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Can Value-Added Measures of Teacher Performance Be Trusted?

  • Guarino, Cassandra M.


    (University of California, Riverside)

  • Reckase, Mark D.


    (Michigan State University)

  • Wooldridge, Jeffrey M.


    (Michigan State University)

We investigate whether commonly used value-added estimation strategies can produce accurate estimates of teacher effects. We estimate teacher effects in simulated student achievement data sets that mimic plausible types of student grouping and teacher assignment scenarios. No one method accurately captures true teacher effects in all scenarios, and the potential for misclassifying teachers as high- or low-performing can be substantial. Misspecifying dynamic relationships can exacerbate estimation problems. However, some estimators are more robust across scenarios and better suited to estimating teacher effects than others.

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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 6602.

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Length: 42 pages
Date of creation: May 2012
Date of revision:
Publication status: published in: Education Finance and Policy, 2015, 10 (1), 117-156
Handle: RePEc:iza:izadps:dp6602
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  1. Buddin, Richard, 2011. "Measuring teacher and school effectiveness at improving student achievement in Los Angeles elementary schools," MPRA Paper 31963, University Library of Munich, Germany.
  2. Cory Koedel & Julian R. Betts, 2011. "Does Student Sorting Invalidate Value-Added Models of Teacher Effectiveness? An Extended Analysis of the Rothstein Critique," Education Finance and Policy, MIT Press, vol. 6(1), pages 18-42, January.
  3. Josh Kinsler, 2012. "Assessing Rothstein's critique of teacher value‚Äźadded models," Quantitative Economics, Econometric Society, vol. 3(2), pages 333-362, 07.
  4. Richard Blundell & Steve Bond, 1995. "Initial conditions and moment restrictions in dynamic panel data models," IFS Working Papers W95/17, Institute for Fiscal Studies.
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  6. Jeffrey M. Wooldridge, 2001. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262232197, December.
  7. Raj Chetty & John N. Friedman & Jonah E. Rockoff, 2011. "The Long-Term Impacts of Teachers: Teacher Value-Added and Student Outcomes in Adulthood," NBER Working Papers 17699, National Bureau of Economic Research, Inc.
  8. Petra E. Todd & Kenneth I. Wolpin, 2003. "On The Specification and Estimation of The Production Function for Cognitive Achievement," Economic Journal, Royal Economic Society, vol. 113(485), pages F3-F33, February.
  9. Andrabi, Tahir & Das, Jishnu & Khwaja, Asim Ijaz & Zajonc, Tristan, 2009. "Do value-added estimates add value ? accounting for learning dynamics," Policy Research Working Paper Series 5066, The World Bank.
  10. Hanushek, Eric A, 1986. "The Economics of Schooling: Production and Efficiency in Public Schools," Journal of Economic Literature, American Economic Association, vol. 24(3), pages 1141-77, September.
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  12. Eric A. Hanushek, 1979. "Conceptual and Empirical Issues in the Estimation of Educational Production Functions," Journal of Human Resources, University of Wisconsin Press, vol. 14(3), pages 351-388.
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  14. 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.
  15. Sass, Tim R. & Semykina, Anastasia & Harris, Douglas N., 2014. "Value-added models and the measurement of teacher productivity," Economics of Education Review, Elsevier, vol. 38(C), pages 9-23.
  16. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
  17. 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.
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