Testing Theory and the Analysis of Time Series Data

Although the relationship between unemployment and crime has been a longstanding interest in criminology, there is little agreement about appropriate models for analyzing this relationship. David Greenberg's (this issue) discussion highlights two issues that raise questions about recent research on the unemployment–crime relationship. First, he extends the work of Hale and Sabbagh (1991) and argues that cointegration methods should be used instead of first-differenced regression models to analyze unemployment and crime time series data. Second, he argues that previous attempts to test his strain theory linking unemployment to the age distribution of crime rely on flawed hypotheses, inappropriate data, and faulty measurement. In this paper, I address both of Greenberg's claims. I begin with a discussion of the relative utility of cointegration analysis and of first-differenced regression models for the analysis of the unemployment–crime relationship, focusing on the link between theory and statistical model. I then discuss the possibility of ever testing and falsifying Greenberg's strain theory.     

Unemployment and Crime Rate Fluctuations: A Comment on Greenberg

Several ways in which the specification of the Cantor and Land (1985) conceptual model of transient relationships between aggregate unemployment and crime rate fluctuations differs from that of Greenberg (2001) are noted. It follows that we do not accept Greenberg's Eq. (1) as a valid theoretical representation of the processes of interest. We briefly review the substantive context from which our investigation began in the mid-1980s. We also review the time series properties of our model and of the aggregate unemployment and crime rates used in its estimation. We note how the time series behavior of various crime rates determines which parts of the Cantor and Land model are and are not likely to be estimated as statistically significant for those series. We conclude with some comments on the limitations of aggregate time series research designs for testing the behavioral hypotheses used to generate expected relationships between aggregate unemployment and crime rates and suggest some alternative research designs.     

EXAMINING THE GENERALITY OF THE UNEMPLOYMENT–CRIME ASSOCIATION

This article examines whether the relationship between unemployment and criminal offending depends on the type of crime analyzed. We rely on fixed‐effects regression models to assess the association between changes in unemployment status and changes in violent crime, property crime, and driving under the influence (DUI) over a 6‐year period. We also examine whether the type of unemployment benefit received moderates the link to criminal behavior. We find significantly positive effects of unemployment on property crime but not on other types of crime. Our estimates also suggest that unemployed young males commit less crime while participating in active labor market programs when compared with periods during which they receive standard unemployment benefits.     

Will Inflation Increase Crime Rate? New Evidence from Bounds and Modified Wald Tests

This paper employs the modified Wald (MWALD) causality test to re-examine the relationship between crime and its determinants (inflation and unemployment) in the United States from 1960 to 2005. Bounds test approach is employed to investigate the existence of a long-run relationship. The empirical evidence suggests that inflation and crime rates are cointegrated with a positive relationship. Moreover, the causal link is from inflation and unemployment to crime.     

Unemployment and Crime: Toward Resolving the Paradox

While official crime statistics from many countries show that unemployed people have high crime rates and that communities with a lot of unemployment experience a lot of crime, this cross-sectional relationship is very often not found in time-series studies of unemployment and crime. In Australia there have been no individual-level or cross-sectional studies of unemployment and adult crime which have failed to find a positive relationship and no time-series which have supported a positive relationship. Consistent with this pattern, a time series of homicide from 1921 to 1987 in Australia reveals no significant unemployment effect. A theoretical resolution of this apparent paradox is advanced in terms of the effect of female employment on crime in a partriarchal society. Crime is posited as a function of both total unemployment and female employment. When female employment is added to the model, it has a strong positive effect on homicide, and unemployment also assumes a strong positive effect.     

UNEMPLOYMENT AND PROPERTY CRIME: A TARGET‐SPECIFIC ASSESSMENT OF OPPORTUNITY AND MOTIVATION AS MEDIATING FACTORS*

Most recent unemployment‐crime (U‐C) research is informed by the possibility that unemployment could both increase motivation for crime and decrease criminal opportunities. The mediating links of motivation and opportunity, though often assumed, have almost never been measured. We directly test for the potential mediating effects of opportunity and motivation using county‐level data for target‐specific crime rates such as convenience store robberies, motorcycle thefts, etc. We link these with data on the supply and value of corresponding crime targets (e.g., number and annual sales of convenience stores). Opportunity levels were generally unrelated to property crime rates and do not appear to mediate the U‐C relationship.     

