COMMUNICATION AND CONSUMER CONFIDENCE: THE ROLES OF MASS MEDIA, INTERPERSONAL COMMUNICATION, AND LOCAL CONTEXT
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
the Degree of Doctor of Philosophy in the Graduate
School of The Ohio State University
By
Lewis R. Horner, M.A.
*****
The Ohio State University 2008
Dissertation Committee:
Dr. Gerald M. Kosicki, Adviser
Dr. Carroll J. Glynn ______Dr. Herbert F. Weisberg Adviser Communication Graduate Program Copyright by
Lewis R. Horner
2008 ABSTRACT
The purpose of this study was to examine the role of different channels of information on individual consumer confidence. Individual consumer confidence is a person’s expectations of future economic conditions. Consumer confidence has economic and political consequences for society. Scholars do not agree on the role of different sources of information in consumer confidence, particularly the role of mass media. Many scholars consider the economy and unemployment, which is known to influence consumer confidence, to be obtrusive, meanings that individuals can acquire issue information from direct experience or observation. Evidence supports both news and direct experience or observation as significant sources of information.
This study examined the effects of attention to news about the economy, interpersonal discussion of the economy, and local unemployment rates on individual consumer confidence. Data were from six months of the Buckeye State Poll during a period of worsening economic conditions in 2001 and 2002. The survey included a unique set of attention to news about the economy measures that focused on different geographic domains and types of media. Local unemployment rates were matched to individuals based on county of residence.
ii Both personal economic experience and attention to news about the economy were significant predictors of individual consumer confidence. Personal economic experience was measured by household unemployment. The majority of households do not experience unemployment, meaning the attention to news about the economy should provide their information. However, attention to news about the economy had a small effect. Of the different forms of attention to news about the economy, attention to news about the local economy on television had the strongest effect. Interpersonal discussion of the economy had no effect. Observation of the economy via local unemployment rates had an unexpected relationship with confidence. Increasing unemployment over a twelve-month period was often associated with higher levels of confidence, not lower levels. This may have been due to the historic circumstances following the September 11 terrorist attacks or because of seasonal factors in some of the unemployment data. The study concludes with a discussion of its limitations and suggestions for future research.
iii For Ann
iv ACKNOWLEDGMENTS
To everyone who has helped me get to this point, mere thanks are not enough.
Jerry Kosicki, my adviser, made this dissertation possible. In 2001 Jerry was the
PI for the Buckeye State Poll, and he asked Ida Mirzaie and me to come up with some additional questions to add to the economic component of BSP. I contributed four questions on attention to media based on some thoughts I had, not guided by any theory.
Those questions piqued my interest in consumer confidence and are central to this dissertation. More than that, Jerry has been my teacher, adviser for both my master’s thesis and this dissertation, boss at the Center for Survey Research, colleague and friend, and for all of these I thank him.
Carroll Glynn and Herb Weisberg were willing to share their time and expertise with to me even though they are both over-committed department chairs. It was a privilege to work with them. They are first-rate scholars and fine individuals. I thank them both.
Special thanks to the former interviewers at the Center for Survey Research who collected these data and to the respondents who were willing to participate in the interviews. Thanks to the Columbus Dispatch for making these data available for research. Thanks, too, to the excellent University Libraries.
v In 2004, Elizabeth Stasny convinced Doug Wolfe and Tom Bishop to hire me as a graduate assistant at the Statistical Consulting Service. Everyone in the Statistics department was good to me, especially Jeni Squiric and Paul Brower. Chris Holloman, now director of the Statistical Consulting Service, gave me valuable advice on multilevel modeling and how I might set my models up in SPSS. I recommend the Statistical
Consulting Service to everyone. I cannot thank the folks at the Statistics department enough.
Former bosses Rob Daves, Rossana Armson, and Paul Lavrakas gave me some wonderful opportunities and made me a better researcher. Their influence is in here.
They have my warmest thanks.
Matt Courser, who was my colleague at the Center for Survey Research, made it his mission to be my one-man support team. He’s a good friend. Thanks, Matt.
Breakfast?
Finally, my wife, Ann, has endured piles of books, piles of papers, and the detritus
I tend to create. She has shouldered more burdens than she should have and has been there for me. I look forward to her smile when I graduate. Thank you, Ann, for everything. England?
vi VITA
September 23, 1956 ...... Born – Kenton, Ohio
1979 ...... B.S. Allied Medical Professions The Ohio State University
1989 ...... M.A., Journalism The Ohio State University
1999-2004 ...... Research Associate Center for Survey Research The Ohio State University
2004-2006 ...... Graduate Research Assistant, Statistical Consulting Service, The Ohio State University
PUBLICATIONS
Horner, L. R. (2008). Web Surveys. In P. J. Lavrakas (Ed.), Encyclopedia of Survey Research Methods. Newbury Park, CA: Sage.
Wright-Isak, C., Faber, R. J., & Horner, L. R. (1997). Comprehensive measurement of advertising effectiveness: Notes from the marketplace. In W. D. Wells (Ed.), Measuring Advertising Effectiveness (pp. 3-12). Mahwah, NJ: Lawrence Erlbaum Associates.
FIELDS OF STUDY
Major Field: Communication
vii TABLE OF CONTENTS
Page
Abstract ...... ii Dedication ...... iv Acknowledgments ...... v Vita...... vii List of Figures ...... xi
Chapters:
1. Introduction...... 1
2. Conceptual Framework ...... 5
Issue Obtrusiveness ...... 5 The Role of Media in Issue Concern ...... 5 Obtrusiveness Research ...... 9 Theoretical issues...... 9 Operational issues...... 11 Channels of information...... 13 Local context and obtrusiveness...... 14 Contextual Effects ...... 15 Local information flow...... 16 Summary ...... 19 Consumer Confidence ...... 20 Obtrusiveness and Consumer Confidence ...... 20 Economic Implications of Consumer Confidence ...... 21 Political Implications of Consumer Confidence ...... 23 Controversy over the Role of Media ...... 26 The Development of Consumer Confidence Measures ...... 28 Conceptual considerations...... 31 Operational considerations...... 34 Consumer confidence indexes...... 37
viii Factors Affecting Consumer Confidence and Perceptions of the Economy ...... 40 Personal Economic Circumstances...... 41 Group Membership...... 43 Political Predispositions...... 44 Information...... 45 Interpersonal Discussion...... 46 Organizational Communication...... 47 Mass Media...... 47 Mass Media and the Economy...... 48 Negative coverage of the economy...... 53 Political bias in coverage of the economy...... 54 Local Context...... 55 Local information flow...... 56 Attention, Adaption, and the Timing of Research ...... 57 Summary and Hypotheses ...... 59
3. Method ...... 67
Data ...... 67 Measures ...... 69 Consumer Confidence ...... 69 Personal Financial Circumstances ...... 70 Group Membership ...... 71 Political Partisanship ...... 73 Information Channels...... 73 Local Economic Context ...... 75 Analysis Plan ...... 78
4. Analysis and Results ...... 81
Individual Consumer Confidence ...... 82 Analysis...... 82 Relevant hypotheses...... 94 Current Conditions Component ...... 99 Analysis...... 99 Relevant hypotheses...... 103
ix Expectations Component ...... 106 Analysis...... 106 Relevant hypotheses...... 110 Interpersonal Communication about the Economy ...... 111 Analysis...... 111 Relevant hypotheses...... 113 Attention to News about the Economy ...... 114 Analysis...... 114 Relevant hypotheses...... 121 Summary ...... 122
5. Conclusions ...... 127
Discussion of the Findings...... 128 Study Relationship to Previous Research ...... 140 Study Limitations and Suggestions for Future Research ...... 141 Some Final Comments...... 147
Appendices
A Bivariate Correlations among Study Variables ...... 149
B Survey Question Wording and Response Options ...... 162
C Missing Values Data Comparison ...... 172
List of References ...... 175
x LIST OF FIGURES
Figure Page
1. Question items for the Index of Consumer Sentiment ...... 37
2. Question items for the Consumer Confidence Index ...... 38
3. Survey response statistics...... 68
4. Example multilevel equations for individual consumer confidence and attention to news about the economy ...... 79
5. Ohio Consumer Confidence Index and average individual consumer confidence score by month...... 83
6. Percentages of neutral responses to individual Index of Consumer Sentiment items by month ...... 84
7. Multilevel analysis of individual consumer confidence using attention to news index, county-level data ...... 86
8. Multilevel analysis of individual consumer confidence using individual attention to news items, county-level data ...... 88
9. Ordinary least squares analysis of individual consumer confidence using attention to news index, county-level data ...... 90
10. Multilevel analysis of individual consumer confidence using attention to news index, MSA-level data ...... 93
11. Multilevel analysis of individual consumer confidence using geographic focus attention to news indexes, county-level data ...... 97
12. Multilevel analysis of individual consumer confidence using media focus attention to news indexes, county-level data ...... 98
xi 13. Multilevel analysis of the current conditions component using attention to news index, county-level data ...... 100
14. Multilevel analysis of the current conditions component using individual attention to news items, county-level data ...... 102
15. Ordinary least squares analysis of the current conditions component using attention to news index, county-level data ...... 104
16. Multilevel analysis of the expectations component using attention to news index, county-level data ...... 105
17. Multilevel analysis of expectations component using individual attention to news items, county-level data ...... 107
18. Ordinary least squares analysis of the expectations component using attention to news index, county-level data ...... 109
19. Multilevel analysis of interpersonal communication about the economy using attention to news index, county-level data ...... 112
20. Multilevel analysis of attention to news about the economy variables, county-level data ...... 115
21. Multilevel analysis of attention to news about the economy variables, MSA-level data ...... 118
22. Summary of Outcomes of Hypotheses...... 124
23. Ohio Seasonally Adjusted and Unadjusted Unemployment Rates ...... 131
24. U.S. and Ohio Aggregate Consumer Confidence Levels ...... 133
25. U.S. and Ohio Seasonally Adjusted Unemployment Rates ...... 134
26. Aggregate Ohio Consumer Confidence, all households and minus households with unemployment...... 139
xii 27. Bivariate correlations among all study variables ...... 150
28. Means, medians and standard deviations for full sample and sample without missing values...... 173
xiii CHAPTER 1
INTRODUCTION
Early communication scholars who expected to find strong media effects on public opinion were disappointed. Mounting evidence suggested weak media effects.
In 1972, a pioneering study suggested a media effect not previously considered.
McCombs and Shaw (1972) found that the amount of issue news coverage correlated with the public’s perception of issues’ importance, what McCombs and Shaw called agenda-setting. The agenda-setting effect was weak for some issues, however. Zucker
(1978) argued that some issues are obtrusive, meaning the public could acquire issue information through personal experience rather than relying on media. There has been little scholarship on the communication processes for obtrusive issues. An exception has been a work by Demers, Craff, Choi and Pessin (1989), who found that issue experience could prime individuals to media issue content or increase attention to issue news. The literature paints an incomplete picture of the communication processes for obtrusive issues. Part of the problem may be that scholars have preferred to focus on the effects of a single channel of information rather than considering multiple communication channels the same time. Contextual analysis provides a conceptual framework and some tools for examining multiple communication processes for obtrusive issues.
1 Issue obtrusiveness has been defined as direct experience with an issue (Demers et al., 1989; Zucker, 1978). This implies local issue conditions. Scholars working in contextual analysis have developed a framework for thinking about local information flows. Books and Prysby (1991) argued that local conditions can create unique information environments, which can affect what information individuals attend to and how that information might be perceived. They suggested several local channels through which issue information might be acquired: direct experience, observation, interpersonal communication, local organizational communication, and local media.
This study examines the communication processes for an ostensibly obtrusive issue, the economy. The dependent variable is consumer confidence. Consumer confidence is predictive of short-term changes in consumer spending on durable goods, which is a major factor in the economy (Katona, 1975). The public’s perceptions of the economy, which are closely related to consumer confidence, are enduring factors in presidential voting (Lewis-Beck & Paldam, 2000). Consumer confidence is an excellent topic to study for insights into the communication process. Scholars disagree about the role of media in changes in consumer confidence. George Katona, who pioneered the study of consumer confidence, argued that information from mass media caused changes in consumer confidence. Time-series research shows that media content about the economy drives changes in consumer confidence (Blood & Phillips,
1995; Fan & Cook, 2003; Rattliff, 2001; Tims, Fan, & Freeman, 1989). Other scholars argue that individuals acquire information about the economy from their everyday activities (e.g., Haller & Norpoth, 1997). Haller and Norpoth and Katona (1960) found
2 no evidence for a media effect on consumer confidence using cross-sectional data.
Another reason for studying consumer confidence is that there is evidence from contextual analysis that local unemployment rates are related to perceptions of national economic conditions (Books & Prysby, 1999; Weatherford, 1983b). Unemployment is one of the main economic factors associated with changes in consumer confidence
(Katona, 1975). This suggests that local information processes could affect consumer confidence.
The data for this study are from the Buckeye State Poll, a joint project of the
Columbus Dispatch, WBNS-TV, and The Ohio State University from 1996 to 2002.
The BSP was a monthly survey of adult Ohioans about the economy and other topics.
The last six months of the BSP, from November 2001 to April 2002, contained a set of four questions that parsed attention to news about the economy into different components. These questions differentiated between attention to news about the local or national economies. In addition, it was possible to associate local unemployment rate information with each survey respondent.
The analysis pits three perspectives–agenda-setting, issue obtrusiveness, and the cognitive priming/media dependency hypothesis–against each other using measures of attention to news about the economy, interpersonal communication about the economy, and local unemployment rate information as a proxy for observation of the economy to predict individual consumer confidence. Other hypotheses examine the role of interpersonal communication on consumer confidence, and the effect of local conditions on attention to news about the economy. Applying the unemployment rate
3 to everyone living in an area violates the linear regression assumption of independent observations. Multilevel analysis relaxes this assumption, and so this method was used for the analyses.
The second chapter presents the background and framework for the study. I first discuss the communication hypotheses–agenda-setting, issue obtrusiveness, and cognitive priming/media dependency–then discuss contextual analysis and Books and
Prysby’s (1991) idea of an information environment. Next, I discuss the conceptualization and measurement of consumer confidence. Finally, I present a series of hypotheses about the relationship between communication behaviors and individual consumer confidence. Several of these hypotheses represent each of the three communication perspectives and essentially pit the perspectives against each other. The third chapter discusses the data, measures and analysis plan. The major dependent variable is individual consumer confidence, which is different from the aggregate measure of consumer confidence reported in media. The calculation of individual confidence differs from the calculation of aggregate confidence, but the month-to- month movement of the average of the individual consumer confidence is similar to the movement of the aggregate confidence measure. The fourth chapter presents the findings and discusses the results. The final chapter summaries the results and discusses the limitations of the study with recommendations for improvements to the study design.
4 CHAPTER 2
CONCEPTUAL FRAMEWORK
Issue Obtrusiveness
The Role of Media in Issue Concern
In the opening of Public Opinion, Walter Lippmann (1922) described a situation in which Englishmen, Frenchmen, and Germans living on an isolated island in 1914 learned from a mail boat that their countries had been at war since the start of the World
War six weeks earlier. Lippmann used this example to show how indirect much of our knowledge of the world is. He noted that we act “not on direct and certain knowledge, but on pictures” made by or given to us (p. 16). Lippmann was concerned that the lack of direct experience with issues leaves the public vulnerable to manipulated or inaccurate information for use in their roles as citizens. Since then a great deal research has focused on the role of media in public opinion. There are, however, issues for which significant portions of a population need not rely on media for information.
Information about these issues might be acquired directly through personal experience or observation or indirectly through other information channels. What are the communication processes for these types of issues? What role, if any, do media play in public opinion about these issues?
5 A major area of work regarding the influence of the media on the public is agenda-setting. McCombs and Shaw (1972) found a correlation between the levels of media coverage of issues and the public’s view of the importance of those issues. They argued that media were setting the public agenda by deciding which issues to cover and how much coverage the issues would be given. Since 1972, there has been a wealth of research in agenda-setting (Weaver, 2007), but there still remain conceptual and operational issues with the theory (Scheufele & Tewksbury, 2007). The original concept has been expanded to include the influence of different spheres on each other’s agendas. For example, scholars have examined the influence of the policy agenda on media, media on policy, and influence of the public agenda on media (e.g., Tan &
Weaver, 2007). The bulk of the research, however, has been on what has been described as the transfer of the media agenda to the public (Kiousis & McCombs,
2004). One area of discussion concerns the mechanism or mechanisms of agenda- setting. McCombs and Shaw did not specify a mechanism for the agenda transfer
(Takesita, 2005). Heavy media coverage of issues is thought to make those issues more salient than issues receiving little or no coverage, but this could happen through different mechanisms. Takeshita (2005) notes that the term ‘salience’ has two meanings in agenda-setting research, which are related to possible mechanisms for the agenda transfer. For some scholars, salience means an increased accessibility of constructs in memory. Exposure to high-volume, high-prominence news coverage of issues is thought to repeatedly activate memory related to those issues. The repeated memory activation increases the accessibility of the issue constructs such that they will
6 more likely to be mentioned when survey respondents are asked about think about which issues are important. Takeshita characterized this version of agenda-setting as
“an almost mindless, mechanical response based on rote learning from media (p. 276).”
One might argue that the low to moderate correlations between the media agenda and the public agenda in some studies (e.g., Tan & Weaver, 2007) suggest that the public does not simply accept the media agenda. The second meaning of salience is perceived importance (Takeshita, 2005). Takeshita argues that the original discussions of agenda- setting focused on salience as issue importance and not accessibility. This distinction between accessibility and perceived importance affects how agenda-setting is operationalized (Scheufele, 2000). Defining salience in terms of issue importance implies more thoughtfulness and consideration of issues than mere exposure and increased memory accessibility. A second area of discussion among scholars regarding agenda-setting is what is termed ‘attribute’ or ‘second order’ agenda-setting. As originally presented, agenda-setting applied only to the transfer of the media agenda to the public; it did not address how people thought about the issues on the agenda.
McCombs (2004) has argued that media attention to different issue attributes makes those attributes more salient in the public mind. In some respects this appears similar to framing, but Price and Tweksbury (1997) argue that agenda-setting concerns accessibility effects and framing concerns applicability effects. Pan and Kosicki (1993) described framing in terms discourse devices such as the thematic or rhetorical structures used by media and how they relate to audiences’ causal reasoning about issues. Causal reasoning might attributions about issue causes and responsibilities more
7 salient. This suggests more than a simple transfer from media to public.
Agenda-setting may be contingent on a number of factors including issue obtrusiveness (McCombs, 2005). Zucker (1978) argued that the effect of media on issue agenda-setting depends in part on what he called an issue’s “obtrusiveness.” He claimed that the less direct experience the public has with an issue, the more influence media will have on public opinion. Issues are obtrusive when individuals can acquire issue information from personal experience and observation. Because Zucker was focusing on agenda-setting, he was thinking about information that might be used to determine an issue’s importance. It is possible that for obtrusive issues individuals might use information from media for purposes such as better understanding an issue or making inferences about issue responsibility. To test his hypothesis, Zucker examined public opinion and television news coverage for several issues that he had categorized as either obtrusive or unobtrusive. He found that the relationship between the perception of issue importance and television news coverage was lower for issues he had categorized at obtrusive, such as the cost of living, unemployment, and energy, than for unobtrusive issues, such as of pollution and drugs. A concept similar to issue obtrusiveness is issue thresholds (Lang & Lang, 1981). Lang and Lang argued that the effect of media on public opinion depends on the proportion of the population directly affected by the issue. As the number of people affected by an issue increases, the influence of media on opinion will decrease. Media influence on public opinion is lowest for issues that affect nearly everyone, low-threshold issues, and is highest for issues that are remote from most of the population, high-threshold issues. A third
8 scholar in this area is Neuman (1990). He examined the relationship between levels of news coverage and public concern about issues. Neuman found that the influence of news coverage on public opinion was stronger for some issues than for others. He argued that media coverage of issues was less influential for issues for which the public could react to real-world cues.
The common element among the works of these scholars is that for some issues the public can acquire issue information through channels other than media, which decreases the influence of media on public opinion. Another group of scholars, however, argues that issue obtrusiveness could instead increase media influence on public opinion. Demers, Craff, Choi, and Pessin (1989) noted that a few studies had found agenda-setting effects for some issues that were often considered obtrusive. As an explanation, Demers et al. offered what they called the cognitive-priming contingency hypothesis, which predicted that personal experience with an issue makes individuals more sensitive to news about the issue. They examined news coverage and public opinion for several issues that they had classified as obtrusive or unobtrusive.
They found no support for the obtrusiveness hypothesis and some support for the cognitive priming hypothesis.
Obtrusiveness Research
Theoretical issues.
The work of Demers et al. (1989) contradicts the work of Zucker (1978), Lang and Lang (1981), and Neuman (1990). The existing research makes it difficult to tease out the underlying processes and contingencies that might explain these contradictory
9 findings. One problem has been a mismatch between micro-level theory and macro- level analyses. Agenda-setting is often described and analyzed at the macro level, but obtrusiveness is defined at the micro level. For example, Zucker (1978) posited that individuals acquire information about obtrusive issues from personal experience or observation, which is an individual-level process, but he tested his hypothesis using macro-level opinion and news content data. Demers et al. (1989) framed their cognitive priming hypothesis in terms of both cognitive priming and media dependency theory.
Cognitive priming is a psychological theory that argues that thought processes are influenced by recently activated memories. When individuals encounter and process information about an obtrusive issue, memory traces associated with that issue are activated. Those memory traces are easier to activate if the issue is soon encountered in media, increasing the chance that an individual will pay attention to the news, which increases the possibility of media influence. Cognitive priming theory does not suggest that experience with an issue will lead to increased exposure or attention to news about the issue. This suggests that cognitive priming may be more likely to occur among those who have direct experience with an issue and attend to news media regularly.
The second theory on which Demers et al. based their hypothesis was media dependency, a sociological theory. Unlike cognitive priming, media dependency theory posits a reason for individuals attend to media about an issue. The media system is part of the social structure and controls information resources; it collects, processes, and distributes information (Ball-Rokeach, 1985). Media-system dependency occurs when individuals must rely on the media system for information needed to achieve goals,
10 which indicates a problem-solving motivation. If individuals perceive part of their social environment as unpredictable or threatening, they may turn to media for information to cope with the uncertainty or threat. Those who seek media information are more likely to be influenced by media regardless of their regular media use patterns.
Like Zucker, Demers et al. used macro-level data that could not address the micro-level foundation of their hypothesis.
Operational issues.
Another problem area has been the operationalization of issue obtrusiveness.
Scholars have categorized the issues in their studies as either obtrusive or unobtrusive.
Demers et al. (1989) argued there is a continuum of obtrusiveness. Demers et al. noted that obtrusiveness has been operationalized inconsistently across studies. For example, some researchers categorized crime as obtrusive, but others categorized it as unobtrusive. In another study, energy was categorized as obtrusive during some time periods and unobtrusive during others. One study operationalized obtrusiveness U.S. involvement in foreign issues (Lee, 2004). There does not appear to be a consistent rationale or rule for classifying issues as obtrusive or unobtrusive other than researchers’ own sense of obtrusiveness. The definitions of obtrusiveness offer little guidance on how issues should be classified. Zucker (1978) defined obtrusive issues as those with which people had direct experience. Demers et al. added the stipulation that information from personal experience must be independent of media exposure to an issue. Issue thresholds are defined in terms of the proportion of people directly affected by an issue (Lang & Lang, 1981). We see the limits of these definitions, however, if we
11 try to apply them at the individual level. Consider the issues of unemployment and crime. In the case of unemployment, often categorized as an obtrusive issue, the majority of adults in the workforce remain employed even during periods of high unemployment. Is unemployment obtrusive for individuals who are employed? The literature suggests that many people can be indirectly affected by unemployment
(Curtin, 2003b), and this may make unemployment obtrusive for them. Crime has been classified as both as obtrusive and unobtrusive. Most people do not have direct experience with serious crime, yet concern about crime is often high. We know that fear of crime or concern about crime is often not related to actual experience (e.g.,
Taylor & Hale, 1986). Fear of street crime may lead to avoidance behaviors, such as moving to low-crime areas, which could reduce the chance of actual experience with crime. Miettinen (1998) called crime psychologically obtrusive. She argued that some issues were physically obtrusive, meaning that individuals directly encountered aspects of the issues, but other issues were psychologically obtrusive, meaning individuals worried about those issues. This approach is problematic, however, because it does not suggest why concern about psychologically obtrusive issues might fluctuate. If we hypothesize that media have little influence on opinion about obtrusive issues and few people have direct experience with the issue, what causes temporal fluctuations in public concern about obtrusive issues? If information is a factor in public concern about obtrusive issues, then part of the public must acquire issue information from somewhere other than direct experience.
12 Channels of information.
This points out a major limitation of issue obtrusiveness research: the focus has been on only two channels of information, personal observation or experience and mass media. Further, these channels have been generally considered alternatives and not possible complements. Individuals’ use of communication channels is based on whether the channels provide needed information, not other criteria (Chaffee, 1982).
We might expect individuals to use channels that provide needed information. To better understand the processes at work in public opinion about obtrusive issues, we need to consider other possible channels of information acquisition. One channel that immediately comes to mind is interpersonal communication. Zucker (1978) recognized the value of interpersonal communication, but he did not address its influence on opinion about obtrusive issues. Demers et al. (1989) specifically excluded interpersonal communication as a channel of information. It seems reasonable, however, that individuals with might talk about their experiences or observations. For example, we may learn about unemployment from friends, family or neighbors who become unemployed (Adams & Green, 1965). Similarly, individuals may know others who have been crime victims. Interpersonal communication could be a valuable source of information for some individuals; excluding it as a channel of information is theoretically limiting. Zucker mentioned another channel of information, one largely ignored in media research: local media. Obtrusiveness studies have focused on either national or local coverage of issues (Hester & Gibson, 2007), with a predominance of studies looking at national-level coverage. At least one study has examined both local
13 and national coverage of an issue at the same time (Hester & Gibson, 2007). Zucker thought that many people might learn about crime from local media. Local media could provide information about the areas where individuals live and work, which may be more relevant than information from more distant locations (Weatherford, 1983b).
Local context and obtrusiveness.
The idea of localness is often missing from obtrusiveness research. The definitions of issue obtrusiveness imply that some aspects of the issues are immediate and close to individuals. Issue conditions often vary across locations (e.g., Hester &
Gibson, 2007; Jablonski & Daniele, 1998). For example, we know that unemployment and crime rates can vary widely across even small geographic areas. Local variations in issue conditions may have implications for media and public opinion (Logan &
Molotch, 1987). For example, Heath (1984) examined the effects of local newspaper coverage of crime and found that individuals compared local crime news to crime news from other places. Crime news from other places often focused on the worst crimes, making local crime appear less negative. Erbring, Goldenberg, and Miller (1980) found that local news and local crime and unemployment rates affected perceptions of the importance of crime and unemployment as issues. Weatherford (1983b) found that the unemployment rates of labor market areas affected the perceptions of national business conditions of those living in the areas. Thus, local information may be a factor in public opinion about obtrusive issues. Differences in perceptions and opinion related to geographic areas are sometimes referred to as contextual effects. One contextual effects framework may be useful for studying issue obtrusiveness as well.
14 Contextual Effects
The term 'contextual effects' refers to effects associated with the social and cultural environments of the areas in which individuals live and work (Books & Prysby,
1991). The emphasis on geographic location differentiates contextual effects from effects associated with families, associations, interest groups, and political parties that are not place bound. A classic example of contextual effects comes from the work of
Tingsten (1937). Tingsten studied Swedish elections and found that support for socialist candidates did not reflect the social class composition of voting districts.
Districts with a high proportion of working class residents gave more support than expected to socialist candidates; districts with a low proportion of working class residents gave socialists less support than expected. The explanation for these differences is that voters were influenced by the overall social class composition of the district. Several mechanisms have been suggested for contextual effects including social interaction and conformity pressures (Books & Prysby, 1991). Books and Prysby argued that “contextual effects are caused by variations in the pattern of information- flow created the social and political contexts surrounding individuals and conditioned by the reactions people have to these variations in information (p. 50).” Social characteristics or features, which might include issue conditions, within geographic areas shape or modify the information individuals might encounter about an issue, influencing their attitudes and behaviors. For instance, a high crime area might produce a different information flow about crime than a low crime area would produce, leading to differences in opinion.
15 Books and Prysby (1991) posited three sets of factors involved in contextual effects: contextual characteristics, information properties, and individual receptivity.
Contextual characteristics and information properties combine to form the information environment of a location. There are three categories of contextual characteristics.1
These characteristics can affect the information individuals in the area might receive.
Most commonly studied are compositional characteristics, which have to do with the population make up of a geographic area. These are operationalized from individual- level measures. The proportion of working class residents in a district, the racial composition of a neighborhood, and the unemployment rate for a state are examples of compositional characteristics or variables. Structural characteristics concern social interaction or behavioral patterns within an area. Books and Prysby cited the degree of housing segregation and political party organization within an area as examples. These activities cannot be derived from population information and must be measured some other way. The third category is global characteristics, which are characteristics of an area not associated with the population or behaviors. Examples of global characteristics include physical proximity to borders, type of local political institutions, and media structure within a geographic area.
Local information flow.
