Abstract

 
 

References (7)



 
 

Citations (6)



 


 



Optimal Fines and Auditing When Wealth is Costly to Observe


A. Mitchell Polinsky


Stanford Law School; National Bureau of Economic Research (NBER)

August 2004

Stanford Law and Economics Olin Working Paper No. 289

Abstract:     
This article studies optimal fines when an offender's wealth is private information that can be obtained by the enforcement authority only after a costly audit. I derive the optimal fine for the underlying offense, the optimal fine for misrepresenting one's wealth level, and the optimal audit probability. I demonstrate that the optimal fine for misrepresenting wealth equals the fine for the offense divided by the audit probability, and therefore generally exceeds the fine for the offense. The optimal audit probability is positive, increases as the cost of an audit declines, and equals unity if the cost is sufficiently low. If the optimal audit probability is less than unity, there are some individuals who are capable of paying the fine for the offense who misrepresent their wealth levels. I also show that the optimal fine for the offense results in underdeterrence due to the cost of auditing wealth levels.

Number of Pages in PDF File: 18

Keywords: fines, auditing, public enforcement, penalties, misrepresentation of wealth

JEL Classification: D31, D62, H23, K14, K42

working papers series


Download This Paper

Date posted: August 30, 2004  

Suggested Citation

Polinsky, A. Mitchell, Optimal Fines and Auditing When Wealth is Costly to Observe (August 2004). Stanford Law and Economics Olin Working Paper No. 289. Available at SSRN: http://ssrn.com/abstract=583923 or http://dx.doi.org/10.2139/ssrn.583923

Contact Information

A. Mitchell Polinsky (Contact Author)
Stanford Law School ( email )
559 Nathan Abbott Way
Stanford, CA 94305-8610
United States
650-723-0886 (Phone)
650-723-3557 (Fax)
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Feedback to SSRN (Beta)


Paper statistics
Abstract Views: 1,683
Downloads: 183
Download Rank: 73,559
References:  7
Citations:  6

© 2013 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright
This page was processed by apollo5 in 0.547 seconds