Inequality and Violent Crime* (original) (raw)

Income Inequality and Crime: A Review and Explanation of the Time?series Evidence

Sociology and Criminology-Open Access, 2013

This review analyses the time-series evidence of the effects of changing income inequality on crime for a number of countries and types of crime. 17 papers analysing this relationship using time-series evidence were found via a systematic search. The papers' findings on the relationship between inequality and crime were classified as providing evidence of Significant Positive Associations, No Significant Associations, or Significant Negative Associations. The analysis indicated that property crime increases with rising income inequality and specific measures of violent crime, such as homicide and robbery, also display sensitivity to income inequality over time. Aggregated non-specific measures of violent crime, however, do not display such sensitivity, which is most likely to be due to differences in crime reporting. The majority of the differences in the findings can be explained by the choice of covariates, and the estimators and measures used in the paper. The paper concludes with a unified interpretation of the time-series evidence.

The Determinants of Income Inequality and the Relationship to Crime

University of Sussex (UK), MSc Thesis, 2014

The goal of this thesis is to study the determinants of income inequality and to establish the relationship between income inequality and crime (which in this dissertation is limited to homicide rates per 100,000 population). Theoretical expectations on the relationship between income inequality and homicide rates are very strong and so are the empirical findings. A panel dataset covering 137 countries from 2000 – 2012 and four econometric methodologies – OLS, fixed effects, 2-stage fixed effects and 2-step difference GMM – are adopted to test for the determinants of income inequality, the link between inequality and homicide rate and to test for criminal inertia in the data. On the determinants of income inequality, I find evidence that income inequality is strongly associated with GDP per capita, the rule of law index, secondary education and unemployment rate. Although, this was not the focus of this research, it is important to state here that amongst other determinants of income inequality, the significance of the rule of law index was constant and consistent in all the different methodologies used. On the relationship between income inequality and homicide rate, I find Gini index to be a strong determinant of homicide rate. Empirical results find that the death penalty is not a crime deterring factor but rather that with good governance, the rate of homicide can be greatly reduced both in the short-run and long-run. Also, not surprising is the fact that factors determining income inequality also determine homicide rates. The results of my dynamic model support the hypothesis that criminal inertia is important in the study of crime rates as the lagged homicide rate is positively associated with the homicide rate. On the basis of my work, it seems clear that other factors determining income inequality and homicide rates should, whenever possible, be studied separately.

Income inequality, poverty and crime across nations

We examine the relationship between income inequality, poverty, and different types of crime. Our results are consistent with recent research in showing that inequality is unrelated to homicide rates when poverty is controlled. In our multi-level analyses of the International Crime Victimization Survey we find that inequality is unrelated to assault, robbery, burglary, and theft when poverty is controlled. We argue that there are also theoretical reasons to doubt that the level of income inequality of a country affects the likelihood of criminal behaviour.

Economic growth, income inequality and lethal violence in developed countries

EconomiA, 2024

Purpose-The paper aims to investigate the effect of GDP growth on crime and to test the hypothesis of nonlinearity. Additionally, we estimate the interaction between GDP and income inequality and examine its impact on the relationship between GDP and homicide rates. Design/methodology/approach-The study utilizes panel data from the Organization for Economic Cooperation and Development (OECD), spanning the period from 2000 to 2018 and estimates dynamic panel GMM models. Findings-We found a nonlinear relationship between GDP and homicide rates, indicating a dual effect of GDP on the occurrence of lethal crimes. Moreover, income inequality conditions the effect of GDP on homicide rates, exerting a significant influence. We conclude that in contexts characterized by high levels of income inequality, GDP growth is more effective in reducing crime, as there is greater potential for improvement. Originality/value-This paper contributes to the existing literature by providing insights into the complex nonlinearity between economic conditions, income inequality and homicide rates.

Crime and Inequality: Reverse Causality

2007

Crime and Inequality are often associated. Although, scholars and the regular press have been mostly looking at income inequality as a determinant of crime, in this study we make the case for reverse causality. We explore the theoretical mechanism through which crime -a toll on property rights-leads to lower levels of disposable income, since individuals resort to costly forms of protection. Given concave preferences, the poor will be much more reluctant to save the remainder income and to invest in future consumption via any sort of high yielding asset. The rich su¤er less from this toll since concavity has a much lower e¤ect for the wealthy . Empirically, we show that violent crime leads poorer people to use more expensive means of transportations to work. We also show that property crime increases the percentage of population that moves to another home. This increase is of the same amount for all income levels above $25,0000. To conclude, we show, using overcrowding litigation of prisions in the US as an instrument for crime, that a doubling in property crime has a 10%-15% positive and signi…cant e¤ect on inequality, measured by the Gini coe¢ cient, after 6 or more years.

