Peter M DeMarzo
Bio: Peter DeMarzo is the Mizuho Financial Group Professor of Finance at the Stanford Graduate School of Business. He earned his BA in cognitive science and applied mathematics from the University of California, San Diego, and his MS in operations research and PhD in economics from Stanford University. In addition to his experience at the Stanford Graduate School of Business, he has taught at the Haas School of Business and the Kellogg Graduate School of Management and was a visiting scholar at the Hoover Institution. His research is in the area of corporate finance, asset securitization, and contracting, as well as market structure and regulation. Recent work has examined issues of the optimal design of securities, the regulation of insider trading and broker-dealers, and the influence of information asymmetries on corporate investment. His research has received awards including the Barclays Global Investors/Michael Brennan best paper award from the Review of Financial Studies, and the Western Finance Association Corporate Finance Award. He won the Sloan Teaching Excellence award in 2004 and 2006, and the Cheit Outstanding Teaching Award in 1998. He currently teaches MBA and PhD courses in Corporate Finance and Financial Modeling.
Abstract: We consider optimal incentive contracts when managers can, in addition to shirking or diverting funds, increase short term profits by putting the firm at risk of a low probability “disaster.” To avoid such risk-taking, investors must cede additional rents to the manager. In a dynamic context, however, because managerial rents must be reduced following poor performance to prevent shirking, poorly performing managers will take on disaster risk even under an optimal contract. This risk taking can be mitigated if disaster states can be identified ex-post by paying the manager a large bonus if the firm survives. But even in this case, if performance is sufficiently weak the manager will forfeit eligibility for a bonus, and again take on disaster risk. When effort costs are convex, reductions in effort incentives is used to limit risk-taking, with a jump to high powered incentives in the gambling region. Our model can explain why suboptimal risk-taking can emerge even when investors are fully rational and managers are compensated optimally.
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