We analyze the optimal design of rank-order tournaments with heterogeneous workers. Iftournament prizes do not differ between the workers(uniform prizes), as in the previous tournament literature, the outcome will be ineffcient. In the case of limited liability, the employer may benefit from...

We study contracting between a consumer and an expert. The expert can invest in diagnosis to obtain a noisy signal about whether a low–cost service is sufficient or whether a high–cost treatment is required to solve the consumer’s problem. This involves moral hazard because...

In this paper, I compare two different approaches to model implicit contracting, the infinite-horizon approach typically used in the literature and afinite-horizon approach building on an adverse-selection model. I demonstrate that even the most convincing result of the infinite-horizon...

In this paper, a principal’s decision between delegating two tasks or handling one of the two tasks herself is analyzed. We assume that the principal uses both, formal contracts and informal agreements sustained by the value of future relationships (relational contracts) as incentive...

We consider a situation where an agent's effort is monitored by a supervisor who cares for the agent's well being. This is modeled by incorporating the agent's utility into the utility function of the supervisor. The first best solution can be implemented even if the supervisor's preferences are...

We consider a double-sided moral hazard problem where each party can renege on the signed contract since there does not exist any verifiable performance signal. It is shown that ex-post litigation can restore incentives of the agent. Moreover, when the litigation can be settled by the parties...

In this paper a tournament between teams (a collective tournament) is analyzed, where each contestant may spend productive effort in order to increase his team's performance or sabotage the members of the opponent team. It is shown that sabotaging the weaker members of a team always decreases...