The effect of reporting errors on the cross-country relationship between inequality and crime

This paper analyzes reporting errors in crime data to see how they impact econometric estimates, particularly of the key relationship between inequality and crime. Criminal victimization surveys of 140,000 respondents in 37 industrial, transition and developing countries are used. Comparing the crimes experienced by these respondents with those reported to the police, non-random and mean-reverting errors are apparent. Time-varying factors affect the propensity of victims to report crimes to the police, undermining the use of country-specific fixed effects as a means of dealing with measurement error in official crime data. These errors substantially attenuate both cross-sectional and panel estimates of the partial correlation between inequality and crime.     

Crime,apprehension and clearance rates: Panel data evidence from Canadian provinces

The Becker model of crime establishes the importance of the probability of apprehension as a key factor in a rational individual's decision to commit a crime. In this respect, most empirical studies based on US data have relied on variation in the number of police officers to estimate the impact of the probability of apprehension or capture. We measure the probability of apprehension by clearance rates and study their effects on crime rates, employing a panel of Canadian provinces from 1986 to 2005. OLS, GMM, GLS and IV estimates yield statistically significant elasticities of clearance rates, ranging from ?0.2 to ?0.4 for violent crimes and from ?0.5 to ?0.6 for property crimes. These findings reflect the importance of police force crime‐solving productivity.     

Keeping up by robbing the Joneses

In this article, we find evidence of a ‘keeping up with the Joneses’ effect in the relationship between inequality and crime in Italy. We use data on minor and major crimes in the 20 Italian regions in the years 2004–2015 and show that for higher (lower) income levels, inequality leads individuals to commit major (minor) crimes to try to keep up with richer people.     

Is property crime caused by drug use or by drug enforcement policy?

The relationships among drug offenses, prorperty crime, and the allocation of police resources are investigated in a structural model using data from Florida countries. Law enforcement resources are scarce, and as efforts to combat drug crime increase the amount of these resources allocated to property crime is reduced. This reallocation of police resources results in reduced deterrence for property crime and, as a result, an increase in these crimes. The evidence presented suggests that rising property crimes in Florida are at least partially the result of drug enforcement policy.     

Violent crime and punishment: an application of the LISREL model

Public anxiety over violent crime has forged a broad consensus to purchase more crime control. Recently, the President brought into law a federal anti-crime bill that will put an additional 100 000 police on the nation's streets. This paper presents empirical evidence on the deterrence effect of police presence. The principal finding is that police presence deters commission of violent crimes by increasing the risk of being punished for committing those crimes. This risk is modelled as a latent variable, because the probability and severity of punishment for committing a violent crime are generally communicated in an onconsistant fashion. The violent crime commission rate is also treated as a latent variable, because it is almost certainly afflicted with measurement error.     

Crime and local inequality in South Africa

We examine the effects of local inequality on property and violent crime in South Africa. The findings are consistent with economic theories relating local inequality to property crime and also with sociological theories that imply that inequality leads to crime in general. Burglary rates are 25–43% higher in police precincts that are the wealthiest among their neighbors, suggesting that criminals travel to neighborhoods where the expected returns from burglary are highest. Finally, while we find little evidence that inequality between racial groups fosters interpersonal conflict at the local level, racial heterogeneity itself is highly correlated with crime.     

Improving Estimates of Inequality and Poverty from Urban China's Household Income and Expenditure Survey

In urban China the Household Income and Expenditure Survey requires respondents to keep a daily expenditure diary for a full 12-month period. This onerous reporting task makes it difficult to recruit respondents, compromising the sample. This article uses monthly expenditure data from two urban areas of China to see if data collection short-cuts, such as extrapolating to annual totals from expenditure reports in only some months of the year, would harm the accuracy of annual expenditure, inequality and poverty estimates. Replacing 12-month diaries with simple extrapolations from either one, two, four or six months would cause a sharp increase in estimates of annual inequality and poverty. This undermines international comparisons of inequality statistics because no country other than China uses such comprehensive 12-month expenditure records. But a corrected form of extrapolation, based on correlations between the same household's expenditures in different months of the year, gives much smaller errors in estimates of inequality and poverty.     

What causes violent crime?

