FACULTY OF ECONOMICS AND BUSINESS A Neighborhood Level Assessment of the Causal Relation Between Income Inequality and Crime: A Case Study of Amsterdam By Anna Wildeboer Bachelor Thesis Economics Supervisor: Prof. Dr. Erik Plug 27 February 2015 Abstract: This paper examines the relationship between income inequality and criminal activity for a sample of 75 neighborhoods in Amsterdam, for the period 2008-2011. As opposed to greater aggregation units, it considers neighborhoods as a more appropriate level of analysis as they constitute more meaningful frames of reference that are necessary for the experience of economic inequality. The economic theory of crime and the relative deprivation theory identify the mechanisms trough which income inequality aggravates crime. For the empirical analysis a panel-data based fixed effect OLS methodology is used that controls for other economic determinants of crime, unobserved neighborhood specific characteristics and trends over time. The analysis considers different income inequality measures and different samples of neighborhoods. The empirical findings indicate that overall crime rates are positively affected by income inequality. The findings related to the specific crime types are based on a different crime registration method and indicate no effect from income inequality on violent crime and robbery, but a positive effect on burglary rates. ii TABLE OF CONTENT Abstract i Table of Content iii Acknowledgements iv 1. Introduction 1 2. Literature Review 2 2.1 Background 2 2.2 Theoretical Foundations 4 2.2.1 The Economic Theory of Crime 4 2.2.2 The Relative Deprivation Theory 5 2.3 Inconsistencies, Types of Crimes and Aggregate Level of Analysis 7 2.4 Identifying Other Relevant Variables Affecting Crime 9 3. Data and Empirical Method 10 3.1 Dependent Variables 11 3.2 Independent Variables 12 3.3 Control Variables 12 3.4 Neighborhood Measurement 13 3.5 Sample Selection 13 3.6 Empirical Strategy and Model 14 4. Results 16 4.1 Basic Results 16 4.2 Alternative Measures of Inequality 19 4.3 Subsamples 20 5. Discussion 22 6. Conclusion 25 Appendices 27 Appendix A: Computation of the Inequality Measures 27 Appendix B: Tables and Figures 29 References 36 iii ACKNOWLEDGEMENTS Hereby I would like to thank Hans van Wijk, working at the Economics Department of the municipality of Amsterdam, for our brainstorm sessions about a suitable topic concerning Amsterdam. I would also like to thank Cor Hylkema from Bureau O+S Amsterdam for his cooperation with regard to my search for data. I am grateful for the suggestions and feedback from prof. dr. Erik Plug that helped to improve the empirical section of my thesis. Lastly, I would like to express my gratitude to Sarah and Annemijn for their support and feedback. iv 1. INTRODUCTION There is an ongoing international debate about economic inequality – the unequal distribution of economic resources – on all levels of society: researchers, governments, policy makers and the public are concerned with the causes and effects of this phenomenon. In his book Capital in the Twenty-First Century, Thomas Piketty (2014) argues that increasing inequality stemming from the returns on capital is an ongoing trend if it is not addressed by economic policy. Increasing rates of income inequality have a range of detrimental social consequences and reduce the social cohesion. According to Wilkinson and Pickett (2010) these negative effects are felt by all members of the society and not only by the poor. One of the argued effects of rising income inequality is increasing rates of violence and crime in society. The concern with crime is well justified by its harmful effect on economic activity and its reducing effect on the quality of life of people who have to deal with a reduced sense of personal and proprietary security (Fajnzylber, Lederman, & Loayza, 2002a, p. 1324). The positive relation between inequality and crime rates is supported by the leading theories on crime of both the economic paradigm as well as of the sociological paradigm and these theories are rather complementary than exclusive (Kelly, 2000, p. 531). According to Becker’s (1968) economic theory of crime, engagement in criminal activity results from a rational decision based on a cost-benefit analysis. A more unequal income distribution - as opposed to an equal one – ceteris paribus would lead to lower opportunity costs and higher potential benefits for the poor. Under the assumption that economic agents are rational this results in an increase in crime rates. The relative deprivation theory (Runciman, 1966; Stack, 1984) developed in sociology and criminology states that income inequality results in social tensions and crime as the poor feel dispossessed when compared with the wealthier and therefore seek compensation and satisfaction by all means. Higher inequality would lead to a greater feeling of disadvantage and unfairness and thus results in higher crime rates (Fajnzylber et al., 2002b, p. 2). Researchers who have studied this relationship have conducted most empirical research with a focus on cross-sectional data on a national, county or city level. Outcomes of these studies have been ambiguous, although the main consensus is that relative higher income inequality is associated with higher levels of crime and violence (Hsieh & Pugh, 1993). 