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Deterrence and Decision Making: Research Questions and Theoretical Refinements

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Handbook on Crime and Deviance

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Deterrence is a process in which threatened or actual sanctions discourage criminal acts. There are not only official sanctions, such as incarceration or probation, but also non-legal punishments. For example, people refrain from offending to avoid stigma or disapproval from others. Deterrence requires that behavior is purposive; it assumes potential criminal actors weigh the incentives and disincentives to offend. The likelihood that an individual will commit a given crime is negatively related to his or her perceptions of the certainty, severity, and celerity of punishment for that crime. The formation of these threat perceptions is central to deterrence and, more generally, to society’s capacity for deterrence-oriented crime control.

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Notes

  1. 1.

    See McCrary’s (2002) discovery of errors in Levitt’s analysis, and Levitt’s (2002) demonstration that the errors did not affect the conclusions in the 1997 paper.

  2. 2.

    One person might be punished for a first offense while others can offend continuously without detection by authorities. The possibilities for incongruous information about sanction risks are enhanced in larger and less organized social systems.

  3. 3.

    These deterrent effects are particularly noteworthy given that the samples are of previously convicted offenders.

  4. 4.

    And if anything, calculated clearance rates overestimate the true clearance rate since the denominator is the crimes known to the police and the police cannot possibly know of all crimes.

  5. 5.

    The authors also reported similar null findings for the severity and celerity of punishment. Using a similar approach with data from the National Longitudinal Survey of Youth 1997 (NLSY97), Lochner (2007) found that without all available controls, the county-level arrest clearance rate for auto theft was strongly and positively correlated with county residents’ perceptions of the certainty of punishment, operationalized as the estimated percent chance of arrest for stealing a car. With additional control variables, the association remained positive but was no longer statistically significant at conventional confidence levels. Auto theft was the only crime for which the NLSY97 elicited estimates of the perceived certainty of punishment.

  6. 6.

    Respondents indicated how wrong it is for someone their age to commit each of the three antisocial acts (smoking marijuana, stealing, and cheating in school). They also indicated their friends’ level of approval or disapproval were the respondent to commit each of the three antisocial acts.

  7. 7.

    The phrase “JDM research” will be used to encompass psychology and behavioral economics research on predictable deviation from the rational norms of economic theory.

  8. 8.

    In Urn 2, the number of red balls is uniformly distributed from 0 to 100. Hence, E[x]=50.

  9. 9.

    However, while certainty judgments are naturally bounded, celerity and severity judgments are not. Therefore, Casey and Scholz (1991a, 1991b) artificially bounded severity judgments by instructing subjects: “Your total payment (penalty) could be anywhere from $1,000 to a maximum of $3,000.” Although the authors found evidence for boundary effects with ambiguous severity judgments, the theory does not address naturally unbounded judgments.

  10. 10.

    As further indication that aversion may only partially explain how ambiguity affects crime decisions, Ellsberg (1961) conducted a variant of the two-color experiment in which subjects could again draw one ball from one of two urns. If they draw number 687, they win. Urn 1 contains 1,000 balls, each numbered 1 to 1,000. Urn 2 also contains 1,000 balls, each with a number from 1 to 1,000. However in Urn 2, numbers can appear more than once. As in the two-color problem, Urn 2 offers a more ambiguous, but identical, probability of winning. Here subjects preferred Urn 2. In this case, subjects were both “ambiguity seeking” and inclined to revise a low, ambiguous probability upward, away from a boundary.

  11. 11.

    Consider a further example, adapted from Gonzalez and Wu (1999). Suppose a researcher must decide whether to improve a manuscript submission with additional analyses that will take 1 week to complete. The contemplated analyses are expected to improve the chances of publication by 10% points. Would the researcher be any more willing to do the additional work if they believed the probability of success without the extra analyses was 0.90 than if they believed that probability was 0.40? Or, what about 0 vs. 0.40? The reasoning from the Russian Roulette example suggests the additional work should be more likely for the increment at the ends of the continuum than in the middle. In the former instance, the result is a certain publication, or improving from no chance to at least some nonzero probability of success.

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Pogarsky, G. (2009). Deterrence and Decision Making: Research Questions and Theoretical Refinements. In: Krohn, M., Lizotte, A., Hall, G. (eds) Handbook on Crime and Deviance. Handbooks of Sociology and Social Research. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0245-0_13

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