Working Paper: CEPR ID: DP8136
Authors: Boyan Jovanovic; Julien Prat
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: Career Learning; Optimal Contract; Principal-Agent Model; Private Information; Reputation
JEL Codes: D82; D83; E24; J41
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Improved information about the agent's quality (L15) | Pareto frontier shifts outward (D69) |
| Better information enhances contract efficiency (D86) | Reduced agent's utility (D11) |
| Better information enhances contract efficiency (D86) | Increased principal's welfare (D69) |
| Wage volatility declines as experience accumulates (J31) | Improved contract efficiency (J41) |
| Parameter measures agent's quality (C52) | Pareto frontier shifts inward (D61) |
| Commitment is more valuable when quality is known precisely (L15) | Enhanced contract design (D86) |