This study uses panel data of intentional homicide and robbery rates for a sample of developed and developing countries for the period 1970-1994, based on information from the United Nations World Crime Surveys, to analyze the determinants of national crime rates both across countries and over time. A simple model of the incentives to commit crimes is proposed, which explicitly considers possible causes of the persistence of crime over time (criminal inertia). A panel-data based GMM methodology is used to estimate a dynamic model of national crime rates. This estimator controls for unobserved country-specific effects, the joint endogeneity of some of the explanatory variables, and the existence of some types of measurement errors afflicting the crime data. The results show that increases in income inequality raise crime rates, crime tends to be counter-cyclical, and criminal inertia is significant.     

Terror and the costs of crime

This paper argues that terrorism, beyond its immediate impact on innocent victims, also raises the costs of crime, and therefore, imposes a negative externality on potential criminals. Terrorism raises the costs of crime through two channels: (i) by increasing the presence and activity of the police force, and (ii) causing more people to stay at home rather than going out for leisure activities. Our analysis exploits a panel of 120 fatal terror attacks and all reported crimes for 17 districts throughout Israel between 2000 and 2005. After controlling for the fixed-effect of each district and for district-specific time trends, we show that terror attacks reduce property crimes such as burglary, auto-theft, and thefts-from-cars. Terror also reduces assaults and aggravated assaults which occur in private homes, but increases incidents of trespassing and “disrupting the police.” Taken as a whole, the results are consistent with a stronger deterrence effect produced by an increased police presence after a terror attack. A higher level of policing is likely to catch more people trespassing, and at the same time, reduce the number of property crimes. The decline in crimes committed in private houses is likely an indication that the tendency for individuals to stay home after a terror attack further increases the costs of crime.     

Measuring the impact of crime on house prices

This paper uses data on over 2800 house sales in Jacksonville, FL to estimate the impact of crime on house prices. A GIS programme is used to develop neighbourhood characteristics that are unique to each observation. Crime data, available for 89 police beats are assigned to each observation. Weighting the seriousness of offences by the cost of crime to victims is used as an alternative to the customary measures of the number of index crimes. The cost of crime has virtually no impact on house prices overall, but homes are highly discounted in high crime areas.     

Crime,inequality and unemployment in England and Wales

A model of crime is developed based on principles from the existing literature with some original insight. The implications of the model are that income inequality and unemployment are important explanatory variables for crimes motivated by economic gain, but do not offer much explanatory power for other types of crime. Panel data of UK regions over the years from 2002 to 2007 are then used to test these predictions. The empirical results strongly support the hypothesis that crime is an economic phenomenon.     

Inequality and criminality revisited: further evidence from Brazil

The objective of this study is to shed light on the determinants of criminality rates in Brazil. A panel data model was estimated using Brazilian states’ data. Our main result suggests that income inequality plays an important role in the determination of the crime rate. Furthermore, there are evidence suggesting that both unemployment and urbanization rates are positively related to crime. Based on a GMM approach we find the existence of an “inertial effect” on criminality. Besides that, the GMM results show that public security spending is effective in reducing criminality rates. Contrary to the common wisdom, we could not find evidence that poverty increases violent crimes. Finally, we have evidence that income inequality Granger causes crime, but not the reverse.     

Police-Monitored Cameras and Crime*

We study the effects of police monitoring on crime. We exploit detailed information on the location and date of installation of police-monitored surveillance cameras, coupled with data at the street-segment level on all reported crimes in the city of Montevideo, Uruguay. We find that the introduction of police-monitored surveillance cameras reduces crime by about 20 percent in monitored areas relative to a pure control group located outside the city. We also explore potential displacement effects, and we do not find evidence of such effects.     

Determinants of violent and property crimes in England and Wales: a panel data analysis

We examine various determinants of property and violent crimes by using police force area level (PFA) data on England and Wales over the period of 1992–2008. Our list of potential determinants includes two law enforcement variables namely crime-specific detection rate and prison population, and various socio-economic variables such as unemployment rate, real earnings, proportion of young people and the Gini Coefficient. By adopting a fixed effect dynamic GMM estimation methodology we attempt to address the potential bias that arises from the presence of time-invariant unobserved characteristics of a PFA and the endogeneity of several regressors. There is a significant positive effect of own-lagged crime rate. The own-lagged effect is stronger for property crime, on an average, than violent crime. We find that, on an average, higher detection rate and prison population leads to lower property and violent crimes. This is robust to various specifications. However, socio-economic variables with the exception of real earnings play a limited role in explaining different crime types.     

