Measuring Quality for Use in Incentive Schemes: The Case of “Shrinkage” Estimators - Nirav Mehta (ZBW – Leibniz Information Centre for Economics, 2018)
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 decisionmaker 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.
Keywords: J01; I21; I28; D81; 330; empirical contracts; teacher incentive schemes; teacher quality; economics of education