Aggregating Performance Measures in Multitask Principal-Agent Relationships

Abstract

It has been argued in the multitask agency literature that effort distortion can be mitigated by applying several performance measures in incentive contracts. This paper analyzes the efficient aggregation of multiple performance measures aimed at motivating non-distorted effort. It demonstrates that non-distorted effort can be induced by combining a sufficient quantity of informative performance measures. However, this is only optimal if the required aggregation concurrently maximizes the precision of the agent's performance evaluation. This paper further illustrates how the optimal performance evaluation is affected by individual agent's ability to perform relevant tasks.