Abstract
Objectives
To test whether individuals differ in deterrability by studying whether the effect of criminal experiences on perceived detection risk varies by criminal propensity.
Methods
Data from the British “Offending, Crime and Justice Survey”, a four-wave panel study on criminal behavior and victimization, are analyzed. Two subsamples for analyses are constructed: one of non-offenders at first measurement, to analyze the effect of gaining first offending experiences during the time of study (n = 1,279) and one sample of individuals who have committed offenses within the past year (n = 567), to analyze the effect of police contact among active offenders. Fixed-effects regressions of perceived detection risk on criminal experiences and interactions between criminal experiences and measures of criminal propensity (risk-affinity, impulsivity) are estimated.
Results
Analyses support learning models for the formation and change of risk perceptions, but individual differences by criminal propensity are present in the deterrence process: After gaining first offending experiences, impulsive individuals as well as risk-averse individuals are more likely to lower their perceptions about the probability of detection than less impulsive or risk-affine individuals are. A positive effect of police contact on expected detection risk is restricted to risk-averse individuals.
Conclusions
Findings support claims that deterrence works differently for crime-prone individuals. The differential effects of impulsivity and risk-affinity underline the importance of not combining constituent characteristics of criminal propensity in composite indices, because they might have differential effects on deterrence.
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Notes
Like most previous research, the remainder of this article focuses on perceptions about detection risk. I will return to perceptions about the severity of sanctions in the discussion section.
An alternative explanation for this finding could be that individuals who have more realistic estimates of getting caught self-select into crime. Even with elaborate statistical models, such dynamic selection processes are hard to disentangle from true causal effects (Bjerk 2009).
The main distinctions between low self-control and TRDM are rooted in a broad notion of low self-control, which was originally stated by Gottfredson and Hirschi (1990) and often measured with a scale with six subdimensions—the Grasmick et al. (1993) self-control scale. Back then, low self-control was described as a multidimensional trait consisting of such diverse things as “low cognitive and academic skills, a desire for easy and immediate gratification, a preference for physical rather than mental activity, enjoyment of thrilling (…) activities, a lack of perseverance, being ill-tempered, and self-centered” (Paternoster and Pogarsky 2009, p. 109). Furthermore, low self-control was seen by Gottfredson and Hirschi (1990) as a stable personal trait, which is supposed to be the result of effective childrearing and largely unalterable after childhood, while Paternoster and Pogarsky (2009) regard TRDM as variable across situations and changeable over the life-course. Amongst others, brain maturation is assumed to lead to better executive functioning, which might lead to improvement in TRDM by increasing the ability for the delay of gratification and decreasing the discount rate (Paternoster and Pogarsky 2009, p. 105).
It was assessed whether the respondent had ever stolen a vehicle, tried to steal a vehicle, had stolen parts from the outside of a vehicle, stolen from inside a vehicle, or tried to steal from outside or inside of a vehicle (vehicle theft offenses), whether the respondent had damaged a vehicle or damaged anything else on purpose (criminal damage offense), whether the respondent had committed domestic or commercial burglary (burglary offense), whether the respondent had stolen from another person, from work, from school, from a shop or anything else (other theft offense), whether the respondent had assaulted with or without injury and whether the respondent had committed commercial or personal robbery (violent offense) and whether the respondent had sold class-A drugs or other drugs (drug offense).
To check for the robustness of results, all individuals transitioning to offender status were combined into one category and analyses were estimated again without 27 cases with police contact early in their criminal career. Results remained robust (coefficient of the offender effect = −3.39, t = −1.92).
Thanks to an anonymous reviewer for this observation.
Thanks again to an anonymous reviewer for drawing my attention to this option.
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Acknowledgments
The Offending, Crime and Justice Survey was commissioned by the UK Home Office (http://homeoffice.gov.uk/). Data for analyses in this paper were obtained via the UK Data Archive (http://www.data-archive.ac.uk/). Neither the original data creators nor the UK Data Archive bear responsibility for the present analysis or interpretation. I am grateful to Clemens Kroneberg, Harald Beier and the anonymous reviewers for comments on an earlier draft of this paper.
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Schulz, S. Individual Differences in the Deterrence Process: Which Individuals Learn (Most) from Their Offending Experiences?. J Quant Criminol 30, 215–236 (2014). https://doi.org/10.1007/s10940-013-9201-6
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DOI: https://doi.org/10.1007/s10940-013-9201-6