An Experimental Study of Compliance and Leverage in Auditing and Regulatory Enforcement

Evidence suggests that a large majority of firms and individuals comply with regulations and tax laws even though the frequency of inspections and audits is often low. Moreover, fines for noncompliance are also typically low when regulatory violations are discovered. These observations are not consistent with static compliance models. Harrington (1988) modified these static models by specifying a dynamic game in which some agents have an incentive to comply even when the cost of compliance each period is greater than the expected penalty. This paper reports a laboratory experiment based on the Harrington model framework, in which subjects move between two inspection groups that differ in the probability of inspection and severity of fine. Subjects decide to comply or not in the presence of low, medium or high compliance costs. Enforcement leverage arises in the Harrington model from movement between the inspection groups based on previous observed compliance and noncompliance. Our results indicate that consistent with the model, violation rates increase when compliance costs become higher and as the probability of switching groups becomes lower. Behavior does not change as sharply as the model predicts, however, since violation rates do not jump from 0 to 1 as parameters vary across critical thresholds. A simple model of bounded rationality explains these deviations from optimal behavior.