Is peniaphobia an incentive to crime?

This article analysed the relationship between crime categories and unemployment rates using a set of panel data for 14 states in Malaysia with data spanning from 1982 to 2008. It is well documented that crime and unemployment are negatively related in Malaysia; the same is the case for both violent and property crime. Increases in unemployment rates cause the consumption expenditure to decrease, especially among households, hence, causing potential earnings from illegitimate activities to drop and discouraging a person from committing a crime. However, the significant properties of the t-statistics indicate that it is important to consider the labour market conditions in employing appropriate policies in fighting crime. That being said, unemployment can indirectly explain hunger, poverty, decreasing standards of life and economic downturn.     

Testing for seasonality in reported crime data

In spite of the apparent importance of crime statistics to policy-makers and the public, these data are not often analyzed or refined in the same manner as other social series such as unemployment. In this paper, seasonal variation in FBI index crimes is investigated for a major urban area. Using Miami data for 1949–1970, a test for seasonality is developed and seasonal indices are constructed for a number of crime types. A definite seasonal pattern in Miami crime data is found to exist, although its importance seems to be declining in recent years. Some applications of seasonally adjusted data to public information and operations are also briefly discussed.     

Unemployment and the dynamics of offender populations

This paper models the increase in the participation rate of criminal behavior as either the initiation rate or the career length of criminals changes in response to increases in unemployment. Even with large instantaneous increases in unemployment, the models show a very slow increase in the criminal participation rate, giving a possible explanation of the failure of many studies to demonstrate a link between unemployment and crime levels.     

Reconsidering the unemployment and crime relationship: Variation by age group and historical period

Although considerable research has examined the direct effects of age and economic conditions on crime, relatively little work has investigated the joint influence that age and unemployment may have on rates of criminal behavior. This study extends prior research on the unemployment-crime relationship by testing simultaneously for (1) variation in the unemployment-crime relationship by age group and (2) variation in the unemployment-crime relationship over time. Age-specific arrest and unemployment time-series data for the United States from 1958 to 1995 are used to test these hypotheses. The two main findings indicate that (1) unemployment has a greater motivational effect on property crime among youth and young adults and (2) the unemployment-crime relationship varies over time, but in a way that appears to be more random than systematic. The implications for future research are discussed.     

UNEMPLOYMENT,CRIME, AND IMPRISONMENT: A PANEL APPROACH*

Despite the widespreach acceptance of the notion that during periods of economic downturn, higher levels of unemployment lead to higher levels of crime and imprisonment, the research literature reveals very little consistent support for the existence of such a relationship. Studies that do suggest unemployment causes crime and imprisonment have used methodological techniques which, especially in over-time studies, could lead to the acceptance of spurious effects caused by trend and lag as evidence of a true relationship. Using data over a six-year period for the United States, a panel model is specified in which appropriate controls for intra-series trend and cross-series lagged effects are included. Although bivariate correlations are strongly suggestive of a relationship between unemployment and crime, results of the panel approach suggest that most of the apparent relationship is due to common trend effects. Little evidence is found for the existence of a relationship between crime/imprisonment and unemployment, regardless of the type of effect considered. In addition, results from stability tests indicate that the crime-unemployment relationship has been unstable. while the unemployment-imprisonment relationship has been relatively invariant.     

The economy,crime and time: An analysis of recorded property crime in England & Wales 1961–2006

We seek to determine whether one of the unanticipated side-effects of social and economic changes associated with the adoption of neoliberal and monetarist economics during the 1970s/1980s was rising crime rates. Undertaking time series analysis of social and economic determinants of property crime (using official statistics on recorded crime for England and Wales from 1961 to 2006) we develop a model of the effect of changes in socio-economic variables (unemployment, inequality, welfare spending and incarceration) on property crime rates. We find that while three of these had significant effects on change in the property crime rate, income inequality did not. We conclude with a discussion of the extent to which neoliberal economic and welfare (and later criminal justice) policies can be held to have influenced the property crime rate since the early 1980s and what this tells us about the social and economic determinants of crime at the macro-level.     

