27.5 29.5 100.0 Total 224 93.3 100.0 Missing System 16 6.7 Total 240 100.0
4.13: What is your level of educational attainment?
Cumulative Frequency Percent Valid Percent Percent Valid not past 8th grade 81 33.8 33.9 33.9 have GED 22 9.2 9.2 43.1 some hs 37 15.4 15.5 58.6 hs grad 77 32.1 32.2 90.8 some college 19 7.9 7.9 98.7 college degree 3 1.3 1.3 100.0 Total 239 99.6 100.0 Missing System 1 .4 Total 240 100.0
4.16: Considering everything, how satisfied are you with your current primary job?
Cumulative Frequency Percent Valid Percent Percent Valid 0/1 not satisfied 74 30.8 33.0 33.0 2/3 indifferent/somewhat 86 35.8 38.4 71.4 4/5 satisfied 64 26.7 28.6 100.0 Total 224 93.3 100.0 Missing System 16 6.7 Total 240 100.0
4.17: Have you ever been out of work over the last ten years?
Cumulative Frequency Percent Valid Percent Percent Valid no 46 19.2 20.2 20.2 yes, once 81 33.8 35.5 55.7 yes, more than once 101 42.1 44.3 100.0 Total 228 95.0 100.0 Missing System 12 5.0 Total 240 100.0
367 4.20: How do you get along with the people at work?
Cumulative Frequency Percent Valid Percent Percent Valid 0/1 don't get along well 3 1.3 1.4 1.4 2/3 somewhat/indifferent 22 9.2 10.5 11.9 4/5 get along well 185 77.1 88.1 100.0 Total 210 87.5 100.0 Missing System 30 12.5 Total 240 100.0
5.04: Do you feel that work interferes with your personal life?
Cumulative Frequency Percent Valid Percent Percent Valid no 206 85.8 91.2 91.2 yes 18 7.5 8.0 99.1 yes w/comment 2 .8 .9 100.0 derogatory toward work Total 226 94.2 100.0 Missing System 14 5.8 Total 240 100.0
5.05: Are you/have you been invovled with a religious group?
Cumulative Frequency Percent Valid Percent Percent Valid not involved 115 47.9 47.9 47.9 involved recently 45 18.8 18.8 66.7 involved long standing 80 33.3 33.3 100.0 Total 240 100.0 100.0
5.05: Are you/have you been invovled with a labor union or political party?
Cumulative Frequency Percent Valid Percent Percent Valid not involved 215 89.6 89.6 89.6 involved recently 5 2.1 2.1 91.7 involved long standing 20 8.3 8.3 100.0 Total 240 100.0 100.0
5.05: Are you/have you been invovled with a group concerned with public issues?
Cumulative Frequency Percent Valid Percent Percent Valid not involved 208 86.7 86.7 86.7 involved recently 9 3.8 3.8 90.4 involved long standing 23 9.6 9.6 100.0 Total 240 100.0 100.0
368 5.05: Are you/have you been invovled with a self-improvement or self-help group?
Cumulative Frequency Percent Valid Percent Percent Valid not involved 201 83.8 83.8 83.8 involved recently 17 7.1 7.1 90.8 involved long standing 22 9.2 9.2 100.0 Total 240 100.0 100.0
5.05: Are you/have you been invovled with a group concerned with community betterment?
Cumulative Frequency Percent Valid Percent Percent Valid not involved 203 84.6 84.6 84.6 involved recently 26 10.8 10.8 95.4 involved long standing 11 4.6 4.6 100.0 Total 240 100.0 100.0
5.05: Are you/have you been invovled with a social or recreational group?
Cumulative Frequency Percent Valid Percent Percent Valid not involved 214 89.2 89.2 89.2 involved recently 9 3.8 3.8 92.9 involved long standing 17 7.1 7.1 100.0 Total 240 100.0 100.0
5.05: Are you/have you been invovled with a concerned with or concerning children?
Cumulative Frequency Percent Valid Percent Percent Valid not involved 197 82.1 82.1 82.1 involved recently 20 8.3 8.3 90.4 involved long standing 23 9.6 9.6 100.0 Total 240 100.0 100.0
5.05: Are you/have you been invovled with an other group?