The information flow specific to an area can influence the information that individuals in the area acquire. Books and Prysby (1991) discussed three attributes of information flow that can vary across communities. The first is the content or the
1 Books and Prysby adapted this scheme from Lazarsfeld and Menzel (1961).
16 substance of issue information. Information may vary both in its real and perceived relevance to an issue. The more relevant to an issue that information appears to be, the stronger its contextual effect is expected to be. The second attribute is the volume of information. Higher volumes of information should lead to stronger contextual effects.
A higher volume of information can increase the number of individuals exposed to information and increase the amount of information any individual might receive. The third information attribute is consistency. The more consistent the information about an issue, the stronger its expected effect. Although Books and Prysby discussed these as separate attributes, they may often be related. As an issue develops, the volume, consistency, and relevance of issue information are likely to increase together. This will create an information ‘signal’ about the issue that will help it stand out from competing issues and background noise. Information may be available through several channels. Books and Prysby (1991) described four information channels: personal observation, informal interpersonal communication, organizationally-based communication, and mass media. They noted that little attention has been paid to personal observation as an information source. It is personal observation as a possible information source that suggests that contextual effects might be a factor in issue obtrusiveness. Books and Prysby thought that information from personal observation may show a clearer link to local contexts than information from other sources. They argue that media and interpersonal communication deliver “a lower per cue volume of information about the context” than does personal observation (p. 55). Information from personal observation may be more concrete and appear more relevant to the
17 observer (Weatherford, 1983b). Interpersonal communication with others in the same area can provide information unattainable through other sources. Geographic mobility, self-selection of friends, and asymmetric exchange of information can limit the information available through this channel. Books and Prysby argued that it was important to not only measure the amount of interpersonal communication, but an individual's role in it, such as information provider or receiver. The third information channel is organizationally-based communication, referring to communication through local organizations and associations. Organizational communication can be formal through official organization channels or informal through interpersonal communication with other members. Books and Prysby differentiated informal organizational communication from other interpersonal communication because they expect that informal organizational communication will reinforce an organization's formal communications. They also distinguished between membership in local and national organizations. The role of organizational communication may be limited because membership is generally self-selecting, and the number of organizations may be limited in some areas. Finally, Books and Prysby named mass media as the fourth channel for local contextual information. As with organizations, they differentiated between local and national. They discussed the role of media primarily in terms of agenda-setting and speculated that media effects might be stronger when there was disagreement over how to define an issue or when media presented unambiguous information about nonrecurring issues.
18 Summary
Many scholars believe that the effects of media on public opinion are reduced for obtrusive issues because personal experience and observation are alternatives to media as sources of issue information. There is also evidence that personal experience and observation may increase media exposure about an issue, thereby increasing media influence. The existing studies shed no light on the processes or contingencies that might explain these differences because they examined only macro-level data. Further, a brief examination of the conceptualization of issue obtrusiveness reveals theoretical and methodological limitations. The research has focused on personal observation and experience as an alternative to news media as a source of information, yet other channels of information including interpersonal communication and local media may provide information about obtrusive issues. Contextual analysis provides a framework to begin thinking about the communication processes at work with obtrusive issues. In order to better understand the communication processes at work for obtrusive issues, it is necessary to study obtrusive issues at the individual level. In this respect issue obtrusiveness is at a stage similar to early agenda-setting scholarship. To develop as an area of inquiry, it was necessary for agenda-setting research to expand to other types of studies including the examination of micro-level influences for individual issues
(Dearing & Rogers, 1996).
The study presented here is an examination of micro-level communication influences on consumer confidence in the economy. Although not often studied as a public opinion topic, consumer confidence is economically and politically important. I
19 define issue obtrusiveness as the degree to which individuals may directly experience or observe salient aspects of an issue. The salient aspects of an issue are those conditions that are perceived as affecting or potentially affecting one’s life. Issue obtrusiveness may vary across individuals, social groups, and geographic locations. This definition does not specify how issue information is communicated. In the next section I discuss consumer confidence and some related concepts including factors that have been shown to affect consumer confidence.
Consumer Confidence
Obtrusiveness and Consumer Confidence
This study is an attempt to expand issue obtrusiveness scholarship by examining micro-level communication influences on an individual issue. The issue is consumer confidence in the state of the economy. The existing work on issue obtrusiveness is part of the agenda-setting tradition, which focuses on media influences on the public’s concern about issues. Consumer confidence may be thought of as concern about economic conditions. There are several advantages to using consumer confidence to examine issue obtrusiveness at the micro level. Although consumer confidence was not examined in obtrusiveness research, unemployment and inflation have been, and they are both factors in consumer confidence (Katona, 1975). Although the public is exposed to many types of economic information (Curtin, 2003a), research suggests that unemployment and inflation are the predominant forces affecting consumer confidence
(Kinsey 1993). Unemployment appears to be an especially powerful force in the movement of consumer confidence (Curtin, 2003b; Weiss, 2003). Consumer
20 confidence is important because it signals changes in consumer spending, which is a major economic force. In addition, the public’s perceptions of economic conditions, which are the basis for consumer confidence, are a major factor in Presidential politics.
Much of what we know about the public’s perceptions of economic conditions comes from studies of economic voting. Finally, completely apart from issue obtrusiveness research there has been scholarship examining the influence of media on consumer confidence. Some scholars have argued that media news content drives change in consumer confidence, and others have argued that news coverage of the economy has no effect on confidence because the public can acquire this information directly. This body of work might be able to inform obtrusiveness research. In this section I will briefly discuss these points as a way to make a case for consumer confidence as a topic for issue obtrusiveness research.
Economic Implications of Consumer Confidence
Consumer confidence is a factor in the performance of the economy and as such it gets considerable attention. Indexes have been developed to monitor changes in consumer confidence, and they are reported on regularly in media. Data from the indexes are included in the Index of Leading Economic Indicators, which is monitored by the Federal Reserve Bank (Ludvigson, 2004). The consumer confidence indexes play several 'roles' for policy makers and economic analysts (Burdekin & Langdana,
1995). Some see consumer confidence as an independent factor affecting macroeconomic activity. Others think of consumer confidence only as a product of economic conditions and confidence indexes as instruments to predict economic
21 fluctuations. Still others think that consumer confidence magnifies the effects of other economic conditions and activities. The inclusion of ‘anticipations’ variables such as consumer confidence might improve econometric models (Adams & Duggal, 1974).
The major value of the consumer confidence indexes lies in their ability to improve economic predictions. The Index of Consumer Sentiment (ICS) consistently provides accurate forecasts of consumer economic behavior six to 12 months in advance (Curtin,
2002a). Change in consumer confidence leads to change in spending on durable goods
(Throop, 1992). Although most economists do not think the ICS predicts spending on non-durable goods (e.g., Throop, 1992), others have reported a relationship between the
ICS and spending on non-durable goods (ACNielson, 2002). The ICS is especially good at predicting auto sales (Adams, 1964; Mueller, 1963). By itself the ICS can explain about 14 percent of growth in total real personal consumption between 1954 and the 1990s (Carroll, Fuhrer, & Wilcox, 1994). The ICS by itself or used with other variables is a significant predictor of the Gross Domestic Product (Howrey, 2001).
Consumer confidence has shown some ability to predict changes in retail spending at the state level (Garrett, Hernandez-Murillo, & Owyang, 2004). The confidence indexes of other countries show similar predictive abilities (Bryant & Macri, 2005; Golinelli &
Parigi 2003). The confidence indexes are especially useful in explaining shifts in consumer behavior during unusual economic periods (Blanchard, 1993; Desroches &
Gosselin, 2004; Throop, 1992). Some economists, however, feel that consumer confidence indexes contribute little to understanding economic behavior. Croushore
(2005) argued that the indexes made for worse predictions than using ‘realtime’ data.
22 One of the major criticisms of the consumer confidence indexes is that they contain little information that is not already part of other economic data. Hymans, for example, found he could explain 80 percent of variation in the ICS with econometric data that included changes in income levels, consumer prices, and stock prices (Hymans, Ackley,
& Juster, 1970). Straszheim (1974) found that the unemployment rate for married men, the consumer price index, and the short-term interest rate could explain about 89 percent of ICS. Young, Mowen, and Silpakit (1984) replicated Hymans' work using quarterly data from 1964 to 1983, and they too found the ICS could be predicted from other economic statistics. Recently Mehra and Martin (2003) revisited this issue and found that consumer confidence did not have a direct effect on consumption after controlling for other economic factors. Still, several scholars maintain that the confidence indexes contain some information that is not part of other economic data
(Carroll et al., 1994; Eppright, Arguea, & Huth, 1998; Fuhrer, 1988; Golinelli & Parigi,
2003; Mueller, 1963). Even if the confidence indexes contain redundant economic information, they are useful because they are available sooner than other forms of economic data (Dunn & Mirzaie, 2006).
Political Implications of Consumer Confidence
There’s another audience for consumer confidence information: politicians.
Voters may be thought of a choosing political candidates and parties to maximize the utility they receive from government (Downs, 1957). That utility includes the performance of the economy. Many people assign the government major responsibility for current economic conditions (Kinder & Mebane, 1983). Political discontent among
23 voters increases as the country’s economic performance worsens (Curtin, 2003a).
Voters may consider international as well as domestic economic performance (Burden
& Mughan, 2003). Different economic conditions are associated with corresponding political behaviors and attitudes. In the United States, high unemployment helps liberal governments, but inflation hurts them (Carlsen, 2000). Shifts in the economy may be related to shifts of in support for social policies with higher expectations about economic performance leading to increased support for liberal policies (Durr, 1993).
Support for government action on unemployment varies with unemployment rates, and inflation rates affect support for government controls on wages and prices (Page &
Shapiro, 1992). Macro-levels of party identification are influenced by unemployment and inflation levels (Weisberg & Smith, 1991). High levels of unemployment may increase identification with Democrats and decrease identification with Republicans
(Haynes & Jacobs, 1994).
Of course, the most important political behavior is voting. The economy is an important and enduring issue in democratic elections, and is a factor in elections around the world regardless of other campaign issues (Alvarez, Nagler, & Willette, 2000). For example, Holbrook (1994) found that national economic conditions were more important than campaign events in Presidential vote choice. Most of the public possesses “ordinary economic theory” about how the economy operates, which includes beliefs about who is responsible for economic conditions (Kinder & Mebane, 1983).
Economic voting research is based on the hypothesis that voters hold the government responsible for economic conditions (Lewis-Beck & Paldam, 2000). Many forces act
24 on voters’ perceptions of economic conditions. For their part, politicians try to influence both the economy and the public’s confidence in the economy (DeBoef &
Kellstedt, 2004). Lewis-Beck and Paldam noted that the economic voting research showed that unemployment and inflation are two of the most important economic conditions voters respond to, that voters react more strongly to negative changes than to positive changes, and that voters consider only short time periods when making economic evaluations. The importance of the economy may make coverage of economic issues during Presidential campaigns more powerful than coverage of non- economic events even though the volume of economic news is less (Shah, Watts,
Domke, Fan, & Fibison, 1999). When unemployment and inflation are increasing, the economy becomes a topic for political ads (Benoit, 2003). However, it is possible that voters’ candidate choices may affect perceptions of the economy (Wlezein, Franklin, &
Twiggs, 1997). There is mixed evidence about the effect of the state of the economy on
Congressional voting. Erikson (1990) found that voters ignore the economy when voting for congress, but Durr and Gilmour (1997) found that Congressional approval was a function of economic news coverage of Congress. Kuklinski and West (1981) found evidence of economic voting for Senate races but not for House races. Chubb
(1988) found that state legislators and governors are little affected by state economic conditions, but are becoming susceptible to national economic conditions. It is important to distinguish between objective economic conditions and voters’ perceptions of the economy. This can be seen in the 1992 Presidential election. Economist Ray
Fair (1978, 1996) developed a model of the Presidential vote that used Gross Domestic
25 Product (GDP) data among its inputs. The GDP data is a measure of the actual state of the economy. Fair's model had been successful in predicting the Presidential vote until the 1992 election. In 1992, however, voters were pessimistic about the economy even though the GDP indicated a strengthening economy. Hetherington (1996) attributed the public’s negative view of the economy at this time to the negative media reports about the economy. Voters reacted negatively to their perceptions of the economy, and – depending on your theoretical orientation to economic voting – they either punished
George H. W. Bush for economic conditions or decided that Bill Clinton would be more likely to improve the economy.
Controversy over the Role of Media
Completely apart of issue obtrusiveness research, there has been scholarship on the influence of media on consumer confidence and the public’s perceptions of the economy. Scholars have at least three different views of the role of media in the public’s perceptions of economic conditions. Some believe that media do not affect the public’s perceptions of the economy, supporting the view that economic issues are obtrusive. Paldam and Nannestad (2000) argued that most of the public’s economic decisions are fairly small, so there is little need for most people to acquire much information in order to make economic forecasts. Haller and Norpoth (1997) and
Linden (1982) argued that individuals’ perceptions of the economy are based on cues from everyday life. Using data from the University of Michigan Survey of Consumers from which the Index of Consumer Sentiment is calculated, Haller and Norpoth found little difference in perceptions of the economy between those who said they recalled
26 hearing news about the economy and those who said they did not hear such news.
Katona (1960) found that many people didn’t pay attention to economic news. About
38% of the public claimed to regularly pay attention to news about the economy, but many people could not recall specific economic news (Katona, 1960). Another view of media influence on consumer confidence that some scholars take is that those who are well informed about the economy, generally elites, influence the perceptions of those who pay little attention to it (Granato & Krause, 2000; MacKuen, Erikson, & Stimson,
1992). This is a two-step flow model, and so the influence of mass media is indirect for most of the public. Finally, some scholars argue that there is a relationship between news about the economy and the public’s perceptions of it. Consumer confidence moves when the perceptions of large groups of people move together, what is termed
“synchronization of change” (Curtin, 2002b). Katona (1960, 1975) argued that mass media were responsible for changes in consumer confidence levels. He examined the reasons people gave for their consumer confidence evaluations; he found that large numbers of people gave the same reason for change at any point in time. Further, most people gave reasons that reflected actual changes in the economy. Katona noted that media can rapidly spread fairly uniform economic news across the country to many different types of people. This would shift consumer confidence levels. As noted above, Katona found that many people could not recall any news about the economy.
Several researchers, however, have found a relationship between news coverage of the economy and consumer confidence at the aggregate level using time-series data (Blood
& Phillips, 1995; Fan & Cook, 2003; Rattliff, 2001; Tims et al., 1989).
27 The Development of Consumer Confidence Measures
Much of how we think about consumer confidence has been shaped by the work of George Katona and his colleagues at the University of Michigan. Katona (1975) trained in Germany as a psychologist, focusing memory and learning. He became interested in economics after witnessing hyperinflation in Germany during the 1920s, and while still in Germany he became an associate editor for an economic newspaper.
After coming to the United States in 1933 Katona lectured on psychological issues related to the economy. Later he worked for the Cowles Commission for Research in
Economics at the University of Chicago, then the U.S. Department of Agriculture
Division of Program Surveys on economic topics, and finally the Economic Behavior
Program of the Survey Research Center at the University of Michigan (Katona, 1975;
Campbell & Katona, 1946).
The economic upheavals of the Great Depression and World War II had stimulated interest in consumer behavior. Economists had predicted high unemployment and deflation following World War II, but unemployment didn’t rise as high as predicted and inflation became a concern (Curtin, 2000). The difference between the predicted and actual conditions was partially because of unpredicted consumer demand. The economic models used at the time did not consider consumer psychology to be a factor in economic behavior (Katona, 1957). As a field, economics has largely ignored or rejected the inclusion of data about how people think in economic models (Bourgoyne & Routh, 1995; Lewin, 1996; Manski, 2004), preferring an emphasis on assumptions of rational behavior and perfect information. This view is
28 breaking down somewhat as research in behavioral economics becomes more prominent. Economics generally assumes that individuals have stable and coherent economic preferences and act rationally to maximize those preferences, yet work in psychology shows that those assumptions are unrealistic (Rabin, 1998). Katona (1975) argued for an approach to economic modeling that took into account the public's psychological reactions to economic conditions. His research supported the inclusion of consumer psychology in economic research. Katona found that, contrary to standard theory, consumer demand decreased rather than increased during inflationary periods.
A reason many people gave for this unexpected behavior was their feelings of uncertainty about the future. Feelings of economic uncertainty are not accounted for in most economic theory or models. Traditional economic models use only changes in household income levels to predict changes in consumer spending; Katona (1974) pointed out that most people are not aware of ‘real’ changes in their income. Katona
(1975) did not dismiss the role of household income in predicting economic behavior, but instead characterized income as the ability to spend and consumers' psychological reactions to the economy as their willingness to spend. One of the objections to including consumer psychology in economic models was the difficulty in measuring it.
Katona and his colleagues set out to develop acceptable psychological measures.
Katona (1975) was influenced by the work of the economist John Maynard
Keynes. Keynes (1936) had argued, that contrary to classical economic theory, investors and producers act not only on current economic information, but also on their expectations about future conditions. For example, a producer might decrease
29 production in anticipation of reduced demand instead of waiting until demand actually decreased. Keynes specifically excluded consumers from the concept of expectations
(Keynes, 1936; Larson, 2002). Katona (1951) argued that Keynes was wrong and that consumers have economic expectations. Perhaps Keynes’ position made sense when he published in the 1930s, but Katona recognized that following World War II
Americans were becoming more affluent. With affluence comes the ability to exercise discretion in how to spend part of one’s income. Fluctuations in consumers’ discretionary spending can affect the economy. Discretionary spending has three features. First, there is no compelling need to make discretionary expenditures at any given time. Second, discretionary expenditures are not governed by habit. Third, discretionary purchases are usually made after consideration and discussion within a household. Thus, consumers can delay discretionary purchases if they have concerns about economic conditions (Curtin, 2002b). The discretionary purchases on which
Katona focused were for 'durable goods,' things such as cars and large household appliances. Large scale changes in spending on durable goods have significant economic impact; being able to predict such change is valuable. Katona and his colleagues developed the Index of Consumer Sentiment (ICS) as a measure of consumer expectations that could be incorporated into economic models. The ICS does not measure absolute levels of consumer 'sentiment' or confidence about the economy, but instead tracks change in consumer confidence levels (Curtin, 1982). It is change in consumer confidence that leads to change in consumer behavior. The ICS was started in 1955 and was calculated quarterly until 1978 when it became a monthly index
30 (Curtin, 1982). Other confidence indexes were developed later. Probably the most well-known competitor to the ICS is the Consumer Confidence Index (CCI), started in
1985 by The Conference Board, an economic research organization. Another index is the Consumer Comfort Index developed by ABC News and Money magazine in 1985 and now sponsored by the Washington Post with ABC News. State-level versions of the ICS have been used in Ohio and Florida (Dunn & Mirzaie, 2006). Other countries have their own versions of the confidence indexes as well (Bryant & Macri, 2005;
Golinelli & Parigi, 2003; Iguzquiza, 1996).
Conceptual considerations.
The term ‘consumer confidence’ is used with many meanings. Keynes (1936) described confidence as the inverse of uncertainty. Expectations about future conditions have some degree of uncertainty. According to Keynes, as uncertainty increases, the “state of confidence” decreases (p.148). Recall that Katona (1975) had found that consumers expressed feelings of uncertainty about the economy during downturns. The decision to make large purchases often means making financial commitments into an uncertain future (Morgan, 1980). As uncertainty about the future increases, the willingness to make long-term commitments may decrease. Thus, consumer confidence indexes should measure consumers’ sense of confidence or uncertainty about the future (Hymans et al., 1970). Dominitz and Manski (2003), however, argued that there is little research to back the claim that the indexes actually measure confidence. The indexes may measure uncertainty and confidence indirectly.
Lovell (1975; Lovell & Tien, 2000) argued that the confidence indexes measure
31 ‘economic discomfort,’ which is reaction to unemployment and inflation levels. In his work on economic decline in Britain, Alt (1979) discussed a concept he called
“economic outlook,” which appears similar to consumer confidence. Alt defined economic outlook as a “subjective assessment of economic well-being (p.89).”
Katona (1975) defined consumer confidence2 as the willingness to make large, discretionary purchases. He also characterized the Index of Consumer Sentiment, which was designed to track consumer confidence, as a broad measure that could gauge consumer reactions to a range of different economic conditions. For the purpose of this study, the willingness to make discretionary purchases is incidental to consumer reaction to economic conditions. By that I mean that I am interested in the processes that affect perceptions of economic conditions; I am not interested in the effects of those judgments. I will return to Keynes’ original thinking for my definition of consumer confidence. I will define consumer confidence as consumer expectations about future economic conditions. These expectations can affect the willingness to make large, discretionary purchases. Operationalizing consumer confidence entails of number of considerations.
Although Katona argued that consumer confidence has both cognitive and affective components, he chose the term ‘consumer sentiment’ for his own index to focus on affective reactions to the economy (Curtin, 2002). A variety of affective reactions are associated with economic conditions. Conover & Feldman (1986)
2 Katona generally used the term ‘consumer sentiment,’although he also referred to confidence. The term ‘consumer confidence’ appears to be dominant now, and I will use that term for clarity.
32 identified two types of negative reactions to economic conditions. They characterized one reaction as anger/disgust and the other as fear/uneasiness. Anger/disgust about economic conditions was more closely associated with political attitudes than fear/uneasiness. Poor economic conditions can provoke psychological stress (e.g.,
MacFadyen, MacFadyen, & Prince, 1996). Others have found that positive life situations are associated with positive perceptions of economic conditions (Iguzquiza,
1996). Affective reactions to economic conditions are important because of their role in behavior. Affective evaluations of stimuli are associated with the willingness to approach or avoid stimuli (Cacioppo & Berntson, 1994; Rozin & Royzman, 2001;
Soroka, 2006). Individuals can easily make positive or negative evaluations of objects or situations with which they are familiar (Osgood, Suci, & Tannenbaum, 1957).
Evaluations of economic conditions require drawing on knowledge of economics and events, so the amount and type of knowledge individuals have about the economy and economics may be important (Conover, Feldman, & Knight, 1986). Higher levels of economic knowledge may aid understanding of news stories about economic events
(Adoni & Cohen, 1978). Relatively little is known about how the public thinks about the economy, although a few studies indicate that most people have limited knowledge of economics (Bourgoyne & Routh, 1995). The public’s knowledge of economics appears to be organized around phenomena such as unemployment and inflation rather than broad economic principles (Bastounis, Leiser, & Roland-Lévy, 2004). A small study of Australian voters found that they did not share a common cognitive model of the economy (Williamson & Wearing, 1996). Individuals in that study described the
33 economy as a mix of economic, social, psychological, and moral issues. They knew little about fiscal issues, but they understood the connection between government revenues and expenditures. Another Australian study found that unemployment was perceived of as a social issue as well as an economic issue (Blount, 2002). Classic economic theory assumes that individuals consider all available information when making decisions, but there is ample evidence that most of the public uses only limited economic information when making decisions (Conlisk, 1996). This general lack of economic knowledge has implications for economic behavior. For example, consumers do not understand the reasons for fluctuations in oil prices and so do not change their consumption patterns in relation to price changes (Curtin, 2005). The public often mis estimates economic conditions and economic forecasts compared to official reports
(Blendon, Benson, Brodie, Morin, Altman, Drew, et al., 1997; Haller & Norpoth, 1994).
Those with higher levels of economic knowledge tend to hold different positions on economic policy than those with lower levels of knowledge (Mulligan, 2003).
Although people often lack knowledge about the details about economic conditions, they often have a general sense of conditions, especially the direction of economic changes (Dua & Smyth, 1993; Sanders, 2000).
Operational considerations.
Alt (1979) discussed a framework for operationalizing his concept of economic outlook, which shares features with consumer confidence. Alt identified what he called three “analytic decisions”required to measure economic outlook. With one exception, these analytic decisions reflect the operationalization of the consumer confidence
34 indexes and measures of perceptions of the economy used in economic voting studies suggesting that economic outlook subsumes those concepts. The first decision is whether the evaluation should focus on economic conditions or on economic aspirations. Alt said that evaluations of economic conditions should capture perceptions of change in conditions and their perceived direction. Evaluations related to aspirations should capture feelings of satisfaction with conditions. For example,
Wiefek (2001) found that long-term changes associated with global economic shifts were making Americans more anxious about the future. Consumer confidence and economic voting research clearly focus on perceptions of economic conditions and ignore economic aspirations. When Katona (1975) discussed economic aspirations, he did so separately from consumer confidence, which suggests he thought of aspirations as a distinct concept. The second analytic decision that Alt discussed is the temporal focus of evaluations. Evaluations can focus on the present conditions or on expectations about future conditions. Recall that Keynes' (1936) investors and producers made decisions based on information from two time frames: knowledge of current conditions and expectations about future conditions. The temporal focus of voters’ economic evaluations is a major point of debate in economic voting studies.
One group of scholars argues that voters are retrospective, using evaluations of recent economic conditions compared to past conditions in their voting calculus (e.g., Fiorina,
1981). This view assumes that voters reward or punish the incumbent President for economic conditions. Another group of scholars argues that voters are prospective and factor their economic expectations in their vote choice (e.g., Kuklinski & West, 1981).
35 In this perspective, voters view the political parties or Presidential candidates as having different abilities to maintain or improve economic conditions. There is roughly equal support for the retrospective and prospective economic voting models (Lewis-Beck &
Paldam, 2000). Evaluations for different time periods may require individuals to draw on different knowledge stores. Nadeau, Niemi, Fan, & Amato (1999) argued that individuals could draw on personal experience and observation for evaluations of current conditions, but would require information from media to make judgments about the future. The last analytical decision that Alt outlined was the unit of focus for evaluations. Evaluations can focus on conditions affecting a household, the nation or some other collective group. The unit of economic evaluation has been another major point of debate in economic voting scholarship. 'Pocketbook' theories of economic voting assume that individuals focus on their own economic self-interests (e.g., Kinder
& Kewiet, 1979). Sociotropic theories assume that individuals focus on what is best for the nation (e.g., Kinder & Kewiet, 1979). Weatherford (1983a) argued that these approaches are not mutually exclusive and that sociotropic outlook should increase as individuals acquire more information about national conditions. Presidential election campaigns may promote sociotropic voting positions (Shah et al., 1999). Lewis-Beck and Paldam (2000) noted that the evidence favors sociotropic voting theories.
Evaluations for different units of focus may draw upon different bodies of knowledge.
Funk and Garia-Monet (1997) found the personal evaluations were generally distinct from group- or collective-focused evaluations. Media may be instrumental in providing information about group or societal risks and conditions (Coleman, 1993).
36 Q1 We are interested in how people are getting along financially these days. Would you say that you and your family living there are better off or worse off financially than you were a year ago? Q2 Now looking ahead, do you think a year from now you (and your family living there) will be better off financially, or worse off, or just about the same as now? Q3 Now, turning to business conditions in the country as a whole, do you think that during the next 12 months we'll have good times financially, or bad times, or what? Q4 Looking ahead, which would you say is more likely, that in the country as a whole we'll have continuous good times during the next five years or so, or that we will have periods of widespread unemployment or depression, or what? Q5 Now I'd like to ask you about the big things people buy for their homes, such as furniture, a refrigerator, stove, television, and things like that. Generally speaking, do you think now is a good or bad time for people to buy major household items?
Figure 1. Question items for the Index of Consumer Sentiment
Consumer confidence indexes.
It should be clear that consumer confidence can be operationalized in many ways. An examination of the two major consumer confidence indexes, the Index of
Consumer Sentiment and the Consumer Confidence Index, demonstrates these differences. Figure 1 shows the five questions used in the Index of Consumer
Sentiment. The first question asks for an evaluation of current personal financial circumstances compared to the prior year. The evaluation unit is the household and the temporal focus is the current situation, which in economic voting terms is a retrospective evaluation. The second question asks about expectations for personal financial circumstances in one year. The unit remains the household, but the temporal
37 Q1 How would you rate present general business conditions in your area? Q2 What would you say about available jobs in your area right now? Q3 Six months from now do you think business conditions in your area will be better, the same, or worse Q4 Six months from now, do you think there will more, the same, or fewer jobs in your area? Q5 How would you guess your total family income to be six months from now?
Figure 2. Question items for the Consumer Confidence Index.
focus is on expectations with a one-year horizon. The third question asks about national economic conditions for the next year. The unit changes to the national, but the temporal focus remains the same as the pervious question. The fourth question has the same unit and temporal direction, but the time horizon is now five years. Finally, the fifth question asks whether it is currently a good time to buy items often considered durable goods. Here, the unit is not clear and the temporal focus returns to the present.
Although the ICS measures economic perceptions for several different units and time frames, Curtin (1973) claimed the index has a single dimension.
Figure 2 shows the questions used in the Conference Board’s Consumer
Confidence Index.3 The first question asks for an evaluation of current business conditions in the survey respondent’s local area. The unit is business in the respondent’s local area, and the temporal focus is current. The second question asks
3 The Conference Board does not publish the question wording for the Consumer Confidence Index. The wording presented here is from Ludvigson (2004).
38 about available jobs in the respondent’s local area. The unit appears to be business, but the question asks about a specific aspect of business conditions. Alt did not mention this as an analytical consideration. The temporal focus is current. The next two questions mirror the first two except for changing the temporal focus to six months in the future. These questions are prospective. Finally, the fifth question asks about the respondents’ family income in six months. The unit changes to the household and the temporal focus remains the future.
We can immediately see differences between the ICS and CCI index questions.