THE SOCIAL EMBEDDEDNESS OF CRIME AND UNEMPLOYMENT*

A missing piece in the literature that links crime and unemployment is an understanding of the proximate causes of joblessness in the lives of individuals. Granovetter has demonstrated with his concept of social embeddedness that early employment contacts can enhance the prospects of getting a job and subsequent occupational mobility. The alternative implication is that youths who are embedded in criminal contexts can become isolated from the likelihood of legitimate adult employment. This has important implications for an understanding of crime and unemployment, for while much of past macro-level research confirms that unemployment leads to crime in the aggregate, the reverse is likely true at the individual level among adolescents and young adults, especially in community settings with serious crime and unemployment problems. The implications of criminal embeddedness are explored in a well-known set of London panel data. Understanding the process of embeddedness is important because it helps to identify points of intervention, such as peer and justice system contacts.     

Crime,unemployment, and social structures of accumulation: An inquiry into historical contingency

This article examines whether prior inconsistency in findings about the impact of unemployment on crime is the result of historical contingency caused by changes in the social structures of accumulation (SSAs) associated with the development of twentieth-century U.S. capitalism. We explore this question by comparing the relationship between official measures of unemployment and the crimes of burglary, robbery, assault, and homicide during four phases of recent U.S. economic development identified by SSA theorists: economic exploration from 1933 to 1947, economic consolidation from 1948 to 1966, economic decay from 1967 to 1979, and a new period of exploration from 1980 to 1992. We propose that the unemployment-crime (U-C) relationship is shaped not merely by the fact of unemployment, but rather by its social meaning within developmental stages of social structures of accumulation. Time-series analysis of the U-C relationship within each SSA stage from 1933 to 1992 supports our hypothesis that periods of structural unemployment will be characterized by a stronger U-C relationship than those in which unemployment is primarily frictional. We then validate the periodization of shifts in the U-C relationship suggested by SSA theory by applying time-varying parameter analysis to the entire series from 1933 to 1992. On the basis of these findings we conclude that crime control policies and future research into the relationship between unemployment and crime should take into consideration the historically contingent nature of the U-C relationship.     

Unemployment,Guardianship, and Weekday Residential Burglary

The absence of a consistent positive effect of the unemployment rate on the crime rate is perplexing, but it may be partly due to the countervailing effect of guardianship. Using weekly state-level data and a pooled cross-sectional time-series research design, we investigate whether the unemployment rate influences residential burglary. This study contributes to the extant literature by distinguishing between weekday residential burglaries, or those burglaries that occur between the hours of 6 am to 6 pm on weekdays, from weeknight/weekend burglaries. If unemployment increases guardianship because previously employed individuals are now at home during the workday protecting their possessions, the expectation is that the unemployment rate will have an instantaneous negative effect on residential burglaries that transpire during normal working hours. Results buttress the logic associated with the guardianship thesis in that a rise in the unemployment rate only engenders a decrease in weekday residential burglaries.     

Social context of crime control: a time-series analysis of the Korean case, 1973–2002

Regardless of recent attempts to explain crime control in relation to its social structural conditions, few studies have assessed the economic, organizational, and political context of crime control simultaneously. This study integrated these three contexts into a single project to test the relevance of social structural explanations on major crime control practices over the past three decades in South Korea. By using a variety of official statistics, time-series regressions were used. The level of crime consistently explained most variation in the arrest rates for all four categories of crimes. Prosecutions also seemed to be closely responsive to the level of crime. However, the link between crime and incarceration rates was not found for all categories of crimes. This finding indicates that levels of incarceration could be determined by external factors such as the economic conditions, organizational capacity, and political climates. In addition, economic conditions, which were measured by the unemployment rate, appeared to have a strong relationship to all crime control practices; it was positively and statistically significant for arrest, prosecution and incarceration rates. Political repression was inversely related to all three practices. However, organizational capacity only seemed to affect incarceration rates. Failure or inconsistencies of some of the social contexts in explaining crime control practice in South Korea can be assessed in both methodological and substantive grounds. This underscores the need to develop more solid theoretical arguments and empirical measures for their roles in crime control.     

