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Enforcing Regulation under Illicit Adaptation

Andrés González Lira and Ahmed Mobarak ()
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Andrés González Lira: UC Berkeley

No 2143, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: Attempts to curb illegal activity by enforcing regulations gets complicated when agents react to the new regulatory regime in unanticipated ways to circumvent enforcement. We present a research strategy that uncovers such reactions, and permits program evaluation net of such adaptive behaviors. Our interventions were designed to reduce over-fishing of the critically endangered Pacific hake by either (a) monitoring and penalizing vendors that sell illegal fish or (b) discouraging consumers from purchasing using an information campaign. Vendors attempt to circumvent the ban through hidden sales and other means, which we track using mystery shoppers. Instituting random monitoring visits are much more effective in reducing true hake availability by limiting such cheating, compared to visits that occur on a predictable schedule. Monitoring at higher frequency (designed to limit temporal displacement of illegal sales) backfires, because targeted agents learn faster, and cheat more effectively. Sophisticated policy design is therefore crucial for determining the sustained, longer-term effects of enforcement. Data collected from fishermen, vendors, and consumers allow us to document the upstream, downstream, spillover, and equilibrium effects of enforcement on the entire supply chain. The consumer information campaign generates two-thirds of the gains compared to random monitoring, but is simpler for the government to implement and almost as cost-effective.

Date: 2018-08
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Working Paper: Enforcing Regulation Under Illicit Adaptation (2018) Downloads
Working Paper: Enforcing Regulation under Illicit Adaptation (2018) Downloads
Working Paper: Enforcing Regulation under Illicit Adaptation (2018) Downloads
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