Cumulative Frequency Percent Valid Percent Percent Valid not involved 234 97.5 97.5 97.5 involved recently 6 2.5 2.5 100.0 Total 240 100.0 100.0
369 5.07: How satisfied are you with the services you receive from protective service authorities?
Cumulative Frequency Percent Valid Percent Percent Valid 3, not satisfied 72 30.0 33.2 33.2 2, somewhat satisfied 104 43.3 47.9 81.1 1, satisfied 38 15.8 17.5 98.6 3 3 1.3 1.4 100.0 Total 217 90.4 100.0 Missing System 23 9.6 Total 240 100.0
5.07: How satisfied are you with the services you receive from local govt authorities?
Cumulative Frequency Percent Valid Percent Percent Valid 3, not satisfied 72 30.0 34.3 34.3 2, somewhat satisfied 106 44.2 50.5 84.8 1, satisfied 32 13.3 15.2 100.0 Total 210 87.5 100.0 Missing System 30 12.5 Total 240 100.0
5.07: How satisfied are you with the services you receive from state govt authorities?
Cumulative Frequency Percent Valid Percent Percent Valid 3, not satisfied 77 32.1 38.7 38.7 2, somewhat satisfied 94 39.2 47.2 85.9 1, satisfied 28 11.7 14.1 100.0 Total 199 82.9 100.0 Missing System 41 17.1 Total 240 100.0
5.07: How satisfied are you with the services you receive from national govt authorities?
Cumulative Frequency Percent Valid Percent Percent Valid 3, not satisfied 69 28.8 36.1 36.1 2, somewhat satisfied 98 40.8 51.3 87.4 1, satisfied 24 10.0 12.6 100.0 Total 191 79.6 100.0 Missing System 49 20.4 Total 240 100.0
370 5.07: How satisfied are you with the services you receive from housing authorities?
Cumulative Frequency Percent Valid Percent Percent Valid 3, not satisfied 79 32.9 42.0 42.0 2, somewhat satisfied 77 32.1 41.0 83.0 1, satisfied 32 13.3 17.0 100.0 Total 188 78.3 100.0 Missing System 52 21.7 Total 240 100.0
5.07: How satisfied are you with the services you receive from employment agencies authorities?
Cumulative Frequency Percent Valid Percent Percent Valid 3, not satisfied 77 32.1 41.0 41.0 2, somewhat satisfied 82 34.2 43.6 84.6 1, satisfied 24 10.0 12.8 97.3 3 5 2.1 2.7 100.0 Total 188 78.3 100.0 Missing System 52 21.7 Total 240 100.0
5.07: How satisfied are you with the services you receive from local welfare institutions autthorities?
Cumulative Frequency Percent Valid Percent Percent Valid 3, not satisfied 80 33.3 40.4 40.4 2, somewhat satisfied 87 36.3 43.9 84.3 1, satisfied 31 12.9 15.7 100.0 Total 198 82.5 100.0 Missing System 42 17.5 Total 240 100.0
5.07: How satisfied are you with the services you receive from financial institutions authorities?
Cumulative Frequency Percent Valid Percent Percent Valid 3, not satisfied 72 30.0 37.5 37.5 2, somewhat satisfied 90 37.5 46.9 84.4 1, satisfied 28 11.7 14.6 99.0 3 2 .8 1.0 100.0 Total 192 80.0 100.0 Missing System 48 20.0 Total 240 100.0
371 5.07: How satisfied are you with the services you receive from medical institutions authorities?
Cumulative Frequency Percent Valid Percent Percent Valid 3, not satisfied 63 26.3 32.1 32.1 2, somewhat satisfied 92 38.3 46.9 79.1 1, satisfied 38 15.8 19.4 98.5 3 3 1.3 1.5 100.0 Total 196 81.7 100.0 Missing System 44 18.3 Total 240 100.0
5.07: How satisfied are you with the services you receive from educational institutions authorities?
Cumulative Frequency Percent Valid Percent Percent Valid 3, not satisfied 67 27.9 34.0 34.0 2, somewhat satisfied 96 40.0 48.7 82.7 1, satisfied 31 12.9 15.7 98.5 3 3 1.3 1.5 100.0 Total 197 82.1 100.0 Missing System 43 17.9 Total 240 100.0
5.07: How satisfied are you with the services you receive from utilitiies companies authorities?
