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Does Student Sorting Invalidate Value-Added Models of Teacher Effectiveness? An Extended Analysis of the Rothstein Critique

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  • Cory Koedel

    ()
    (Department of Economics, University of Missouri)

  • Julian R. Betts

    ()
    (Department of Economics, University of California, San Diego and NBER)

Abstract

Value-added modeling continues to gain traction as a tool for measuring teacher performance. However, recent research questions the validity of the value-added approach by showing that it does not mitigate student-teacher sorting bias (its presumed primary benefit). Our study explores this critique in more detail. Although we find that estimated teacher effects from some value-added models are severely biased, we also show that a sufficiently complex value-added model that evaluates teachers over multiple years reduces the sorting bias problem to statistical insignificance. One implication of our findings is that data from the first year or two of classroom teaching for novice teachers may be insufficient to make reliable judgments about quality. Overall, our results suggest that in some cases value-added modeling will continue to provide useful information about the effectiveness of educational inputs. © 2011 Association for Education Finance and Policy

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Bibliographic Info

Article provided by MIT Press in its journal Education Finance and Policy.

Volume (Year): 6 (2011)
Issue (Month): 1 (January)
Pages: 18-42

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Handle: RePEc:tpr:edfpol:v:6:y:2011:i:1:p:18-42

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Keywords: student sorting; teacher effectiveness; value-added modeling;

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  1. Cory Koedel & Julian Betts, 2007. "Re-Examining the Role of Teacher Quality In the Educational Production Function," Working Papers 0708, Department of Economics, University of Missouri.
  2. Eric A. Hanushek & John F. Kain & Daniel M. O'Brien & Steven G. Rivkin, 2005. "The Market for Teacher Quality," NBER Working Papers 11154, National Bureau of Economic Research, Inc.
  3. Anderson, T. W. & Hsiao, Cheng., 1980. "Estimation of Dynamic Models with Error Components," Working Papers 336, California Institute of Technology, Division of the Humanities and Social Sciences.
  4. Brian A. Jacob & Lars Lefgren, 2005. "Principals as Agents: Subjective Performance Measurement in Education," NBER Working Papers 11463, National Bureau of Economic Research, Inc.
  5. Daniel F. McCaffrey & Tim R. Sass & J. R. Lockwood & Kata Mihaly, 2009. "The Intertemporal Variability of Teacher Effect Estimates," Education Finance and Policy, MIT Press, vol. 4(4), pages 572-606, October.
  6. Jonah E. Rockoff, 2004. "The Impact of Individual Teachers on Student Achievement: Evidence from Panel Data," American Economic Review, American Economic Association, vol. 94(2), pages 247-252, May.
  7. Charles T. Clotfelter & Helen F. Ladd & Jacob L. Vigdor, 2006. "Teacher-Student Matching and the Assessment of Teacher Effectiveness," Journal of Human Resources, University of Wisconsin Press, vol. 41(4).
  8. Eric A. Hanushek, 1996. "Measuring Investment in Education," Journal of Economic Perspectives, American Economic Association, vol. 10(4), pages 9-30, Fall.
  9. 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.
  10. Daniel Aaronson & Lisa Barrow & William Sander, 2002. "Teachers and student achievement in the Chicago public high schools," Working Paper Series WP-02-28, Federal Reserve Bank of Chicago.
  11. Thomas J. Kane & Douglas O. Staiger, 2008. "Estimating Teacher Impacts on Student Achievement: An Experimental Evaluation," NBER Working Papers 14607, National Bureau of Economic Research, Inc.
  12. Michael J. Podgursky & Matthew G. Springer, 2007. "Teacher performance pay: A review," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 26(4), pages 909-950.
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