A New Method for Estimating Teacher Value-Added

76 Pages Posted: 5 May 2020 Last revised: 14 Jul 2022

See all articles by Michael Gilraine

Michael Gilraine

New York University (NYU) - Department of Economics

Jiaying Gu

University of Toronto

Robert McMillan

University of Toronto - Department of Economics

Date Written: May 2020

Abstract

This paper proposes a new methodology for estimating teacher value-added. Rather than imposing a normality assumption on unobserved teacher quality (as in the standard empirical Bayes approach), our nonparametric estimator permits the underlying distribution to be estimated directly and in a computationally feasible way. The resulting estimates fit the unobserved distribution very well regardless of the form it takes, as we show in Monte Carlo simulations. Implementing the nonparametric approach in practice using two separate large-scale administrative data sets, we find the estimated teacher value-added distributions depart from normality and differ from each other. To draw out the policy implications of our method, we first consider a widely-discussed policy to release teachers at the bottom of the value-added distribution, comparing predicted test score gains under our nonparametric approach with those using parametric empirical Bayes. Here the parametric method predicts similar policy gains in one data set while overestimating those in the other by a substantial margin. We also show the predicted gains from teacher retention policies can be underestimated significantly based on the parametric method. In general, the results highlight the benefit of our nonparametric empirical Bayes approach, given that the unobserved distribution of value-added is likely to be context-specific.

Suggested Citation

Gilraine, Michael and Gu, Jiaying and McMillan, Robert, A New Method for Estimating Teacher Value-Added (May 2020). NBER Working Paper No. w27094, Available at SSRN: https://ssrn.com/abstract=3592171

Michael Gilraine (Contact Author)

New York University (NYU) - Department of Economics ( email )

19 West 4th Street
New York, NY 10012
United States

Jiaying Gu

University of Toronto

Robert McMillan

University of Toronto - Department of Economics ( email )

150 St. George Street
Toronto, Ontario M5S 3G7
Canada
416-978-4190 (Phone)
416-978-6713 (Fax)

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