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A Framework for Using Value-Added in Regressions

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  • Antoine Deeb

Abstract

As increasingly popular metrics of worker and institutional quality, estimated value-added (VA) measures are now widely used as dependent or explanatory variables in regressions. For example, VA is used as an explanatory variable when examining the relationship between teacher VA and students' long-run outcomes. Due to the multi-step nature of VA estimation, the standard errors (SEs) researchers routinely use when including VA measures in OLS regressions are incorrect. In this paper, I show that the assumptions underpinning VA models naturally lead to a generalized method of moments (GMM) framework. Using this insight, I construct correct SEs' for regressions that use VA as an explanatory variable and for regressions where VA is the outcome. In addition, I identify the causes of incorrect SEs when using OLS, discuss the need to adjust SEs under different sets of assumptions, and propose a more efficient estimator for using VA as an explanatory variable. Finally, I illustrate my results using data from North Carolina, and show that correcting SEs results in an increase that is larger than the impact of clustering SEs.

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  • Antoine Deeb, 2021. "A Framework for Using Value-Added in Regressions," Papers 2109.01741, arXiv.org, revised Oct 2021.
    • Handle: RePEc:arx:papers:2109.01741
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    References listed on IDEAS

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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Adrian Pagan, 1986. "Two Stage and Related Estimators and Their Applications," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 517-538.
    3. Brian A. Jacob & Lars Lefgren & David P. Sims, 2010. "The Persistence of Teacher-Induced Learning," Journal of Human Resources, University of Wisconsin Press, vol. 45(4), pages 915-943.
    4. 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.
    5. Joshua D. Angrist & Peter D. Hull & Parag A. Pathak & Christopher R. Walters, 2017. "Leveraging Lotteries for School Value-Added: Testing and Estimation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(2), pages 871-919.
    6. Serena Canaan & Antoine Deeb & Pierre Mouganie, 2022. "Adviser Value Added and Student Outcomes: Evidence from Randomly Assigned College Advisers," American Economic Journal: Economic Policy, American Economic Association, vol. 14(4), pages 151-191, November.
    7. Chamberlain, Gary, 1987. "Asymptotic efficiency in estimation with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 34(3), pages 305-334, March.
    8. Newey, Whitney K., 1984. "A method of moments interpretation of sequential estimators," Economics Letters, Elsevier, vol. 14(2-3), pages 201-206.
    9. Marianne Bertrand & Antoinette Schoar, 2003. "Managing with Style: The Effect of Managers on Firm Policies," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1169-1208.
    10. Peter Arcidiacono & Josh Kinsler & Joseph Price, 2017. "Productivity Spillovers in Team Production: Evidence from Professional Basketball," Journal of Labor Economics, University of Chicago Press, vol. 35(1), pages 191-225.
    11. 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.
    12. C. Kirabo Jackson, 2018. "What Do Test Scores Miss? The Importance of Teacher Effects on Non–Test Score Outcomes," Journal of Political Economy, University of Chicago Press, vol. 126(5), pages 2072-2107.
    13. Edward P. Lazear & Kathryn L. Shaw & Christopher T. Stanton, 2015. "The Value of Bosses," Journal of Labor Economics, University of Chicago Press, vol. 33(4), pages 823-861.
    14. Jing Liu & Susanna Loeb, 2021. "Engaging Teachers: Measuring the Impact of Teachers on Student Attendance in Secondary School," Journal of Human Resources, University of Wisconsin Press, vol. 56(2), pages 343-379.
    15. 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.
    16. Isaac M. Opper, 2019. "Does Helping John Help Sue? Evidence of Spillovers in Education," American Economic Review, American Economic Association, vol. 109(3), pages 1080-1115, March.
    17. Janet Currie & Jonathan Zhang, 2021. "Doing More with Less: Predicting Primary Care Provider Effectiveness," NBER Working Papers 28929, National Bureau of Economic Research, Inc.
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