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Ranking Teachers when Teacher Value-Added is Heterogeneous Across Students

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  • Stacy, Brian

Abstract

The typical measure used by researchers and school administrators to evaluate teachers is based on how the students' achievement increases after being exposed to the teacher, or based on the teacher's "value-added''. When teacher value-added is heterogeneous across her students, the typically used measure reflects differences in the average value-added the teacher provides. However, researchers, administrators, and parents may care not just about the average value-added, but also its dispersion. In this paper, I examine the robustness of typical teacher quality measures to alternate ranking systems factoring in the variance of value-added. Encouragingly, ranking systems factoring in the variance produce similar rankings as the ranking system based only on the mean. I also examine whether classroom characteristics and teacher experience affect a teacher's value-added variance and find that they explain little of the variation in value-added variances.

Suggested Citation

  • Stacy, Brian, 2014. "Ranking Teachers when Teacher Value-Added is Heterogeneous Across Students," EconStor Preprints 104743, ZBW - Leibniz Information Centre for Economics.
    • Handle: RePEc:zbw:esprep:104743
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    References listed on IDEAS

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    1. Steven G. Rivkin & Eric A. Hanushek & John F. Kain, 2005. "Teachers, Schools, and Academic Achievement," Econometrica, Econometric Society, vol. 73(2), pages 417-458, March.
    2. Harris, Douglas N. & Sass, Tim R., 2011. "Teacher training, teacher quality and student achievement," Journal of Public Economics, Elsevier, vol. 95(7-8), pages 798-812, August.
    3. Jesse Rothstein, 2009. "Student Sorting and Bias in Value-Added Estimation: Selection on Observables and Unobservables," Education Finance and Policy, MIT Press, vol. 4(4), pages 537-571, October.
    4. 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.
    5. 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.
    6. 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(1), pages 95-135.
    7. Raj Chetty & John N. Friedman & Jonah E. Rockoff, 2014. "Measuring the Impacts of Teachers I: Evaluating Bias in Teacher Value-Added Estimates," American Economic Review, American Economic Association, vol. 104(9), pages 2593-2632, September.
    8. Dan Goldhaber & Michael Hansen, 2013. "Is it Just a Bad Class? Assessing the Long-term Stability of Estimated Teacher Performance," Economica, London School of Economics and Political Science, vol. 80(319), pages 589-612, July.
    9. Imberman, Scott A. & Lovenheim, Michael F., 2016. "Does the market value value-added? Evidence from housing prices after a public release of school and teacher value-added," Journal of Urban Economics, Elsevier, vol. 91(C), pages 104-121.
    10. Dan Goldhaber & Duncan Dunbar Chaplin, "undated". "Assessing the "Rothstein Falsification Test": Does It Really Show Teacher Value-Added Models Are Biased?," Mathematica Policy Research Reports 93f34c834817419a9efccecdf, Mathematica Policy Research.
    11. 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.
    12. Thomas S. Dee, 2004. "Teachers, Race, and Student Achievement in a Randomized Experiment," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 195-210, February.
    13. Harvey, A C, 1976. "Estimating Regression Models with Multiplicative Heteroscedasticity," Econometrica, Econometric Society, vol. 44(3), pages 461-465, May.
    14. Raj Chetty & John N. Friedman & Jonah E. Rockoff, 2014. "Measuring the Impacts of Teachers II: Teacher Value-Added and Student Outcomes in Adulthood," American Economic Review, American Economic Association, vol. 104(9), pages 2633-2679, September.
    15. 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.
    16. Derek Neal & Diane Whitmore Schanzenbach, 2010. "Left Behind by Design: Proficiency Counts and Test-Based Accountability," The Review of Economics and Statistics, MIT Press, vol. 92(2), pages 263-283, May.
    17. J. R. Lockwood & Daniel F. McCaffrey, 2009. "Exploring Student-Teacher Interactions in Longitudinal Achievement Data," Education Finance and Policy, MIT Press, vol. 4(4), pages 439-467, October.
    18. 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.
    19. Condie, Scott & Lefgren, Lars & Sims, David, 2014. "Teacher heterogeneity, value-added and education policy," Economics of Education Review, Elsevier, vol. 40(C), pages 76-92.
    20. 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.
    21. repec:mpr:mprres:7333 is not listed on IDEAS
    22. Donald Boyd & Pam Grossman & Hamilton Lankford & Susanna Loeb & James Wyckoff, 2008. "Who Leaves? Teacher Attrition and Student Achievement," NBER Working Papers 14022, National Bureau of Economic Research, Inc.
    23. 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.
    24. 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.
    25. 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.
    26. repec:mpr:mprres:7330 is not listed on IDEAS
    27. Winters, Marcus A. & Dixon, Bruce L. & Greene, Jay P., 2012. "Observed characteristics and teacher quality: Impacts of sample selection on a value added model," Economics of Education Review, Elsevier, vol. 31(1), pages 19-32.
    28. Wiswall, Matthew, 2013. "The dynamics of teacher quality," Journal of Public Economics, Elsevier, vol. 100(C), pages 61-78.
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    More about this item

    Keywords

    teacher value-added; heterogeneity; value-added variance; teacher quality;
    All these keywords.

    JEL classification:

    • I0 - Health, Education, and Welfare - - General
    • I20 - Health, Education, and Welfare - - Education - - - General
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
    • J08 - Labor and Demographic Economics - - General - - - Labor Economics Policies
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J44 - Labor and Demographic Economics - - Particular Labor Markets - - - Professional Labor Markets and Occupations
    • J45 - Labor and Demographic Economics - - Particular Labor Markets - - - Public Sector Labor Markets

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