Decentralized deterrence, with an application to labor tax auditing

This paper studies a new strategic auditing game in which atomistic auditors maximize the success rate of audits, and provides a method to calibrate its parameters based on audit data. Calibrating the model to Italian auditing data, we provide an estimate of tax evasion based on (non-random) audit data alone. Counterfactual simulation of the model quantifies the costs and benefits of alternative auditing policies. We compare decentralized enforcement with a counterfactual "commitment policy," and compute the loss from the former.