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Fines, Appeals and Liability in Public Enforcement with Stochastic Damage and Asymmetric Information

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  • Robert Innes

Abstract

This paper studies an enforcement game between a regulator and firms that can cause harmful accidents. The distribution of potential accident damage is private information to the firms, and realized damage can be observed only at the cost of going to court. Under conditions described in the paper, an optimal policy involves the separate assessment of regulatory/settlement fines and court liability. In this optimum, injurers self-select by appealing (or not) to the court process; liability takes a 'threshold' form, assessing maximal liability when damages are high and zero liability otherwise; and, "vis-à-vis" a first-best, some firms are over-deterred-and others under-deterred-from having accidents. Copyright (c) The London School of Economics and Political Science 2004.

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  • Robert Innes, 2004. "Fines, Appeals and Liability in Public Enforcement with Stochastic Damage and Asymmetric Information," Economica, London School of Economics and Political Science, vol. 71(283), pages 391-416, August.
  • Handle: RePEc:bla:econom:v:71:y:2004:i:283:p:391-416
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    Cited by:

    1. Motta, Alberto & Burlando, Alfredo, 2007. "Self reporting reduces corruption in law enforcement," MPRA Paper 5332, University Library of Munich, Germany, revised 23 Jun 2007.

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