Decentralized Deterrence, with an Application to Labor Tax Auditing
研究了一个新的战略审计博弈，其中原子化审计员最大化审计成功率，并基于意大利审计数据校准模型，估计逃税规模，比较分散执法与承诺政策的成本收益。
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.