First, the CCI starts by asking about general economic conditions and not personal or family financial situation. In fact, only the fifth question on the CCI asks about personal financial situation. Second, the CCI asks about conditions “in your area” instead of national conditions. Weatherford (1983b) has argued that individuals would have a more accurate sense of knowledge about conditions in their area than about more distant locations or areas. Third, the CCI asks about general business conditions and employment separately. Employment has been shown to be a major concern even during periods of national crisis (Bechtel, 2003); more people may be aware of employment conditions than of general business conditions. Mughan and Lacy (1998) found that feelings of job insecurity were distinct from perceptions of economic performance. Finally, the CCI the time frame for expectations is only six months compared to a year and five years on the ICS. The operational differences between these indexes result in different predictive abilities (Bechtel, 2003; Bram & Ludvigson,
1998). Bram and Ludvigson (1998) found the CCI better than the ICS at improving
39 economic forecasts, and the two indexes combined were better still. The Index of
Consumer Sentiment is better at predicting changes in durable goods purchases, but the
Consumer Confidence Index is better at predicting changes in general economic activity
(Huth, Eppright, & Taube, 1994). The indexes appear to track together, but their different question wordings make them subject to somewhat different influences
(Merkle, Langer, & Sussman, 2003). Mowen, Young, and Silpakit (1985) have argued that the two indexes measure different concepts, with the ICS measuring predictions of financial assets and the CCI measuring employment-related perceptions. Both indexes can be broken down into current/retrospective and expectations components (Bram &
Ludvigson, 1998; Kinsey, 1993). Expectations appear more volatile than current perceptions (Merkle et al., 2003). The expectations components of the indexes have more predictive power than the current/retrospective components (Bram & Ludvigson,
1998). Kinsey (1993) claimed the expectations and current/retrospective components predict different spending behaviors.
Factors Affecting Consumer Confidence and Perceptions of the Economy
Changes in consumer confidence at the aggregate level are not random. Change occurs when large numbers of people gain or lose confidence in the economy at about the same time (Curtin, 2002b). Scholars in economic voting have identified four factors thought to influence perceptions of economic conditions: personal financial circumstances, group membership, political attitudes, and information (Duch, Palmer,
& Anderson, 2000). Katona (1975) discussed these same factors, although he focused on what he considered to be mass media’s ability to influence consumer confidence at
40 the macro level. Duch et al. argued that these factors bias individuals’ perceptions of objective economic events and conditions. That is, if these factors were not present, individuals should perceive the same objective economic conditions. In addition to these factors, other work suggests that local economic context might affect how individuals evaluate economic conditions. In this section I discuss each of these factors. I also discuss a consideration that may be important to understanding communication influences on consumer confidence: the timing of research in terms of the public’s reactions to changes in the economy.
Personal economic circumstances.
One of the most common findings across the literature is that evaluations of the economy are related to personal or household financial circumstances. For example, individual consumer confidence is often lower when the head of the household is unemployed (Mueller, 1966). Duch et al. (2000) argued that personal economic circumstances might be used as a heuristic for evaluating national conditions.
Alternatively, individuals may simply project their own financial circumstances onto the national situation. Katona (1960, 1975) and Weatherford (1983b) argued that personal information would be more compelling than information from other sources.
On the other hand, Mutz (1993) and Krause (1997) argued that those who are well informed could better make the connection between personal circumstances and national conditions. Duch et al. argued that the influence of personal circumstances on economic perceptions would decrease as political sophistication increased. They found that the influence of personal economic circumstances persisted to some degree. That
41 is, personal economic circumstances influenced everyone’s perceptions of the economy to some degree, even those with high levels of political sophistication. Conover,
Feldman and Knight (1987) and Weatherford (1983a) had similar findings. It is possible that the influence of personal financial circumstances on other economic perceptions may be partly artifactual. We know question order can affect how people respond to survey questions (Sears & Lau, 1983; Tourangeau, Rips, & Rasinski, 2000).
For example, Mason, Carlson, and Tourangeau (1994) found that the order of questions asking for evaluations of state and local economic conditions affected those evaluations.
The response distributions were significantly different depending on the order of the questions. The ICS asks for an evaluation of personal financial circumstances before evaluations of national economic conditions. This question order may make evaluations of personal financial circumstances salient when making evaluations of other economic conditions.
Definitions of issue obtrusiveness have focused on personal experience or observation of issue conditions (Demers et al., 1989; Zucker, 1978). For consumer confidence, personal experience with the economy is manifested in a household’s financial circumstances. Households need income to cover the expenses of maintaining themselves. Households can control their financial circumstances by controlling spending on nonessential goods; they may have little or no control over employment. If unemployment rises such that households feel their employment is threatened, they may limit spending on nonessential goods until the threat passes.
42 Group membership.
Duch and his colleagues termed this factor “group self-interest,” but that may imply an awareness of group interests that many individuals do not have. Perceptions of group conditions appear to be distinct from those of personal or national conditions
(Mutz & Mondak, 1997). Group membership may be associated with different types or levels of ‘resources,’ such as economic or political knowledge, on which individuals might draw to think about issues (Brady, Verba & Schlozman, 1995). Group members may have had similar life experiences or have been socialized in similar ways, leading them to form similar perceptions of conditions (Katona, 1975). For example, financial hardship may be a substantial concern among those who experienced the Great
Depression. Groups may differ in their motivations for attending to economic information (Aidt, 2000; Blinder & Krueger, 2004; Duch et al., 2000; Katona, 1960).
For example, investors probably pay more attention to the stock market than do factory workers. Some group differences may also be associated with type of employment
(Hibbs, 1979). Dunn and Mirzaie (2006) speculated that differences in consumer confidence between Ohio and Florida were related to different levels of manufacturing employment between the states. Those working in manufacturing might have different economic experiences and knowledge than those working in other industries. Most of the evidence is for group differences associated with demographics. Those with higher incomes, men, those with higher education levels, and younger individuals generally tend to be more optimistic about economy conditions (Dominitz & Manski, 2003;
Mueller, 1957). For example, those who are middle aged and those with higher
43 incomes tend to think inflation is lower than those who are younger, older, or with lower incomes (Bryan & Venkatu, 2001a, 2001b). Krause and Granato (1998) found that those who are well educated make more accurate predictions of inflation than those less well educated. Souleles (2004) found that economic forecasting errors were correlated with consumers' demographic characteristics. Gender differences are common. Women appear to be less willing than men to take economic risks (Powell &
Ansic, 1997). Welch and Hibbing (1992) found that women are less likely to vote based on their own economic self-interest even after controlling for socioeconomic factors. They suggested that women may be more socialized than men to consider group needs.
Issue obtrusiveness scholarship has ignored the effects of group membership on public opinion. At the micro level, however, group membership might be a powerful influence on consumer confidence. To properly assess communication influences on consumer confidence, we must account and control for differences associated with group membership. I define group membership as belonging to a socioeconomic group that has a high likelihood of sharing economic socialization and experiences.
Political predispositions.
Considering the importance of perceptions of the state of the economy to presidential voting (Lewis-Beck & Paldam, 2000), it should come as no surprise that economic perceptions vary by political predisposition (Caplan, 2002; Duch et al., 2000;
Katona, 1975). Kramer (1983) argued that differences in perceptions of economic conditions are largely the result of partisan biases. His argument is that those
44 identifying with the incumbent President’s party are more likely to give the economy a favorable evaluation. Zaller (1992), who found also significant partisan differences in perceptions of the economy, argued that those with high levels of political awareness would accept or reject media messages according to their politics biases. As with group membership, obtrusiveness scholarship has ignored political predispositions. I define political predisposition as identification with a political party. In the context of consumer confidence and economic voting, political predispositions will affect the perceptions of political parties’ economic policies and their ability to manage the economy.
Information
Duch et al. (2000) called the fourth factor “information.” They found differences in perceptions of economic conditions related to how well voters were informed about the economy. Duch et al., however, used national-level data for their study and examined only one channel of information acquisition, mass media. Katona
(1975) noted three channels for obtaining information about the economy: personal observation and experience, interpersonal communication, and mass media. We might add organization-based communication to this list (Books & Prysby, 1991). The influence of information might vary by channel. For example, Katona felt that information from personal observation and interpersonal communication could be more powerful than information from mass media although he considered their effects to be idiosyncratic. Channels of communication must be examined separately in order to assess their influence on opinion. For the purposes of this study, communication is
45 defined as an issue-specific exchange or acquisition of information. Communication not related to the issue should not affect opinion. Each channel of communication can be operationalized in terms of its issue-specific content.
Interpersonal discussion.
In obtrusiveness research, personal experience and observation are often discussed together, but they are distinct channels of information. Little attention has been given to personal observation as distinct from personal experience. This may be because of the difficulty in assessing any effects from personal observation. I will revisit personal observation in the discussion about local context. Somewhat more attention has paid to interpersonal communication. For example, Carroll (2003) developed an epidemiological model of economic information transmission in which communication among neighbors improved the flow of information. Social networks have been found to be a major source of information about jobs (Granovetter, 2005).
Interpersonal communication may enhance comprehension of news from media
(Robinson & Levy, 1986). Engaging in interpersonal communication about a topic may depend on education, knowledge, interest in the topic, and opportunities for discussion
(Straits, 1991). As a topic of discussion, the economy appears to be similar to politics and dissimilar from topics such as religion, family, sports (Wyatt, Katz, & Kim, 2000).
I will define interpersonal communication as the self-perception of the amount of discussion about the economy.
46 Organizational communication.
There does not appear to be any research on organizational communication related to the economy. Unions might be a source of this type of communication.
Because unions often concentrate in particular industries such as manufacturing, union leadership might communicate industry-specific economic information to their members. This study will not examine organizational communication because there are not suitable measures in the data.
Mass media.
Most obtrusiveness and economic voting scholarship has focused on the influence of mass media. Although Katona (1975) thought personal observation and interpersonal communication were powerful influences on consumer confidence, he considered their influence to be “idiosyncratic.” That is, information from personal observation and interpersonal communication might be based on events not part of changes in the wider economy. For example, individuals might learn about layoffs at a local company, but those layoffs could be because of poor management and not because of contractions in the economy. In contrast to personal observation and interpersonal communication, Katona felt that mass media could deliver the fairly uniform economic information to large numbers of people at about the same time. Katona’s view is similar to an agenda-setting view of the influence of media on consumer confidence.
Uniformity of information can be important. Curtin (2003b) made a distinction between what he called public and private information. Public information is information from public announcements about the economy. The same information is
47 available to everyone who pays attention to media. Private information, on the other hand, can come from personal experience, observation, interpersonal communication, and personal interpretation of media information. Sims (2003) argued that media provide coded information about the economy, so that the public can understand what is happening without closely monitoring events. The fairly uniform coded messages from media may be thought of as constituting a ‘signal’ about the economy, which could overwhelm ‘noise’ from other sources of information. Changes in the media information signal could drive changes in consumer confidence at the aggregate level.
Katona (1960, 1975) failed to find support for his view, however. He found that those who paid little or no attention to news about the economy had perceptions of the economy that were not significantly different from those who did attend to such news
(Katona, 1960). Later scholars using different methods have found some support for
Katona’s view. Fan and his colleagues (Fan & Cook, 2003; Tims et al., 1989) predicted changes in Index of Consumer Sentiment from Associated Press news stories about the economy. Rattliff (2001) found a relationship between the volume of stories about the economy in the New York Times and the perceived importance of the economy as an issue from 1989 through 1994. Blood and Phillips (1995) found a relationship between recession-related headlines in the New York Times and the Index of Consumer
Sentiment from 1989 through 1993.
Mass Media and the Economy
Do changes in the economy drive news about the economy or is there some other basis for news about the economy? Behr and Iyengar (1985) examined television
48 news coverage from 1974 through 1980 for several issues including unemployment.
They found that positive and negative changes in unemployment levels lead to changes in coverage of unemployment. However, Blood and Phillips (1995) found that changes in Presidential popularity rather than in economic conditions lead to an increase in recession headlines in the New York Times from 1989 to 1993. Their study found that the public was influenced by the headlines, which suggests that the public was responding to news about the economy and not to actual economic conditions.
Stevenson, Gonzenbach, and David (1994) examined the relationship between news, consumer confidence, and indicators of objective economic conditions. They found that after controlling for objective economic conditions, consumer confidence was a better predictor of news coverage than news coverage was a predictor of confidence.
The authors suggested that the public’s personal experiences and interpersonal communication affected their attitudes, which media picked up. Wu, Stevenson, Chen, and Güner (2002) extended the Stevenson et al. analysis. They examined the period from January 1987 through March 1996. January 1987 through January 1991 marked an economic downturn; from February 1991 through March 1996 marked an economic upturn. They found that news was a predictor of confidence during the downturn even after controlling for objective economic conditions. They also found that news during the downturn was more a reflection of the public’s attitudes than objective economic conditions. During the upturn, however, confidence was influenced by economic conditions and not by news reports. Goidel and Langley (1995) argued that news coverage of economy gives cues about its importance as an issue. They examined New
49 York Times coverage of the economy and the Index of Consumer Sentiment from 1981 to 1992. They found that evaluations of the economy were a function of both real economic conditions and negative economic news. Each negative New York Times story lowered consumer confidence by a half a percentage point. The evidence suggests that news coverage of economic conditions affects public opinion to some degree even though some aspects of the economy, such as unemployment and inflation, appear to be obtrusive. If media coverage of economic events and conditions can influence individuals’ perceptions of the economy, then the way in which the events and conditions are covered is important (Sanders & Gavin, 2004; Sims, 2003). Mutz (1992) noted that media can help shape perceptions of issues even when issue information is obtrusive. Consider coverage of another issue sometimes called obtrusive, crime.
From 1992 to 1994 perceptions of the importance of crime as an issue increased, not because of changes in levels of crime but because of changes in the news coverage of crime (Lowry, Nio, & Leitner, 2003).
News coverage of the economy had its origins in media coverage of business events and transactions (Parsons, 1989). In his work on the financial press, Parsons noted that market economies depend on information networks to function; media are a large part of those networks. Newspapers were vital to the development of the capitalistic economic system. The early financial press provided the business community with information about markets and opportunities to advertise products and services; they were also a vehicle for spreading ideas and opinions about economics.
Even during periods noted for their levels of political censorship, the commercial
50 aspects of the press were not repressed and continued to develop. Parsons noted that in addition to helping business expand, newspapers sometimes figured in the spread of financial panics. Changes in the 1930s and 1940s led to coverage of the economy as well as business. In the 1930s John Maynard Keynes introduced the term ‘the economy’ to use when discussing the economic system and problems of the system
(Emmison, 1983). Washington and the government became sources for economic news the way Wall Street and businesses were sources for business news (Parsons, 1989). At the same time, business was becoming more corporate and managerial. Management wanted information about economic conditions and policy, the type of information provided by government. Parsons argued that the press helped spread the notion of national economy with economic problems and solutions that were distinct from business problems and solutions.
The process of deciding what is newsworthy, collecting, and presenting news has many influences at different levels such that news seldom mirrors actual conditions
(Shoemaker & Reese, 1991). Reporting about the economy relies heavily on government or specialized institutions for information and interpretation (Parsons,
1989). Government and other institutions collect and disseminate information about different economic indicators, which include the consumer confidence indexes. Reports about economic indicators act as information subsidies for news organizations (e.g.,
Gandy, 1982). That is, relatively little needs to be done to collect that news and disseminate it, and the regularity at which the indicators are reported facilitates news planning. Since the government and other institutions control the flow of economic
51 statistics, it is likely that different media will carry similar information. This consonance among media may increase their influence on public opinion (Noelle-
Neumann & Mathis, 1987). Further, these information subsidies may set the frames that media use to present news about economic events and conditions. Reporting about the economy is largely abstract and statistical (Jensen, 1987). Changes in economic conditions are often reported on in terms of statistical changes in economic indicators, such as a percentage drop in consumer confidence. Coverage of the economy can be complex. A study of British news coverage of inflation found that 13 different causes for inflation were mentioned (Gavin & Goddard, 1998). Economic coverage is often formulaic, with media relying on several devices to aid reporting (Richardson, 1998).
A study of economic reporting on British television found that voice over images or graphics with the speech dominant was common (Goodard, Gavin, & Richardson,
1998). Visuals were used to provide thematic story support. Stories often used
‘typical’ families or case studies to explain or personalize larger economic events or trends. Emmison (1983) found that the economy is often anthropomorphized and reported on in terms of sickness and health, which could aid the public’s understanding of events. Although media may share the same information, there can be differences in the way types of media cover economic news. Neuman, Just, and Crigler (1992) found that newspapers gave the stock market crash of 1987 proportionally more coverage than did television. Learning was higher from television, however. They suggested that the events seemed more complicated in print and television’s presentation was more dramatic, which captured attention.
52 Negative coverage of the economy.
A common finding is that media tend to focus on negative aspects of the economy (Hester & Gibson, 2003; Niven, 2001; Smith, 1988; Smith & Lichter, 1997).
Harrington (1989) found that stories about unemployment, inflation, and the GDP were longer and were more likely to be lead stories when the economy was worsening.
Rattliff examined coverage from 1989 through 1994 and found that coverage was most negative in 1989 and became less negative through 1994. Only Lott and Hassett (2004) found that positive economy events get more coverage volume and prominence than negative events. They examined Associated Press and major newspapers from1991 through 2004. Negativity doesn’t appear to be characteristic of any medium. Hester &
Gibson (2003) found the pattern and tone of coverage similar between television and newspapers. The tone of coverage might vary across outlets, however (Lott & Hassett,
2004). Overall, an emphasis on negative events and conditions might lead the public to think the economy is in worse condition than it really is (Blendon et al., 1997). There are several possible explanations for the emphasis on negative economic conditions. A cynical explanation is that the emphasis on negative news is an attempt to attract a larger audience (Alsem, Brakman, Hoogduin, & Kuper, 2004). Another explanation is that one of the functions of media is to warn the public about adverse conditions
(Laswell, 1948). Yet another view is that negative conditions are more newsworthy than positive conditions, and so journalists devote more attention to them. Thinking in terms of the issue-attention cycle (Downs, 1972), routine news about the economy might be characterized as pre- or post-problem stage reporting depending on its
53 temporal proximity to other stages. When the economy worsens, coverage increases in what Downs called the “alarmed discovery” phase. Visibility of the issue increases in terms of the amount of coverage and its prominence within a newscast or publication
(Kiousis, 2004). For economic news, this may mean moving from the business pages to the front page of the newspaper or to the upper portion of a newscast. Coverage of the economy must compete with other issues.
Political bias in coverage of the economy.
Some media critics and scholars have found periods during which coverage of the economy is politically biased and favors Democrats (Lott & Hassett, 2004; Shah et al., 1999; Smith, 1988). Rattliff (2001) found the coverage of the economy during election campaigns was more negative than reporting during non-campaign periods.
Economic coverage during the 1991-1992 presidential election campaign has often been called biased. Recall that Fair’s (1996) model of voter behavior based on the state of the economy was successful until 1992 when it predicted Bush would be elected.
Hetherington (1996) found that negative coverage of the economy during the 1991-
1992 campaign affected retrospective evaluations of the economy. He did not find a similar pattern during the 1984 and 1988 campaigns. The public’s expectations for the economy tend to increase during election campaigns (Suzuki, 1992). Politicians, of course, try to influence perceptions of the economy (De Boef & Kellstedt, 2004). Page and Shapiro (1992) found that comments by political actors could influence public opinion. Presidential comments in media appear to affect perceptions of the economy
(Shields & Goidel, 1998; Wood, Owens, & Durham, 2005).
54 Local Context
Most research in issue obtrusiveness has been conducted using national-level opinion, news content, and ‘real world’ indicator data. This approach may ignore potentially important local-level processes. Some scholars argue that local contexts may influence the opinions of their residents. Geographic areas can provide distinct information environments that help structure attitudes and perceptions of the residents of those areas (Books & Prysby, 1991). Weatherford (1983b) and Books and Prysby
(1999) applied this perspective to economic perceptions. Weatherford thought voters could potentially be exposed to economic information from a series of nested geographic areas. For example, voters might have access to economic information from their city, state, region or the nation. Weatherford argued that economic information from the area closest to a person would be the most clearly perceived, although it would not necessarily be generalizable to the nation. Information about the nation as a whole would be generalizable, but more complex and harder to understand. He examined the impact of local context on evaluations of personal economic circumstances and national economic conditions. Weatherford found that the unemployment rate of an individual's
Labor Market Area was a significant factor in assessing national conditions, but not in assessing personal circumstances. Books and Prysby (1999) attempted to replicate and extend Weatherford’s work. They used county and state unemployment rates as contextual information. They found that state unemployment rates were a factor in the national economic perceptions, but county unemployment rates were not. Books and
Prysby suggested that the reason for this was that media reported on unemployment
55 rates for the state but not for counties. Weatherford noted that care was needed in selecting the relevant geographic area for study. Using too large an area would group people with different experiences; using too small an area fails to group those who have similar experiences.
Local information flow.
Books and Prysby’s (1991) approach focuses on the information flow within an area. They discussed several information channels important to information flow including personal observation. Two channels, personal observation and local media, bring a needed dimension to obtrusiveness research. As I noted earlier, there has been little attempt to actually examine information acquisition from personal observation.
The contextual analysis approach may give us the tools to examine the effects of personal observation. We can examine differences in consumer confidence geographically using real-world indicators of economic conditions that the public is likely to react to. If all individuals are exposed to the same conditions, then it would be difficult to detect differences due to observation. However, when conditions vary geographically, geographic variations in consumer confidence should be at least partially due to observation after controlling for other information sources. Another information channel that contextual research suggests will be important to obtrusiveness research is local media. Obtrusiveness studies have typically operationalized mass media either in terms of national or local news but not both.
Research on the economy or related issues often focuses on national news. This could be because the issue is thought of as national and researchers assume little variation at
56 the local level. Local news is largely ignored in media studies (Kaniss, 1991). Ignoring local news, however, assumes that either local news is consonant with national news and so does not merit study or that differences in local news coverage average out nationally. Yet local media may contain news or viewpoints not present in national- level coverage. Consider crime and unemployment. Zucker (1978) thought that local news affected concern about crime. Behr and Iyengar (1985) noted that national media give little coverage to unemployment, one of the major economic conditions to which the public reacts. Local media may report on unemployment because of its importance to the local economy. Local media are often part of the local economic and power structure and may emphasize economic news that concerns local powers (Kaniss, 1991;
Logan & Molotch, 1987).
Attention, Adaption, and the Timing of Research
There is one last ‘factor’ that must be considered. Classical economic theory assumes that individuals pay constant attention to the economy in order to make the best possible decisions at any given time (Headrick & Lanoue, 1991; Reis, 2004). We know, however, that this is not true. Information acquisition is not costless, and people direct their limited attention and energy to tasks that will have the most payoff (Gabaix,
Laibson, Moloche, & Weinberg, 2003; Mankiw & Reis, 2002; Reis, 2004). Much of the public uses somewhat outdated economic information, termed ‘sticky information,’ because it fits their needs reasonablely well and does not require the effort of updating
(Mankiw & Reis, 2002; Reis, 2004). This happens with other topics as well. For example, in their study of Americans’ political knowledge, Delli Carpini and Keeter
57 (1996) found that much of the public had outdated knowledge of political actors. Many people will update their information when it becomes apparent that updating is necessary or when the flow of information overcomes existing information. Updating economic information may occur during periods of economic change and increased news coverage (Doms & Morin, 2004). Periods of heavy news coverage of a topic may lead even the relatively inattentive to acquire information about an issue (Mutz, 1994).
Of course, the obtrusiveness hypothesis suggests that during periods of economic change the public may directly observe or encounter economic information. Soroka
(2002) examined the relationship between news coverage and public concern about unemployment in the United Kingdom. He found that news about unemployment in the
United Kingdom had its greatest effect on public concern when unemployment levels were low; as unemployment increased, media influence on the public decreased.
Soroka argued that as unemployment increased it became more ‘prominent,’ suggesting that the information was through channels other than media. Further, when conditions are stable–even when conditions are poor–the public may adapt to those conditions and judge future changes against them (Middleton, 1996). Scholars of economic voting have found that voters base their evaluations of the economy on short time periods
(Lewis-Beck & Paldam, 2000). For example, the public may judge changes in unemployment against recent unemployment levels, even if unemployment has been high. Because of this adaption to economic conditions, changes in the public’s consumer confidence may be relatively small. The implication of the public’s slowness to update information and the tendency to adapt to current conditions is that the window
58 to detect differences in opinion because of communication processes is small and will most likely occur during periods of substantial economic change (c.f., Bartels, 1993).
Summary and Hypotheses
The agenda-setting hypothesis predicted that the perception that an issue was important increased as media coverage of the issue increased (McCombs & Shaw,
1972). After noticing that the hypothesis did not hold for all issues, Zucker (1978) hypothesized that some issues were obtrusive, meaning the public could acquire some issue information through experience or observation. This reduces or negates media influence on perceptions of issue importance. Some researchers, however, noticed that media were influential for some obtrusive issues. Demers et al. (1989) hypothesized that issue obtrusiveness could lead individuals to seek further information from media or could make the issue more salient when encountered in media. Under this hypothesis, issue obtrusiveness alone was more influential on issue importance than media alone, but obtrusiveness and media together were the most influential.
Research supports both the Zucker and Demers et al. hypotheses. The research has been problematic, however. First, these macro-level studies did not examine micro- level processes, which might have explained the conflicting results. Second, the research focused on primarily on two channels of information acquisition, personal experience and national-level information from media, ignoring other potential information channels. Third, the research did not consider differences in issue conditions at the local level, which could affect information acquisition. In order to further obtrusiveness research it is necessary to consider individual-level processes,
59 examining multiple information channels. This is most easily done by studying the processes for a single issue. I will use a contextual analysis framework developed by
Books and Prysby (1991) that focuses on information flow.
Earlier I defined issue obtrusiveness as the degree to which individuals may directly experience or observe salient aspects of an issue. Direct experience or observation implies local information. Weatherford (1983b) argued that local information may be perceived as more relevant than information from other areas and therefore may be more influential. This suggests that national information from media may less influential than local information. There are, however, arguments favoring the influence of national information from media, even if an issue is obtrusive. First, many individuals may be accustomed to turning to media for information. Media dependency theory (Ball-Rokeach, 1985) argues that media, as part of the social structure, control information resources, and so many individuals will turn to media for information.
Second, media information may be easier to understand than ‘everyday’ information.
Sims (2003) noted that economic information in media is “coded” so that the public can understand the information. By comparison, information acquired through experience and observation is uncoded. Coded media information might be used to interpret uncoded obtrusive information. Third, media may present consistent messages, increasing the likelihood of message reception. Since media outlets share the same or similar news sources, audiences for different media outlets are likely to receive similar messages about the economy. Local media may follow national media as a guide for presenting information (Shoemaker & Reese, 1991). This could create a consonance of
60 media information about the economy, with similar information being communicated about national and local conditions (Noelle-Neumann & Mathis, 1987).
The opinion topic for this study is consumer confidence, which is a set of evaluations of economic conditions. Consumer confidence is related to the perception of the economy as an important issue. As the public becomes more concerned about economic conditions, consumer confidence drops. For this topic, the agenda-setting hypothesis predicts that as news coverage of the economy increases, the perception of the economy as an important issue will increase and consumer confidence will decrease. The agenda-setting hypothesis focuses on information transmission from media; other channels of information should not be significant predictors of consumer confidence. Therefore, we should see differences in consumer confidence related only to levels of attention to news about the economy.
H1a-1: Consumer confidence levels will vary with attention to news about the
economy, but will not vary with personal economic experience of the economy.
H1a-2: Consumer confidence levels will vary with attention to news about the
economy, but will not vary with observation of the economy.
The agenda-setting hypothesis is essentially a straw man here, since we expect the economy to be obtrusive, which should reduce the effect of media on public opinion. The obtrusiveness hypothesis is based on the assumption that the individual may acquire issue information through personal observation of experience for some
61 issues. The economy is such an issue; we can experience many aspects of the economy in everyday life (Haller & Norpoth, 1997). The obtrusiveness hypothesis predicts that personally experienced or observed information influences consumer confidence much more than media.
H1b-1: Consumer confidence levels will vary inversely with personal economic
experience and will not vary with attention to news about the economy.
H1b-2: Consumer confidence will vary positively with observation of the
economy and will not vary with attention to news about the economy.
The cognitive priming/media dependency hypothesis may be thought of as a cross between the agenda-setting and obtrusiveness hypotheses. Obtrusive information may lead some individuals to seek out more information from in media or it may make media information more salient if it is encountered. Obtrusiveness and media together may be more influential than either channel alone. For example, Iyengar and Kinder
(1987) found that, under some conditions, news about unemployment affected those who were unemployed more than those employed.
H1c-1: Consumer confidence will vary inversely with personal economic
experience and will vary with attention to news about the economy.
H1c-2: Consumer confidence will vary positively with observation of the
economy and will vary with attention to news about the economy.
62 For this project, consumer confidence is operationalized using the Index of
Consumer Sentiment questions. The ICS can be divided into components that measure consumer perceptions of current economic conditions and consumer expectations.
Nadeau et al. (1999) argued that individuals could make judgments of current economic conditions based on their experiences and observations, but that their expectations would be based on information from media. Several scholars have found that personal financial circumstances are a factor in perceptions of economic conditions even for those with high levels of attention to news about the economy (Conover, Feldman, &
Knight, 1986; Duch et al., 2000; Weatherford, 1983a). Media dependency theory (Ball-
Rokeach, 1985) predicts that many people will turn to media for information about the economy if they feel threatened. This implies that they perceive current conditions without the benefit of media.