Cumulative Frequency Percent Valid Percent Percent Valid 3, not satisfied 83 34.6 41.1 41.1 2, somewhat satisfied 89 37.1 44.1 85.1 1, satisfied 30 12.5 14.9 100.0 Total 202 84.2 100.0 Missing System 38 15.8 Total 240 100.0
5.07: How satisfied are you with the services you receive from insurance companies authorities?
Cumulative Frequency Percent Valid Percent Percent Valid 3, not satisfied 91 37.9 43.5 43.5 2, somewhat satisfied 86 35.8 41.1 84.7 1, satisfied 32 13.3 15.3 100.0 Total 209 87.1 100.0 Missing System 31 12.9 Total 240 100.0
372 5.12: How well do you trust family members in making decisions on your behalf?
Cumulative Frequency Percent Valid Percent Percent Valid 0/1 do not trust 35 14.6 14.6 14.6 2/3 indifferent/somewhat 77 32.1 32.2 46.9 4/5 trust 126 52.5 52.7 99.6 5 1 .4 .4 100.0 Total 239 99.6 100.0 Missing System 1 .4 Total 240 100.0
5.12: How well do you trust good old friends in making decisions on your behalf?
Cumulative Frequency Percent Valid Percent Percent Valid 0/1 do not trust 83 34.6 34.9 34.9 2/3 indifferent/somewhat 98 40.8 41.2 76.1 4/5 trust 56 23.3 23.5 99.6 5 1 .4 .4 100.0 Total 238 99.2 100.0 Missing System 2 .8 Total 240 100.0
5.12: How well do you trust work companions in making decisions on your behalf?
Cumulative Frequency Percent Valid Percent Percent Valid 0/1 do not trust 132 55.0 55.9 55.9 2/3 indifferent/somewhat 74 30.8 31.4 87.3 4/5 trust 29 12.1 12.3 99.6 5 1 .4 .4 100.0 Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
5.12: How well do you trust residential neighbors in making decisions on your behalf?
Cumulative Frequency Percent Valid Percent Percent Valid 0/1 do not trust 131 54.6 54.8 54.8 2/3 indifferent/somewhat 85 35.4 35.6 90.4 4/5 trust 22 9.2 9.2 99.6 5 1 .4 .4 100.0 Total 239 99.6 100.0 Missing System 1 .4 Total 240 100.0
373 5.12: How well do you trust local govt officials in making decisions on your behalf?
Cumulative Frequency Percent Valid Percent Percent Valid 0/1 do not trust 143 59.6 59.8 59.8 2/3 indifferent/somewhat 83 34.6 34.7 94.6 4/5 trust 12 5.0 5.0 99.6 5 1 .4 .4 100.0 Total 239 99.6 100.0 Missing System 1 .4 Total 240 100.0
5.12: How well do you trust state govt officials in making decisions on your behalf?
Cumulative Frequency Percent Valid Percent Percent Valid 0/1 do not trust 164 68.3 68.6 68.6 2/3 indifferent/somewhat 60 25.0 25.1 93.7 4/5 trust 14 5.8 5.9 99.6 5 1 .4 .4 100.0 Total 239 99.6 100.0 Missing System 1 .4 Total 240 100.0
5.12: How well do you trust federal govt officials in making decisions on your behalf?
Cumulative Frequency Percent Valid Percent Percent Valid 0/1 do not trust 158 65.8 66.1 66.1 2/3 indifferent/somewhat 64 26.7 26.8 92.9 4/5 trust 16 6.7 6.7 99.6 5 1 .4 .4 100.0 Total 239 99.6 100.0 Missing System 1 .4 Total 240 100.0
5.12: How well do you trust yourself in making decisions on your behalf?
Cumulative Frequency Percent Valid Percent Percent Valid 0/1 do not trust 26 10.8 10.9 10.9 2/3 indifferent/somewhat 54 22.5 22.6 33.5 4/5 trust 158 65.8 66.1 99.6 5 1 .4 .4 100.0 Total 239 99.6 100.0 Missing System 1 .4 Total 240 100.0
374 6.01: What insurance do you have?
