Dynamic Amnesty Programs

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A regulator faces a stream of agents each engaged in crime with stochastic returns. The regulator designs an amnesty program, committing to a time path of penalty reductions for criminals who self-report before they are detected. In an optimal time path, the intertemporal variation in the returns from crime can generate intertemporal variation in the generosity of amnesty. I construct an optimal time path and show that it exhibits amnesty cycles. Amnesty becomes increasingly generous over time until it hits a bound, at which point the cycle resets. Agents engaged in high return crime self-report at the end of each cycle, while agents engaged in low return crime self-report always. I discuss applications to desertion in war, tax evasion, and illegal gun ownership.


Type of resource text
Date created August 20, 2021


Author Kapon, Sam
Organizer of meeting Board, Simon
Organizer of meeting Cisterna, Gonzalo
Organizer of meeting Frick, Mira
Organizer of meeting Georgiadis, George
Organizer of meeting Skrzypacz, Andrzej
Organizer of meeting Sugaya, Takuo


Subject dynamic mechanism design
Subject self-reporting
Subject amnesty
Subject crime
Subject war
Genre Text
Genre Working paper
Genre Grey literature

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Kapon, S. (2022). Dynamic Amnesty Programs. Stanford Digital Repository. Available at https://purl.stanford.edu/jk190zp4023


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