A Nonparametric Method for Estimating Teacher Value-Added

Michael Gilraine, Jiaying Gu and Robert McMillan

Working Papers from University of Toronto, Department of Economics

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.

Keywords: Teacher Value-Added; Nonparametric Empirical Bayes; Education Policy; Teacher Release Policy (search for similar items in EconPapers)
JEL-codes: C11 H75 I21 J24 (search for similar items in EconPapers)
Pages: Unknown pages
Date: 2021-02-13
New Economics Papers: this item is included in nep-ecm, nep-lma and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.economics.utoronto.ca/public/workingPapers/tecipa-689.pdf Main Text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tor:tecipa:tecipa-689

Access Statistics for this paper

More papers in Working Papers from University of Toronto, Department of Economics 150 St. George Street, Toronto, Ontario.
Bibliographic data for series maintained by RePEc Maintainer ().