H2a: The current conditions component of consumer confidence will be more
strongly associated with personal economic experience than with attention to
news about the economy.
H2b: The current conditions component of consumer confidence will be more
strongly associated with observation of the economy than with attention to news
about the economy.
63 H3a: The expectations component of consumer confidence will be more
strongly associated with attention to news about the economy than with
experience with economic conditions.
H3b: The expectations component of consumer confidence will be more
strongly associated with attention to news about the economy than with
observation of the economy.
Media dependency theory (Ball-Rokeach, 1985) predicts that individuals will turn to media for more information when they feel threatened by conditions. If this is true, we should see higher levels of attention to news about the economy by those who are most likely to perceive a threat: those with negative household financial circumstances and those living in areas with higher unemployment levels. We should see a similar pattern for interpersonal discussion of the economy.
H4a: Interpersonal discussion of the economy will vary positively with
household economic experience.
H4b: Interpersonal discussion of the economy will vary positively for those
living in areas with increasing unemployment.
H5a: Attention to news about the economy will vary positively with household
economic experience.
H5b: Attention to news about the economy will vary positively for those living
in areas with increasing unemployment.
64 Earlier studies of issue obtrusiveness operationalized media in terms of national news content. This approach assumes that either local information is consonant with national information or that local information contributes no effect of its own. National media may not carry important information. Unemployment is thought to be a major driver of consumer confidence, but Behr and Iyengar (1985) noted that national media give little coverage to unemployment. Weatherford (1983b) argued that individuals could receive information about multiple geographic areas, and information from the area in which a person resides would be considered the most relevant. Weatherford
(1983b) and Books and Prysby (1999) both found some a relationship for local unemployment rates on perceptions of economic conditions, but neither study examined attention to media nor media use. In this study, attention to news about the economy is operationalized to consider both national and local information. If Weatherford is correct, local information will be more important than national information.
H6: Attention to local news about the economy will be more strongly associated
with consumer confidence than attention to national news about the economy.
In their general forms, the agenda-setting, obtrusiveness, and cognitive priming/media dependency hypotheses do not predict differences in media effects associated with type of media. There are differences, however, in the amount and kind of information that different media convey. Neuman, Just and Crigler (1992) found that television was better at communicating abstract and distant political issues and
65 newspapers were better at concrete and immediate issues. If the economy is a concrete and immediate issue, then attention to news about the economy in newspapers should have more of an effect on consumer confidence than attention to news from television.
H7: Attention to news about the economy in newspapers will be more strongly
associated with consumer confidence than attention to news about the economy
on television.
66 CHAPTER 3
METHOD
Data
Data for this study came from two sources. Individual-level data were from six monthly telephone surveys of Ohioans about consumer confidence and other economic and political topics. These data were collected from November 2001 through April
2002 for the Buckeye State Poll, which was conducted for the Columbus Dispatch.
More than 500 interviews were collected each month. Response rates ranged from 47 percent to 40 percent. The monthly response and cooperation rates are in figure 3.
Data about local economic contexts were from monthly unemployment rate estimates made by the Ohio Bureau of Labor Market Information. During the period these data were collected, county unemployment levels ranged from 3.3 percent to 12.2 percent.
The Buckeye State Poll replicated the University of Michigan’s national Index of Consumer Sentiment at the state level. Dunn and Mirzaie (2006) noted that the
Buckeye State Poll led changes in the national Index of Consumer Sentiment during the period the Buckeye State Poll was in operation. That is, Ohioans tended to react to changes in the economy one or two months sooner than the rest of the nation. By
67 Month/Year Response Rate* Cooperation Rate Sample Size November 2001 45% 81% 549 December 2001 47% 85% 587 January 2002 47% 88% 518 February 2002 44% 83% 509 March 2002 46% 88% 504 April 2002 40% 82% 503 Note: * Response rates were calculated using AAPOR response rate formula one.
Figure 3. Survey response statistics
happenstance the data for this study were collected during a period of economic change, and this may be an asset to the study. Recall that economists have noted that many people do not update their economic information unless it becomes necessary (Mankiw
& Reis, 2002; Reis, 2004). Also, Bartels (1993) argued that it is possible to detect changes in public opinion only when a large volume of new information becomes available to the public. Changes in the economy before and during the period of data collection may have provided sufficient new economic information to the public to increase the chance that their perceptions of the economy changed. The economy was in difficulty from 2000 through 2003, and the period from March 2001 through
November 2001 was labeled a recession (Hall, Feldstein, Frankel, Gordon, Romer,
Romer et al., 2003). Seasonally adjusted national and Ohio unemployment rates generally increased from early 2001 through early 2003. In 2000, both the NASDAQ and Dow Jones Industrial Averages stock indices dropped in value with the 'dot com’
68 bust, and in 2001 the indices lost value again. Both stock indices bottomed out after the
9-11 terrorist attacks and rose through early 2002 only to drop again later in 2002.
Unfortunately, the 9-11 attacks could be a confounding factor for these data, which were collected in the months shortly after 9-11. The 9-11 attacks may have affected consumer confidence. Katona (1975) found that non-economic events such as the Vietnam war and Watergate affected consumer confidence. Hall (1993) has argued that the 1990-1991 recession was at least partially due to consumers’ reactions to the first Gulf War. Berry (2004) found non-economic events could affect consumer confidence in the United Kingdom. John Maynard Keynes (1936) referred to 'animal spirits,' by which he meant unpredictable forces that could affect investors’ economic expectations. Garner (2002), however, has argued that the 9-11 attacks had no real effect on the economy because the economy was already declining and the stock market had started to slide again before 9-11. Both the Index of Consumer Sentiment and the
Consumer Confidence Index dropped before the 9-11 attacks, then rose following them
(Saad, 2002). The Buckeye State Poll followed the same pattern. The results of this study must be evaluated with the understanding that the data were collected during a unique time period.
Measures
Consumer Confidence
The main dependent variable will be an individual-level index of consumer confidence constructed from responses to the questions from the Index of Consumer
Sentiment. Those questions ask for retrospective evaluations of family financial
69 circumstances, one-year expectations for family financial circumstances, one-year expectations for national economic conditions, five-year expectations for national economic conditions, and perceptions of current buying conditions for durable goods.
Appendix B contains the wording and response options for the survey questions that are the basis for the individual-level variables. The Index of Consumer Sentiment that is publicly reported is an aggregate index. A single score is calculated for the population each month; individual-level consumer confidence is not calculated. Because this study is focusing on individual-level processes, it was necessary to create a consumer confidence index at the individual level (CONFID). First, the coding of the individual items was reversed so that positive evaluations had higher values. Next, refusals to respond to a question and ‘don’t know’ responses were recoded to the middle value of each scale. The items were then converted to Z-scores and summed for an individual index of consumer sentiment. Two component indexes were created as well. The current conditions index (CURR) was created by summing the Z-scores of the first and fifth questions from the Index of Consumer Sentiment. The expectations index (EXPT) was created by summing the Z-Scores of the second, third, and fourth questions.
Personal Financial Circumstances
The study will use two measures of personal or household financial circumstances. The first is an objective measure of a household’s ability to cope as an economic entity, household unemployment (HHEMP). Loss of employment can be a serious blow to the financial stability of many households. The questionnaire asked for the respondent’s employment status and the employment status of the respondent’s
70 spouse or partner if there was one. If either person was unemployed, a household’s unemployment status was coded as a ‘1.’ All other situations were coded as ‘0.’ The second measure of personal or household financial circumstances is related to respondents’ subjective evaluations of their household’s debt load (DEBT). Even during periods of high unemployment many households will not have a major income- provider out of work, but they might have debt loads that could make them concerned about possible changes in the economy. Individuals may perceive their own financial situation differently than others would. This measure captures that subjective reaction.
The question asked respondents how often they worried about their overall debt using a five-point scale. Those who said they had no debt were given a separate code.
Responses were reverse coded to a six-point scale (0 = no debt, 1 = not at all, 2 = hardly ever, 3 = some times, 4 = most of the time, and 5 = all of the time). Those who refused to respond to the question or said they didn’t know were set to missing (15 cases).
Group Membership
The literature suggests that those belonging to different social groups share economic perceptions because they share similar economic experiences or because they have the same motivations to attend to economic information. Group membership has usually been assigned based on socioeconomic indicators. The Buckeye State Poll included several items that might be used as indicators of group membership.
Age (AGE) – Based on the respondent’s year of birth, recoded into age in years.
Refusals were treated as missing (37 cases).
Gender (SEX) – Coded as “1” for male and “0” for female.
71 Education (EDUC) – Highest level of respondent’s education. Refusals were treated as missing (11 cases)
Race (RACE) –Whites were coded as “0” and all other racial and ethnic groups as “1.” Refusals were treated as missing (44 cases).
Household income (HHINC) – The questionnaire contained two questions asking about household income. The first question asked for the best estimate of a household’s income for the previous year. Those unable or unwilling to respond to that question were then asked to identify the income category that best described their household’s income. Responses to these two questions were combined and recoded into five categories (1 = less than $20,000; 2 = $20,001 to $30,000; 3 = $30,001 to $50,000; 4 = $50,001 to $75,000, 5 = greater than
$75,000). Refusals to both questions were treated as missing. There were 408 cases for which household income was missing. This is about 13 percent of the entire six months of data. November 2001 had the highest percentage of non- response for household income, 14.9 percent; April 2002 was lowest with 10.9 percent.
Home ownership (OWN) – Home ownership is a significant financial investment. Home owners might be concerned about economic conditions that threaten their investment. This item was coded as “1” for home ownership and
“0” for all other types of housing arrangements.
Marital Status (MARR) – Individuals married or in a committed relationship with another person might find it easier to weather difficult economic
72 conditions. Those married or living in a relationship as married were coded as
“1”and all other statuses were coded as “0.” Refusals were treated as missing (7
cases).
Children in the household (KIDS) – The responsibility of children in a
household might increase concern about the economy during downturns.
Households with any children present were coded as “1” and all others were
coded as “0.” Refusals were treated as missing (5 cases).
Political Partisanship
A persistent finding is that political attitudes and partisanship are related to evaluations of economic conditions, which affects Presidential voting and approval
(Lewis-Beck & Paldam, 2000). In general, those identifying with the party holding the
White House tend to judge the economy more positively. George W. Bush was
President during the period these data were collected, so I expect Republicans to have more positive outlooks about the economy. Political partisanship (PARTY) was coded on a seven-point scale based on party identification and strength of identification or leanings toward a party (0 = strong Democrat, 1 = not so strong Democrat, 2 = lean toward Democrats, 3 = neither Democrat nor Republican, 4 = lean toward Republicans,
5 = not so strong Republican, and 6 = strong Republican).
Information Channels
The literature suggests that information about the economy affects perceptions of conditions (Duch et al., 2000). Katona (1975) argued that information from media drove consumer confidence. Katona (1960) and Haller and Norpoth (1997) did not find
73 evidence that media use affected consumer confidence in individual-level studies, but both of these studies may have used inadequate measures of media. The measure used in both studies asked survey respondents if they recalled hearing any news about the economy. This measure does not address actual media use or attention. There are several factors that must be considered for constructing media measures. One is whether for measure exposure or attention to media. Chaffee and Schleuder (1986) found that measures of attention to media were better than exposure measures, especially for television. Another factor is content. Traditional media use measures, such as the number of days read a newspaper in the past week, may be of little use as well because they don’t focus on any particular content. Individuals may be heavy media users of content other than the issue being studied. Zaller (1992) argued that measures designed for specific topics or content domains were preferable to general measures. Finally, Weatherford (1983b) noted that information can apply to different geographic areas. It is possible to increase the specificity of the measure by asking about the geographic areas respondents pay attention to.
Four questions on the survey account for these factors. Each question asks attention to news about the economy for a different combination of medium and geographic information area. The four combinations are: newspapers and news about the local economy (NSPLOC), newspapers and news about the national economy
(NSPNAT), television and news about the local economy (TVLOC), and television and news about the national economy (TVNAT). Responses to these questions were reverse coded so that higher attention levels had higher values (1 = no attention at all, 2 = a
74 little bit of attention, 3 = some attention, and 4 = a lot of attention). Correlations among these items ranged from 0.299 to 0.645 (Please see figure 27 in Appendix A.). These four items were used to create indexes of media attention. Total attention to news about the economy was created by summing the four items (ATTMED, " = .77). Attention to news about the local economy (ATTLOC, " = .56) was created by summing (NSPLOC and TVLOC). Attention to news about the national economy (ATTNAT " = .64) was created by summing (NSPNAT and TVNAT). Attention to news about the economy in newspapers (ATTNSP " = .80) was created by summing (NSPNAT and NSPLOC).
Finally, Attention to news about the economy on television (ATTTV " = .73) was created by summing (TVNAT and TVLOC)
Katona (1975) acknowledged that personal and observation and interpersonal communication about the economy were powerful, although, in his view, idiosyncratic influences on consumer confidence. Interpersonal discussion might be a way of both acquiring information and confirming one’s own perceptions of conditions. One question asked respondents how often they talked to others about the economy (TALK).
Responses to these questions were reverse coded so that higher levels of discussion had higher values (1 = almost never, 2 = hardly ever, 3 = once in a while, 4 = fairly often, and 5 = all the time). Refusals were treated as missing (2 cases)
Local Economic Context
Local context can create an information environment that affects what information is attended to and how it is processed (Books & Prysby, 1999). The public may respond to a variety of economic stimuli (Curtin, 2003). For example, individuals
75 may react to changes in the price of gasoline or other commodities, fluctuations in the stock market, and changes in unemployment levels. Many of these factors have limited variation at the local level. Unemployment, however, can vary widely over small areas.
The U.S. Bureau of Labor Statistics and state governments track unemployment down to the county level. Unemployment is considered one of the main economic influences on consumer confidence, and there is evidence that unemployment at the state or labor market area level affects perceptions of economic conditions (Books & Prysby, 1999;
Weatherford, 1983b). Monthly county unemployment estimates were made by the
Ohio Bureau of Labor Market Information. These county-level unemployment data were merged with the Buckeye State Poll data based on the respondents’ county of residence. Books and Prysby noted that determining the appropriate unit of analysis was a fundamental problem in contextual analysis. Books and Prysby did not find any contextual relationship for using county-level data, but they and Weatherford found a relationship using unemployment rates from large labor market areas. Labor market areas are defined as geographic areas in which labor supply and demand needs are met from within the area (Goldstein, 2005). It could be that the overall unemployment rate in a labor market area is more important than a county-level unemployment rate. In practice, large metropolitan statistical areas are close approximations of labor market areas. This suggests another reason why labor market areas might be the proper unit of analysis: MSAs are often large media markets. Local media could provide information about the local economy (Kaniss, 1991; Logan & Molotch, 1987). The Ohio Bureau of
Labor Market Information provides unemployment estimates for the larger MSAs in
76 Ohio. This information was also merged with individual-level data based on the county of residence. Twenty cases did not have the county of residence recorded, so the local unemployment data were missing for these cases.
Unfortunately, there’s little theoretical guidance about how to operationalize contextual unemployment information. There are several ways in which unemployment information could be operationalized. Weatherford used a weighted average of nine months of unemployment data with the most recent months more heavily weighted.
Books and Prysby used an average of three months of unemployment data.
Weatherford and Books and Prysby were interested in the processes affecting election attitudes and used data from periods immediately prior to elections. In both studies, the months immediately before the election were considered the most important. This study does not have that constraint, and there are several ways in which the contextual unemployment data could be operationalized. An obvious choice is to use the unemployment rate from the month in which a respondent was interviewed. Another approach is to use the change in unemployment levels over some time period. Some scholars have noted the public seems to react to changes in unemployment levels rather than absolute levels (Haller & Norpoth, 1994; Middleton, 1996). If the public responds to changes in unemployment levels, we don’t know whether they notice absolute changes or proportional changes. Additionally, there is no guidance as to the period of time over which change must occur. Given this lack of theoretical justification for any particular operationalization, I include several different operationalizations of unemployment rate information. These operationalizations are: the absolute
77 unemployment rate for the month when respondents were interviewed (CEMR for the county, MEMR for the MSA; one, three, six, nine and twelve month absolute changes in the unemployment rate (CUD[1,3,6,9,12]; MUD[1,3,6,9,12]); and one, three, six, nine and twelve month proportional changes in the unemployment rate
(CUP[1,3,6,9,12]; MUP[1,3,6,9,12]). The absolute change in the unemployment rate was computed by subtracting the prior base month’s unemployment rate from the unemployment rate of the month of the interview. The proportional change in the unemployment rate was computed by taking the absolute change for month and dividing it by the unemployment rate for the prior base month.
Analysis Plan
Most of the variables thought to affect consumer confidence or attention to media are individual-level variables. This suggests using ordinary least squares regression. Contextual analysis, however, also uses variables that are not measured at the individual level. Unemployment rates and changes in unemployment rates are measured at the county and MSA level. Treating these variables as individual-level variables would violate one of the assumptions of OLS regression because errors at the county or MSA level will be correlated. Individuals in the sample are nested within time-space groups. An alternative to OLS regression is a multilevel analysis, which relaxes some of the assumptions of OLS regression.
Equations 1 and 2 are examples of equations for hypotheses with consumer confidence as the dependent variable. Equation 1 contains the variables at the individual level; equation 2 contains the county level variables. The second equation
78 $ $ $ $ $ CONFIDij = 0j + 1jHHEMPij + 2jDEBTij + 3jAGEij + ß4jSEXij + 5jEDUCij
$ $ $ $ $ + 6jRACEij + 7jHHINCij + 8jOWNij + 9jMARRij + 10jKIDSij
$ $ $ + 11jPARTYij + 12jATTMEDij + 16jTALKij + rij
$( ( ( 00 = 00 + 1CEMRj0 + 2CUD1j + u0
$ $ $ $ $ ATTMEDij = 0j + 1jHHEMPij + 2jDEBTij + 3jAGEij + ß4jSEXij + 5jEDUCij $ $ $ $ $ + 6jRACEij + 7jHHINCij + 8jOWNij + 9jMARRij + 10jKIDSij $ + 11jPARTYij + rij
$( ( ( 00 = 00 + 1CEMRj0 + 2CUD1j + u0j
Figure 4. Example multilevel equations for individual consumer confidence and attention to news about the economy.
allows the intercept to vary for each county. Equations 3 and 4 are examples for hypotheses with attention to media as the dependent variable.
A general issue with the analysis of survey data is missing data. Survey respondents may refuse to answer questions or may not know an answer. If a question’s response options are categorical, it is possible to treat refusals and ‘don’t know’ responses as a category and include them in the analysis. This is not the case for questions with ordered or continuous response options, such as education, income, or age. There are two paths to take to deal with these missing data. One path is to use imputation techniques to substitute other values for the missing values, such as mean substitution, random substitution, and hot decking. The other path is to simply drop the cases with missing values from the analysis. This can have a cumulative effect when
79 many cases have a missing value and are dropped from the analysis. In addition to decreasing the power of the analysis because of the reduced sample size, this could potentially affect the outcome of the analysis by causing shifts in the distribution of other variables. For the analysis here, cases with missing values previously noted will be dropped from the analyses. Unfortunately, 408 cases have missing data for household income. When combined with the other cases with missing values, this means 489 of the 3161 cases in the sample will be dropped from the multilevel analysis and 479 cases will be dropped from the ordinary least squares analysis. Figure 28 in
Appendix C shows the means (or medians) and standard deviations for the major analysis variables for the full sample and with the 489 cases with missing values removed from the sample. The shifts in the means or medians are small, which suggest that dropping the cases with missing values will have a small effect. The largest effect appears to be a shift in the mean of consumer confidence from 0.0 to 0.66 with a slight change in the standard deviation (from 2.89 to 2.90). The cases for which there are no missing values in the analysis are slightly more confident about the economy. Both the current conditions and expectations components of consumer confidence shifted more positively as well. This may have some small effect on the analysis.
80 CHAPTER 4
ANALYSIS AND RESULTS
There are several dependent variables to be analyzed for this study: individual consumer confidence, the current conditions and expectations components of consumer confidence, attention to news about the economy, and interpersonal communication of the economy. The primary analysis technique used here is multilevel analysis.
Multilevel analysis was chosen because most of the predictors were measured at the individual level, but the contextual data – the county and metropolitan statistical area unemployment rate data – were measured at a different level. Everyone living within a county or MSA shares the same unemployment rate at any point in time. Thus, the unemployment rate observations were not independent, which violates one of the assumptions of ordinary least squares regression (Hayes, 2005; Luke, 2004). Multilevel analysis techniques relax this assumption. Errors associated with the different levels are treated separately rather than pooling them into a single error term, which may reduce the chance of Type I errors and improve level-one hypothesis testing (Luke).
Unfortunately, some aspects of multilevel models can be difficult to interpret compared to ordinary least squares regression models. For example, programs for multilevel models do not provide standardized regression coefficients making it hard to compare the effects of individual predictors. Model fit is harder to interpret with multilevel
81 models because they do not have an R-square statistic that reports the percentage of variance accounted for (Hayes; Luke). The pseudo-R square of multilevel models allows gauging of the improvement of fit for in serially constructed models, but it is not possible to use the pseudo-R square to compare models that use alternate versions of a variable (Luke). The coefficients of the multilevel and OLS models should be similar if the level-two effects of the multilevel model are small. This would also mean that the
R-square of the OLS regression should give a reasonable approximation of how well the models account for the variance in the dependent variable. Where possible, I will use multilevel models for hypothesis testing, but will use OLS models to help explain the level-one effects and estimate the variance accounted for.
Individual Consumer Confidence
Analysis.
The main dependent variable is individual consumer confidence. The notation
‘individual’ is necessary to distinguish this measure from consumer confidence as it is normally reported. The consumer confidence indexes are aggregate indexes. That is, a single confidence score is calculated for the entire population. Aggregate index scores aren’t useful for examining individual-level processes. For this reason I created an individual-level confidence index by summing the z-scores of the five questions used in the Index of Consumer Sentiment. Figure 5 shows the average of the individual-level scores and the aggregate consumer confidence score by month. Much of the difference in magnitude between the aggregate confidence index and the average of the individual confidence index scores is because the aggregate index is scaled up to fluctuate around
82 Ohio Consumer Average Individual Month Confidence Index Consumer Confidence November 2001 85.5 -.249 December 2001 85.0 -.327 January 2002 86.7 .000 February 2002 88.7 -.031 March 2002 93.2 .342 April 2002 90.5 .336
Figure 5. Ohio Consumer Confidence Index and average individual consumer confidence score by month.
100. Despite the difference in scale, we can see that the aggregate index and the average of individual indexes move somewhat together. Both rise from November and
December to higher levels in March and April. However, the month-to-month changes in the indexes do not track exactly. A reason for this difference may be in how ‘neutral’ responses are handled in calculating the indexes. The calculation of the aggregate index involves subtracting the percentage of unfavorable responses (the economy will get worse) from the percentage of favorable responses (the economy will get better).
Neutral responses (no change in the economy) are not included in the calculation of the aggregate index and so do not affect the final value. It is possible (although probably unlikely) to have two aggregate index scores that are equal but differ on the percentage of the population giving neutral responses. In contrast to the aggregate index, the calculation of the individual-level index includes neutral responses, and this affects the average. The percentage of neutral responses to the individual question differs each
83 Nov. Dec. Jan. Feb. Mar. Apr. Item 2001 2001 2002 2002 2002 2002 Q1 31.5% 31.8% 33.1% 30.3% 27.3% 26.5% Q2 49.0 54.3 45.4 55.3 50.0 44.3 Q3 19.2 17.9 14.8 13.9 16.5 19.7 Q4 16.9 15.5 11.2 13.3 17.1 17.2 Q5 16.5 18.0 19.2 20.5 19.5 21.8
Figure 6. Percentages of neutral responses to individual Index of Consumer Sentiment items by month.
month. Figure 6 shows the percentage of neutral responses to each of the five questions by month. The comparison of the aggregate and individual indexes shows that, although there are some differences between the indexes, they are sufficiently similar that we can be assured that the individual-level index is not a major distortion of the concept of consumer confidence.
The traditional place to start a multilevel analysis is with a model containing no predictors. This ‘null’ model tests whether there are any differences in the dependent variable across the level-two units (Hayes, 2005; Luke, 2004). There are two dimensions of second level. Individuals are nested in both time and space. The unemployment rate an individual is exposed to is a function of both the area and the point in time. I examined four null models using month and county as individual factors and in combination. The differences among these null models were small, but the best null model was the one in which county and month were combined as a single factor. This combination also reflects the way in which the contextual data are
84 recorded. For the six-month period that these data span, there are 528 unemployment rates–a unique unemployment rate for each county for each month. The total variance of individual consumer confidence is 8.381. The estimated variance associated the county-month second-level units is 0.246. The Wald Z statistic is 2.802, p = .005, so the variance associated with the county-month combination is statistically significant.
The intra-class correlation (ICC) tells us the proportion of variance in the dependent variable accounted for by the second level units; it is the same as a one-way ANOVA random-effects model (Luke). The ICC is 0.029, which shows that the county-month second-level random effects account for only 2.9 percent of the total variance in the null model. This is such a small portion of the total variance that we could perhaps rely on ordinary least squares for the analysis. However, a multilevel analysis makes sense conceptually and as noted may improve hypothesis testing. The small ICC will make it easy to use OLS regression to help interpret the multilevel model.
Figure 7 shows the multilevel model for individual consumer confidence. I will first discuss the level-one predictors in terms of the conceptual factors that appear in the literature (e.g., Duch et al., 2000). The first factor is household financial circumstances, which has been one of the most consistent findings in the literature. Individuals might project their own financial circumstances onto the greater economy or may use their own circumstances as a heuristic when making judgments about other economic conditions. There were two measures of household financial circumstances included in the model. One measure gauged significant household unemployment, defined as whether the survey respondent or the respondent’s spouse or partner (if there was one)
85 Variable B SE Household unemployment -1.257*** .252 Worry about debt -.308*** .039 Age -.035*** .004 Gender .568*** .108 Education .082* .029 Race .092 .171 Household Income .266*** .047 Home ownership -.240# .139 Marital status .015 .121 Children in the home -.128 .121 Partisanship .232*** .026 Attention to news about the local and national economies, -.046* .019 in newspapers and on television Talk about the economy .068 .056 County unemployment rate -.005 .047 12-month proportional change in county unemployment rate .905* .398
Note: N= 2,672, # p < .1; * p < .05; ** p < .01, *** p < .001
Figure 7. Multilevel analysis of individual consumer confidence using attention to news index, county-level data.
86 were unemployed. The second measure captured respondents’ subjective concern over their household’s debt, which might be perceived as burdensome. Both of these measures were significantly related to consumer confidence. Those who were unemployed or who had a spouse or partner who was unemployed had less consumer confidence (-1.257, p < .000). The more individuals said they worried about their household debt, the lower their consumer confidence (-.308, p < .000). The second factor concerns group memberships. Consumer confidence may be related to membership in several social or demographic groups. Members of these groups may share similar socialization toward the economy or similar economic experiences. They may also share similar media use and attention patterns. Several indicators of group membership were statistically significant at the .05 level. Consumer confidence was negatively related to age (-.035, p < .000). Older survey respondents may have had more negative experiences with the economy; some older respondents may be retired and living on fixed incomes. Men tended to be more confident about the economy than women (.568, p < .000). Education was positively related to consumer confidence
(.082, p < .05), as was household income (.266, p < .000). Respondent race, the presence of children under age 18 in the home, marital status, and home ownership were not statistically significant. The third factor is political partisanship. Those who identify with the party holding the White House tend to be more confident about the economy than those identifying with the opposition party. That was the finding here.
Republican George W. Bush held the White House during the period of data collection.
Strong Republicans were more positive about the economy than strong Democrats
87 Variable B SE Household unemployment -1.024*** .252 Worry about debt -.303*** .039 Age -.035*** .004 Gender .544*** .109 Education .074* .030 Race .092 .171 Household Income .255*** .047 Home ownership -.246# .139 Marital status .020 .121 Children in the home -.118 .121 Partisanship .229** .026 Attention to news about the local economy, newspapers -.027 .070 Attention to news about the national economy, newspapers .028 .075 Attention to news about the local economy, television -.162* .066 Attention to news about the national economy, television -.017 .076 Talk about the economy .058 .056 County unemployment rate .003 .048 12-month proportional change in county unemployment rate .900* .399
Note: N= 2,672, # p < .1; * p < .05; ** p < .01, *** p < .001
Figure 8. Multilevel analysis of individual consumer confidence using individual attention to news items, county-level data.
88 (.232, p < .000), even after controlling for group memberships and household financial circumstances. The fourth factor is information or communication. Two channels of communication are included in the model: attention to news about the economy and interpersonal discussion of the economy. Interpersonal discussion of the economy was not a significant predictor of consumer confidence. The attention to news about the economy measure was measured with an additive index of the four attention to news items, and this index was significant (-.046, p < .05). Those who paid more attention to news about the economy tended to have less consumer confidence. It is possible the individual attention to news items have different relationships with consumer confidence and combining them in an index suppresses important information. The analysis in figure 8 is the counterpart to the analysis in figure 7, substituting the four individual attention to news items for the attention to news index. Only one of the individual attention to news items was statistically significant. Attention to news about the local economy on television was negatively associated with consumer confidence (-
.162, p < .05).
