Abstract
We analyze task allocation and randomization in Principal Agent models. We identify a new rationale that determines the allocation of tasks and show that it can be optimal to assign tasks that are very different to one agent. Similar to randomization, the reason to assign several tasks to one agent is to mitigate the effect of the participation constraint. We show that the allocation of tasks can be used as a substitute if randomization is not feasible.