MICRO/THEORY: Information-trigger contracts; Professor Ke Rongzhu (Zhejiang University)

Abstract

We study moral-hazard problems where principal and agent are risk neutral with bounded agent compensation. We show optimality of information-trigger (IT) contracts, where the agent receives a bonus when the likelihood ratio of output signals between two actions exceeds a trigger value and otherwise receives the minimum. The likelihood ratio maps multi-dimensional outputs into a single-dimensional space where triggers correspond to a simple bonus structure. In the binary-action case, we reformulate the problem as a covariance (between likelihood ratio and payment) maximization problem to establish the optimality of IT contracts. For more actions, we leverage the binary-action result by showing an equivalence to a problem where the order of optimization is swapped. Under the monotone likelihood-ratio property, we show optimality of quota-bonus contracts directly from the underlying IT structure. Additional assumptions, like the first-order approach, are not needed. And we extends the results when MLRP does not hold.