Dynamic Amnesty Programs
Abstract/Contents
- Abstract
- 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.
Description
| Type of resource | text |
|---|---|
| Date created | August 20, 2021 |
Creators/Contributors
| 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 |
Subjects
| Subject | dynamic mechanism design |
|---|---|
| Subject | self-reporting |
| Subject | amnesty |
| Subject | crime |
| Subject | war |
| Genre | Text |
| Genre | Working paper |
| Genre | Grey literature |
Bibliographic information
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- License
- This work is licensed under a Creative Commons Attribution 4.0 International license (CC BY).
Preferred citation
- Preferred citation
- Kapon, S. (2022). Dynamic Amnesty Programs. Stanford Digital Repository. Available at https://purl.stanford.edu/jk190zp4023
Collection
SITE Conference 2021
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