Optimal law enforcement under asymmetric information

Mohamed Jellal () and Nuno Garoupa

Economics Working Papers from Department of Economics and Business, Universitat Pompeu Fabra

Abstract: 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.

Keywords: Fine; probability of detection; asymmetry of information (search for similar items in EconPapers)
JEL-codes: K4 (search for similar items in EconPapers)
Date: 1999-06
New Economics Papers: this item is included in nep-ind, nep-law and nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:upf:upfgen:401

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