Performance Measurement in Agency Models

Abstract

This note explores how to evaluate an agent’s performance in standard incentive contracts. We show that the MPS criterion proposed by Kim (1995) becomes a tight condition for one performance measurement system to be more informative than another, as long as the first-order approach can be justified. In the one-signal case obeying the monotone likelihood ratio property, the MPS criterion is equivalent to the way of ordering signals developed by Lehmann (1988), establishing a link to statistical decision theory. Our results demonstrate that depending on the agent’s potential deviations, ideal performance measures can be different.