The Desirability of Forgiveness in Regulatory Enforcement
I present a model that explains two common features of regulatory enforcement: selective forgiveness of noncompliance, and the collection of information on a firms compliance activities and not just its compliance status. I show that forgiving noncompliance is optimal if the information on a firms compliance activities constitutes sufficiently strong evidence of the firm having exerted a high level of compliance effort. The key benefit of forgiving noncompliance is a reduction in the probability with which the firm needs to be monitored. If fines are costly, a further benefit is a reduction in fine costs.
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