Police Violence and the Underreporting of Crime

This paper examines the relationship between police violence and the reporting of crime. Utilizing original data from a large‐scale household survey conducted in Costa Rica from October 2013 to April 2014 (n = 4,200), we find that the observation of police violence significantly reduces citizens’ willingness to report crime. The implications of this finding are explored using a game‐theoretic model of crime, crime reporting, and police misconduct. The model reveals that although the prospect of police violence against criminals may generate a degree of deterrence for criminal behavior, permissiveness toward police violence also raises expectations about the likelihood of police abuse against law‐abiding citizens. Consistent with our empirics, this reduces citizens’ propensity to report crime, thereby fostering a climate of impunity for criminal activity.     

On the Political Economy of Income Redistribution and Crime

This article analyzes a general equilibrium model in which agents choose to specialize in either legitimate or criminal activities. Expenditures on police to apprehend criminals, as well as income redistribution, are determined endogenously through majority voting. We investigate how crime, redistribution, and police expenditures depend on characteristics of the underlying distribution of income-earning abilities and on the apprehension technology. Our model accounts for the positive correlation between inequality and crime, the positive correlation between expenditures on police and redistribution, and the lack of correlation between crime and redistribution observed in U.S. data.     

THE IMPACT OF LOW‐PRIORITY LAWS ON CRIMINAL ACTIVITY: EVIDENCE FROM CALIFORNIA

We examine the impact of low‐priority initiatives on criminal activity. Low‐priority initiatives mandate that minor marijuana possession offenses be the lowest enforcement priority for police. Localities pass these laws because they believe if officers devote fewer resources toward minor marijuana crimes, more resources will be available to deter more serious crimes. Using data from California, we find that jurisdictions that adopted low‐priority laws experienced a reduction in arrests for misdemeanor marijuana offenses. However, we do not find evidence of a consistent effect of enacting a low‐priority initiative on the crime or clearance rate of other felonies. (JEL H1, H4, K4)     

Does longer incarceration deter or incapacitate crime? Evidence from Truth-in-Sentencing reform

This article evaluates how Truth-in-Sentencing (TIS) laws impact both violent and property crimes through mandating violent offenders to serve a substantial proportion of sentenced terms before being eligible to release to community supervision. Focusing on states with effective TIS laws, I utilize the difference-in-differences design to investigate the treatment effect of TIS on crime. I observe statistically significant decline in both violent and property crimes in TIS states. A series of placebo tests confirm the robustness of the estimates and inferences. The dynamic impact of TIS is heterogeneous among the seven categories of violent and property crimes in TIS states: murder and robbery rates decline almost immediately after TIS, while property crime takes longer time to exhibit significant decline.     

Inequality and Growth: What Can the Data Say?

This paper describes the correlations between inequality and the growth rates in cross-country data. Using non-parametric methods, we show that the growth rate is an inverted U-shaped function of net changes in inequality: changes in inequality (in any direction) are associated with reduced growth in the next period. The estimated relationship is robust to variations in control variables and estimation methods. This inverted U-curve is consistent with a simple political economy model but it could also reflect the nature of measurement errors, and, in general, efforts to interpret this evidence causally run into difficult identification problems. We show that this non-linearity is sufficient to explain why previous estimates of the relationship between the level of inequality and growth are so different from one another.     

Examining the link between crime and unemployment: a time-series analysis for Canada

We use national and regional Canadian data to analyse the relationship between economic activity (as reflected by the unemployment rate) and crime rates. Given potential aggregation bias, we disaggregate the crime data and look at the relationship between six different types of crimes rates and unemployment rate; we also disaggregate the data by region. We employ an error correction model in our analysis to test for short-run and long-run dynamics. We find no evidence of long-run relationship between crime and unemployment, when we look at both disaggregation by type of crime and disaggregation by region. Lack of evidence of a long-run relationship indicates we have no evidence of the motivation hypothesis. For selected types of property crimes, we find some evidence of a significant negative short-run relationship between crime and unemployment, lending support to the opportunity hypothesis. Inclusion of control variables in the panel analysis does not alter the findings, qualitatively or quantitatively.