Figure 9 shows the ordinary least squares model for the individual-level variables. The unstandardized coefficients of the OLS model are very similar to the coefficients of the multilevel model, which makes sense since that the second-level contextual variables play only a limited role in consumer confidence. The standardized coefficients provide additional information about relationships of the individual-level predictors and individual consumer confidence. The strongest single predictor was age, which was negatively related to consumer confidence. The second strongest predictor
89 Variable B SE B $ Household unemployment -1.288*** .254 -.091 Worry about debt -.305*** .039 -.152 Age -.035*** .004 -.199 Gender .566*** .108 .096 Education .086* .029 .058 Race .164 .169 .018 Household Income .277*** .046 .136 Home ownership -.246# .139 -.037 Marital status .001 .121 .000 Children in the home -.151 .122 -.026 Partisanship .236*** .026 .169 Attention to news about the local and national -.043* .019 -.045 economy, all media Talk about the economy .056 .056 .020
Note: N= 2,682; # p < .1; * p < .05; ** p < .01; *** p < .001
Figure 9. Ordinary least squares analysis of individual consumer confidence using attention to news index, county-level data.
90 was political partisanship. The R2 for the household financial circumstances variables was .021 (p < .000). The R2 change of the OLS model with the group membership variables added was .108 (p < .000); after adding political partisanship to the model the
R22 change was .027 (p < .000). The R change after adding the communication variables to the model was .002 (p = .088). The R2 for the complete OLS model was
.157. As a set, group memberships account for the most variance, followed by political partisanship, and then personal/household financial circumstances. Interpersonal communication and attention to news about the economy account for a negligible portion of individual consumer confidence.
The obtrusiveness hypothesis was based on the idea that individuals might use direct issue experience to evaluate the social importance of issues. For this study, direct experience of the economy was household unemployment, which was a significant predictor of consumer confidence. Even in a fairly poor economy, however, most households will not have someone out of work. It might be possible for individuals to observe signs of local unemployment. These data do not include a measure of attention to or observation of local unemployment. However, if individuals do observe local unemployment conditions and those observations in turn affect individual consumer confidence, then we should see variations in consumer confidence associated with variations in local unemployment. The multilevel model presented in figure 7 includes two types of local contextual data: county unemployment rates during the month respondents were interviewed and the proportional 12-month change in the county unemployment rate. Several measures of change in the county unemployment rate over
91 time were tested: the actual percentage point change and the proportional change in the county unemployment rate over one, three, six, nine, and twelve month periods. The nine and twelve-month percentage point and proportional changes in unemployment were statistically significant, but the 12-month proportional change in the county unemployment rate had the best model fit. The current county unemployment rate was not a significant predictor of consumer confidence. The unstandardized coefficient for the 12-month proportional change in the county unemployment rate was .905 (p =
.024). What is puzzling is the sign of the coefficient. The positive sign indicates that the larger the proportional increase in unemployment more than 12 months, the more positive consumer confidence was. This is counter intuitive. I will discuss this finding later.
Weatherford (1983b) noted that an issue for contextual analysis is determining the proper area of analysis. The area of analysis should closely match the area from which individuals draw their information. Too large or too small an analysis area could lead to a misestimation of an effect size. It is possible that some geographical area other than county might be a better fit for unemployment as local context. Weatherford originally found a relationship between the unemployment rates of labor market areas and perceptions of economic conditions. The U.S. Bureau of Labor Statistics defines a labor market area as an economically integrated area. In terms of employment, labor market areas are self-contained but counties are not. A reason that labor market areas could be more appropriate geography for this analysis is that many people travel across county boundaries for work, but the majority of people working in a labor
92 Variable B SE Household unemployment -1.301*** .302 Worry about debt -.322*** .047 Age -.035*** .005 Gender .535*** .130 Education .064 .035 Race .042 .190 Household Income .250*** .056 Home ownership -.196 .168 Marital status .024 .147 Children in the home -.217 .145 Partisanship .219*** .032 Attention to news about the local and national economy, all -.064** .024 media Talk about the economy .098 .068 MSA unemployment rate .081 .098 12-month proportional change in MSA unemployment rate 1.555# .793
Note: N= 2,672; # p < .1; * p < .05; ** p < .01; *** p < .001
Figure 10. Multilevel analysis of individual consumer confidence using attention to news index, MSA-level data.
93 market area also live in the area. Metropolitan statistical areas (MSA) are generally considered labor market areas. A large portion of Ohio’s population resides in eight large MSAs. Figure 10 shows a multilevel model using unemployment information from the eight large MSAs as contextual data. The sample size is smaller for this analysis because it does include those living in counties outside of the eight MSAs. The coefficients of the individual-level predictors are similar to those of the multilevel model using county-level contextual data. The main difference here is that education is no longer statistically significant. These coefficients should be similar because the individuals in this analysis are a subset of the individuals in the analysis with county contextual data. Again, the current unemployment rate was not significant. Neither was the 12-month proportional change in MSA unemployment rate, although it approached significance. This result suggests that county unemployment levels are more meaningful as contextual information than unemployment levels for larger metropolitan statistical areas. Of course, it is possible that information from smaller geographic areas, such as a neighborhood, is more meaningful than county information, but unemployment data are not available for smaller areas.
Relevant hypotheses.
The agenda-setting, obtrusiveness, and cognitive priming/media dependency hypotheses make different predictions about media influences on the perception of issue conditions. Hypothesis H1a is the agenda-setting hypothesis. It predicts that attention to news about the economy and not direct experience with the economy or observation of economic conditions will be related to individual consumer confidence. Hypotheses
94 H1b-1 and H1b-2 are based on Zucker’s (1978) obtrusiveness hypothesis. They predict that direct experience with the economy and observation of economic conditions will be associated with consumer confidence and attention to news about the economy will not.
Hypotheses H1c-1 and H1c-2 are based on Demers et al.’s (1989) cognitive priming/media dependency hypothesis. These hypotheses predict that direct experience with the economy, observation of economic conditions, and attention to news about the economy will all be significantly related to consumer confidence. Figure 7 shows that personal experience with the economy, as measured by household unemployment, attention to news about the economy, and observation of economic conditions, as measured by the twelve-month proportional change in county unemployment rates, were statistically significant predictors of individual consumer confidence. The measure for observation of the economy was not in the expected direction, however.
These results support the hypothesis from two different approaches. Because direct experience and attention to news about the economy were significant, hypothesis H1c-
1, a cognitive priming/media dependency hypothesis, was supported. Because observation of economic conditions was not significant in the expected direction and attention to news about the economy was significant, hypothesis H1a-2, an agenda- setting hypothesis, was supported.
There were two hypotheses about the relationship of different facets of attention to news about the economy to consumer confidence. The first hypothesis concerns the geographic focus of the information attended to, and the second concerns media preferences. The underlying assumption of contextual analysis is that local conditions
95 create an information environment that affects what information is attended to and how that information is processed (Books & Prysby, 1991). Here, we are assuming that local economic conditions affect perceptions of economic conditions and consumer confidence. Weatherford (1983b) noted that individuals could attend to news about the economy for different geographies, from the local area to the nation as a whole. He argued that news from areas closer to the individual would be more relevant than news from more distance areas. This suggests that attention to news about the local economy will have a stronger association with consumer confidence than will attention to national news, which is hypothesis H6. The attention to news about the local economy was significantly associated with consumer confidence (figure 11), and the attention to news about the national economy was not, which supports hypothesis H6.
Finally, if people do augment their own experience or observation of economic conditions through news or if media are their only source of information, then media preference may affect the information obtained and their perceptions of economic conditions. There are, of course, differences in the amount and way in which newspapers and television present information (Neuman, Just, & Crigler, 1992).
Neuman, Just, and Crigler found that newspapers were better than television at communicating about concrete and immediate issues. Assuming that unemployment and the economy are concrete and immediate, attention to news about the economy in newspapers should be more strongly associated with consumer confidence than attention to news on television (H7). The analysis shows that attention to news about the economy on television was significantly associated with consumer confidence, and
96 Variable B SE Household unemployment -1.245*** .252 Worry about debt -.305** .039 Age -.035*** .004 Gender .549*** .108 Education .079* .030 Race .091 .171 Household Income .261*** .047 Home ownership -.240# .139 Marital status .017 .121 Children in the home -.121 .121 Partisanship .230** .026 Attention to news about the local economy -.096* .040 Attention to news about the national economy .010 .044 Talk about the economy .058 .056 County unemployment rate .006 .048 12-month proportional change in county unemployment rate .905* .397
Note: N= 2,672; # p < .1; * p < .05; ** p < .01; , *** p < .001
Figure 11. Multilevel analysis of individual consumer confidence using geographic focus attention to news indexes, county-level data.
97 Variable B SE Household unemployment -1.252*** .252 Worry about debt -.306*** .039 Age -.035*** .004 Gender .561*** .108 Education .077* .030 Race .093 .171 Household Income .259*** .047 Home ownership -.244# .139 Marital status .020 .121 Children in the home -.126 .121 Partisanship .231** .026 Attention to news about the economy, newspapers .000 .034 Attention to news about the economy, television -.095** .035 Talk about the economy .068 .056 County unemployment rate .002 .048 12-month proportional change in county unemployment rate .900* .399
Note: N= 2,672; # p < .1; * p < .05; ** p < .01; *** p < .001
Figure 12. Multilevel analysis of individual consumer confidence using media focus attention to news indexes, county-level data.
98 newspaper attention was not significantly associated with confidence (figure 12). This is the opposite of the predicted results, and so we fail to reject the null hypothesis for
H7.
Current Conditions Component
Analysis.
The Index of Consumer Sentiment can be broken into two component indexes: the current conditions and expectations indexes. These components differ on the time- frame being evaluated. Recall that Alt’s (1979) economic outlook concept had both current and forward-looking time dimensions. Evaluations of different time-frames may draw on different stores or sources of information. Nadeau et al. (1999) argued that individuals could use their own experience to evaluate current conditions, but they would be more likely to draw on media for information about future conditions. Figure
13 shows the multilevel model for the current economic conditions component of consumer confidence. We start with household financial circumstances. Both measures of household financial circumstances were statistically significant. As we might expect, those who were experiencing household unemployment had more negative evaluations of current conditions (-1.046, p < .000). Those who worried more about household debt also had more negative perceptions of current conditions (-.200, p
<.000). The next factor is group memberships. Only two group membership variables were significant predictors of the current conditions component. Older individuals were more likely to have negative perceptions of current conditions (-.019, p < .000).
99 Variable B SE Household unemployment -1.046** .138 Worry about debt -.200*** .021 Age -.019*** .002 Gender .057 .059 Education -.009 .016 Race -.034 .093 Household Income .133*** .025 Home ownership .006 .076 Marital status .009 .066 Children in the home -.015 .066 Partisanship .043** .014 Attention to news about the local and national economy, all -.023* .010 media Talk about the economy -.002 .031 County unemployment rate .009 .025 One-month proportional change in county unemployment -.215 .240 rate
Note: N= 2,672; * p < .05; ** p < .01; *** p < .001
Figure 13. Multilevel analysis of the current conditions component using attention to news index, county-level data.
100 Positive perceptions of current conditions increased as household income increased
(.133, p < .000). Gender, education, race, home ownership, marital status, and the presence of children in the home were not associated with perceptions of current economic conditions. The third factor is political partisanship. Political partisanship was significantly associated with current conditions (.043, p < .01). Strong Republicans were more likely to have more positive perceptions of current conditions than strong
Democrats. The fourth factor is communication. Interpersonal communication about the economy was not significantly related to perceptions of current conditions. The attention to news about the economy index was negatively related to perceptions of current conditions (-.023, p < .05). The more attention was paid to news about the economy, the less positive perceptions of current economic conditions were likely to be.
Last is the contextual information. Neither the current county unemployment rate nor the change in unemployment over time were significantly related to perceptions of current conditions. Figure 13 shows the one-month proportional change in county unemployment rate, which gave a marginally better model fit than the other change in unemployment measures. It is possible that the attention to news index obscures relationships between the confidence component indexes and different forms of attention to news about the economy. Figure 14 repeats the analysis in figure 13, substituting the four attention to news about the economy items for the attention to news index. The results using the individual attention measures are quite different from those using the attention index. None of the individual attention to news about the economy items were statistically significant, although attention to news about the local
101 Variable B SE Household unemployment -1.049*** .138 Worry about debt -.201*** .021 Age -.019*** .002 Gender .063 .059 Education -.009 .016 Race -.034 .093 Household Income .133*** .026 Home ownership .005 .076 Marital status .010 .066 Children in the home -.018 .066 Partisanship .044** .014 Attention to news about the local economy, newspapers .002 .038 Attention to news about the national economy, newspapers -.023 .041 Attention to news about the local economy, television -.010 .036 Attention to news about the national economy, television -.070# .041 Talk about the economy .002 .031 County unemployment rate .008 .025 One-month change in county unemployment rate -.220 .240
Note: N= 2,672; # p < .1; * p < .05; ** p < .01; *** p < .001
Figure 14. Multilevel analysis of the current conditions component using individual attention to news items, county-level data.
102 economy on television approached significance. All of the items except for attention to news about the local economy in newspapers have a negative sign. The different types of attention to news have an additive, negative relationship with perceptions of current economic conditions. No one medium or area of focus dominates perceptions of current conditions.
The OLS model (figure 15) shows that age had the strongest association with the current conditions component (-.204). This was followed by worry about household debt (-.184), household unemployment (-.140), political partisanship (.059), and attention to news (-.043). The R2 for the model was .109, about 11 percent of the total variance. The group membership variables together accounted for the largest portion of the variance (.065, p < .000), followed by the household financial circumstances variables (.038, p < .000). Partisanship contributed only .003 (p < .01) of the total R2.
The communication variables did not make a significant contribution to the total variance.
Relevant Hypotheses.
Hypotheses H2a and H2b predict that economic experience and observation of the economy have a stronger relationship with the current conditions component of consumer confidence than does attention to news about the economy. Direct experience of the economy in terms of household employment was more strongly related to consumer confidence than attention to news about the economy. This supports hypothesis H2a. However, neither measure of observation of economic conditions–the current unemployment rate nor the change in the unemployment rate
103 Variable B SE B $ Household unemployment -1.048*** .138 -.140 Worry about debt -.196*** .021 -.184 Age -.019*** .002 -.204 Gender .049 .059 .016 Education -.009 .016 -.011 Race -.026 .092 -.006 Household Income .132*** .025 .122 Home ownership .015 .076 .004 Marital status .008 .066 .002 Children in the home -.018 .066 -.006 Partisanship .044** .014 .059 Attention to news about the local and national -.022* .010 -.043 economy, all media Talk about the economy -.004 .031 -.003
Note: N= 2,682; * p < .05; ** p < .01; *** p < .001
Figure 15. Ordinary least squares analysis of the current conditions component using attention to news index, county-level data.
104 Variable B SE Household unemployment -.219 .194 Worry about debt -.108** .030 Age -.016*** .003 Gender .511*** .083 Education .092*** .023 Race .127 .131 Household Income .133*** .036 Home ownership -.249* .106 Marital status .009 .093 Children in the home -.112 .093 Partisanship .188*** .020 Attention to news about the local and national economy, all -.023 .015 media Talk about the economy .070 .043 County unemployment rate -.005 .037 12-month proportional change in county unemployment rate .938** .308
Note: N= 2,672; * p < .05; ** p < .01; *** p < .001
Figure 16. Multilevel analysis of the expectations component using attention to news index, county-level data.
105 over time–was significantly associated with the evaluation of current conditions. Thus, we fail to reject the null hypothesis for H2b.
Expectations Component
Analysis.
Figure 16 shows the multilevel model for the expectations component of consumer confidence. First are the household financial circumstances items. Unlike for the current conditions component, household unemployment was not significantly related to expectations. Worry about household debt, however, was negatively associated with expectations (-.108, p < .01). Those who worried more about household debt had more negative expectations about future economic conditions. Next are the group membership items. Several group membership variables were significantly associated with expectations, including variables not associated with the current conditions component. Age was negatively associated with expectations (-.016, p < .000). Men tended to have more positive expectations than women (.511, p < .000).
Those with higher levels of education (.092, p < .000) and higher household incomes
(.133, p < .000) also tended to have more positive expectations. Those who owned their homes tended to have more negative expectations (-.249, p < .000). Race, marital status, and the presence of children in the home were not significantly related expectations. The third factor is political partisanship, which was significantly associated with expectations. Strong Republicans were more likely to have more positive expectations about future economic conditions than strong Democrats. This was not the situation for the current conditions component. The next factor is
106 Variable B SE Household unemployment -.200 .194 Worry about debt -.102** .030 Age -.016*** .003 Gender .482*** .083 Education .083*** .023 Race .127 .131 Household Income .122** .036 Home ownership -.254* .106 Marital status .013 .093 Children in the home -.100 .093 Partisanship .185*** .020 Attention to news about the local economy in newspapers -.030 .053 Attention to news about the national economy in newspapers .051 .058 Attention to news about the local economy on television -.150** .051 Attention to news about the national economy on television .052 .058 Talk about the economy .056 .043 County unemployment rate -.006 .037 12-month proportional change in county unemployment rate .937** .308
Note: N= 2,672; * p < .05; ** p < .01; *** p < .001
Figure 17. Multilevel analysis of expectations component using individual attention to news items, county-level data.
107 communication about the economy. Neither interpersonal discussion of the economy nor the attention to news about the economy index was significantly associated with economic expectations. Last are the contextual variables. There were mixed results for the contextual variables. The current county unemployment rate was not significantly associated with expectations, but the 12-month proportional change in the county unemployment rate was significant (.938, p < .01). As with the overall consumer confidence measure, the proportional change in unemployment rates had a positive sign, indicating that those living in areas with increasing unemployment over the previous 12 months had more positive economic expectations. Figure 17 repeats the analyses in figure 16 using the four attention to news about the economy items instead of the attention to news index. Again, the results of the individual attention measures are quite different from the attention index. Attention to news about the local economy on television was significantly associated with economic expectations (-.150, p < .01).
Those who paid more attention to news about the local economy on television tended to have lower expectations. This is similar to the situation for the full consumer confidence index. Although the other attention to news items were not significant, the pattern among the items is interesting. The signs for the attention to news about the national economy items are positive and signs for the attention to news about the local economy are negative. When summed in the index of attention to news about the economy, the items cancel out, and so the attention to news about the economy index was not statistically significant for the expectations index.
108 Variable B SE B $ Household unemployment -.241 .195 -.023 Worry about debt -.108*** .030 -.072 Age -.016*** .003 -.122 Gender .517*** .083 .117 Education .095 .022 .085 Race .191 .130 .028 Household Income .146*** .036 .095 Home ownership -.261* .107 -.053 Marital status -.007 .093 -.002 Children in the home -.133 .093 -.030 Partisanship .192*** .020 .185 Attention to news about the local and national -.021 .015 -.029 economy, all media Talk about the economy -.060 .043 -.029
Note: N= 2,682; * p < .05; ** p < .01; *** p < .001
Figure 18. Ordinary least squares analysis of the expectations component using attention to news index, county-level data.
109 The OLS model for the expectations component (figure 18) is quite different from the model for current conditions. The strongest association was with political partisanship (.185). This was followed by age (-.122), which was the strongest predictor of current conditions. The third strongest association was with gender (.117).
Gender was not significantly associated with the current conditions component.
Household income had the fourth strongest association with expectations (.095), followed by worry about debt (-.072). Household unemployment was not significantly associated with expectations. The R2 for the model was .116, about 12 percent of the total variance. Again, the group membership variables together accounted for the largest portion of the variance (.077, p < .000). This was followed by the political partisanship (.032, p < .000). The household financial circumstances variables accounted for a relatively small portion of the variance (.003, p < .01). Again, the communication variables did not make a significant contribution to the total variance.
Relevant hypotheses.
Hypotheses H3a and H3b predict that attention to news about the economy will be a stronger predictor of economic expectations than experience or observation of the economy. Direct experience of the economy in terms of household employment was not significantly associated with expectations. The summative index of the four attention to media measures was not significant either. However, attention to news about the local economy on television was significantly associated with expectations.
This gives some support to hypothesis H3a. The results suggest that those paying attention to different types of sources or news about the economy might receive mixed
110 messages. Observation of economic conditions as measured indirectly by the current county unemployment rate was significantly related to expectations, but the relationship was positive, not negative as predicted. This means that hypothesis H3b was not supported.
Interpersonal Communication about the Economy
Analysis.
There is little theoretical discussion of the role of interpersonal communication in relation to issue obtrusiveness. Demers et al. (1989) specifically excluded interpersonal communication from their definition of obtrusiveness, but they did not give any justification for this exclusion. It seems likely that individuals will discuss local events and conditions that are important to them. Figure 19 shows the multilevel model for interpersonal communication about the economy. There are mixed results for the personal financial circumstances variables. Household unemployment was not a statistically significant predictor of talking about the economy, but worry about household debt was significant (.060, p < .000). The more people worried about their household debt, the more likely they were to talk to others about the economy. Several group membership variables were statistically significant. Age was negatively related to interpersonal communication about the economy (-.005, p < .000). Education (.022, p < .05) and household income (.049, p < .01) were positively related to talking about the economy. Non-whites (.144, p < .05) were more likely than whites to talk to others about the economy. Gender, home ownership, marital status, and the presence of children in the home were not associated with interpersonal discussion about the
111 Variable B SE Household unemployment -.022 .087 Worry about debt .060*** .134 Age -.005*** .001 Gender .049 .037 Education .022* .010 Race .144* .059 Household Income .049** .016 Home ownership .043 .048 Marital status .079 .042 Children in the home -.043 .042 Partisanship .006 .009 Attention to news about the local and national economy, all .150*** .006 media County unemployment rate .024 .018 Six-month proportional change in county unemployment rate -.412** .117
Note: N= 2,672; * p < .05; ** p < .01; *** p < .001
Figure 19. Multilevel analysis of interpersonal communication about the economy using attention to news index, county-level data.
112 economy. Despite the importance that the economy appears to have to voters, political partisanship was not significantly associated with interpersonal discussion of the economy. Attention to news about the economy is positively related to interpersonal discussion of the economy (.150, p < .000). There were mixed results for the contextual data. The current county unemployment rate was not a significant predictor, but some of the change in unemployment rate variables were significant. The best model fit was obtained with the six-month proportional change in county unemployment rate. The coefficient was negative (-.412, p < .01), meaning that increasing unemployment in a county over six months was associated with lower levels of interpersonal discussion about the economy.
Relevant hypotheses.
Despite Demers et al.’s (1989) exclusion of interpersonal communication as a form of obtrusiveness, it seems as though interpersonal communication about an issue would be common if an issue was obtrusive. Hypotheses H4a and H4b predict that experience and observation of the economy respectively will be positively associated with increased discussion of the economy. Direct experience of the economy as measured by household unemployment was not significantly associated with interpersonal discussion of the economy. We fail to reject the null hypothesis for H4a.
There are mixed results for the two indirect measures of observation of economic conditions. The current county unemployment rate was not significantly associated with discussion of the economy. The six-month proportional change in county unemployment rates was significantly associated with discussion of the economy.
113 However, the relationship was negative, meaning that the more unemployment increased over six months, the less people talked about the economy. This is contrary to the predicted relationship, and so we fail to reject the null hypothesis for H4b.
Attention to News about the Economy
Analysis.
The final dependent variable is attention to news about the economy. Demers et al.’s (1989) hypothesis is partially based on media dependency theory (Ball-Rokeach,
1985), which argues the public turn to media when they feel threatened by an issue because media control society’s information. If this is true, we might expect to see an increase in attention to news about the economy in areas with increasing unemployment. The measurement of attention to news about the economy in this project allows for some interesting analyses. The individual attention items can be analyzed separately or in different combinations. Figures 20 and 21 display the multilevel analyses for the attention to news about the economy measures. The analyses in figure 20 used contextual information at the county level, and the analyses in figure 21 used MSA-level contextual data. In both tables, the left most column shows the analysis for the index of all four attention to news about the economy items.
Moving to the right, the next two columns look at indexes of attention to news in newspapers and then on television without regard to the geographic focus of the information. Next come two columns for attention to news about the national economy and attention to news about the local economy regardless of medium. Finally, the last columns show analyses for the individual attention to news about the economy items.
114 B All Media /All Newspapers Television, National, Local, (SE) Geographies Nat. /Loc. Nat. /Loc. TV/Nsp TV/Nsp Household .121 .016 .106 -.056 .178 unemployment (.254) (.157) (.150) (.137) (.149) Worry about debt .035 -.002 .037 -.011 .046* (.039) (.024) (.023) (.021) (023) Age .034*** .017*** .017*** .017*** .017*** (.004) (.002) (.002) (.002) (.002) Gender .093 .109 -.016 .232*** -.140* (.108) (.067) (.064) (.058) (.063) Education .056# .083*** -.026 .060*** -.004 (.030) (.018) (.017) (.016) (.017) Race -.022 -.039 .005 .001 -.023 (.172) (.106) (102) (.092) (.101) Household .153** .146*** .005 .121*** .031 income (.047) (.029) (.028) (.025) (.027) Home ownership -.011 .033 -.044 -.008 -.003 (.140) (.086) (.083) (.075) (.082) Marital status .113 .011 .104 .040 .075 (.122) (.075) (.072) (.065) (.071) Children .141 .066 .081 .000 .140* (.122) (.075) (.072) (.066) (072) Partisanship -.010 .006 -.017 .009 -.021 (.026) (.016) (.015) (.014) (.015) Talk about 1.280*** .668*** .612*** .694*** .585*** the economy (.051) (.031) (.030) (.027) (.030) Co. .042 .041 .002 .008 .036 unemployment (.045) (.027) (.028) (.024) (.026) rate Prop change in (1 mnth lag) (1 mnth lag) (1 mth lag) (1 mth lag) (1 mth lag) unemployment -.650 -.121 -.485# -.309 -.353 rate (.448) (.269) (.276) (.244) (.256) Note: N= 2,672; # p < .10; * p < .05; ** p < .01; *** p < .001
Figure 20. Multilevel analysis of attention to news about the economy variables, county-level data.
(Continued)
115 Figure 20 (Continued)
B Newspapers, Newspapers, Television, Television, (SE) National Local National Local Household -.048 .063 -.011 .116 unemployment (.085) (.091) (.080) (.091) Worry about debt -.015 .014 .004 .033* (.013) (.014) (.124) (.014) Age .009*** .009*** .008*** .009*** (.001) (.001) (.001) (.001) Gender .158*** -.048 .072* -.090* (.036) (.039) (.034) (.039) Education .053*** .030** .007 -.033** (.010) (.010) (.009) (.011) Race -.009 -.031 .008 -.001 (.057) (.061) (.054) (.062) Household income .093*** .051** .025# -.020 (.016) (.017) (.015) (.017) Home ownership -.003 .040 -.002 -.043 (.047) (.050) (.044) (.050) Marital status -.005 .016 .045 .058 (.041) (.043) (.038) (.044) Children .013 .054 -.011 .090* (.041) (.043) (.039) (.044) Partisanship .004 .002 .006 -.022* (.009) (.009) (.008) (.009) Talk about .361*** .308*** .334*** .278*** the economy (.017) (.018) (.016) (.018) Co. -.005 .034* -.000 .001 unemployment rate (.016) (.016) (.014) (.017) Prop change in (9 mnth lag) (1 mnth lag) (1 mnth lag) (1 mnth lag) unemployment rate .124 -.021 -.212 -.283# (.071) (.155) (.142) (.169) Note: N= 2,672; # p < .10; * p < .05; ** p < .01; *** p < .001
116 We start with household financial circumstances. Unlike for consumer confidence, household or personal financial circumstances appear to have a limited relationship to attention to news about the economy. Household unemployment was not related to any measure of attention to news about the economy. Worry about household debt was positively associated with attention to news about the local economy, particularly on television. Next are the group membership variables. Several group membership indicators were associated with attention to news about the economy. Most striking was the relationship between age and attention to news about the economy. Age was positively related to all measures of attention to news about the economy. Attention to news about the economy tends to increase with age and without regard to the geographical focus of the information or to the medium. There are gender differences in attention to news about the economy, and these differences appear to cancel out somewhat. Men tend to pay more attention to news about the national economy; this association is stronger for newspapers than for television. Women tend to pay more attention to news about the local economy and appear to prefer television to newspapers. In the full, newspaper and television indexes, however, these effects cancel out. Education is positively associated with some attention to news measures and negatively associated with others. Education is positively related to attention to news about the economy in newspapers, with a slightly stronger relationship to news about the national economy than the local economy. Education is negatively associated with attention to news about the local economy on television. Race is not significantly associated with any of the attention to news about the economy measures. Household
117 B All Media /All Newspapers Television, National, Local, (SE) Geographies Nat. /Loc. Nat. /Loc. TV/Nsp TV/Nsp Household .310 .127 .178 -.054 .254 unemployment (.294) (.182) (.176) (.157) (.174) Worry about debt .046 .015 .030 .024 .069* (.046) (.028) (.027) (.025) (027) Age .032*** .017*** .015*** .015*** .017*** (.005) (.003) (.003) (.002) (.003) Gender .139 .128 .011 .216** -.079 (.127) (.078) (.076) (.068) (.075) Education .060# .084*** -.025 .060** .000 (.034) (.021) (.020) (.018) (.020) Race -.132 -.086 -.042 -.041 -.091 (.185) (.114) (110) (.099) (.109) Household .181** .176*** .004 .151*** .031 income (.055) (.034) (.033) (.029) (.032) Home ownership -.139 -.058 -.076 -.115 -.023 (.164) (.101) (.098) (.087) (.097) Marital status .035 -.024 .062 -.015 .051 (.143) (.088) (.085) (.077) (.085) Children .146 .036 .112 -.010 .156# (.141) (.087) (.084) (.075) (083) Partisanship -.002 .002 -.005 .024 -.026 (.031) (.019) (.018) (.016) (.018) Talk about 1.258*** .667*** .595*** .706*** .552*** the economy (.060) (.037) (.036) (.032) (.035) MSA .069 .009 .029 .021 .047 unempl. rate (.081) (.056) (.048) (.043) (.046)
Prop change in (1 mnth lag) (1 mth lag) (1 mth lag) (1 mth lag) (1 mth lag) unemployment -.839 .360 -.873* -.397 -.449 rate (.623) (.315) (.373) (.330) (.354) Note: N= 2,672; # p < .10; * p < .05; ** p < .01; *** p < .001
Figure 21. Multilevel analysis of attention to news about the economy variables, MSA-level data.
