IV. Understanding the Causes of Theft: Criminological Research and Theory
The field of criminology has approached the study of theft with respect to two theoretical issues that have occupied scholarly attention for several decades. The first is the relationship between macro-level economic forces and theft, typically conceptualized in terms of classic strain theory (Merton, 1938) or social disorganization theory (Shaw & McKay, 1942). The second centers on the extent to which rates of theft reflect the opportunities for crime provided by certain locations and the processes by which potential victims and offenders converge in space and time. This conceptual focus was strongly influenced both by the development of routine activities theory (Cohen & Felson, 1979) and a growing emphasis on the role of the physical and social environment in shaping opportunities for theft (Reppetto, 1974). In the following sections, a summary of research in these two main conceptual areas is provided. Following that, research is reviewed that has examined the relationship between drug use and addiction and theft.
A. Economic Conditions and Theft
1. Income Inequality and Theft
The relationship between income inequality and theft is one of the most enduring in all of criminology and is generally conceptualized in terms of classic strain theory (Merton, 1938). Strain theory posits that theft is the result of the gap between the culturally induced aspirations for economic success and the structurally distributed possibilities for achieving it. Merton predicted that some individuals would respond to the strain between aspiration and the lack of opportunity by engaging in criminal behavior such as theft. The theory assumes similar success aspirations across social classes and posits that crime is disproportionately concentrated in the lower class because they have the fewest legitimate opportunities for achievement and so are the most vulnerable to this pressure or strain. Simply put, overemphasis on material success and lack of opportunity for this kind of success lead to crime.
Recent research indicates that income inequality is the most consistent structural correlate of rates for theft and other forms of property crime (Bursik & Grasmick, 1993; Walsh &Taylor, 2007). All forms of theft tend to occur disproportionately in poor, isolated, socially disadvantaged neighborhoods (Bernasco & Nieuwbeerta, 2005; Reisig & Cancino, 2004). In the United States in particular, social isolation and poverty are highly racialized. Research also finds that residential segregation, which is often a proxy measure for black–white income inequality, is strongly associated with burglary, larceny, and motor vehicle theft (Akins, 2003). Racialized income inequality leading to residential segregation can be traced to fundamental changes in the labor market, which resulted in the elimination of industrial jobs in major cities (Wilson, 1987). This fundamental economic shift is consistent with both sociological and criminological anomie theories, which predict an inability or failure of certain segments of the population to effectively adapt to major structural or economic changes (Merton, 1938), or that they will react to such changes by engaging in crime.
Similarly, research has also found links between welfare and theft suggested by classic strain, familial support, and variations of social disorganization theory. Both monetary assistance levels and welfare participation rates are negatively associated with all forms of theft (R. C. Allen & Stone, 1999). Basically, if state and local governments take measures to alleviate economic inequality by providing job training, welfare benefits, as well as ground-level efforts to improve communities by providing access to after-school programs and such, rates of theft decline substantially. In general, it is evident that state and local governments with strong welfare and monetary assistance programs will experience lower rates of theft. This research is also consistent with more recent formulations of social disorganization theory (Hunter, 1985; Sampson, Raudenbush, & Earls, 1997). That is, the inability or unwillingness of families and neighbors to come together for the betterment of their community tends to result in higher rates of all forms of crime. These factors are particularly well established as correlates of major forms of theft such as residential burglary, motor vehicle theft, and robbery (Reisig & Cancino, 2004; Rice & Smith, 2002). Accordingly, establishing higher levels of social control and cooperation among families, friends, neighbors, and public organizations such as the police will lead to lower rates of theft.
