Yi Chen (Cornell)
“Misconduct, Peer Learning, and Strategic Enforcement,” (joint with Kai Du, Phillip Stocken and Zhe Wang)
- We consider a dynamic model, wherein two firms test a regulator’s enforcement propensity with misconduct actions, and the regulator disciplines the firms to build a reputation of strict enforcement. We characterize the regulator’s enforcement strategies and the firms’ equilibrium misconduct levels. We show that when the regulator has full discretion on enforcement, allowing firms to learn from the peers’ enforcement outcomes increases misconduct and reduces the regulator’s payoff. However, if the regulator is restricted to a uniform enforcement criterion across firms and over time, peer learning reduces misconduct and increases the regulator’s payoff. Our results imply that whether to embrace enforcement transparency depends on the level of discretion over enforcement criterion.
- Date: 20 Oct 2021 16:00
- Ends: 20 Oct 2021 17:00
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