(Continued)
118 Figure 21 (Continued)
B Newspapers, Newspapers, Television, Television, (SE) National Local National Local Household -.004 .130 .056 .132 unemployment (.099) (.106) (.094) (.106) Worry about debt -.014 .029 -.011 .040** (.015) (.017) (.015) (.016) Age .008*** .009*** .007*** .008*** (.002) (.002) (.001) (.002) Gender .146** -.019 .070# -.059 (.043) (.045) (.040) (.046) Education .054*** .030* .005 -.028* (.011) (.012) (.011) (.012) Race -.036 -.051 -.001 -.042 (.062) (.066) (.059) (.067) Household income .118*** .058** .032# -.029 (.018) (.020) (.015) (.020) Home ownership -.064 .006 -.051 -.032 (.055) (.059) (.052) (.059) Marital status -.024 .001 .010 .050 (.048) (.051) (.046) (.052) Children -.014 .052 .008 .106* (.047) (.051) (.045) (.051) Partisanship .007 -.005 .017 -.019# (.010) (.011) (.010) (.011) Talk about .371*** .296*** .337*** .256*** the economy (.020) (.021) (.019) (.021) MSA -.010 .021* .032 .049 unemployment rate (.029) (.031) (.026) (.034) Prop change in (6 mnth lag) (6 mnth lag) (3 mnth lag) (6 mnth lag) unemployment rate .192 .160 -.334 -.489* (.163) (.171) (.142) (.192) Note: N= 2,672; # p < .10; * p < .05; ** p < .01; *** p < .001
119 income was positively associated with several attention to news about the economy measures. The pattern suggests a stronger relationship for newspapers and for news about the national economy. Neither home ownership nor marital status were associated with any attention to news about the economy measures. The presence of children in the home was positively related to attention to news about the local economy, primarily on television. There was a weak association of political partisanship and attention to news about the economy. Strong democrats were more likely to pay attention to news about the local economy on television, but this relationship held only for the analyses that used county-level contextual data. This may be because the analysis using county-level data has a larger sample size. This leaves the local contextual information. Current county and MSA unemployment rates were positively related only to attention to news about the local economy in newspapers.
Attention to news about the local economy in newspapers was higher in counties or
MSAs with higher unemployment rates. Several time lags using actual and proportional changes in unemployment rates were tested. The best fitting model for each analysis is shown in the table, and the one-month time lag appears to be the best fit in most cases. Proportional changes in unemployment rates fit the models marginally better than actual percentage point changes. None of the county-level proportional changes in unemployment rates were significant, and the MSA-level proportional changes were significant for only two models. A proportional, one-month change in
MSA unemployment was negatively related to attention to news about the national and local economies on television. A proportional, six-month change in MSA
120 unemployment was negatively related to attention to news about the local economy on television. These results are counterintuitive. Attention to news about the economy is lower for MSAs with increasing unemployment rates.
Relevant hypotheses.
In keeping with the cognitive priming/media dependency hypothesis, hypotheses H5a and H5b predict that experience and observation of the economy respectively will be positively associated with higher levels of attention to news about the economy. The cognitive priming/media dependency hypothesis posits that individuals may seek further issue information from media after they have experienced or observed threatening issue conditions. Direct experience of the economy as measured by household unemployment was not significantly associated with any measure of attention to news about the economy. We fail to reject the null hypothesis for H5a. The results are little better for observation of the economy. The current county unemployment rate was significantly associated with only attention to news about the local economy in newspapers. The direction of the associated was in the expected direction. Those living in areas with higher levels of unemployment were tended to pay more attention to news about the local economy in newspapers. Changes in unemployment rates over time were significantly associated with only two of the attention to news about the economy measures, and the relationships were negative, not positive as predicted. We fail to reject the null hypothesis for H5b.
121 Summary
Figure 22 summarizes the outcomes of the hypotheses. The results paint a mixed picture. Both personal issue experience in terms of household unemployment and attention to news about the economy were significantly associated with individual consumer confidence, which supported hypothesis H1c-1, a cognitive priming/media dependency hypothesis. However, observation of the economy as measured by contextual local unemployment rate information was not significantly associated with individual consumer sentiment and attention to news about the economy was significantly associated with confidence. This supported hypothesis H1a-2, an agenda- setting hypothesis.
Experience with and observation of the economy were predicted to be more strongly associated with the current conditions component of confidence than attention to news about the economy. Experience was more strongly associated with the current conditions component than attention to news, but attention to news was more strongly associated with current conditions than observation. Attention to news about the economy was predicted to be more strongly associated with the expectations component than experience or observation. Attention to news was more strongly associated with the expectations component than personal experience. Observation of the economy had about the same level of association as attention to news, which did not support the hypothesis. The nature of the relationship between the indirect measure of observation of economic conditions was unexpected, although there was no prediction about the nature of the relationship.
122 Work by scholars in contextual effects suggested that news about the local economy might be more strongly associated with individual consumer confidence than news about the national economy, and this was the case. Work in media effects suggested that newspapers might be better at portraying unemployment, but attention to news on television was more strongly associated with consumer confidence than attention to newspapers. The cognitive priming/media dependency hypothesis suggests that some individuals will turn to media for information about an issue when they feel threatened. Experience with and observation of threatening economic conditions were predicted to be associated with higher levels of attention to news about the economy.
This was not the case.
123 H1a-1: Consumer confidence levels will vary with attention to news about the economy, but will not vary with personal economic experience of the economy. Outcome: Confidence varied with both attention to the news about the economy and personal economic experience. This hypothesis is not supported. H1a-2: Consumer confidence levels will vary with attention to news about the economy, but will not vary with observation of the economy. Outcome: Confidence varied with attention to news about the economy. Confidence varied with observation of the economy, but in a limited and unexpected way. This hypothesis is supported. H1b-1: Consumer confidence levels will vary inversely with personal economic experience and will not vary with attention to news about the economy. Outcome: Confidence varied inversely personal economic experience, but also varied with attention to news about the economy. This hypothesis was not supported. H1b-2: Consumer confidence will vary positively with observation of the economy and will not vary with attention to news about the economy. Outcome: Confidence varied with positively (but in a limited fashion) with observation of the economy, but also with attention to news about the economy. This hypothesis was not supported H1c-1: Consumer confidence will vary inversely with personal economic experience and will vary with attention to news about the economy. Outcome: Confidence varied inversely with personal economic experience, and also with attention to news about the economy. This hypothesis was supported. H1c-2: Consumer confidence will vary positively with observation of the economy and will vary with attention to news about the economy. Outcome: Although consumer confidence varied with observation of the economy, it was not in the expected direction. Confidence also varied with attention to news about the economy. This hypothesis was not supported.
Figure 22. Summary of Outcomes of Hypotheses
(Continued)
124 Figure 22 (Continued)
H2a: The current conditions component of consumer confidence will be more strongly associated with personal economic experience than with attention to news about the economy. Outcome: The current conditions component was more strongly associated with personal economic circumstances than with attention to news about the economy. This hypothesis was supported. H2b: The current conditions component of consumer confidence will be more strongly associated with observation of the economy than with attention to news about the economy. Outcome: The current conditions component was more strongly associated with attention to news about the economy than with observation of the economy. This hypothesis was not supported. H3a: The expectations component of consumer confidence will be more strongly associated with attention to news about the economy than with experience with economic conditions. Outcome: Attention to news about the local economy on television was associated the expectations component while personal economic situation was not associated. This hypothesis is partially supported. H3b: The expectations component of consumer confidence will be more strongly associated with attention to news about the economy than with observation of the economy. Outcome: Attention to news about the local economy on television and observation of the economy were both significantly associated with the expectations component, but the association for attention to news was not stronger than for observation. This hypothesis was not supported.
(Continued)
125 Figure 22 (Continued)
H4a: Interpersonal discussion of the economy will vary positively with household economic experience. Outcome: Interpersonal discussion of the economy was not associated with personal financial circumstances. This hypothesis was not supported. H4b: Interpersonal discussion of the economy will vary positively for those living in areas with increasing unemployment. Outcome: Interpersonal discussion of the economy decreased as local unemployment increased. This hypothesis was not supported. H5a: Attention to news about the economy will vary positively with household economic experience. Outcome: Household financial circumstances were not associated with attention to news about the economy. This hypothesis was not supported. H5b: Attention to news about the economy will vary positively for those living in areas with increasing unemployment. Outcome: Only a few of the various attention to news about the economy measures were associated with attention to news about the economy, and in those cases attention to news decreased in areas with higher unemployment. This hypothesis was not supported. H6: Attention to local news about the economy will be more strongly associated with consumer confidence than attention to national news about the economy. Outcome: The attention to news about the local economy was significantly associated with consumer confidence, but attention to news about the national economy was not. This hypothesis was supported. H7: Attention to news about the economy in newspapers will be more strongly associated with consumer confidence than attention to news about the economy on television. Outcome: Attention to news about the economy on television was associated with confidence, but attention to news in newspapers was not. This hypothesis was not supported.
126 CHAPTER 5
CONCLUSIONS
The goal of this study was to examine the role of communication processes on individual consumer confidence about the state of the economy. There are several perspectives that could be applied to individual consumer confidence. McCombs and
Shaw’s (1972) agenda-setting hypothesis posited that public concern about the importance of issues (the public agenda) is a function of the amount of news coverage issues receive. If news coverage of the economy and unemployment drives public concern about the economy and consumer confidence, then individual consumer confidence should be related to attention to news about the economy. Zucker (1978) argued that some issues were obtrusive, allowing individuals to acquire issue information through personal experience rather than media. If this is true, then experience should be related to consumer confidence and not attention to media.
Demers et al. (1989) developed the cognitive priming/media dependency hypothesis, which predicts that issue experience primes individuals to be sensitive to news coverage of the issue or that issue experience may lead individuals to turn to media for further issue information. If this is true, then attention to news and other channels of information should be related to consumer confidence. In addition to these communication perspectives, the work of scholars in contextual analysis suggests that
127 local information sources such as observation of issue conditions, interpersonal communication, or local media could be factors in concern about an issue. Books and
Prysby (1991) presented a contextual effects model in which local contexts can create an information environment that affects how issue information is perceived and what information is attended to. This study compared these different theoretical approaches by examining the relationships between individual consumer confidence and direct issue experience, indirectly measured observation of issue conditions, interpersonal communication about the issue, and attention to news about the issue in media and individual consumer confidence.
Discussion of the Findings
Scholars have consistently found a relationship between personal or household financial circumstances and perceptions of economic conditions (Duch et al., 2000;
Katona, 1975). Direct issue experience as operationalized by household unemployment was a strong predictor of consumer confidence. This certainly supports the view that unemployment is obtrusive, if obtrusiveness is defined as direct experience. However, we should not place too much emphasis on this finding in the context of this study.
Individual consumer confidence was measured using Katona’s Index of Consumer
Sentiment. The first question of this index asks survey respondents about their household financial circumstances compared to 12 months prior. We should expect that most households experiencing unemployment will respond negatively, and this negative response will be a factor in their overall individual consumer confidence score. Note that household unemployment was strongly associated with the current conditions
128 component, which uses the first question, and not with the expectations component, which does not use that question. The relationship between household unemployment and consumer confidence may have been weaker if confidence had been operationalized using a different index that does not ask for a judgment of a household’s financial circumstances, such as the Conference Board’s Consumer
Confidence Index.
Issue experience was not related to attention to news about the economy or to interpersonal communication about the economy. This contradicts the media dependency aspect of Demers et al.’s (1989) hypothesis. A possible reason why household unemployment might not be associated with higher levels of communication about the economy is that the frequency of these communication behaviors were fairly high. If attention to news about the economy is already high, it may be hard for local conditions to cause an increase in attention. On the other hand, worry about household debt, a subjective measure of household financial circumstances, was associated with higher levels of interpersonal discussion about the economy and attention to news about the local economy on television. We don’t know whether worry about debt led to increased communication or if high levels of communication increased concern about debt. The different relationships of household unemployment and worry about household debt with the communication behaviors may because of the notion of threat that Ball-Rokeach (1985) referred to in media dependency theory. Worry about debt suggests concern about future conditions, and this may lead to seeking information. For those experiencing household unemployment, the danger has arrived and the need to
129 acquire information may have passed.
Even in a relatively poor economy, the majority of households will not experience unemployment. Contextual effects theory suggests that individuals might be able to observe signs of unemployment in their local area. Weatherford (1983b) and
Books and Prysby (1999) found a relationship between unemployment levels for state and local labor market areas and perceptions of national economic conditions. I linked county and MSA unemployment rates to individuals as an indirect measure of observation of local economic conditions. The assumption was that consumer confidence would be negatively related to local unemployment if individuals observe local unemployment conditions and those observations affect consumer confidence.
The results were disappointing. Local unemployment that increased over 12 months prior to the survey interview was associated with higher or more positive consumer confidence. This contradicts the findings by Weatherford (1983b) and Books and
Prysby (1999). There are several possible explanations for the difference in the findings. Weatherford, Books and Prysby were working in the tradition of presidential voting effects, and they analyzed data from campaign periods. Candidates actively try to influence voter opinion and vote choice, so there may have been campaign communications that made local unemployment more salient that it would have been otherwise. Data for this study were from a non-campaign period. There would have been only ‘ordinary’ reporting of economic events during or prior to the data collection period. However, this alone would not explain the direction of the relationship between unemployment rate information and consumer confidence in these data. It is possible
130 Figure 23. Ohio Seasonally Adjusted and Unadjusted Unemployment Rates
131 that the ‘wrong’ unemployment data were used. Unemployment typically shows seasonal variation. Figure 23 shows both seasonally adjusted and unadjusted statewide unemployment rates for Ohio. Unadjusted unemployment rates typically rise in January after the holidays. In figure 23, note the sharp rise of seasonally unadjusted unemployment during the data collection period (highlighted in yellow) compared to the adjusted rate. It is possible that the public may be accustomed to seasonal variations in unemployment and respond only to the underlying trends. Analyzing data that show seasonal fluctuations could obscure public reactions to trends in unemployment. Although seasonally adjusted unemployment data show trends in unemployment without the seasonal fluctuations, seasonally adjusted data are not available for counties or MSAs. Another possible explanation for the unexpected relationship between local unemployment and consumer confidence could be consumer optimism. Scholars have noted that consumers generally tend to be optimistic about the economy (Blendon et al., 1997; Mueller, 1966; Souleles, 2004). Over a long period of time, consumers may start expecting the economy to improve even though there is little evidence to support such an expectation. Simply put, consumers may want the economy to get better and predict that it will. Such optimism may be a defensive posture against actual conditions. Prior to the data collection period there was a period of negative economic developments. The ‘dot-com’ bust took place the year before these data were collected (Said, 2000) and according to the National Bureau of
Economic Research the 2001 recession technically ended in November of 2001 (Hall et al., 2003), the first month these data were collected. This extended period of poor
132 Figure 24. U.S. and Ohio Aggregate Consumer Confidence Levels
133 Figure 25. U.S. and Ohio Seasonally Adjusted Unemployment Rates
134 economic performance could have triggered consumer optimism. Finally, unique historical events may have indirectly affected consumer confidence. These data were collected in the months that followed the September 11, 2001 terrorist attacks.
President Bush and others may have made remarks that heightened feelings of pride in the United States, creating ‘rally around the flag’ effects. These feelings may have positively influenced perceptions of economic conditions including consumer confidence. Figures 24 and 25 may show these latter two effects. Figure 24 shows the
U.S. and Ohio aggregate consumer confidence levels. The U.S. levels were from the
University of Michigan’s Index of Consumer Sentiment. Figure 25 shows the U.S. and
Ohio adjusted unemployment rates. The gray shading is for the period classified as a recession by the National Bureau of Economic Research (Hall et al., 2003). The yellow shading shows the period of data collection. The data collection period and the recession overlap during November 2001. For both the U.S. and Ohio, consumer confidence began to fall before unemployment began to climb. This suggests that events related to the dot-com bust affected consumer confidence and caused it to drop.
Unemployment begins to rise just before the beginning of the recession period.
However, consumer confidence also began to rise somewhat as unemployment began to rise. This could have been consumer optimism surfacing after a period of bad economic conditions. The black line in Figures 24 and 25 marks the September 11 attacks. Consumer confidence began to drop again just before the September 11 terrorist attacks. This was perhaps in response to the rising unemployment. Saad
(2002) notes that news reports about the economy in the days immediately before 9-11
135 were negative. It is common to attribute the September 2001 drop in consumer confidence to the attacks, but Saad argues the evidence shows that confidence was already dropping in early September. Consumer confidence then bottomed out and began to rise about the time the data for this study were being collected. Saad noted that in October consumers spent more than expected. The rise in confidence and consumer spending appears to be a reaction to the terrorist attacks since unemployment continued to rise. Finally, note that consumer confidence began to fall after April 2002.
This suggests that any rally effects and optimism effects were losing their effect.
The role of interpersonal communication on evaluations of issue importance has largely been ignored by most scholars. Here it produced limited but some interesting results. Interpersonal discussion of the economy was not significantly related to consumer confidence or its components. The role of interpersonal discussion could be validation of perceptions and information, not the acquisition of new information.
Household unemployment was not related to discussion, but worry over household debt was positively associated with discussion. This is similar to the pattern for attention to news about the economy; the underlying reasons could be similar as well. A six-month increase in county unemployment rates was significantly associated with lower levels of discussion of the economy. This relationship was not in the expected direction. This pattern suggests that the larger the economic threat, the less likely people will engage in discussion of the economy.
Of course, the main focus of the research has been on the role of mass media in the perception of issue importance. This study used a unique set of four measures of
136 attention to news about the economy, each measuring a different combination of medium (television or newspapers) and geographic area of news focus (local or national economy). These items were summed into different indexes and examined individually when desired. The attention to news about the economy index of all four items was negatively associated with individual consumer confidence. Higher levels of attention to news about the economy tended to be associated with lower levels of consumer confidence. This association was driven by attention to news about the local economy on television. Unfortunately, these cross-sectional data do not provide enough information to determine the direction of causation. We don’t know if low consumer confidence led to an increase in attention to news about the local economy, or if attention to news about the local economy led to a decrease in consumer confidence.
The picture for the components of the confidence index is more complex. The index of the four attention items was negatively related to the current conditions component.
However, when the four individual items were used in the analysis, none of them were significantly related to the current conditions component. No one medium or geographic news focus appears to be dominant in relation to the perception of current economic conditions. Three of the four items had a negative relationship with current conditions, so the additive effect was a significant negative relationship with the current conditions component. The situation was different for the expectations component.
The relationship between the index of the attention to news items and the expectations component was not significant. Of the four individual items, only attention to news about the local economy on television was significantly related to the expectations
137 component. The analysis of the individual items showed counteracting relationships that accounted for the non-significance of the index. The two attention to news about the local economy items had a negative relationship with expectations; the two attention to news about the national economy items had a positive relationship with expectations.
Thus, the opposing relationships cancelled out in the analysis using the index of the four measures. Demers et al. (1989) based their hypothesis in part on media dependency theory, which argues that those who feel threatened by issue conditions will seek further information from media. These data show little evidence of that.
Household unemployment was not related to any measure of attention to news about the economy. Worry about household debt was related to attention to news about the local economy especially on television. Those living in areas with higher unemployment did not appear to have higher levels of attention to news about the economy. Neither the current local unemployment rate nor the change in unemployment rates over time were related to any measure of attention to news about the economy. Some of the factors related to higher levels of attention to news about the economy were similar to those for higher levels of attention to news in general: age, education and household income
(Jeffres, 1986).
The data show different communication or information acquisition patterns for two groups. Household unemployment was a significant predictor of lower consumer confidence. In addition to household unemployment, attention to news about the economy, driven by attention to news about the local economy on television, was also a negative predictor of consumer confidence. Household unemployment was not a
138 Nov. ‘01 Dec. ‘01 Jan. ‘02 Feb. ‘02 Mar. ‘02 Apr. ‘02 All House- 85.555 84.718 88.298 88.835 93.133 92.608 holds Minus HH 86.074 84.728 88.339 88.910 93.200 92.936 Unemployment
Figure 26. Aggregate Ohio Consumer Confidence, All Households and Minus Households with Unemployment.
predictor of attention to news about the economy. These results give partial support for
Demers et al.’s (1989) cognitive priming/media dependency hypothesis among households experiencing household unemployment. However, relatively few households experience unemployment. Does the strong effect of household unemployment among a few households significantly affect aggregate consumer confidence? Figure 26 shows the monthly aggregate Ohio consumer confidence index calculated first for all households and then with the households experiencing unemployment removed from the data.4 Removing the households experiencing unemployment from the data has very little effect on the monthly aggregate consumer confidence scores. It is apparent the month-to-month changes in consumer confidence are not being driven by changes in unemployment that directly affect a few households.
What are the communication processes among households not experiencing unemployment? Among households not experiencing unemployment, attention to news
4 The index scores for the full sample are slightly different from those published by the Columbus Dispatch. The scores reported there were for weighted data; the data here were unweighted.
139 about the economy was the only communication variable significantly associated with individual consumer confidence. Observation of local unemployment, measured indirectly using county and MSA unemployment rate information, and interpersonal communication about the economy were not associated with confidence. Nor were local unemployment rates related to attention to news about the economy. Because only attention to news about the economy was associated with consumer confidence, these results support the agenda-setting hypothesis, albeit very weakly. The analyses found that attention to news about the economy accounted for very little of the variance of individual consumer confidence.
Study Relationship to Previous Research
Unfortunately, this study doesn’t firmly support one theoretical position over others. Katona (1960; 1975) thought that information from media was the major force behind changes in aggregate consumer confidence levels. Several scholars found a relationship between media coverage of the economy and aggregate consumer confidence using time-series techniques (Blood & Phillips, 1995; Fan & Cook, 2003;
Rattliff, 2001; Tims et al., 1989). This study found an extremely weak effect for attention to news about the economy, which applied regardless of experience with unemployment. The effect was so small it does not seem adequate to lead to major changes on aggregate consumer confidence. The results also suggest that information about the local economy, not considered in many studies, could be important. Erbring et al. (1980) found that local newspaper content about the economy was associated with perceptions of the economy. It is possible that agenda-setting theory needs to address
140 both national and local sources of news for ‘obtrusive’ issues. The opposing theoretical perspective is that the economy is obtrusive and individuals acquire information about the economy. Agenda-setting studies have found a lower correlation between the volume of news content about the economy and perceptions of the importance of the economy as an issue (Zucker, 1978). Haller and Norpoth (1997) found few differences in consumer confidence associated with recall of news about the economy. Katona (1960) had a similar finding. Weatherford (1983b) and Books and
Prysby (1999) found that those living in areas with higher unemployment rates had more negative perceptions of the economy. Neither the Weatherford nor the Books and
Prysby studies specified a mechanism for the transmission of the unemployment information. This study found that household unemployment was an obtrusive aspect of the economy and strongly affected the consumer confidence of those experiencing it.
This effect may have been enhanced because of the operationalization of the dependent variable. However, few households experienced unemployment, so the aggregate effect was small. True support for any of the theoretical positions will require evidence of a communication or information acquisition behavior strong enough to have an effect on aggregate consumer confidence. This study had several limitations which must be addressed in order to have a chance to detect such effects or relationships.
Study Limitations and Suggestions for Future Research
This study suffered from at least two major limitations. Future research should address these limitations if feasible. In addition, there are several other ways in which future designs could be improved. In this section I will discuss the limitations and
141 improvements with an eye toward what might I might consider an ideal study.
The first major limitation of this study had to do with the timing of the study.
Data for this study were used simply because they were available. It was not possible to choose a particular period for data collection. Ideally, one would like to collect data just as information about conditions begins to change. Bartels (1993) argued that a large quantity of new information is required to lead to detectable opinion change.
Doms and Morin (2004) found that individuals update their economic information more often during times of heavy media coverage. The point at which economic conditions begin to change is when a large quantity of new information is most likely to be available. Downs’ (1972) description of the issue-attention cycle suggests that the
“alarmed discovery” stage of increasing issue coverage should be associated with change in public opinion. In keeping with the issue-attention cycle, worsening economic conditions would probably receive heavy coverage. Scholars have found that the public reacts strongly to negative information about the economy (Goidel &
Langley, 1995; Lewis-Beck & Paldam, 2000), and news coverage of the economy has been criticized for focusing on the negative (Goidel & Langley, 1995; Smith, 1988;
Smith & Lichter, 1997). Public concern about the issue wanes as well.
The second major limitation has to do with the cross-sectional sample design.
These data were collected for a major newspaper to report on monthly consumer confidence levels. The survey used a cross-sectional sample design to measure aggregate confidence each month. Cross-sectional designs can show some differences in consumer confidence that may be associated with communication behaviors and
142 processes, but they can’t establish the direction of any communication relationships.
We need to capture changes in individual confidence and communication behaviors.
We might think of individual consumer confidence as having multiple fractions. One fraction might be relatively stable. If we were able to track an individual’s confidence over a long period of time, we might find that it tends to fluctuate around some point.
This point may move slowly over time as the individual acquires life experience that could affect how the economy is perceived. A second fraction might be related to changes in the economy over some ‘medium’ period of time. We might track a drop in confidence over weeks or months during a sustained downturn in the economy.
Presumably, these movements would be caused by some broad trend in information about the economy. A third fraction might be related to very short-term influences on confidence. These would appear as brief deviations in confidence, perhaps lasting only a few days. They would be the result of individual pieces of information about the economy, not a broader flow of information. For example, news of a business closing may affect an individual’s confidence for a few days, but a lack of sustained information about the event may not lead to a sustained change in confidence. Finally, there must be a random fraction to individual confidence due to measurement error.
From a communication and information perspective, the second and possibly the third fractions are the fractions of interest, although it may not be practical to try to distinguish between the two fractions. A panel design can capture changes in consumer confidence and communication behaviors over time. The first wave of the panel should be collected before or at the earliest stages of changes of economic conditions. This
143 will establish a baseline of confidence. The second wave, reinterviews of first-wave respondents, would be after sufficient information about the economy had reached the public. The time lag between the waves would need to be determined through trail and error or guided by time lags in time-series studies. The need to have a baseline measurement and the inability to know when conditions will change will mean continuous interviewing. Realistically, such a study would probably need to be part of monthly consumer confidence survey. There are a couple of ways the panel aspect of a study could be handled. One way would be to continuously run a second wave, reinterviewing some portion of a previous sample. The University of Michigan uses this approach in their monthly survey. A second technique might be to start a second wave when certain economic indicators begin to change. For example, if the stock market or employment dropped a certain amount, a second wave would be started.
Addressing the two major limitations of this study would greatly improve any future research, but there are several other additions or modifications that could improve future work. I have already touched on the idea of monitoring economic indicators. Curtin (2002b) has noted that consumers can respond to a wide range economic information. This study used local unemployment rates as a variable in the analyses. Other indicators, both local and national, could be monitored and included in models. Such indicators might include interest rates, the consumer price indexes, stock market averages, and housing starts. One of the innovative features of this study was the attempt to parse attention to news about the economy into different foci of attention.
However, individuals sharing the same level and focus of attention to news could be
144 exposed to different content depending on the media outlets they used. As designed, the attention to news measures assume similar news content across geographic areas. A better approach would be to collect local and national media content data that could be linked to individuals. This was done for the 1974 National Election Study. Individuals were asked about their use of local newspapers, then corresponding local front-page content was coded for a number of issues. Using those data, Erbring et al. (1980) found that the issue salience of unemployment was affected by local newspaper content. It would also be necessary to monitor political and historical events in addition to economic events. Katona (1975) reported that non-economic events affected confidence, and of course we know political predispositions play a significant role in confidence. A complete study would code the volume and prominence of news about the economy and also factors such as the tone, sources cited, and framing devices used.
While collecting media content to match to individuals would be a tremendous addition to the basic study design, it would also complicate the study quite a bit.
Monitoring a large number of local media would be an obstacle. It could be managed by focusing on two or more metropolitan areas for comparison and over sampling in those areas. This could aid the analysis by providing large samples for good local-level comparisons. Metropolitan areas could be selected based on different criteria. One way to choose metro areas would be to select areas with distinctly different economic structures. For example, one area could have a concentration of manufacturing and another area could have an economy based on some other industry. This would be similar to how Dunn and Mirzaie (2006) used Ohio and Florida data for their analysis
145 because of the different economic structures of the states. One might also select areas with similar economic structures but different media structures to compare effects related to media structures. Focusing on a small number of locations would also make it easier to collect local television content. Although it is fairly easy to code local and national content in newspapers and there is a national archive of national television news content, there are few sources of content for local television outlets. In terms of media and news sources, this study has a significant omission, attention to news on the
Internet. Online sites have become a significant source of news and information for many individuals. Future studies must include measures of attention to news about the economy on the Internet. Tracking online content may be difficult. Individuals may pay attention to online media sources, unlimited blogs, and many of the institutional sources of economic information on which media rely. Individuals may tailor their media use to suit their needs and desires, so there is an increased possibility they will attend to information that is not consonant with mediated news.
