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- W3151354093 abstract "We investigate the role of punishment progressivity and individual characteristics in the determination of crime. To analyze welfare implications we model individuals’ re- sponse to judges’ optimal punishment in a dynamic setting. We introduce two distinctive features motivated by our empirical setting. First, judges rarely imposes maximum pun- ishment for first time offenders. Instead, we observe low fines (or just a warning) even when crime detection technology is efficient and punishment is not costly. We account for this by allowing an unobservable (to the judge) individual state to be correlated with a public signal (the environment). This generates an optimal punishment that is conditional on individual observables. Second, judges punishments follow a progressive system: con- ditioning on type, recidivists are punished harsher than first-time offenders for the same crime. We account for these dynamics by introducing a persistent unobservable (to the judge) component. Judges update their beliefs about individuals depending on whether they committed a crime in the previous period; this gives rise to progressivity in the opti- mal punishment system. For the empirical analysis we examine a novel trial data set from a self-governed community of farmers in Southern Spain. We find that judges vary the degree of imposed punishments based on individual characteristics—such as when victims or accused have a Don honorific title indicating they are wealthy. Recidivists are punished harsher than first time offenders." @default.
- W3151354093 created "2021-04-13" @default.
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- W3151354093 date "2014-01-01" @default.
- W3151354093 modified "2023-09-23" @default.
- W3151354093 title "Let the Punishment Fit the Criminal" @default.
- W3151354093 hasPublicationYear "2014" @default.
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