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A Comparison of Growth Percentile and Value-Added Models of Teacher Performance

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Author Info

  • Guarino, Cassandra

    ()
    (Indiana University)

  • Reckase, Mark D.

    ()
    (Michigan State University)

  • Stacy, Brian

    ()
    (Michigan State University)

  • Wooldridge, Jeffrey M.

    ()
    (Michigan State University)

Abstract

School districts and state departments of education frequently must choose between a variety of methods to estimating teacher quality. This paper examines under what circumstances the decision between estimators of teacher quality is important. We examine estimates derived from growth percentile measures and estimates derived from commonly used value-added estimators. Using simulated data, we examine how well the estimators can rank teachers and avoid misclassification errors under a variety of assignment scenarios of teachers to students. We find that growth percentile measures perform worse than value-added measures that control for prior year student test scores and control for teacher fixed effects when assignment of students to teachers is nonrandom. In addition, using actual data from a large diverse anonymous state, we find evidence that growth percentile measures are less correlated with value-added measures with teacher fixed effects when there is evidence of nonrandom grouping of students in schools. This evidence suggests that the choice between estimators is most consequential under nonrandom assignment of teachers to students, and that value-added measures controlling for teacher fixed effects may be better suited to estimating teacher quality in this case.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 7973.

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Length: 42 pages
Date of creation: Feb 2014
Date of revision:
Handle: RePEc:iza:izadps:dp7973

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Related research

Keywords: teacher labor markets; teacher value-added; teacher quality;

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  1. Gadi Barlevy & Derek Neal, 2011. "Pay for Percentile," NBER Working Papers 17194, National Bureau of Economic Research, Inc.
  2. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
  3. Daniel Aaronson & Lisa Barrow & William Sander, 2007. "Teachers and Student Achievement in the Chicago Public High Schools," Journal of Labor Economics, University of Chicago Press, vol. 25, pages 95-135.
  4. Roland G. Fryer, Jr & Steven D. Levitt & John List & Sally Sadoff, 2012. "Enhancing the Efficacy of Teacher Incentives through Loss Aversion: A Field Experiment," NBER Working Papers 18237, National Bureau of Economic Research, Inc.
  5. Thomas J. Kane & Douglas O. Staiger, 2002. "The Promise and Pitfalls of Using Imprecise School Accountability Measures," Journal of Economic Perspectives, American Economic Association, vol. 16(4), pages 91-114, Fall.
  6. Dieterle, Steven G. & Guarino, Cassandra & Reckase, Mark D. & Wooldridge, Jeffrey M., 2012. "How do Principals Assign Students to Teachers? Finding Evidence in Administrative Data and the Implications for Value-added," IZA Discussion Papers 7112, Institute for the Study of Labor (IZA).
  7. Brian A. Jacob & Lars Lefgren, 2008. "Can Principals Identify Effective Teachers? Evidence on Subjective Performance Evaluation in Education," Journal of Labor Economics, University of Chicago Press, vol. 26, pages 101-136.
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