There were few findings for interpersonal communication in this study. I feel that this is most likely because the measure was crude and interpersonal communication about the economy was at a fairly high level. Ganovetter (2005) has argued that economy might be obtrusive through social networks. Networks can affect the flow and quality of information received. We need to incorporate techniques for capturing these flows of information. Zaller (1992) argued for using measures of awareness or knowledge rather than attention or exposure to media measures. This approach could be used for interpersonal communication to tease out what interpersonal information
146 individuals are aware of. For example, we might ask if survey respondents were aware of any friends or family who had recently lost a job.
This study used the Index of Consumer Sentiment as the measure of consumer confidence. It may be useful to use a different index, such as the Index of Consumer
Sentiment to the Consumer Confidence Index. There are two reasons for this. The
Index of Consumer Sentiment may be overly sensitive to household financial circumstances because the first question in the sequence asks about household financial circumstances. This may make household circumstances highly salient when thinking about other economic conditions. The Consumer Confidence Index does not ask about household circumstances until after it asks about other conditions. This may give a clearer picture of how respondents see national economic conditions. Another reason to use that Consumer Confidence Index is that it asks about perceptions of employment conditions in the local community, so this index should be more sensitive to changes in unemployment. The Conference Board administers this index as part of a mail survey, but it could be adapted for a phone or web survey.
Some Final Comments
When judged against typical standards of social research–support for hypotheses–this study has not been a major success. By other standards, it has been successful. First, it introduced a set of measures that parsed attention to news about an issue based on medium and geographic focus of information. The results suggest that attention to information from different areas could cancel out any effect of attention to media. Second, these results suggest that at the individual level information acquisition
147 for obtrusive issues is more complex that reliance on media or direct experience. Books and Prysby’s (1991) framework and the techniques of contextual analysis will be useful for examining the communication and information acquisition processes of obtrusive issues. Finally, I hope this work will lead communication scholars to focus on consumer confidence and the public’s perceptions of economic conditions.
148 APPENDIX A
BIVARIATE CORRELATIONS AMONG STUDY VARIABLES
149 1234567 Consumer Confidence (1) Current .681*** Conditions Component (2) Expectations .859*** .209*** Component (3) Household -.081*** -.136*** -.013 Unemployment (4) Worry about Debt -.094*** -.117*** -.044* .103*** (5) Age -.205*** -.165*** -.158*** -.068*** -.347*** (6) Gender .167*** .066*** .178*** .059** -.096*** -.050** (7) Education .143*** .060** .149*** -.038* -.012 -.131*** .052** (8) Household .220*** .166*** .176*** -.018 .016 -.195*** .155*** Income (9) Home Ownership -.010 .008 -.019 -.043* -.075*** .279*** .041* (10) Married .054** .035* .048** .021 .031 .023 .101*** (11) Children in the .068*** .066*** .045* .035* .253*** -.439*** -.022 Home (12) Political .221*** .108*** .220*** -.034 -.039* -.049** .125*** Partisanship (13) * p < .05; ** p < .01; *** p < .001
Figure 27. Bivariate correlations among study variables
(Continued)
150 Figure 27 (Continued)
1234567
Discussion of the .029 -.008 .044* .008 .111*** -.066*** .050** Economy (14)
Attention to news -.012 -.024 .000 .001 .022 .087*** .005 about the local economy, in newspapers (15)
Attention to news .039* -.004 .055** -.018 -.020 .081*** .116*** about the national econ. in newspapers (16)
Attention to news -.112*** -.084*** -.090*** .033 .059** .097*** -.047** about the local economy, on television (17)
Attention to news -.028 -.058** .003 -.003 .008 .107*** .066*** about the national econ. on television (18)
Attention to local -.074*** -.065*** -.054** .020 .048** .111*** -.025 econ news (19)
Atten. to national .008 -.034 .035* -.012 -.008 .109*** .107*** econ news (20)
Attention to econ -.081*** -.081*** -.051** .018 .039* .115*** .008 news on TV (21)
(Continued)
151 Figure 27 (Continued)
1234567
Atten to econ .015 -.015 .030 -.009 .001 .093*** .066*** news in newspapers (22)
Local -.051** -.018 -.056** .015 .005 .024 -.028 unemployment rate (23)
Change -.034 -.015 -.035 .003 -.015 .022 .008 unemployment rate, 1 month (24)
Proportional -.035 -.018 -.034 -.001 -.015 .021 .009 change unemployment rate, 1 month (25)
Change -.026 -.001 -.034 .021 -.019 .017 .015 unemployment rate, 3 months (26)
Proportional -.021 .000 -.028 .018 -.021 .016 .019 change unemployment rate, 3 months (27)
Change -.011 -.006 -.010 .029 .001 -.006 .001 unemployment rate, 6 months (28)
(Continued)
152 Figure 27 (Continued)
1234567
Proportional .012 .002 .015 .030 .000 -.021 .011 change unemployment rate, 6 months (29)
Change .027 .002 .035 .018 -.008 -.029 .008 unemployment rate, 9 months (30)
Proportional .047** .009 .056** .013 -.011 -.037* .011 change unemployment rate, 9 months (31)
Change .044* .009 .052** -.003 .000 -.033 -.027 unemployment rate, 12 months (32)
Proportional .084*** .024 .096*** -.020 -.007 -.056** -.006 change unemployment rate, 12 months (33)
(Continued)
153 Figure 27 (Continued)
8 9 10 11 12 13 14
Household .401*** Income (9)
Home Ownership .117*** .319*** (10)
Married .112*** .401*** .369*** (11)
Children in the .029 .181*** .003 .207*** Home (12)
Political .059** .143*** .090*** .105*** .046** Partisanship (13)
Discussion of the .143*** .175*** .083*** .120*** .049*** .019 Economy (14)
Attention to news .113*** .131*** .117*** .099*** .009 .020 .328*** about the local economy, in newspapers (15)
Attention to news .201*** .226*** .129*** .127*** -.009 .045* .395*** about the national econ. in newspapers (16)
Attention to news -.036* -.029 .032 .042* .003 -.073*** .275*** about the local economy, on television (17)
(Continued)
154 Figure 27 (Continued)
8 9 10 11 12 13 14
Attention to news .091*** .097*** .093*** .101*** -.037* .015 .382*** about the national econ. on television (18)
Attention to local .046* .061*** .090*** .085*** .007 -.031 .362*** econ news (19)
Atten. to national .172*** .192*** .130*** .133*** -.026 .036* .452*** econ news (20)
Attention to econ .028 .035 .069*** .079*** -.018 -.035 .367*** news on TV (21)
Atten to econ .172*** .196*** .135*** .124*** .000 .036* .397*** news in newspapers (22)
Local -.135*** -.104*** .036* .033 .010 -.026 -.024 unemployment rate (23)
Change -.029 -.004 .008 .026 -.004 -.018 -.066*** unemployment rate, 1 month (24)
Proportional -.023 .002 .007 .021 -.014 -.014 -.072*** change unemployment rate, 1 month (25)
(Continued)
155 Figure 27 (Continued)
8 9 10 11 12 13 14 Change -.072*** -.041* .022 .023 -.011 .012 -.062** unemployment rate, 3 months (26) Proportional -.061** -.030 .027 .024 -.013 .017 -.071*** change unemployment rate, 3 months (27) Change -.077*** -.043* .022 .030 -.004 .026 -.069*** unemployment rate, 6 months (28) Proportional -.036* -.006 .013 .022 -.013 .045* -.078*** change unemployment rate, 6 months (29) Change -.034 -.004 -.006 .015 .014 .016 -.034 unemployment rate, 9 months (30) Proportional .004 .030 -.011 .005 .012 .026 -.029 change unemployment rate, 9 months (31) Change -.032 .001 -.015 -.010 .032 .019 -.001 unemployment rate, 12 months (32)
Proportional .062*** .072*** -.046* -.040* .021 .044* .015 change unemployment rate, 12 months (33)
(Continued)
156 Figure 27 (Continued)
15 16 17 18 19 20 21 Attention to news .659*** about the national econ. in newspapers (16) Attention to news .391*** .299*** about the local economy, on television (17) Attention to news .345*** .477*** .577*** about the national econ. on television (18) Attention to local .835*** .575*** .833*** .552*** econ news (19) Atten. to national .592*** .872*** .502*** .846*** .656*** econ news (20) Attention to econ .415*** .433** .898*** .877*** .787*** .750*** news on TV (21) Atten to econ .911*** .910*** .379*** .451*** .774*** .803*** .466*** news in newspapers (22) Local .021 -.035 .014 -.014 .021 -.029 .001 unemployment rate (23)
Change -.039* -.046* -.057** -.050** -.057** -.056** -.061** unemployment rate, 1 month (24)
(Continued)
157 Figure 27 (Continued)
15 16 17 18 19 20 21 Proportional -.036* -.043* -.061** -.052** -.059** -.055** -.064*** change unemployment rate, 1 month (25) Change .001 -.025 -.017 -.036* -.010 -.035 -.029 unemployment rate, 3 months (26) Proportional -.005 -.025 -.024 -.040* -.017 -.038* -.036* change unemployment rate, 3 months (27) Change .015 -.027 -.021 -.040* -.004 -.038* -.034 unemployment rate, 6 months (28) Proportional .015 -.012 -.034 -.042* -.011 -.031 -.042* change unemployment rate, 6 months (29) Change .008 .007 .011 -.006 .011 .000 .003 unemployment rate, 9 months (30) Proportional .009 .023 .012 .001 .013 .014 .008 change unemployment rate, 9 months (31) Change .012 -.001 -.001 .000 .007 -.001 -.001 unemployment rate, 12 months (32)
(Continued)
158 Figure 27 (Continued)
15 16 17 18 19 20 21 Proportional -.015 .015 -.010 .006 -.015 .013 -.003 change unemployment rate, 12 months (33)
22 23 24 25 26 27 28 Local -.008 unemployment rate (23) Change -.046** .178*** unemployment rate, 1 month (24) Proportional -.044* .130*** .981*** change unemployment rate, 1 month (25) Change -.013 .489*** .616*** .580*** unemployment rate, 3 months (26) Proportional -.016 .394*** .666*** .651*** .971*** change unemployment rate, 3 months (27) Change -.006 .744*** .290*** .274*** .642*** .609*** unemployment rate, 6 months (28)
(Continued)
159 Figure 27 (Continued)
22 23 24 25 26 27 28
Proportional .001 .475*** .317*** .326*** .600*** .621*** .928*** change unemployment rate, 6 months (29)
Change .008 .610*** .172*** .159*** .542*** .522*** .779*** unemployment rate, 9 months (30)
Proportional .017 .375*** .165*** .170*** .477*** .500*** .651*** change unemployment rate, 9 months (31)
Change .006 .374*** .014 -.051** .152*** .122*** .412*** unemployment rate, 12 months (32)
Proportional .000 -.320*** -.157*** -.168*** -.188*** -.164*** -.109*** change unemployment rate, 12 months (33)
(Continued)
160 Figure 27 (Continued)
29 30 31 32
Change unemployment rate, .706*** 9 months (30)
Proportional change .680*** .932*** unemployment rate, 9 months (31)
Change unemployment rate, .358*** .532*** .491*** 12 months (32)
Proportional change .015 .117*** .247*** .714*** unemployment rate, 12 months (33)
161 APPENDIX B
SURVEY QUESTION WORDING AND RESPONSE OPTIONS
162 CONSUMER CONFIDENCE Q1 (CURRENT CONDITIONS COMPONENT) We are interested in how people are getting along financially these days. Would you say that you and your family living there are better off or worse off financially than you were a year ago?
<1> BETTER OFF <2> SAME (VOLUNTEERED) <3> WORSE OFF <9> DK, NO OPINION
Q2 (EXPECTATIONS CONDITIONS COMPONENT) Now looking ahead, . . . do you think a year from now you (and your family living there) will be better off financially, or worse off, or just about the same as now?
<1> BETTER OFF <2> SAME <3> WORSE OFF <9> DK, NO OPINION
Q3 (EXPECTATIONS CONDITIONS COMPONENT) Now, turning to business conditions in the country as a whole, . . . do you think that during the next 12 months we'll have good times financially, or bad times, or what?
<1> GOOD TIMES <2> GOOD TIMES, BUT WITH QUALIFICATION <3> UNCERTAIN, GOOD & BAD <4> BAD, BUT WITH QUALIFICATION <5> BAD TIMES <9> DK, NO OPINION
Q4 (EXPECTATIONS CONDITIONS COMPONENT) Looking ahead, which would you say is more likely, . . . that in the country as a whole we'll have continuous good times during the next five years or so, . . . or that we will have periods of widespread unemployment or depression, or . . . what?
<1> GOOD TIMES <2> GOOD TIMES, BUT WITH QUALIFICATION <3> UNCERTAIN, GOOD & BAD <4> BAD, BUT WITH QUALIFICATION <5> BAD TIMES <9> DK, NO OPINION
163 Q5 (CURRENT CONDITIONS COMPONENT) Now I'd like to ask you about the big things people buy for their homes, . . . such as furniture, a refrigerator, stove, television, and things like that. Generally speaking, do you think now is a good or bad time for people to buy major household items?
<1> GOOD TIME <2> UNCERTAIN; DEPENDS <3> BAD TIME <9> DK, NO OPINION
HOUSEHOLD UNEMPLOYMENT--RESPONDENT EMPLOYMENT STATUS Last week were you working full-time, part-time, going to school, keeping house, retired, or what?
<1> WORKING FULL-TIME (35 HRS/WK OR MORE) <2> WORKING PART-TIME <3> WITH JOB BUT VACATION/SICK/ETC <4> UNEMPLOYED/LAID OFF <5> RETIRED <6> IN SCHOOL <7> KEEPING HOUSE <8> OTHER (SPECIFY) <9> REFUSED
MARITAL STATUS What is your current marital status?
<1> MARRIED <2> COHABITATING/LIVING AS MARRIED/ETC <3> DIVORCED <4> SEPARATED <5> SINGLE/NEVER MARRIED <6> WIDOW/WIDOWER <8> REFUSED
164 HOUSEHOLD UNEMPLOYMENT--RESPONDENT’S SPOUSE/PARTNER EMPLOYMENT STATUS Last week was your [spouse/partner] working full-time, part-time, going to school, keeping house, retired, or what?
<1> WORKING FULL-TIME (35 HRS/WK OR MORE) <2> WORKING PART-TIME <3> WITH JOB BUT VACATION/SICK/ETC <4> UNEMPLOYED/LAID OFF <5> RETIRED <6> IN SCHOOL <7> KEEPING HOUSE <8> OTHER (SPECIFY) <9> REFUSED
INTERPERSONAL DISCUSSION OF THE ECONOMY Sometimes people hear news about the economy, such news about prices, jobs, business, or the stock market, and discuss this news with others. How often do you discuss news about the economy with family or friends? Would you say . . . .
<1> all the time, <2> fairly often, <3> once in a while, <4> hardly ever, or <5> almost never? <8> REFUSED <9> DON'T KNOW
ATTENTION TO NEWS ABOUT THE ECONOMY IN NEWSPAPERS In the past seven days, between [day] of last week and yesterday, how many days did you read or look at a daily newspaper?
TOTAL # DAYS <0-7> <9> UNCERTAIN
165 ATTENTION TO NEWS ABOUT THE LOCAL ECONOMY IN NEWSPAPERS When you read the newspaper, how much attention do you pay to news about the local economy? This might include news about local businesses, the local job market, and the local housing market. When you read the newspaper, would you say you pay . . .
<1> a lot of attention, <2> some attention, <3> a little bit of attention, or <4> no attention at all to news about the local economy? <8> REFUSED <9> DON'T KNOW
ATTENTION TO NEWS ABOUT THE NATIONAL ECONOMY IN NEWSPAPERS When you read the newspaper, how much attention do you pay to news about the national economy? This might include news about businesses, jobs, housing, and the stock market. When you read the newspaper, would you say you pay . . .
<1> a lot of attention, <2> some attention, <3> a little bit of attention, or <4> no attention at all to news about the national economy? <8> REFUSED <9> DON'T KNOW
ATTENTION TO NEWS ABOUT THE LOCAL ECONOMY ON TELEVISION When you watch the news on television, how much attention do you pay to news about the local economy? Would you say you pay . . .
(IF NEEDED: this might include news about local businesses, the local job market, and The local housing market.)
<1> a lot of attention, <2> some attention, <3> a little bit of attention, or <4> not attention at all to news about the local economy? <7> DO NOT WATCH TV <8> REFUSED <9> DON'T KNOW
166 ATTENTION TO NEWS ABOUT THE NATIONAL ECONOMY ON TELEVISION When you watch the news on television, how much attention do you pay to news about the national economy? Would you say you pay . . .
(IF NEEDED: this might include news about businesses, jobs, the housing market, and the stock market.)
<1> a lot of attention, <2> some attention, <3> a little bit of attention, or <4> not attention at all to news about the national economy? <7> DO NOT WATCH TV <8> REFUSED <9> DON'T KNOW
AGE In what year were you born?
<1880-1984> <8888> REFUSED
RACE/ETHNIC GROUP And, what race or races do you consider yourself?
1) ALASKAN NATIVE 2) AMERICAN INDIAN/NATIVE AMERICAN 3) ASIAN 41) AFRICAN AMERICAN 42) BLACK 5) HISPANIC/LATINO/LATINA/CHICANO/CHICANA 6) PACIFIC ISLANDER 7) WHITE/CAUCASIAN 0) OTHER (SPECIFY) 88) REFUSED/DK 99) FINISHED, NO OTHER ANSWER GIVEN
167 EDUCATION Now we'd like to ask you about your education. What is the highest grade or year of school you have completed?
<1> <2> <3> <4> <5> <6> <7> <8> ELEMENTARY SCHOOL <9> <10> <11> <12> HIGH SCHOOL <13> SOME COLLEGE <14> ASSOCIATES CERTIFICATE/2 YEAR PROGRAM <15> BACHELOR'S DEGREE <16> SOME GRADUATE SCHOOL <17> MASTER'S DEGREE <18> DOCTORATE/ADVANCED DEGREE <88> REFUSED <99> DON'T KNOW
POLITICAL PARTISANSHIP POLITICAL PARTY IDENTIFICATION Generally speaking, do you usually think of yourself as a Republican, Democrat, Independent, or what?
<1> DEMOCRAT <2> REPUBLICAN <3> OTHER (SPECIFY) <4> INDEPENDENT <8> REFUSED <9> UNCERTAIN
POLITICAL PARTY LEANING (if not partisan) Do you think of yourself as closer to the Republican Party or to the Democratic Party?
<1> CLOSER TO REPUBLICAN <2> NEITHER <3> CLOSER TO DEMOCRAT <8> REFUSED <9> DON'T KNOW/NO ANSWER
168 PARTISAN STRENGTH OF IDENTIFICATION Would you call yourself a strong [democrat/republican] or a not very strong [democrat/republican]?
<1> STRONG <2> NOT VERY STRONG <8> REFUSED <9> DON'T KNOW/NO ANSWER
HOME OWNERSHIP Do you own or rent your home?
<1> OWN <2> RENT <3> OTHER (SPECIFY) <8> REFUSED
CHILDREN UNDER AGE 18 IN HOUSEHOLD How many children, 17 years of age or younger, live in your household?
<0> NONE # OF CHILDREN IN HOUSEHOLD <1-50> <88> REFUSED
169 COUNTY OF RESIDENCE What county do you live in?
<1> Adams <37> Darke <73> Hocking <109> Miami <145> Scioto <3> Allen <39> Defiance <75> Holmes <111> Monroe <147> Seneca <5> Ashland <41> Delaware <77> Huron <113> Montgomery<149> Shelby <7> Ashtabula <43> Erie <79> Jackson <115> Morgan <151> Stark <9> Athens <45> Fairfield <81> Jefferson <117> Morrow <153> Summit <11> Auglaize <47> Fayette <83> Knox <119> Muskingum <155> Trumbull <13> Belmont <49> Franklin <85> Lake <121> Noble <157> Tuscarawas <15> Brown <51> Fulton <87> Lawrence <123> Ottawa <159> Union <17> Butler <53> Gallia <89> Licking <125> Paulding <161> Van Wert <19> Carroll <55> Geauga <91> Logan <127> Perry <163> Vinton <21> Champaign <57> Greene <93> Lorain <129> Pickaway <165> Warren <23> Clark <59> Guernsey <95> Lucas <131> Pike <167> Washington <25> Clermont <61> Hamilton <97> Madison <133> Portage <169> Wayne <27> Clinton <63> Hancock <99> Mahoning <135> Preble <171> Williams <29> Columbiana<65> Hardin <101> Marion <137> Putnam <173> Wood <31> Coshocton <67> Harrison <103> Medina <139> Richland <175> Wyandot <33> Crawford <69> Henry <105> Meigs <141> Ross <888> REFUSED <35> Cuyahoga <71> Highland <107> Mercer <143> Sandusky <999> Don't Know
HOUSEHOLD INCOME Q1 And, approximately what was your total household income from all sources, before taxes for 2001?
# OF TOTAL HOUSEHOLD INCOME <0-8888887>
170 Q2 (If refused or uncertain on Q1.) Well, then, would you please tell me if it was...
(CONTINUE ON LADDER UNTIL "NO")
<0> more than $10,000? NO <1> more than $20,000? NO <2> more than $30,000? NO <3> more than $40,000? NO <4> more than $50,000? NO <5> more than $60,000? NO <6> more than $75,000? NO <7> more than $100,000? NO <8> more than $150,000? NO <9> MORE THAN $150,000? YES <88> REFUSED <99> UNCERTAIN
GENDER Gender of respondent:
<0> FEMALE <1> MALE
171 APPENDIX C
MISSING VALUES DATA COMPARISON
172 Mean/Median (Standard Deviation Variable Full Sample Reduced Sample Consumer confidence .000 .0660 (2.90) (2.89) Current conditions component .000 .0323 (1.52) (1.53) Expectations component .000 .0336 (2.17) (2.166) Household unemployment .00 (median) .00 (median) (.21) (0.21) Worry about debt 2.25 2.34 (1.45) (1.44) Age 47.44 46.52 (16.79) (16.39) Gender .00 (median) .00 (median) (.49) (.49) Education 13.22 13.22 (1.90) (1.93) Household income 3.0 (median) 3.0 (median) 1.42 (1.41) Home ownership 1.0 (median) 1.0 (median) (0.44) (0.44) Race 0.0 (median) 0.0 (median) (.32) (.32) Married 1.0 (median) 1.0 (median) (.50) (0.50)
Figure 28. Means, medians and standard deviations for full sample and sample without missing values.
(Continued)
173 Figure 28 (Continued)
Children in the home 0.0 (median) 0.0 (median) (.049) (.049) Political partisanship 3.0 (median) 3.0 (median) (2.06) (2.08) Discussion of the economy 3.24 3.24 (1.05) (1.05) Attention to news about the local economy in 2.79 2.79 newspapers (1.02) (1.01) Attention to news about the local economy on 2.88 2.88 television (1.02) (1.02) Attention to news about the national economy in 2.85 2.85 newspapers (1.02) (1.01) Attention to news about the national economy on 3.11 3.11 television (0.94) (0.93) Current county unemployment rate 5.83 5.84 (1.22) (1.22)
174 LIST OF REFERENCES
ACNielson. (2002, January 14). ACNielson finds nine month lag between consumer sentiment and purchasing of non-durable goods (News release). Retrieved from www.acnielsen.com/news/american/us/2002/20020114.htm.
Adams, F. G. (1964). Consumer attitudes, buying plans, and purchases of durable goods: A principal components, times series approach. The Review of Economics and Statistics, 46(4), 347-355.
Adams, F. G., & Duggal, V. G. (1974). Anticipations variables in an economic model: Performance of the anticipations version of Wharton Mark III. International Economic Review, 15(2), 267-284.
Adams, F. G., & Green, E. W. (1965). Explaining and predicting aggregate consumer attitudes. International Economic Review, 6(3), 275-293.
Adoni, H., & Cohen, A. A. (1978). Television economic news and the social construction of economic reality. Journal of Communication, 28(3), 61-70.
Aidt, T. S. (2000). Economic voting and information. Electoral Studies, 19, 349-362.
Alsem, K.-J., Brakman, S., Hoogduin, L., & Kuper, G. (2004, October). The impact of newspapers on consumer confidence: Does spin bias exist? (Working Paper No. 011/2004). Amsterdam: De Nederlandsche Bank.
Alt, J. E. (1979). The politics of economic decline: Economic management and political behavior in Britain since 1964. Cambridge: Cambridge University Press.
Alvarez, R. M., Nagler, J., & Willette, J. R. (2000). Measuring the relative impact of issues and the economy in democratic elections. Electoral Studies, 19, 237-253.
Ball-Rokeach, S. J. (1985). The origins of individual media-system dependency: A sociological framework. Communication Research, 12(4), 485-510.
Bartels, L. M. (1993). Messages received: The political impact of media exposure. The American Political Science Review, 87(2), 267-285.
175 Bastounis, M., Leiser, D., & Roland-Lévy, C. (2004). Psychosocial variables involved in the construction of lay thinking about the economy: Results of a cross-national survey. Journal of Economic Psychology, 25(2), 263-278.
Bechtel, G. G. (2003). One voice for consumer confidence: Case 9/11. International Journal of Public Opinion Research, 15(3), 325-334.
Behr, R. L., & Iyengar, S. (1985). Television news, real-world cues, and changes in the public agenda. Public Opinion Quarterly, 49(1), 38-57.
Benoit, W. L. (2003). State of the economy and presidential television spots. Communication Research Reports, 20(3), 269-276.
Berry, S. (2004, Autumn). Home should we think about consumer confidence? Bank of England Quarterly Bulletin, 44(3), 282-290.
Blanchard, O. (1993). Consumption and the recession of 1990-1991. American Economic Review, 83(2), 270-274.
Blendon, R. J., Benson, J. M., Brodie, M., Morin, R., Altman, D. E., Gitterman, D. et al. (1997). Bridging the gap between the public's and economists' views of the economy. The Journal of Economic Perspectives, 11(3), 105-118.
Blinder, A. S., & Krueger, A. B. (2004, May). What does the public know about economic policy and how does it know it? (Working Paper Number 99). Princeton Center for Economic Policy.
Blood, D. J., & Phillips, P. C. B. (1995). Recession headlines news, consumer sentiment, the state of the economy and presidential popularity: A times series analysis 1989-1993. International Journal of Public Opinion Research, 7(1), 2-22.
Blount, S. (2002). Unemployment and economic voting. Electoral Studies, 21, 91-100.
Books, J. W., & Prysby Charles L. (1991). Political behavior and the local context. New York: Praeger.
Books, J. W., & Prysby Charles L. (1995). On the future of contextual models of political behavior. In M. Eagles (Ed.), Spatial and contextual models in political research (pp. 255-273). London: Taylor and Francis, Ltd.
Books, J., & Prysby, C. (1999). Contextual effects of retrospective economic evaluations: The impact of the state and local economy. Political Behavior, 21(1), 1-16.
176 Bourgoyne, C. B., & Routh, D. A. (1995). Economic actors, minds, and contexts: Towards an ecological economic psychology? Journal of Economic Psychology, 16, 355-360.
Brady, H. E., Verba, S., & Schlozman, K. L. (1995). Beyond SES: A resource model of political participation. American Political Science Review, 89(2), 271-294.
Bram, J., & Ludvigson, S. (1998, June). Does consumer sentiment forecast household expenditure? A sentiment index horse race. Economic Policy Review, 4(2), 59-78.
Bryan, M. F., & Venkatu, G. (2001, October 11). He said, she said: The curious case of male and female inflation perceptions. Federal Reserve Bank of Cleveland, Economic Commentary.
Bryan, M. F., & Venkatu, G. (2001, October 5). Understanding surveys of public inflation psychology--clue one: Demographics are important. Federal Reserve Bank of Cleveland, Economic Commentary.
Bryant, W. D. A., & Macri, J. (2005). Does sentiment explain consumption? Journal of Economics and Finance, 29(1), 97-111.
Burdekin, R. C. K., & Langdana, F. K. (1995). Confidence, Credibility, and Macroeconomic Policy. London: Routledge.
Burden, B. C., & Mughan, A. (2003). The international economy and Presidential approval. Public Opinion Quarterly, 67, 555-578.
Cacioppo, J. T., & Berntson, G. G. (1994). Relationship between attitudes and evaluative space: A critical review, with emphasis on the separability of positive and negative substrates. Psychological Bulletin, 115(3), 401-423.
Campbell, A., & Katona, G. (1946). A national survey of wartime savings. Public Opinion Quarterly, 10(3), 373-381.
Caplan, B. (2002). Sociotropes, systemic bias, and political failure: Reflections on the survey of Americans and economists on the economy. Social Science Quarterly, 83(2), 416-435.
Carlsen, F. (2000). Unemployment, inflation, and government popularity -- are there partisan effects? Electoral Studies, 40, 141-150.
