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A Nonparametric Method for Estimating Teacher Value-Added

Author

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  • Michael Gilraine
  • Jiaying Gu
  • Robert McMillan

Abstract

This paper proposes a computationally feasible nonparametric methodology for estimating teacher value-added. Our estimator, drawing on Robbins (1956), permits the unobserved teacher value-added distribution to be estimated directly, rather than assuming normality as is standard. Simulations indicate the estimator performs very well regardless of the true distribution, even in moderately-sized samples. Implementing our method in practice using two large-scale administrative datasets, the estimated teacher value-added distributions depart from normality and differ from each other. Further, compared with widely-used parametric estimates, we show our nonparametric estimates can make a significant difference to teacher-related policy calculations, in both short and longer terms.

Suggested Citation

  • Michael Gilraine & Jiaying Gu & Robert McMillan, 2021. "A Nonparametric Method for Estimating Teacher Value-Added," Working Papers tecipa-689, University of Toronto, Department of Economics.
    • Handle: RePEc:tor:tecipa:tecipa-689
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    References listed on IDEAS

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    More about this item

    Keywords

    Teacher Value-Added; Nonparametric Empirical Bayes; Education Policy; Teacher Release Policy;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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