Are value-added models good enough for teacher evaluations? Assessing commonly used models with simulated and actual data

Gary Henry (), Roderick Rose () and Doug Lauen ()
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Gary Henry: Vanderbilt University
Roderick Rose: University of North Carolina at Chapel Hill
Doug Lauen: University of North Carolina at Chapel Hill

Chapter 20 in Investigaciones de Economía de la Educación, 2014, vol. 9, pp 383-405 from Asociación de Economía de la Educación

Abstract: Teachers’ evaluations in many states include information about their students test score gains. In this paper, we describe the assumptions that are required for teacher value-added (TVA) estimates to be treated as unbiased causal effects. We compare commonly used TVA models on policy-relevant criteria using simulated data in which the assumptions of unconfounded assignment of students and teachers and no peer effects are violated and with actual data. The three-level hierarchical linear performs best when either assumption is violated. For year-to-year consistency, the dynamic ordinary least squares model performs best. A common policy goal – identifying the lowest performing quintile of teachers—can be done with reasonable accuracy but between 3.2 and 9.3 percent of all teachers are misclassified.

Keywords: value-added models; teacher policy; personnel evaluation (search for similar items in EconPapers)
JEL-codes: I28 J24 (search for similar items in EconPapers)
Date: 2014
ISBN: 978-84-942418-8-8
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