Cumulative Frequency Percent Valid Percent Percent Valid none 74 30.8 31.0 31.0 medical only (or 1 other) 124 51.7 51.9 82.8 extensive (more than 1) 41 17.1 17.2 100.0 Total 239 99.6 100.0 Missing System 1 .4 Total 240 100.0
6.04: How would you best describe your health?
Cumulative Frequency Percent Valid Percent Percent Valid poor = bad 48 20.0 20.1 20.1 fair/good = ok 145 60.4 60.7 80.8 excellent = good 46 19.2 19.2 100.0 Total 239 99.6 100.0 Missing System 1 .4 Total 240 100.0
6.05: Have you had a need for health care or mdedical advice in the past 12 months and did not seek it?
Cumulative Frequency Percent Valid Percent Percent Valid no, didn't need or got help 163 67.9 68.5 68.5 yes, didn't get help (svc 39 16.3 16.4 84.9 oriented ans) yes, didn't get help 36 15.0 15.1 100.0 (personal ans) Total 238 99.2 100.0 Missing System 2 .8 Total 240 100.0
6.06: Do you worry about your health?
Cumulative Frequency Percent Valid Percent Percent Valid no 114 47.5 47.9 47.9 yes 119 49.6 50.0 97.9 2 5 2.1 2.1 100.0 Total 238 99.2 100.0 Missing System 2 .8 Total 240 100.0
375 6.13: How often do you go to sleep hungry?
Cumulative Frequency Percent Valid Percent Percent Valid never 101 42.1 42.4 42.4 sometimes 96 40.0 40.3 82.8 often 41 17.1 17.2 100.0 Total 238 99.2 100.0 Missing System 2 .8 Total 240 100.0
7.01: Do you feel discriminated against by political orientation?
Cumulative Frequency Percent Valid Percent Percent Valid no 224 93.3 93.3 93.3 yes 16 6.7 6.7 100.0 Total 240 100.0 100.0
7.01: Do you feel discriminated against in your community?
Cumulative Frequency Percent Valid Percent Percent Valid no 236 98.3 98.3 98.3 yes 4 1.7 1.7 100.0 Total 240 100.0 100.0
7.01: Do you feel discriminated against by age?
Cumulative Frequency Percent Valid Percent Percent Valid no 233 97.1 97.1 97.1 yes 7 2.9 2.9 100.0 Total 240 100.0 100.0
7.01: Do you feel discriminated against at work?
Cumulative Frequency Percent Valid Percent Percent Valid no 237 98.8 98.8 98.8 yes 3 1.3 1.3 100.0 Total 240 100.0 100.0
7.01: Do you feel discriminated against by gender?
Cumulative Frequency Percent Valid Percent Percent Valid no 238 99.2 99.2 99.2 yes 2 .8 .8 100.0 Total 240 100.0 100.0
376 7.01: Do you feel discriminated against at school?
Cumulative Frequency Percent Valid Percent Percent Valid no 238 99.2 99.2 99.2 yes 2 .8 .8 100.0 Total 240 100.0 100.0
7.01: Do you feel discriminated against by sexuality?
Cumulative Frequency Percent Valid Percent Percent Valid no 232 96.7 96.7 96.7 yes 8 3.3 3.3 100.0 Total 240 100.0 100.0
7.01: Do you feel discriminated against in your home?
Cumulative Frequency Percent Valid Percent Percent Valid no 237 98.8 98.8 98.8 yes 3 1.3 1.3 100.0 Total 240 100.0 100.0
7.01: Do you feel discriminated against by religion?
Cumulative Frequency Percent Valid Percent Percent Valid no 239 99.6 99.6 99.6 yes 1 .4 .4 100.0 Total 240 100.0 100.0
7.01: Do you feel discriminated against by/in other way?
Cumulative Frequency Percent Valid Percent Percent Valid no 239 99.6 99.6 99.6 yes 1 .4 .4 100.0 Total 240 100.0 100.0
7.02: What determined your level of formal education, personal choice?
