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An Evaluation of Empirical Bayes’s Estimation of Value-Added Teacher Performance Measures

Author

Listed:
  • Cassandra M. Guarino

    (Indiana University)

  • Michelle Maxfield

    (Amazon)

  • Mark D. Reckase

    (Michigan State University)

  • Paul N. Thompson

    (Oregon State University)

  • Jeffrey M. Wooldridge

    (Michigan State University)

Abstract
Empirical Bayes’s (EB) estimation has become a popular procedure used to calculate teacher value added, often as a way to make imprecise estimates more reliable. In this article, we review the theory of EB estimation and use simulated and real student achievement data to study the ability of EB estimators to properly rank teachers. We compare the performance of EB estimators with that of other widely used value-added estimators under different teacher assignment scenarios. We find that, although EB estimators generally perform well under random assignment (RA) of teachers to classrooms, their performance suffers under nonrandom teacher assignment. Under non-RA, estimators that explicitly (if imperfectly) control for the teacher assignment mechanism perform the best out of all the estimators we examine. We also find that shrinking the estimates, as in EB estimation, does not itself substantially boost performance.

Suggested Citation

  • Cassandra M. Guarino & Michelle Maxfield & Mark D. Reckase & Paul N. Thompson & Jeffrey M. Wooldridge, 2015. "An Evaluation of Empirical Bayes’s Estimation of Value-Added Teacher Performance Measures," Journal of Educational and Behavioral Statistics, , vol. 40(2), pages 190-222, April.
    • Handle: RePEc:sae:jedbes:v:40:y:2015:i:2:p:190-222
    DOI: 10.3102/1076998615574771
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    References listed on IDEAS

    as
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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. Naven, Matthew, 2019. "Human-Capital Formation During Childhood and Adolescence: Evidence from School Quality and Postsecondary Success in California," MPRA Paper 97716, University Library of Munich, Germany.
    3. Nirav Mehta, 2019. "Measuring quality for use in incentive schemes: The case of “shrinkage” estimators," Quantitative Economics, Econometric Society, vol. 10(4), pages 1537-1577, November.
    4. Schiltz, Fritz & Sestito, Paolo & Agasisti, Tommaso & De Witte, Kristof, 2018. "The added value of more accurate predictions for school rankings," Economics of Education Review, Elsevier, vol. 67(C), pages 207-215.
    5. Anna Godøy & Venke F. Haaland & Ingrid Huitfeldt & Mark Votruba, 2024. "Hospital Queues, Patient Health, and Labor Supply," American Economic Journal: Economic Policy, American Economic Association, vol. 16(2), pages 150-181, May.
    6. Brehm, Margaret & Imberman, Scott A. & Lovenheim, Michael F., 2017. "Achievement effects of individual performance incentives in a teacher merit pay tournament," Labour Economics, Elsevier, vol. 44(C), pages 133-150.
    7. Guarino, Cassandra M. & Reckase, Mark D. & Stacy, Brian & Wooldridge, Jeffrey M., 2014. "A Comparison of Growth Percentile and Value-Added Models of Teacher Performance," IZA Discussion Papers 7973, Institute of Labor Economics (IZA).
    8. Eric Parsons & Cory Koedel & Li Tan, 2019. "Accounting for Student Disadvantage in Value-Added Models," Journal of Educational and Behavioral Statistics, , vol. 44(2), pages 144-179, April.
    9. Steven Dieterle & Cassandra M. Guarino & Mark D. Reckase & Jeffrey M. Wooldridge, 2015. "How do Principals Assign Students to Teachers? Finding Evidence in Administrative Data and the Implications for Value Added," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 34(1), pages 32-58, January.
    10. David Blazar, 2018. "Validating Teacher Effects on Students’ Attitudes and Behaviors: Evidence from Random Assignment of Teachers to Students," Education Finance and Policy, MIT Press, vol. 13(3), pages 281-309, Summer.
    11. Nirav Mehta, 2019. "Measuring quality for use in incentive schemes: The case of “shrinkage” estimators," Quantitative Economics, Econometric Society, vol. 10(4), pages 1537-1577, November.
    12. Mariesa Herrmann & Elias Walsh & Eric Isenberg & Alexandra Resch, 2013. "Shrinkage of Value-Added Estimates and Characteristics of Students with Hard-to-Predict Achievement Levels," Mathematica Policy Research Reports 2b140369be0242ac83eeb5b0a, Mathematica Policy Research.
    13. 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.
    14. Michael Gilraine & Jiaying Gu & Robert McMillan, 2020. "A New Method for Estimating Teacher Value-Added," NBER Working Papers 27094, National Bureau of Economic Research, Inc.
    15. David Blazar & Blake Heller & Thomas J. Kane & Morgan Polikoff & Douglas O. Staiger & Scott Carrell & Dan Goldhaber & Douglas N. Harris & Rachel Hitch & Kristian L. Holden & Michal Kurlaender, 2020. "Curriculum Reform in The Common Core Era: Evaluating Elementary Math Textbooks Across Six U.S. States," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(4), pages 966-1019, September.
    16. Bartanen, Brendan & Husain, Aliza N., 2022. "Connected networks in principal value-added models," Economics of Education Review, Elsevier, vol. 90(C).
    17. Michael Gilraine & Jiaying Gu & Robert McMillan, 2021. "A Nonparametric Method for Estimating Teacher Value-Added," Working Papers tecipa-689, University of Toronto, Department of Economics.
    18. Nirav Mehta, 2014. "Targeting the Wrong Teachers: Estimating Teacher Quality for Use in Accountability Regimes," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20143, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
    19. Vosters, Kelly N. & Guarino, Cassandra M. & Wooldridge, Jeffrey M., 2018. "Understanding and evaluating the SAS® EVAAS® Univariate Response Model (URM) for measuring teacher effectiveness," Economics of Education Review, Elsevier, vol. 66(C), pages 191-205.
    20. Backes, Ben & Cowan, James & Goldhaber, Dan & Koedel, Cory & Miller, Luke C. & Xu, Zeyu, 2018. "The common core conundrum: To what extent should we worry that changes to assessments will affect test-based measures of teacher performance?," Economics of Education Review, Elsevier, vol. 62(C), pages 48-65.
    21. Sarah S. Stith, 2018. "Organizational learning-by-doing in liver transplantation," International Journal of Health Economics and Management, Springer, vol. 18(1), pages 25-45, March.

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