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Evaluating Specification Tests in the Context of Value-Added Estimation

Author

Listed:
  • Guarino, Cassandra M.

    (University of California, Riverside)

  • Reckase, Mark D.

    (Michigan State University)

  • Stacy, Brian

    (World Bank)

  • Wooldridge, Jeffrey M.

    (Michigan State University)

Abstract

We study the properties of two specification tests that have been applied to a variety of estimators in the context of value-added measures (VAMs) of teacher and school quality: the Hausman test for choosing between random and fixed effects and a test for feedback (sometimes called a "falsification test"). We discuss theoretical properties of the tests to serve as background. An extensive simulation study provides important further insight to the VAM setting. Unfortunately, while both the Hausman and feedback tests have good power for detecting the kinds of nonrandom assignment that can invalidate VAM estimates, they also reject in situations where estimated VAMs perform very well. Consequently, the tests must be used with caution when student tracking is used to form classrooms.

Suggested Citation

  • Guarino, Cassandra M. & Reckase, Mark D. & Stacy, Brian & Wooldridge, Jeffrey M., 2014. "Evaluating Specification Tests in the Context of Value-Added Estimation," IZA Discussion Papers 7974, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp7974
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    References listed on IDEAS

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    1. Jesse Rothstein, 2010. "Teacher Quality in Educational Production: Tracking, Decay, and Student Achievement," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(1), pages 175-214.
    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. Cassandra M. Guarino & Mark D. Reckase & Jeffrey M. Woolrdige, 2014. "Can Value-Added Measures of Teacher Performance Be Trusted?," Education Finance and Policy, MIT Press, vol. 10(1), pages 117-156, November.
    4. McClain, Katherine T. & Wooldridge, Jeffrey M., 1995. "A simple test for the consistency of dynamic linear regression in rational distributed lag models," Economics Letters, Elsevier, vol. 48(3-4), pages 235-240, June.
    5. Josh Kinsler, 2012. "Assessing Rothstein's critique of teacher value‐added models," Quantitative Economics, Econometric Society, vol. 3(2), pages 333-362, July.
    6. 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 3-33, February.
    7. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    8. 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.
    9. Wooldridge, Jeffrey M., 1990. "A Unified Approach to Robust, Regression-Based Specification Tests," Econometric Theory, Cambridge University Press, vol. 6(1), pages 17-43, March.
    10. Guggenberger, Patrik, 2010. "The impact of a Hausman pretest on the size of a hypothesis test: The panel data case," Journal of Econometrics, Elsevier, vol. 156(2), pages 337-343, June.
    11. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
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    Citations

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    Cited by:

    1. Stacy, Brian & Guarino, Cassandra & Wooldridge, Jeffrey, 2018. "Does the precision and stability of value-added estimates of teacher performance depend on the types of students they serve?," Economics of Education Review, Elsevier, vol. 64(C), pages 50-74.
    2. Ost, Ben & Schiman, Jeffrey C., 2017. "Workload and teacher absence," Economics of Education Review, Elsevier, vol. 57(C), pages 20-30.
    3. Gershenson, Seth, 2016. "Should Value-Added Models Control for Student Absences?," IZA Discussion Papers 9978, Institute of Labor Economics (IZA).
    4. Seth Gershenson & Diane Whitmore Schanzenbach, 2016. "Linking Teacher Quality, Student Attendance, and Student Achievement," Education Finance and Policy, MIT Press, vol. 11(2), pages 125-149, Spring.

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    More about this item

    Keywords

    teacher labor markets; teacher quality; value-added;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • I20 - Health, Education, and Welfare - - Education - - - General
    • J45 - Labor and Demographic Economics - - Particular Labor Markets - - - Public Sector Labor Markets
    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General

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