Distortion and Risk in Optimal Incentive Contracts

Abstract

Performance measurement is an essential part of the design of any incentive system. The strength and value of incentives in organizations are strongly affected by the performance measures available. Yet, the characteristics of valuable performance measures have not been well explored in the agency literature. In this paper, I use a multitask model to develop a two-parameter characterization of performance measures and show how these two parameters-distortion and risk-affect the value and use of performance measures in incentive contracts. I show that many complex issues in the design of real-world incentive contracts can be fruitfully viewed as tradeoffs between these two features of performance measures. I also use this framework to analyze the provision of incentives in several specific environments, including R&D labs and nonprofit organizations.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 470 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.