1 There is however a gap in the existing literature that covers the income inequality-crime relation on local level rather than on a higher aggregate level. By employing data on neighborhood level, this thesis is able to include much more detailed information and nuances than cross-national and cross-county studies. It is highly interesting to consider the consequences of increasing income inequality on a neighborhood level rather than on a national or regional level because cities can supplement national policies with effective local policies to decrease the incidence of crime and violence. This thesis is therefore concerned with the following research question: can support be found for the claim that income inequality has a causal positive effect when neighborhood level data is used? To study this question, Amsterdam is taken as a case study. In order to answer this research question literature is studied and an empirical analysis is performed. The revised literature identifies the underlying theories and the mechanisms. Furthermore, the empirical research tests the causal effect of income inequality on crime rates. To do so, other economic control variables are taken into account. The properties of panel data are utilized and a fixed effect regression is employed to control for unobserved neighborhood specific characteristics and trends over time. The outcomes indicate that increased income inequality results in more criminal activity by the residents who experience this increased inequality. In addition, neighborhoods with higher income inequality are more prone to property crimes but not to violence. The rest of this thesis proceeds as follows. The next section discusses the studied theoretical and empirical literature. Section 3 involves the methodology that describes the data and the empirical model. The empirical results are presented in section 4 and discussed in section 5. Section 6 contains concluding remarks. 2. LITERATURE REVIEW 2.1 Background Income inequality describes the phenomenon where income is unequally distributed across the population. The more unequal this distribution, the higher the concentration of the total income in the hands of a few. Inequality can be measured in various ways, but all express the dispersion or width of the income distribution. A simple statistical measure of dispersion that portrays income inequality is the variance (McKay, 2002). Another informative measure is the ratio of the income share of the poorest in relation to the richest quintile of the population. 2 However, despite its imperfections1, the most common measurement of income inequality is the Gini coefficient, which is mathematically based on the graphical representation of the Lorenz curve (Schutz, 1951, p. 108). The Lorenz curve plots the cumulative income distribution for the cumulative share of the population sorted from the poorest to the richest economic agent. The Gini coefficient ranges from zero to one. Zero indicates perfect equality: a situation in which all economic agents have equal shares of the aggregate income. One represents perfect inequality, where one economic agent has all income and the rest have none. An assessment of the presence of economic inequality sheds light on possible positive and negative effects of the phenomenon. On the one hand, Persson and Tabellini (1994) argue that economic inequality is related to lower economic growth and Bénabou (1996) perceives reduced human capital formation to be a negative consequence of this inequality. Yet, on the other hand inequality can be seen as a necessary incentive to work, invest and/or engage in entrepreneurial activity and therefore it leads to higher productivity and national output (Okun, 1975; Mankiw, 2013). A much more immediate social cost of inequality is its impact on crime. This negative effect of economic inequality is the focus of this research. The concern with crime in this study is well justified since it hampers economic development (Mehlum, Moene, & Torvik, 2005) and imposes significant costs both on society (Lederman, Loayza, & Menendez, 2002) and on individuals (Atkinson, Healey, & Mourato, 2005). Costs on the society firstly include a significant share of government