Economic cycles and punishment: Unemployment and imprisonment

Research on the relations between the labor market and forms of punishment, inaugurated by Rusche, has developed along two lines, broadly speaking: first, the historical evolution of the links between the structure of the labor market and the structure of punishment and secondly, the conjunctural variations in admissions to prison and in prison populations with fluctuations in the employment situation. The present study is of the latter type. It stems from observations on two aspects of the French situation:

The concomitant long-term evolution (1875–1985) of curves for unemployment and for prison populations, given the downward trend in imprisonment rates until recent years.

The constant over-representation, among prisoners, of groups whose position on the labor market is insecure.

The link between unemployment and imprisonment was tested by multiple regression using data on economic, demographic, penal and correctional aspects (French figures, 1920–1985). The results show the participation of demographic factors in the variations in prison populations. They point to a significant correlation between variations in unemployment (in volume and rate) and the evolution of prison populations, all else being equal in terms of recorded crime. Analysis of the functioning of the criminal justice system, showing the existence of an internal subsystem characterized by its procedures — pretrial detention —, the offenses — street crime —, the sentences — imprisonment — and the social characteristics of those convicted, suggests an approach to the interpretation of these findings.     

Unemployment, Economic Theory, and Property Crime: A Note on Measurement

Drawing on rational choice theory, this study considers how best to measureunemployment within the context of the unemployment–property crimerelationship. Specifically, we use ARIMA techniques to examine the relativeefficacy of using the conventional Bureau of Labor Statistics (BLS)unemployment rate and two alternative measures of the demand for labor aspredictors of monthly counts of U.S. property offenses for the years 1982through 1996. The bivariate time series analyses indicate that while theBLS unemployment rate exhibits null effects, the number of individualsunemployed for 15 weeks or more and the capacity utilization ratesignificantly affect the level of property crime. The implications ofthese results are discussed.     

Explaining the UCR-NCVS Convergence: a Time Series Analysis

The study intends to explain the convergence of the UCR and NCVS data series (1973–2008). Hypothesized explanatory variables include increased police productivity, change in people’s attitudes toward crime and the police, demographic changes, changes in the measurements used in data collections, and the advancement of telecommunication tools. The time series models with relevant predictor variables are estimated to explain the convergence of the two crime data series in five different crime categories. The results show that an increase in the total number of employees in the police, changes in measurements, especially the methodological changes adopted in the victimization survey in 1992, and changing attitudes toward crime and the police affect the relationship between the two crime data series and may have helped the convergence of the two. We argue that (1) the convergence of the two crime data series is not a mere convergence of methodological inadequacies resulting from the declining quality of the victimization survey and (2) all the predictor variables only partially affect the convergence of the two crime data series. Methodological limitations of this study are also addressed.     

Unemployment and crime: the role of apprehension

An increase in the unemployment rate decreases the opportunity cost of crime and increases the crime rate according to standard microeconomics models. However, a large body of empirical research has shown that an increase in unemployment may increase or decrease crime. By incorporating the return to crime into standard economic models, this paper shows that an increase in unemployment, as in recessions, decreases the opportunity cost of crime and the return to crime as well. As a result, the effect of unemployment on crime is ambiguous and depends on the apprehension rate. An increase in the unemployment rate tends to decrease the crime rate at lower apprehension rates, but to increase it at higher apprehension rates. An increase in the generosity of unemployment insurance benefits does not necessarily reduce the crime rate, and the effect of more generous unemployment insurance on crime depends again on the apprehension rate.