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The Economics of Fraudulent Accounting

Simi Kedia
Rutgers University, Newark, School of Business-Newark, Department of Finance & Economics

Thomas Philippon
New York University - Department of Finance; National Bureau of Economic Research (NBER)


January 2005

AFA 2006 Boston Meetings Paper

Abstract:     
We study the consequences of earnings management for the allocation of resources among firms, and we argue that fraudulent accounting has important economic consequences. We first build a model where the costs of earnings management are endogenous, and we show that, in equilibrium, bad managers hire and invest too much, distorting the allocation of real resources. We test the predictions of the multidimensional signalling model using new historical and firm-level data. We first show that periods of high stock market valuations are systematically followed by large increases in reported frauds. We then show that, during periods of suspicious accounting, insiders sell their stocks, while misreporting firms hire and invest like the firms whose income they are trying to match. When they are caught, they shed labor and capital and improve their true productivity. In the aggregate, our model seems able to account for the recent period of jobless and investment-less growth.

JEL Classifications: D21, E22, E24, G3

Working Paper Series

Date posted: March 23, 2005 ; Last revised: March 23, 2005

Suggested Citation

Kedia, Simi and Philippon, Thomas, The Economics of Fraudulent Accounting (January 2005). AFA 2006 Boston Meetings Paper. Available at SSRN: http://ssrn.com/abstract=687225


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Contact Information

Thomas Philippon (Contact Author)
New York University - Department of Finance ( email )
Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Simi Kedia
Rutgers University, Newark, School of Business-Newark, Department of Finance & Economics ( email )
111 Washington Avenue
Newark, NJ 07102
United States
973-353-1145 (Phone)
Feedback to SSRN (Beta)


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