Micro-level dynamics in hidden action situations with limited information

The hidden-action model provides an optimal sharing rule for situations in which a principal assigns task to agent who makes effort carry out the assigned him. However, can only observe outcome but not agent’s actual action, is why be based on outcome. builds somewhat idealized assumptions about principal’s and capabilities related information access. We propose agent-based that relaxes some of these assumptions. Our analysis lays particular focus micro-level dynamics triggered by limited access information. For sphere, we identify so-called Sisyphus effect explains with incentives take action difficult achieve if limited, factors moderate this effect. In addition, analyze behavioral sphere. show might make even more than under unlimited information, refer as excess effort. Interestingly, control probability making via incentive mechanism. how much finally direct control.