A principal incentivizes a group of agents to work by choosing a monitoring structure and a scheme of performance-contingent rewards. The monitoring structure partitions the set of agents into monitoring teams, each delivering a signal of joint performance. We show that unlike under partial implementation, the principal always exhausts her monitoring capacity to optimally implement work as a unique outcome. Optimal monitoring teams are homogeneous between them: equally sized and with agents allocated in an anti-assortative fashion. Higher-effort-cost agents receive lower rents, and they tend to be monitored more closely than lower-effort-cost agents when the principal's allocation is constrained.
A firm raises capital from multiple investors to fund a project. The project succeeds only if the capital raised exceeds a stochastic threshold, and the firm offers payments contingent on success. We study the firm's optimal unique-implementation scheme, namely the scheme that guarantees the firm the maximum payoff. This scheme treats investors differently based on size. We show that if the distribution of the investment threshold is log-concave, larger investors receive higher net returns than smaller investors. Moreover, higher dispersion in investor size increases the firm's payoff. Our analysis highlights strategic risk as an important potential driver of inequality.
A manager who learns privately about a project over time may want to delay quitting it if recognizing failure/lack of success hurts his reputation. In the banking industry, managers may want to roll over bad loans. How do distortions depend on expected project quality? What are the effects of releasing public information about quality? A key feature of banks is that managers learn about project quality from bad news, i.e., a default. We show that in such an environment, distortions tend to increase with expected quality and imperfect information about quality. Results differ if managers instead learn from good news.