2. Unemployment and Theft
The unemployment rate is one of the most commonly used measures in research on the relationship of economic conditions and theft. Research and theory addressing the connection between unemployment and theft consistently predict that higher rates of unemployment lead to higher rates of theft (Bursik & Grasmick, 1993; Merton, 1938; Wilson, 1987). Given the theoretical consensus, one would assume that the empirical relationship would be fairly strong regardless of its interpretation. Findings, however, are quite inconsistent. Some research has found a positive relationship between unemployment and theft (Carmichael & Ward, 2001; Reilly & Witt, 1996), some research has found a negative relationship (Cantor & Land, 1985; Land, Cantor, & Russell, 1995), and other work has failed to find any appreciable effect (Weatherburn, Lind, & Ku, 2001). The continuation of mixed findings has led some criminologists to question whether the unemployment rate is a useful indicator in conceptualizing the relationship between economic conditions and theft, or at least, to conclude that it must be understood as one of a number of measures of economic hardship (Cantor & Land, 1985).
A growing body of research suggests that the effect of unemployment on theft is not straightforward, but rather, is contingent on various demographic or contextual factors. One consistent predictor is length of unemployment. Research suggests that individuals are more likely to commit crime the longer they are unemployed (Witt, Clarke, & Fielding, 1996). This indicates that individuals are generally able to endure short-lived instances of economic hardship, but will resort to theft if no legitimate opportunities surface in a reasonable period of time. Other demographic predictors are less reliable. The relationship appears to vary by age, but research is mixed as to the precise nature of the relationship. For example, some research has identified a link between adult male unemployment and theft (Carmichael &Ward, 2001), while other studies have found that unemployment is only related to rates of theft among juveniles (Britt, 1997). The kind of theft that occurs as a result of unemployment also appears to be impacted by considerations related to national or regional culture. For example, one recent study (Herzog, 2005) examined the relationship between unemployment and crime by focusing on the unique framework provided by the large, integrated labor force of Palestinian workers employed in Israel over the past few decades. Overall, a relationship between unemployment among Palestinians and theft in Israel was not found, except in one case: motor vehicle theft. As such, it appears that the relationship between economic hardship and crime may not be a general one, but rather, is specific to certain forms of activity (Herzog, 2005).
The main point to emphasize is that the relationship between unemployment and theft is far more nuanced than previously believed. The complexity of this relationship is further illustrated by Cantor and Land’s (1985) seminal work on the differential effects of motivation and opportunity. They argue that although rises in the unemployment rate may increase criminal motivation to commit theft, they may also decrease the opportunity to successfully complete theft. Simply put, if people aren’t working, they’re likely at home, which increases guardianship (Cantor & Land, 1985; Land et al., 1995). Despite this reasoning, recent research has found that overall, opportunity levels are unrelated to theft rates and do not appear to mediate the unemployment– crime relationship for most forms of theft (Kleck & Chiricos, 2002). Presently, then, it appears that the motivation to commit theft due to unemployment is stronger than the decreased opportunities that are theorized to decrease theft during periods of unemployment.
3. Market Forces and Theft
Theft is also directly impacted by the nature of the capitalist economy and the market for certain items, as well as other, more subjective economic indicators such as consumer confidence. A recent study (Rosenfeld & Fernango, 2007) found that consumer confidence and optimism had significant effects on theft rates that were largely independent of objective indicators such as unemployment and economic growth. Consumer sentiment also accounted for a significant portion of the overall crime decline that began during the early 1990s. This suggests that broad economic conditions, beyond the unemployment rate, are useful in modeling rates of theft in recent decades.
Research also suggests that theft rates are directly impacted by the cycle of the free market. Patterns of theft seem to be initially related to goods production. The relationship is straightforward: with more new items to consume, there is more to steal (Von Hofer & Tham, 2000). Then, when products reach the “saturation” stage, where people who want an item (such as a VCR or CD player) already have it, prices decline and such items are less likely to be stolen (Felson, 1996). This line of research supports a theft market life cycle of innovation, growth, mass market, and saturation. The optimum time to steal goods is during the “growth” phase, where demand for newer items is highest. The most inopportune time to steal goods is during the “saturation” period, where most everyone who wants an item already has it. These factors are also related to both prices and ownership levels of an item (Felson, 1996; Von Hofer & Tham, 2000). This research suggests that instances of theft can likely be reduced by an awareness and manipulation of certain licit markets as well as the pricing of merchandise (Wellsmith & Burrell, 2005).