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Optimal Long-Term Contracting with Learning

Zhiguo He¹; Bin Wei²; Jianfeng Yu³; Feng Gao⁴

¹ Booth School of Business, University of Chicago and NBER · ² Federal Reserve Bank of Atlanta · ³ PBC School of Finance, Tsinghua University and Carlson School of Management, University of Minnesota · ⁴ School of Economics and Management, Tsinghua University

We introduce uncertainty into Holmstrom and Milgrom (1987) to study optimal long-term contracting with learning. In a dynamic relationship, the agent’s shirking not only reduces current performance, but also increases the agent’s information rent due to the persistent belief manipulation effect. We characterize the optimal contract using the dynamic programming technique in which information rent is the unique state variable. In the optimal contract, the optimal effort is front-loaded and stochastically decreases over time. Furthermore, the optimal contract exhibits an option-like feature in that incentives increase after good performance. Implications about managerial incentives and asset management compensations are discussed. Received August 31, 2015; editorial decision October 20, 2016 by Editor Francesca Cornelli.

DOI

10.1093/rfs/hhx007

Volume

30 (6)

Pages

2006-2065

Language

en

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