Robust contracting under distributional uncertainty - LI, Jiangtao (Institutional Knowledge at Singapore Management University, 2023)
We study the design of contracts when the principal has limited statistical information about the output distributions induced by the agent’s actions. In the baseline model, we consider a principal who only knows the mean of the output distribution for each action, and show that it is optimal for the principal to adopt a monotone affine contract. We further show that the optimality of monotone affine contracts persists even if the principal has access to other information about the output distributions, such as the information that the output distribution induced by each action has full support.