English, Article, Journal or magazine article edition: Optimal Law Enforcement under Asymmetric Information Mohamed Jellal; Nuno Garoupa

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Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Optimal Law Enforcement under Asymmetric Information
Author
  • Mohamed Jellal
  • Nuno Garoupa
Physical Description
  • preprint
Notes
  • In this paper, we focus on the problem created by asymmetric information about the enforcer's (agent's) costs associated to enforcement expenditure. This adverse selection problem affects optimal law enforcement because a low cost enforcer may conceal its information by imitating a high cost enforcer, and must then be given a compensation to be induced to reveal its true costs. The government faces a trade-off between minimizing the enforcer's compensation and maximizing the net surplus of harmful acts. As a consequence, the probability of apprehension and punishment is usually reduced leading to more offenses being committed. We show that asymmetry of information does not affect law enforcement as long as raising public funds is costless. The consideration of costly raising of public funds permits to establish the positive correlation between asymmetry of information between government and enforcers and the crime rate.
  • Fine, probability of detection, asymmetry of information
  • RePEc:upf:upfgen:401
Language
  • English
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