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Contracting on the Stock Price and Forward-Looking Performance Measures


Shane S. Dikolli


Duke University - Fuqua School of Business

Igor Vaysman


CUNY Baruch College, Zicklin School of Business

September 30, 2006


Abstract:     
We examine the use of earnings, forward-looking performance measures, and stock prices in managerial compensation. When the firm's owner and its manager have identical time preferences, the stock price is not useful for motivating the manager, as it is a noisy aggregation of a forward-looking measure and future earnings. In contrast, when the owner and the manager have conflicting time preferences, the noisy stock price is useful for contracting. If the manager has no access to banking and cannot trade the firm's shares, the timeliness of the stock price dominates the extra risk imposed by its noise. At the same time, forward-looking performance measures (such as customer satisfaction) can induce a desirable allocation of management effort between the short-term and long-term more efficiently than the stock price can. Forward-looking performance measures and the stock price are thus not direct substitutes in rewarding farsighted effort.

Number of Pages in PDF File: 22

Keywords: Incentive pay, Non-financial performance measures, Agency theory, Forward-looking performance measures, Contractible performance measures, Stock-based compensation

JEL Classification: J33, M41

working papers series


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Date posted: December 1, 2006  

Suggested Citation

Dikolli, Shane S. and Vaysman, Igor , Contracting on the Stock Price and Forward-Looking Performance Measures (September 30, 2006). Available at SSRN: http://ssrn.com/abstract=947584 or http://dx.doi.org/10.2139/ssrn.947584

Contact Information

Shane Sami Dikolli (Contact Author)
Duke University - Fuqua School of Business ( email )
100 Fuqua Drive
Box 90120
Durham, NC 27708-0120
United States
919-660-1949 (Phone)
919-869-1901 (Fax)
Igor Vaysman
CUNY Baruch College, Zicklin School of Business ( email )
One Bernard Baruch Way, Box B12-225
New York, NY 10010
United States
646-312-3207 (Phone)
Feedback to SSRN (Beta)


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