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Dynamic Amnesty Programs

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  • Sam Kapon

Abstract

A regulator faces a stream of agents engaged in crimes with stochastic returns. The regulator designs an amnesty program, committing to a time path of punishments for criminals who report their crimes. In an optimal program, time variation in the returns from crime can generate time 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, after which the cycle resets. Agents engaged in high return crime report at the end of each cycle, while agents engaged in low return crime report always.

Suggested Citation

  • Sam Kapon, 2022. "Dynamic Amnesty Programs," American Economic Review, American Economic Association, vol. 112(12), pages 4041-4075, December.
    • Handle: RePEc:aea:aecrev:v:112:y:2022:i:12:p:4041-75
    DOI: 10.1257/aer.20211428
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    Cited by:

    1. Achim, Peter & Knoepfle, Jan, 0. "Relational enforcement," Theoretical Economics, Econometric Society.
    2. Patricia Gil & Justin Holz & John List & Andrew Simon & Alejandro Zentner, 2023. "Toward an Understanding of Tax Amnesties: Theory and Evidence from a Natural Field Experiment," Natural Field Experiments 00772, The Field Experiments Website.

    More about this item

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D86 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Economics of Contract Law
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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