Dynamic Incentive Contracts under Parameter Uncertainty

Boyan Jovanovic () and Julien Prat

No 8136, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: We analyze a long-term contracting problem involving common uncertainty about a parameter capturing the productivity of the relationship, and featuring a hidden action for the agent. We develop an approach that works for any utility function when the parameter and noise are normally distributed and when the effort and noise affect output additively. We then analytically solve for the optimal contract when the agent has exponential utility. We find that the Pareto frontier shifts out as information about the agent's quality improves. In the standard spot-market setup, by contrast, when the parameter measures the agent's 'quality', the Pareto frontier shifts inwards with better information. Commitment is therefore more valuable when quality is known more precisely. Incentives then are easier to provide because the agent has less room to manipulate the beliefs of the principal. Moreover, in contrast to results under one-period commitment, wage volatility declines as experience accumulates.

Keywords: Principal-agent model; Optimal contract; Learning; Private information; Reputation; Career (search for similar items in EconPapers)
JEL-codes: D82 D83 E24 J41 (search for similar items in EconPapers)
Date: 2010-12
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Related works:
Journal Article: Dynamic contracts when agent's quality is unknown (2014)
Working Paper: DYNAMIC INCENTIVE CONTRACTS UNDER PARAMETER UNCERTAINTY (2011)
Working Paper: Dynamic Incentive Contracts under Parameter Uncertainty (2010)
Working Paper: Dynamic Incentive Contracts Under Parameter Uncertainty (2010)
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