Violent Crime driven by income inequality between countries

The literature has suggested several approaches to explain violent crime, such as the heat hypothesis that more violence is associated to very hot temperature. However, the manifold determinants of violent crime in society are hardly known. This study shows that, controlling the climate, the intentional homicides (per 100,000 people) can be explained by the high level of income inequality, both in hot tropical areas and in temperate regions of the globe. Overall, then, the socioeconomic inequality is one of factors that generates aversive social environments and, as a consequence, a deteriorated human behavior leading to high rates of intentional homicides in society.

Identifying the Dynamic Effects of Income Inequality on Crime

Oxford Bulletin of Economics and Statistics, 2020

What happens to crime after an increase in income inequality? The microeconomics literature that attempts to answer this question often employs identification strategies that exploit external sources of variation that provide quasi-experiments to identify causal effects. In contrast, this paper tackles this question by using structural vector autoregressions (SVAR), a methodology typically employed in modern empirical macroeconomics to identify and estimate dynamic causal effects of exogenous shocks. Unlike the macroeconomic SVAR models that are often applied to time-series data, we exploit the time series and crosssectional dimensions of our data, leading to the estimation of panel SVAR models. Using U.S. state-level data for the period 1960-2015, our results indicate that structural shocks to inequality increase both violent and property crime. Variance decomposition analyses show that inequality has little explanatory power for movements in crime.

Crime and income inequality: An economic approach

Atlantic Economic Journal, 1992

The criminology and sociology literature are rich with scholarly attempts to identify the variables affecting criminal activity, giving particular emphasis to crimes against property. Naturally, special attention has been devoted to the influence of inequality in the distribution of income, since its importance is so intuitively appealing. An excellent study of this type is that of Carroll and Jackson [1983], who used a sample from 93 non-southern cities with a population of over 50,000. Their regression results demonstrated [p. 186] "that inequality has strong causal effects on crime rates." In their introductory survey of the literature, Caroll and Jackson [p. 179] also point out that "recent research tends to the conclusion that it is inequality rather than poverty that is the crucial variable." As they correctly point out, this argument was very strongly made by Braithwaite [1979, p. 211], who after an exhaustive review of the literature concluded that while the evidence regarding the effect of poverty on crime rate is inconsistent, "the literature shows fairly uniform support for a positive association between inequality and crime .... " This relationship, first noted by Eberts and Schwirian [1968], is generally accepted today. Surprisingly, this positive association seems to hold true only for the U.S. In a cross-national study of 62 countries, Stack [1984, p. 247] concludes that, "the best estimates in the analysis offer no support for the hypotheses on property crime and inequality. The results of research based predominantly on American samples are not replicated for a large set of nations with varied cultural and institutional frameworks." The most significant variable affecting crime rates according to Stack was the total level of wealth of the society or what he termed the degree of economic development [p. 246]. "Again, however, a control variable does most of the explaining of the variance in crime: the level of economic development." The importance of the total level of wealth in explaining property crime within the U.S. itself is also pointed out by Jacobs [1981]. He finds [p. 23] that, "if we look at the effects of particular variables we find that the indicator with the most consistent effects was the measure of economic development." And he shows once again that (in contrast to cross-national data) for the U.

Does Inequality really increase Crime? Theory and Evidence

2018

The standard model of the economics of crime predicts that inequality and (property) crime are positively associated. We show that, allowing for simple modification to the standard framework, such relationship becomes ambiguous. In order to give robustness to this intuition, we conduct a meta-analysis based on 37 empirical papers and 1,130 effect sizes. We find evidence of the presence of (positive) publication bias. When the bias is taken care of, the true effect of inequality on crime becomes almost zero. Finally, we also provide evidence of the source of the estimates’ heterogeneity.

Absolute Inequality and Violent Property Crime

CIEF Working Papers, No. 16-26, 2016

Rational choice models argue that income inequality leads to a higher expected utility of crime and thus generates incentives to engage in illegal activities. Yet, the results of empirical studies do not provide strong support for this theory; in fact, Neumayer provides apparently strong evidence that income inequality is not a significant determinant of violent property crime rates when a representative sample is used and country specific fixed effects are controlled for. An important limitation of this and other empirical studies on the subject is that they only consider proportional income differences, even though in rational choice models absolute difference in legal and illegal incomes determine the expected utility of crime. Using the same methodology and data as Neumayer, but using absolute inequality measures rather than proportional ones, this paper finds that absolute income inequality is a statistically significant determinant of robbery and violent theft rates. This result is robust to changes in sample size and to different absolute inequality measures, which not only implies that inequality is an important correlate of violent property crime rates but also suggests that absolute measures are preferable when the impact of inequality on property crime is studied.