Value by Design: Performance Evaluation and Learning from Wages

Franz Ostrizek

Working Papers from HAL

Abstract: We study a dynamic principal-agent setting in which both sides learn about the importance of effort. The quality of the agent's output is not observed directly. Instead, the principal jointly designs an evaluation technology and a wage schedule. More precise performance evaluation reduces current agency costs but promotes learning, which can increase future agency costs. As a result, the optimal evaluation technology is noisy. Performance information that solely pertains to effort is revealed, while the principal optimally conceals information about the agent's ability. The optimal evaluation features a censorship pattern with a base wage and tailored bonuses/penalties when the threshold is exceeded. With binary output, it is both imprecise and tough if effort and ability are strong complements: a bad performance is always sanctioned, but a good one is not always recognized.

Date: 2025-02-09
Note: View the original document on HAL open archive server: https://sciencespo.hal.science/hal-04938068v1
References: Add references at CitEc
Citations:

Downloads: (external link)
https://sciencespo.hal.science/hal-04938068v1/document (application/pdf)

Related works:
Working Paper: Value by Design: Performance Evaluation and Learning from Wages (2025)
Working Paper: Value by Design: Performance Evaluation and Learning from Wages (2025)
Working Paper: Vague by Design: Performance Evaluation and Learning From Wages (2022)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:wpaper:hal-04938068

Access Statistics for this paper

More papers in Working Papers from HAL
Bibliographic data for series maintained by CCSD ().