A Nonparametric Approach for Studying Teacher Impacts

Mike Gilraine, Jiaying Gu and Robert McMillan

Working Papers from University of Toronto, Department of Economics

Abstract: We propose a nonparametric approach for studying the impacts of teachers, built around the distribution of unobserved teacher value-added. Rather than assuming this distribution is normal (as standard), we show it is nonparametrically identified and can be feasibly estimated. The distribution is central to a new nonparametric estimator for individual teacher value-added that we present, and allows us to compute new metrics for assessing teacher-related policies. Simulations indicate our nonparametric approach performs very well, even in moderately-sized samples. We also show applying our approach in practice can make a significant difference to teacher-relevant policy calculations, compared with widely-used parametric estimates.

Keywords: Teacher Impacts; Teacher Value-Added; Value-Added Distribution; Nonparametric Estimation; Empirical Bayes; Education Policy; Teacher Release Policy; False Discovery Rate (search for similar items in EconPapers)
JEL-codes: C11 H75 I21 J24 (search for similar items in EconPapers)
Pages: Unknown pages
Date: 2022-01-06
New Economics Papers: this item is included in nep-ecm and nep-ure
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