We study optimal incentive contracts with multiple agents when performance evaluation is delegated to a reviewer. The reviewer may be biased in favor of the agents, but the degree of the bias is unknown to the principal. We show that a contest, which is a contract in which the principal...

We consider the design of contests when the principal can choose both the prize profile and how the prizes are allocated as a function of a possibly noisy signal about the agents’ efforts. We provide sufficient conditions that guarantee optimality of a contest. Optimal contests have a...

We consider the design of contests for n agents when the principal can choose both the prize profile and the contest success function. Our framework includes Tullock contests, Lazear-Rosen tournaments and all-pay contests as special cases, among others. We show that the optimal contest has an...

We study optimal incentive contracts with multiple agents when performance evaluation is delegated to a reviewer. The reviewer may be biased in favor of the agents, but the degree of bias is unknown to the principal. We show that a contest, which is a contract in which the principal determines a...

We present a model of startup acquisitions, which may give rise to inefficient "talent hoarding." We develop a model with two competing firms that can acquire and integrate (or "acquihire") a startup operating in an orthogonal market. Such an acquihire improves the competitiveness of the...

Surveys that are designed to measure subjective states (e.g., happiness) typically generate ordinal data. A fundamental problem is that methods used to analyse ordinal data (e.g., ordered probit) rely on strong and often unjustified distributional assumptions. In this paper, we propose using...