177 Carroll, C. D. (2003, April 15). The epidemiology of macroeconomic expectations. Working Paper. Downloaded from: http://www.econ.jhu.edu/people/ccarroll/EpidemiologySFI.pdf.
Carroll, C. D., Fuhrer, J. C., & Wilcox, D. W. (1994). Does consumer sentiment forecast household spending? If so, why? The American Economic Review, 84(5), 1397-1408.
Chaffee, S. H. (1982). Mass media and interpersonal channels: Competitive, convergent, or complementary? In G. Gumpert & R. Cathcart (Eds.), Inter/media: Interpersonal communication in a media world (2nd ed.) (pp. 57-77). New York: Oxford University Press.
Chaffee, S. H., & Schleuder, J. (1986). Measurement and effects of attention to media news. Human Communication Research, 13(1), 76-107.
Chubb, J. E. (1988). Institutions, the economy, and the dynamics of state elections. The American Political Science Review, 82(1), 133-154.
Coleman, C.-L. (1993). The influence of mass media and interpersonal communication on societal and personal risk judgments. Communication Research, 20(4), 611-628.
Conlisk, J. (1996, June). Why bounded rationality? Journal of Economic Literature, 34, 669-700.
Conover, P. J., & Feldman, S. (1986). Emotional reactions to the economy: I'm mad as hell and I'm not going to take it anymore. The American Journal of Political Science, 30(1), 50-78.
Conover, P. J., Feldman, S., & Knight, K. (1986). Judging inflation and employment: The origins of retrospective evaluations. The Journal of Politics, 48(3), 565-588.
Conover, P. J., Feldman, S., & Knight, K. (1987). The personal and political underpinnings of economic forecasts. American Journal of Political Science, 31(3), 559-583.
Croushore, D. (2005, December). Do consumer confidence indexes help forecast consumer spending in real time? North American Journal of Economics and Finance, 16(3), 435-450.
178 Curtin, R. T. (1973). Index construction: An appraisal of the index of consumer sentiment. In L. Mandel, G. Katona, J. N. Morgan & J. Schmiedeskamp (Eds.), Surveys of Consumers 1971-1972. Ann Arbor, MI: The Institute for Social Research, The University of Michigan.
Curtin, R. T. (1982). Indicators of consumer behavior: The University of Michigan surveys of consumers. Public Opinion Quarterly, 46(3), 340-352.
Curtin, R. T. (2000). Psychology and macroeconomics: Fifty years of the surveys of consumers. In J. House, T. Juster, R. Kahn & E. Singer (Eds.), Telescope on Society: Survey Research and Social Science in the 20th and 21st Centuries. Ann Arbor: University of Michigan Press.
Curtin, R. T. (2002a, September). Surveys of consumers: Theory, methods, and interpretation. Presented at the NABE 44th annual meeting, Washington, D.C.
Curtin, R. T. (2002b, October). Consumer confidence in the 21st century: Changing sources of economic uncertainty. Presented at the 26th CIRET Conference, Taipei.
Curtin, R. T. (2003a, April). What recession? What recovery? The arrival of the 21st century consumer. Business Economics, 38(2), 25-32.
Curtin, R. T. (2003b). Unemployment expectations: The impact of private information on income uncertainty. Review of Income and Wealth, 49(4), 539-554.
Curtin, R. T. (2005, 14 March). Energy and the consumer: "What me worry?" Federal Reserve Bank of Chicago, Detroit branch.
De Boef, S., & Kellstedt, P. M. (2004). The political (and economic) origins of consumer confidence. American Journal of Political Science, 48(4), 633-649.
Dearing, J., & Rogers, E. (1996). Agenda-Setting. Thousand Oaks, CA: Sage Publishers.
Delli Carpini, M. X., & Keeter, S. (1996). What Americans know about politics and why it matters. New Haven: Yale University Press.
Demers, D. P., Craff, D., Choi, Y.-H., & Pessin, B. M. (1989). Issue obtrusiveness and agenda-setting effects of national network news. Communication Research, 16(6), 793-812.
Desroches, B., & Gosselin, M.-A. (2004). Evaluating threshold effects in consumer sentiment. Southern Economic Journal, 70(4), 942-952.
179 Dominitz, J., & Manski, C. F. (2003, August). How should we measure consumer confidence (sentiment)? Evidence from the Michigan survey of consumers. Working paper 03-10. Retrieved from http://www.northwestern.edu/ipr/publications/workingpapers/wpabstracts04/wp 0310.html.
Doms, M., & Morin, N. (2004). Consumer sentiment, the economy, and the news media (2004-09). Federal Reserve Bank of San Francisco Working Paper.
Downs, A. (1972). Up and down with the ecology: The issue-attention cycle. The Public Interest, 28(Summer), 38-50.
Dua, P., & Smyth, D. J. (1993). Survey evidence of excessive public pessimism about the future behavior of unemployment. Public Opinion Quarterly, 57(4), 566-574.
Duch, R. N., Palmer, H. D., & Anderson, C. J. (2000). Heterogeneity in perceptions of national economic conditions. American Journal of Political Science, 44(4), 635-652.
Dunn, L., & Mirzaie, I. (2006). Turns in consumer confidence: An information advantage linked to manufacturing. Economic Inquiry, 44(2), 343-351.
Durr, R. H. (1993). What moves policy sentiment? The American Political Science Review, 87(1), 158-170.
Durr, R. H., & Gilmour, J. B. (1997). Explaining congressional approval. American Journal of Political Science, 41(1), 175-207.
Emmison, M. (1983). 'The economy': Its emergence in media discourse. In H. Davis & P. Walton (Eds.), Language, Image, Media. Oxford: Basil Blackwell.
Eppright, D. R., Arguea, N. M., & Huth, W. (1998). Aggregate consumer expectation indexes as indicators of future consumer expenditures. Journal of Economic Psychology, 19(2), 215-235.
Erbring, L., Goldenberg, E. N., & Miller, A. H. (1980). Front-page news and real-world cues: A new look at agenda-setting by the media. American Journal of Political Science, 24(1), 16-49.
Erikson, R. S. (1990). Economic conditions and the congressional vote: A review of the macrolevel evidence. American Journal of Political Science, 34(2), 373-399.
180 Fair, R. C. (1978). The effect of economic events on votes for president. The Review of Economics and Statistics, 60(2), 159-173.
Fair, R. C. (1996). Econometrics and presidential elections. The Journal of Economic Perspectives, 10(3), 89-102.
Fan, D. P., & Cook, R. D. (2003). A differential equation model for predicting public opinions and behaviors from persuasive information: Application to the index of consumer sentiment. The Journal of Mathematical Sociology, 27, 29-51.
Fiorina, M. (1981). Retrospective voting in American national elections. New Haven: Yale University Press.
Fuhrer, J. C. (1988). On the information content of consumer survey expectations. The Review of Economics and Statistics, 70(1), 140-144.
Funk, C. L., & Garia-Monet, P. A. (1997). The relationship between personal and national concerns in public perceptions about the economy. Political Research Quarterly, 50(2), 317-342.
Gabaix, X., Laibson, D., Moloche, G., & Weinberg, S. (2003). The allocation of attention: Theory and evidence. (MIT Department of Economics Working Paper No. 03-31.)
Gandy, O. H., Jr. (1982). Beyond agenda-setting: Information subsidies and public policy. Norwood, NJ: Ablex.
Garner, C. A. (2002). Consumer confidence after September 11. Economic Review (Federal Reserve Bank of Kansas City), Second Quarter.
Garrett, T. A., Hernandez-Murillo, R., & Owyang, M. T. (2004, March/April). Does consumer sentiment predict regional consumption? Review (Federal Reserve Bank of Saint Louis), 87(2 (part 1)), 123-135.
Gavin, N. T., & Goddard, P. (1998). Television news and the economy: Inflation in Britain. Media, Culture & Society, 20, 451-470.
Goidel, R. K., & Langley, R. E. (1995). Media coverage of the economy and aggregate economic evaluations: Uncovering evidence of indirect media effects. Political Research Quarterly, 48(2), 313-328.
Goldstein, H. (2005). Projecting State and Area Industry Employment (Prepared for the Projections Workgroup, Employment and Training Administration, U.S. Department of Labor).
181 Golinelli, R., & Parigi, G. (2003, September). What is this thing called confidence? A comparative analysis of consumer confidence indices in eight major countries (484). (Tempi di discussione). Bank of Italy, Economic Research Department.
Granato, J., & Krause, G. A. (2000). Information diffusion within the electorate: The asymmetric transmission of political-economic information. Electoral Studies, 19, 519-537.
Granovetter, M. (2005). The impact of social structure on economic outcomes. Journal of Economic Perspectives, 19(1), 33-50.
Hall, R. E. (1993, May). Macro theory and the recession of 1990-1991. The American Economic Review, 83(2), 275-279.
Hall, R., Feldstein, M., Frankel, J., Gordon, R., Romer, C., Romer, D. et al. (2003, 21 October). The NBER's Business-Cycle Dating Procedure. .
Haller, H. B., & Norpoth, H. (1994). Let the good times roll: The economic expectations of U.S. voters. American Journal of Political Science, 38(3), 625-650.
Haller, H. B., & Norpoth, H. (1997). Reality bites: News exposure and economic opinion. Public Opinion Quarterly, 61(4), 555-575.
Harrington, D. E. (1989). Economic news on television: The determinants of coverage. Public Opinion Quarterly, 53(1), 17-40.
Hayes, A. F. (2005). Statistical Methods for Communication Science. Mahwah, NJ: Lawrence Erlbaum Associates.
Haynes, S. E., & Jacobs, D. (1994). Macroeconomics, economic stratification, and partisanship: A longitudinal analysis of contingent shifts in political identification. American Journal of Sociology, 100(1), 70-103.
Headrick, B., & Lanoue, D. J. (1991). Attention, asymetry, and government popularity in Britain. Western Political Quarterly, 44(1), 67-86.
Heath, L. (1984). Impact of newspaper crime reports on fear of crime: Multimethodological investigation. Journal of Personality and Social Psychology, 47(2), 263-276.
Hester, J. B., & Gibson, R. (2003). The economy and second-level agenda-setting: A time-series analysis of economic news and public opinion about the economy. Journalism and Mass Communication Quarterly, 80(1), 73-90.
182 Hester, J. B., & Gibson, R. (2007). The agenda-setting function of the national versus local media: A time-series analysis for the issue of same-sex marriage. Mass Communication & Society, 10(3), 299-317.
Hetherington, M. J. (1996). The media's role in forming voters' national economic evaluations in 1992. American Journal of Political Science, 40(2), 372-395.
Hibbs, D. A. (1979). The mass public and macroeconomic performance: The dynamics of public opinion toward unemployment and inflation. American Journal of Political Science, 23(4), 705-731.
Holbrook, T. M. (1994). Campaigns, national conditions, and U.S. presidential elections. American Journal of Political Science, 38(4), 973-998.
Howrey, E. P. (2001). The predictive power of the index of consumer sentiment. Brookings Papers on Economic Activity, 2001(1), 175-207.
Huth, W. L., Eppright, D. R., & Taube, P. M. (1994). The indexes of consumer sentiment and confidence -- leading of misleading guides to future buyer behavior. Journal of Business Research, 29(3), 199-206.
Hymans, S. H., Ackley, G., & Juster, F. T. (1970). Consumer durable spending: Explanation and prediction. Brookings Papers on Economic Activity, 1970(2), 173-206.
Iguzquiza, V. D. D. R. (1996). Is today the right time to buy? Analysis of the factors which shape this opinion. European Journal of Marketing, 30(6), 70-83.
Iyengar, S., & Kinder, D. R. (1987). News that matters: Television and American opinion. Chicago: The University of Chicago Press.
Jablonski, P. M., & Daniele, J. F. (1998). Variations in issue obtrusiveness and its impact on agenda building: The case of base realignment and closing. World Communication, 27(3), 31-45.
Jeffres, L. W. (1986). Mass Media: Processes and Effects. Prospect Heights, IL: Waveland Press.
Jensen, K. B. (1987). News as ideology: Economic statistics and political ritual in television network news. Journal of Communication, 37(4), 8-27.
183 Kaniss, P. (1991). Making Local News. Chicago: University of Chicago Press.
Katona, G. (1951). Psychological Analysis of Economic Behavior. New York: McGarw-Hill.
Katona, G. (1960). The powerful consumer: Psychological studies of the American economy. New York: McGraw-Hill.
Katona, G. (1975). Psychological economics. New York: Elsevier Scientific Publishing Company, Inc.
Keynes, J. M. (1936). The general theory of employment, interest and money. London: McMillan.
Kinder, D. R., & Kewiet, D. (1979). Economic discontent and political behavior: The role of personal greivances and collective economic judgments in congressional voting. American Journal of Political Science, 23, 495-527.
Kinder, D. R., & Mebane, W. R., Jr. (1983). Politics and economics in everyday life. In K. R. Monroe (Ed.), The political process and economic change. Berkeley: University of California Press.
Kinsey, J. D. (1993, January). Consumer confidence: Does it lead or lag economy? Fedgazette, 5(1), 18.
Kiousis, S. (2004). Explicating media salience: A factor analysis of the New York Times Issue Coverage during the 2000 U.S. presidential election. Journal of Communication, 54(1), 71-87.
Kiousis, S., & McCombs, M. (2004). Agenda-setting effects and attitude strength: Political figures during the 1996 presidential election. Communication Research, 31(1), 36-57.
Kramer, G. H. (1983). The ecological fallacy revisited: Aggregate- versus individual-level findings on economics and elections, and sociotropic voting. American Political Science Review, 77(1), 92-111.
Krause, G. A. (1997). Voters, information heterogeneity, and the dynamics of aggregate economic expectations. American Journal of Political Science, 41(4), 1170-1200.
Krause, G. A., & Granato, J. (1998). Fooling some of the public some of the time? A test for weak rationality with heterogeneous information levels. Public Opinion Quarterly, 62, 135-151.
184 Kuklinski, J. H., & West, D. M. (1981). Economic expectations and voting behavior in United States house and senate elections. The American Political Science Review, 75(2), 436-477.
Lang, G. E., & Lang, K. (1981). Watergate: An exploration of the agenda-building process. In G. C. Wilhoit & H. de Bock (Eds.), Mass Communication Review Yearbook. Beverly Hills: Sage.
Larson, S. R. (2002). Uncertainty and consumption in Keynes' theory of effective demand. Review of Political Economy, 14(2), 241-258.
Laswell, H. (1948). The structure and function of communication and society: The communication of ideas. New York: Institute for Religious and Social Studies.
Lazarsfeld, P. F., & Menzel, H. (1961). On the relation between individual and collective properties. In A. Etzioni (Ed.), Complex Organizations (pp. 422-440). New York: Holt, Rinehart, and Winston.
Lee, G. (2004). Reconciling 'cognitive priming' vs 'obtrusive contingency' hypothesis. Gazette: The International Journal for Communication Studies, 62(2), 151-166.
Lewin, S. B. (1996, September). Economics and psychology: Lessons for our own day from the early twentieth century. Journal of Economic Literature, 34(3), 1293-1323.
Lewis-Beck, M. S., & Paldam, M. (2000). Economic voting: An introduction. Electoral Studies, 19, 113-121.
Linden, F. (1982). The consumer as forecaster. Public Opinion Quarterly, 46(3), 353-360.
Lippmann, W. (1922). Public opinion. New York: The Free Press.
Logan, J. R., & Molotch, H. L. (1987). Urban fortunes: The political economy of place. Berkeley: University of California Press.
Lott, J. R. J., & Hassett, K. A. (2004, September 11). Is newspaper coverage of economic events politically biased?.
Lovell, M. C. (1975). Why was the consumer feeling so sad? Brookings Papers on Economic Activity, 1975(2), 473-479.
Lovell, M. C., & Tien, P.-L. (2000). Economic discomfort and consumer sentiment. Eastern Economic Journal, 26(1), 1-8.
185 Lowry, D. T., Nio, T. C. J., & Leitner, D. W. (2003, March). Setting the public fear agenda: A longitudinal analysis of network tv crime reporting, public perceptions of crime, and FBI crime statistics. Journal of Communication, 53(1), 61-73.
Ludvigson, S. C. (2004). Consumer confidence and consumer spending. Journal of Economic Perspectives, 18(2), 29-50.
Luke, D. A. (2004). Multilevel Modeling. Quantitative Applications in the Social Sciences). Thousand Oaks, CA: Sage Publications.
MacFadyen, A. J., MacFadyen, H. W., & Prince, N. J. (1996). Economic stress and psychological well-being: An economic psychology framework. Journal of Economic Psychology, 17, 291-311.
MacKuen, M. B., Erikson, R. S., & Stimson, J. A. (1992). Peasants or bankers? The American electorate and the U.S. economy. The American Political Science Review, 86(3), 597-611.
Mankiw, N. G., & Reis, R. (2002). Sticky information versus sticky prices: A proposal to replace the new Keynesian Phillips curve. The Quarterly Journal of Economics, 119, 1295-1328.
Manski, C. F. (2004, September). Measuring expectations. Econometrica, 72(5), 1329-1376.
Mason, R., Carlson, J. E., & Tourangeau, R. (1994). Contrast effects and subtraction in part-whole questions. Public Opinion Quarterly, 58, 569-578.
McCombs, M. E. (2004). Setting the agenda: The mass media and public opinion. Malden, MA: Blackwell.
McCombs, M. E. (2005). The agenda setting function of the press. In G. Overholser & K. Hall Jamieson (Eds.), The Press (pp. 156-168). Oxford: Oxford University Press.
McCombs, M. E., & Shaw, D. L. (1972). The agenda-setting function of mass media. Public Opinion Quarterly, 36, 176-188.
Mehra, Y. P., & Martin, E. W. (2003, Fall). Why does consumer sentiment predict household spending? Economic Quarterly (Federal Reserve Bank of Richmond), 89, 51-67.
186 Merkle, D. M., Langer, G. E., & Sussman, D. (2003, May). Consumer confidence: Measurement and meaning. Presented at the Annual conference of the American Association for Public Opinion Research, Nashville.
Middleton, E. (1996). Adaption level and 'animal spirits.' Journal of Economic Psychology, 17(4), 479-498.
Miettinen, J. N. (1998). Obtrusiveness and agenda building: Effective public opinion, newspapers, and city councils. Unpublished doctoral dissertation, Stanford University.
Morgan, J. N. (1980). A realistic economics of the consumer requires some psychology. In G. Katona & J. N. Morgan (Eds.), Essays on behavioral economics. Ann Arbor, MI: The Institute for Social Research, The University of Michigan.
Mowen, J. C., Young, C. E., & Silpakit, P. (1985). A comparison of the University of Michigan and Conference Board of consumer economic attitudes. Advances in Consumer Research, 12(1), 532-537.
Mueller, E. (1957). Effects of consumer attitudes on purchases. The American Economic Review, 47(6), 946-965.
Mueller, E. (1963). Tens years of consumer attitude surveys: Their forecasting record. Journal of the American Statistical Association, 58(304), 899-917.
Mueller, E. (1966). The impact of unemployment on consumer confidence. Public Opinion Quarterly, 30(1), 19-32.
Mughan, A., & Lacy, D. (1998). Economic performance, job insecurity, and electoral choice.
Mulligan, K. (2003, April). Knowledge, expertise, and collective perceptions of the economy. Paper presented at the Midwest Political Science Association, Chicago.
Mutz, D. C. (1992). Mass media and the depoliticization of personal experience. American Journal of Political Science, 36(2), 483-508.
Mutz, D. C. (1993). Direct and indirect routes to politicizing personal experience. Public Opinion Quarterly, 57, 483-502.
Mutz, D. C. (1994). Contextualizing personal experience: The role of the mass media. The Journal of Politics, 56(3), 689-714.
187 Mutz, D. C., & Mondak, J. J. (1997). Dimensions of sociotropic behavior: Group-based judgments of fairness and well-being. American Journal of Political Science, 41(1), 284-308.
Nadeau, R., Niemi, R. G., Fan, D. P., & Amato, T. (1999). Elite economic forecasts, economic news, mass economic judgments, and presidential approval. The Journal of Politics, 61(1), 109-135.
Neuman, W. R. (1990). The threshold of public attention. Public Opinion Quarterly, 54(2), 159-176.
Neuman, W. R., Just, M. R., & Crigler, A. N. (1992). Common knowledge: News and the construction of political meaning. Chicago: University of Chicago press.
Niven, D. (2001). Bias in the news: Partisanship and negativity in media coverage of presidents George Bush and Bill Clinton. Harvard International Journal of Press/Politics, 6(3), 31-46.
Noelle-Neumann, E., & Mathis, R. (1987). The 'event as event' and the 'event as news': The significance of 'consonance' for media effects research. European Journal of Communication, 2, 391-414.
Osgood, C. E., Suci, G. J., & Tannebaum, P. H. (1957). The measurement of meaning. Urbana, IL: University of Illinois Press.
Page, B. I., & Shapiro, R. Y. (1992). The rational public: Fifty years of trends in Americans' policy preferences. Chicago: University of Chicago Press.
Paldam, M., & Nannestad, P. (2000). What do voters know about the economy? A study of Danish data, 1990-1993. Electoral Studies, 19, 363-391.
Parsons, W. (1989). The power of the financial press: Journalism and economic opinion in Britain and America. Hauts, England: Edward Elgar Publishing.
Powell, M., & Ansic, D. (1997). Gender differences in risk behavior in financial decision-making: An experimental analysis. Journal of Economic Psychology, 18(6), 605-628.
Price, V., & Tweksbury, D. (1997). News values and public opinion: A theoretical account of media priming and framing. In G. Barett & F. J. Boster (Eds.), Progress in communication sciences: Advances in persuasion (pp. 173-212). Greenwhich: Ablex.
188 Rabin, M. (1998, March). Psychology and economics. Journal of Economic Literature, 36, 11-46.
Rattliff, J. R. (2001). Economic news and public perceptions of the U.S. economy. Ph.D. dissertation, Duke University. Retrieved from ABI/INFORM Global database. (Publication No. AAT 3031008).
Reis, R. (2004, October). Inattentive consumers. Unpublished paper downloaded from http://www.econ.yale.edu/seminars/macro/mac04/reis-040907.pdf.
Richardson, K. (1998). The economy and public language. In N. T. Gavin (Ed.), The economy, media, and public knowledge (pp. 38-52). London: Leicester University Press.
Robinson, J. P., & Levy, M. R. (1986). Interpersonal communication and news comprehension. Public Opinion Quarterly, 50(2), 160-175.
Rozin, P., & Royzman, E. B. (2001). Negativity bias, negativity dominance, and contagion. Personality and Social Psychology Review, 5(4), 296-320.
Saad, L. (2002, May). Chicken Little economics: A tale of consumer confidence after September 11. Paper presented at the annual conference of the American Association for Public Opinion Research, St. Pete Beach, Fl.
Said, C. (2000, 24/December). From Y2K Fizzle, to Dot-Com Bust. San Franscico Chronicle, sec. D, p. 2.
Sanders, D. (2000). The real economy and the perceived economy in popularity functions: How much do voters need to know? A study of British data, 1974-97. Electoral Studies, 19, 275-294.
Sanders, D., & Gavin, N. (2004). Television news, economic perceptions and political preferences in Britain, 1997-2001. Journal of Politics, 66(4), 1245-1266.
Scheufele, D. A. (2000). Agenda-setting, priming, and framing revisited: Another look at cognitive effects of political communication. Mass Communication & Society, 3, 297-316.
Scheufele, D. A., & Tewksbury, D. (2007). Framing, agenda-setting, and priming: The evolution of three media effects models. Journal of Communication, 57, 9-20.
Sears, D. O., & Lau, R. R. (1983). Inducing apparently self-interested political preferences. American Journal of Political Science, 27(2), 223-252.
189 Shah, D. V., Watts, M. D., Domke, D., Fan, D. P., & Fibison, M. (1999). News coverage, economic cues, and the public's presidential preferences, 1984-1996. Journal of Politics, 61(4), 914-943.
Shields, T. G., & Goidel, R. K. (1998). Taking credit and avoiding blame: Good news, spin control, and democratic accountability. Political Communication, 15, 99-115.
Shoemaker, P., & Reese, S. D. (1991). Mediating the message: Theories of influence on mass media content. New York: Longman.
Sims, C. A. (2003). Implications of rational inattention. Journal of Monetary Economics, 50, 665-690.
Smith, T. J., III. (1988). The vanishing economy: Television coverage of economic affairs 1982-1987. Washington, D.C.: The Media Institute.
Smith, T. J., III, & Lichter, S. R. (1997). Lessons in mass media depiction of economic conditions during a recession. In S. S. King & D. P. Cushman (Eds.), Lessons from the Recession: A Management and Communication Perspective (pp. 11-46). Albany, NY: State University of New York Press.
Soroka, S. N. (2002). When does news matter? Public agenda-setting for unemployment (Nuffield College Politics Working Paper No. 2002-W7). Oxford, UK: Nuffield College.
Soroka, S. N. (2006). Good news and bad news: Asymmetric responses to economic information. Journal of Politics, 68(2), 372-385.
Souleles, N. S. (2004). Expectations, heterogeneous forecast errors, and consumption: Micro evidence from the Michigan consumer sentiment surveys. Journal of Money, Credit, and Banking, 36(1), 39-72.
Stevenson, R. L., Gonzenbach, W. J., & David, P. (1994). Economic recession and the news. Mass Communications Review, 21, 4-19.
Straits, B. C. (1991, Autumn). Bringing strong ties back in interpersonal gateways to political information and influence. Public Opinion Quarterly, 55(3), 432-448.
Straszheim, D. H. (1974). Explaining aggregate measures of consumer attitudes. In Papers presented at the annual meeting of the American Statistical Association (pp. 581-586). Washington, D.C.: American Statistical Association.
190 Suzuki, M. (1992). Political business cycles in the public mind. American Political Science Review, 86(4), 989-996.
Takeshita, T. (2005). Current critical problems in agenda-setting research. International Journal of Public Opinion Research, 18(3), 275-296.
Tan, Y., & Weaver, D. H. (2007, Winter). Agenda-setting effects among the media, the public, and Congress, 1946-2004. Journalism and Mass Communication Quarterly, 84(4), 729-744.
Taylor, R. B., & Hale, M. (1986). Testing alternative models of fear of cime. Journal of Criminal Law and Criminology, 77(1), 151-189.
Throop, A. W. (1992). Consumer sentiment: Its cause and effects. Economic Review (Federal Reserve Bank of San Francisco), 1, 35-59.
Tims, A. R., Fan, D. P., & Freeman, J. R. (1989). The cultivation of consumer confidence: A longitudinal analysis of news media influence on consumer sentiment. Advances in Consumer Research, 16, 758-769.
Tingsten, H. (1937). Political behavior: Studies in election statistics. London: P.S. King and Son, Ltd.
Tourangeau, R., Rips, L. J., & Rasinski, K. (2000). The psychology of survey response. Cambridge: Cambridge University Press.
Weatherford, M. S. (1983a). Economic voting and the "symbolic politics" argument: A reinterpretation and synthesis. The American Political Science Review, 77(1), 158-174.
Weatherford, M. S. (1983b). Evaluating economic policy: A contextual model of the opinion formation process. The Journal of Politics, 45(4), 866-888.
Weaver, D. H. (2007). Thoughts on agenda-setting, framing, and priming. Journal of Communication, 57, 142-147.
Weisberg, H. F., & Smith, C. E. J. (1991). The influence of the economy on party identification in the Reagan years. Journal of Politics, 53(4), 1077-1092.
Weiss, M. J. (2003, February). Inside consumer confidence surveys. American Demographics, 25(1), 23-29.
Welch, S., & Hibbing, J. (1992). Financial conditions, gender, and voting in American national elections. The Journal of Politics, 54(1), 197-213.
191 Wiefek, N. M. (2001). Economic anxiety: A link between everyday life and political opinion. Doctoral dissertation, Pennsylvania State University, Political Science.
Williamson, M. R., & Wearing, A. J. (1996). Lay people's cognitive models of the economy. Journal of Economic Psychology, 17, 3-38.
Wlezien, C., Franklin, M., & Twiggs, D. (1997). Economic perceptions and vote choice: Disentangling the endogeneity. Political Behavior, 19(1), 7-17.
Wood, B., Dan, Owens, C. T., & Durham, B. M. (2005, August). Presidential rhetoric and the economy. Journal of Politics, 67(3), 627-645.
Wu, H. D., Stevenson, R. L., Chen, H.-C., & Güner, Z. N. (2002). Conditioned impact of recession news: A time-series analysis of economic communication in the United States, 1987-1996. Journalism and Mass Communication Quarterly, 79.
Wyatt, R. O., Katz, E., & Kim, J. (2000). Bridging the spheres: Political and personal conversations in public and private spaces. Journal of Communication, 50(1), 71-92.
Young, C. E., Mowen, J. C., & Silpakit, P. (1984). Predicting consumer confidence and sentiment: A replication and extension. In R. W. Belk, R. Peterson, G. S. Albaum, M. B. Holbrook, R. A. Kerin, N. K. Malhotra et al. (Eds.), 1984 AMA Educators' Proceedings (Vol. 50, pp. 68-71). Chicago: American Marketing Association.
Zaller, J. R. (1992). The nature and origin of mass opinion. Cambridge: Cambridge University Press.
Zucker, H. G. (1978). The variable nature of news media influence. In B. D. Ruben (Ed.), Communication Yearbook 2 (pp. 225-240). New Brunswick, NJ: Transaction Books.
192