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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.
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Citations
Cited by
Teacher Quality in Educational Production: Tracking, Decay, and Student Achievement*
Rothstein, J. (2010) · Quarterly Journal of Economics · doi:10.1162/qjec.2010.125.1.175 · Cited by 735
Hadfield-Menell, D., Dragan, A., Abbeel, P., & Russell, S. (2017) · Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2017/32 · Cited by 119
Hadfield-Menell, D., Dragan, A., Abbeel, P., & Russell, S. (2016) · arXiv · doi:10.48550/arxiv.1611.08219 · Cited by 119
Formal and Informal Contracting: Theory and Evidence
Gil, R., & Zanarone, G. (2017) · Annual Review of Law and Social Science · doi:10.1146/annurev-lawsocsci-110316-113413 · Cited by 56
Teacher Quality Policy When Supply Matters
Rothstein, J. (2012) · doi:10.3386/w18419 · Cited by 20
Metadata
- Authors
- Baker, G.
- Venue
- The Journal of Human Resources
- Publisher
- JSTOR
- Published
- 2002
- Volume
- 37
- Issue
- 4
- Pages
- 728
- ISSN
- 0022-166X (ISSN-L)
- OpenAlex
- W1534895963
- Cited by
- 466
- References
- 0
- FWCI
- 28.44
- Type
- journal article
- Language
- en
- Open access
- closed
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