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首页> 外文期刊>Economics of governance >Deterring repeat offenders with escalating penalty schedules: a Bayesian approach
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Deterring repeat offenders with escalating penalty schedules: a Bayesian approach

机译：用不断提高的处罚时间表来阻止重犯：贝叶斯方法

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摘要

We model deterrence with costly punishment when criminals have different abilities. Abilities are unobserved by both criminals and the courts. Based on past successes, criminals update their priors on being high-ability criminals. Courts cannot observe a criminal's total past offenses. They do know that criminals with more convictions were undeterred by previous penalties. Thus, they must have had more successes resulting in higher posterior probabilities of being high-ability criminals. Those with fewer convictions include more with lower posterior probabilities of being high-ability. Since they know that they are relatively more likely to be caught, they are deterred with lower penalties.
机译：当罪犯具有不同的能力时，我们会以高昂的惩罚来模拟威慑。犯罪分子和法院都没有察觉到这种能力。根据过去的成功经验，犯罪分子会更新他们成为高能力犯罪分子的先验。法院无法观察犯罪分子过去的全部罪行。他们确实知道，定罪更多的罪犯并不会受到以前的惩罚。因此，他们一定有更多的成功，导致成为高能力犯罪分子的后验概率更高。信念较少的人包括更多具有较低后验概率的人，即高能力。由于他们知道被捕的可能性相对较高，因此他们会以较低的罚款来吓退。

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