Cumulative Frequency Percent Valid Percent Percent Valid no 125 52.1 53.9 53.9 yes 107 44.6 46.1 100.0 Total 232 96.7 100.0 Missing System 8 3.3 Total 240 100.0
377 7.02: What determined your level of formal education, financial cost?
Cumulative Frequency Percent Valid Percent Percent Valid no 155 64.6 66.8 66.8 yes 77 32.1 33.2 100.0 Total 232 96.7 100.0 Missing System 8 3.3 Total 240 100.0
7.02: What determined your level of formal education, time spent?
Cumulative Frequency Percent Valid Percent Percent Valid no 195 81.3 84.1 84.1 yes 37 15.4 15.9 100.0 Total 232 96.7 100.0 Missing System 8 3.3 Total 240 100.0
7.02: What determined your level of formal education, age?
Cumulative Frequency Percent Valid Percent Percent Valid no 214 89.2 92.2 92.2 yes 18 7.5 7.8 100.0 Total 232 96.7 100.0 Missing System 8 3.3 Total 240 100.0
7.02: What determined your level of formal education, location?
Cumulative Frequency Percent Valid Percent Percent Valid no 215 89.6 92.7 92.7 yes 17 7.1 7.3 100.0 Total 232 96.7 100.0 Missing System 8 3.3 Total 240 100.0
7.02: What determined your level of formal education, other?
Cumulative Frequency Percent Valid Percent Percent Valid no 224 93.3 97.0 97.0 yes 7 2.9 3.0 100.0 Total 231 96.3 100.0 Missing System 9 3.8 Total 240 100.0
378 7.03: Are you satisfied with your educational level?
Cumulative Frequency Percent Valid Percent Percent Valid no 159 66.3 67.7 67.7 yes 76 31.7 32.3 100.0 Total 235 97.9 100.0 Missing System 5 2.1 Total 240 100.0
7.13: What kind of life do you have?
Cumulative Frequency Percent Valid Percent Percent Valid good 41 17.1 17.2 17.2 average 133 55.4 55.6 72.8 bad 65 27.1 27.2 100.0 Total 239 99.6 100.0 Missing System 1 .4 Total 240 100.0
7.14: Do you consider yourself poor, average, or well-off?
Cumulative Frequency Percent Valid Percent Percent Valid poor 106 44.2 45.3 45.3 average 101 42.1 43.2 88.5 well off 27 11.3 11.5 100.0 Total 234 97.5 100.0 Missing System 6 2.5 Total 240 100.0
7.18: Do you feel that your children will do better than you?
Cumulative Frequency Percent Valid Percent Percent Valid no 27 11.3 13.8 13.8 yes 167 69.6 85.2 99.0 2 2 .8 1.0 100.0 Total 196 81.7 100.0 Missing System 44 18.3 Total 240 100.0
379 7.19: Do you feel that you are doing better than your parents?
Cumulative Frequency Percent Valid Percent Percent Valid no 102 42.5 51.5 51.5 yes 96 40.0 48.5 100.0 Total 198 82.5 100.0 Missing System 42 17.5 Total 240 100.0
8.01: Do you feel that the gaming industry has helped create jobs for those in your neighborhood?
Cumulative Frequency Percent Valid Percent Percent Valid no 19 7.9 9.5 9.5 yes 180 75.0 90.5 100.0 Total 199 82.9 100.0 Missing System 41 17.1 Total 240 100.0
8.02: Of the people you personally know who work in the gaming industry, what kind of work do they do?
Cumulative Frequency Percent Valid Percent Percent Valid 139 57.9 57.9 57.9 desk clerk 6 2.5 2.5 60.4 housekeeping 93 38.8 38.8 99.2 security 2 .8 .8 100.0 Total 240 100.0 100.0
8.02: Of the people you personally know who work in the gaming industry, what kind of work do they do?
Cumulative Frequency Percent Valid Percent Percent Valid 184 76.7 76.7 76.7 cook/waiter 53 22.1 22.1 98.8 hostess 2 .8 .8 99.6 slots 1 .4 .4 100.0 Total 240 100.0 100.0
380 8.03: How do you feel about the local gaming industry: it creates wealth in the community?
