Measuring quality for use in incentive schemes: The case of “shrinkage” estimators
Quantitative Economics, 2019, vol. 10, issue 4, 1537-1577
Researchers commonly “shrink” raw quality measures based on statistical criteria. This paper studies when and how this transformation's statistical properties would confer economic benefits to a utility‐maximizing decision‐maker across common asymmetric information environments. I develop the results for an application measuring teacher quality. The presence of a systematic relationship between teacher quality and class size could cause the data transformation to do either worse or better than the untransformed data. I use data from Los Angeles to confirm the presence of such a relationship and show that the simpler raw measure would outperform the one most commonly used in teacher incentive schemes.
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Working Paper: Measuring Quality for Use in Incentive Schemes: The Case of “Shrinkage” Estimators (2018)
Working Paper: Measuring Quality for Use in Incentive Schemes: The Case of "Shrinkage" Estimators (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:wly:quante:v:10:y:2019:i:4:p:1537-1577
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