Cumulative Frequency Percent Valid Percent Percent Valid disagree 142 59.2 60.2 60.2 agree 94 39.2 39.8 100.0 Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
8.03: How do you feel about the local gaming industry: it is an acceptable form of entertainment?
Cumulative Frequency Percent Valid Percent Percent Valid disagree 158 65.8 66.9 66.9 agree 78 32.5 33.1 100.0 Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
8.03: How do you feel about the local gaming industry: it is an unacceptable form of entertainment?
Cumulative Frequency Percent Valid Percent Percent Valid disagree 203 84.6 86.0 86.0 agree 33 13.8 14.0 100.0 Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
8.03: How do you feel about the local gaming industry: it is an acceptable industry in which to work?
Cumulative Frequency Percent Valid Percent Percent Valid disagree 145 60.4 61.4 61.4 agree 91 37.9 38.6 100.0 Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
381 8.03: How do you feel about the local gaming industry: it is an unacceptable industry in which to work?
Cumulative Frequency Percent Valid Percent Percent Valid disagree 214 89.2 90.7 90.7 agree 22 9.2 9.3 100.0 Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
8.03: How do you feel about the local gaming industry: it is immoral, but acceptable because it has provided jobs and income for the area?
Cumulative Frequency Percent Valid Percent Percent Valid disagree 134 55.8 56.8 56.8 agree 102 42.5 43.2 100.0 Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
8.03: How do you feel about the local gaming industry: it is immoral and completely unacceptable?
Cumulative Frequency Percent Valid Percent Percent Valid disagree 172 71.7 72.9 72.9 agree 64 26.7 27.1 100.0 Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
8.03: How do you feel about the local gaming industry: it has helped reduce the level of poverty?
Cumulative Frequency Percent Valid Percent Percent Valid disagree 121 50.4 51.3 51.3 agree 115 47.9 48.7 100.0 Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
382 8.03: How do you feel about the local gaming industry: it has not helped to reduce the level of poverty?
Cumulative Frequency Percent Valid Percent Percent Valid disagree 216 90.0 91.5 91.5 agree 20 8.3 8.5 100.0 Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
8.03: How do you feel about the local gaming industry: it has made life worse around here?
Cumulative Frequency Percent Valid Percent Percent Valid disagree 204 85.0 86.4 86.4 agree 32 13.3 13.6 100.0 Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
8.03: How do you feel about the local gaming industry: it has made life better around here?
Cumulative Frequency Percent Valid Percent Percent Valid disagree 119 49.6 50.4 50.4 agree 117 48.8 49.6 100.0 Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
8.04: Were you a resident of Tunica or Coahoma county before the casinos arrived (prior to 1992)?
Cumulative Frequency Percent Valid Percent Percent Valid no 28 11.7 12.8 12.8 yes 188 78.3 86.2 99.1 2 2 .8 .9 100.0 Total 218 90.8 100.0 Missing System 22 9.2 Total 240 100.0
383 8.04: If resident prior, did you participate in activities or discussions regarding the development of the casino industry in the area?
Cumulative Frequency Percent Valid Percent Percent Valid no 188 78.3 86.2 86.2 yes 29 12.1 13.3 99.5 3 1 .4 .5 100.0 Total 218 90.8 100.0 Missing System 22 9.2 Total 240 100.0
8.08: overall conclusion regaring the impact of the gaming industry on your well being within your living environment?
Cumulative Frequency Percent Valid Percent Percent Valid 1/2 significantly or 69 28.8 29.2 29.2 somewhat worse 3, no different 78 32.5 33.1 62.3 4/5 somewhat better 89 37.1 37.7 100.0 or significantly better Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
8.08: overall conclusion regaring the impact of the gaming industry on your well being within your financial environment?
Cumulative Frequency Percent Valid Percent Percent Valid 1/2 significantly or 52 21.7 22.0 22.0 somewhat worse 3, no different 78 32.5 33.1 55.1 4/5 somewhat better 106 44.2 44.9 100.0 or significantly better Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
384 8.08: overall conclusion regaring the impact of the gaming industry on your well being within your work environment?
Cumulative Frequency Percent Valid Percent Percent Valid 1/2 significantly or 58 24.2 24.6 24.6 somewhat worse 3, no different 85 35.4 36.0 60.6 4/5 somewhat better 93 38.8 39.4 100.0 or significantly better Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
8.08: overall conclusion regaring the impact of the gaming industry on your well being within your community/social environment?
Cumulative Frequency Percent Valid Percent Percent Valid 1/2 significantly or 65 27.1 27.5 27.5 somewhat worse 3, no different 92 38.3 39.0 66.5 4/5 somewhat better 79 32.9 33.5 100.0 or significantly better Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
8.08: overall conclusion regaring the impact of the gaming industry on your well being within your health/nutritional environment?
Cumulative Frequency Percent Valid Percent Percent Valid 1/2 significantly or 58 24.2 24.6 24.6 somewhat worse 3, no different 123 51.3 52.1 76.7 4/5 somewhat better 55 22.9 23.3 100.0 or significantly better Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
385 8.08: overall conclusion regaring the impact of the gaming industry on your well being within your attitudes/beliefst?
Cumulative Frequency Percent Valid Percent Percent Valid 1/2 significantly or 73 30.4 30.9 30.9 somewhat worse 3, no different 111 46.3 47.0 78.0 4/5 somewhat better 52 21.7 22.0 100.0 or significantly better Total 236 98.3 100.0 Missing System 4 1.7 Total 240 100.0
9.01: Overall, how would you describe your past level of well being?
Cumulative Frequency Percent Valid Percent Percent Valid 0 4 1.7 1.7 1.7 in extreme hardship 25 10.4 10.6 12.3 not very well off 80 33.3 34.0 46.4 neither in hardship 40 16.7 17.0 63.4 or well off quite well off 53 22.1 22.6 86.0 very well off 33 13.8 14.0 100.0 Total 235 97.9 100.0 Missing System 5 2.1 Total 240 100.0
9.02: Overall, how would you describe your current level of well being?
Cumulative Frequency Percent Valid Percent Percent Valid 0 4 1.7 1.7 1.7 in extreme hardship 14 5.8 6.0 7.7 not very well off 79 32.9 33.6 41.3 neither in hardship 30 12.5 12.8 54.0 or well off quite well off 68 28.3 28.9 83.0 very well off 40 16.7 17.0 100.0 Total 235 97.9 100.0 Missing System 5 2.1 Total 240 100.0
386 VITA
TRACEY L. FARRIGAN
Post Secondary Degrees
Master of Science University of New Hampshire Resource Economics, May 1999 Bachelor of Arts State University of New York at Plattsburgh Geography & Business Economics, December 1994 Associate in Science Hudson Valley Community College International Business, May 1995
Professional Positions Held
Consultant, The Aspen Institute, Economic Opportunities Program, 2004-present Research Assistant, Department of Geography, Penn State, 2001- 2004 Instructor, Department of Geography, Penn State, 2003 Research Assistant, Penn State Cooperative Extension, 1999-2001 Teaching Assistant, Department of Geography, Penn State, 1999-2001 Research Assistant, Department of Resource Economics and Development, University of New Hampshire, 1997-1999 Research Associate, USDA Forest Service, State and Private Forestry, 1997-1998
Awards and Distinctions
National Science Foundation, Doctoral Dissertation Improvement Grant, 2003 Ruby Miller Grant , Department of Geography, The Pennsylvania State University, 2002 The Society of Woman Geographers, fellowship, 2001 Northeast Regional Center for Rural Development , Research Grant, 1998 Northern New England American Planning Association Service Award , 1998 SUNY Plattsburgh School of Business and Economics Award for Excellence , 1994
Publications
Poverty, Sustainability, and the Culture of Despair: Can Sustainable Development Strategies Support Poverty Alleviation in America’s Most Environmentally Challenged Communities? with Amy Glasmeier. The Annals, American Academy of Political and Social Science , volume 590, number 1, pp. 131-149, 2003.
Welcome Back Downtown: A Guide to Revitalizing Pennsylvania’s Small Downtowns with Martin Shields. The Center for Rural Pennsylvania, Harrisburg PA, 2002.
Anatomy of a Community-Level Fiscal Impact Model: FIT-4-NH with John Halstead, Martin Shields, Doug Morris, and Ed Jansen. The Review of Regional Studies, volume 31, number 1, pp. 13-38, 2001.