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Empirical Bayes Methods in Labor Economics

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  • Christopher Walters

    (UC Berkeley)

Abstract

Labor economists increasingly work in empirical contexts with large numbers of unit-specific parameters. These settings include a growing number of value-added studies measuring causal effects of individual units like firms, managers, neighborhoods, teachers, schools, doctors, hospitals, police officers, and judges. Empirical Bayes (EB) methods provide a powerful toolkit for value-added analysis. The EB approach leverages distributional information from the full population of units to refine predictions of value-added for each individual, leading to improved estimators and decision rules. This chapter offers an overview of EB methods in labor economics, focusing on properties that make EB useful for value-added studies and practical guidance for EB implementation. Applications to school value-added in Boston and employer-level discrimination in the US labor market illustrate the EB toolkit in action.

Suggested Citation

  • Christopher Walters, 2024. "Empirical Bayes Methods in Labor Economics," RF Berlin - CReAM Discussion Paper Series 2422, Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM).
    • Handle: RePEc:crm:wpaper:2422
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    References listed on IDEAS

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    1. Dan Goldhaber & Betheny Gross & Daniel Player, 2011. "Teacher career paths, teacher quality, and persistence in the classroom: Are public schools keeping their best?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 30(1), pages 57-87, December.
    2. Bonhomme, Stéphane & Denis, Angela, 2024. "Estimating heterogeneous effects: Applications to labor economics," Labour Economics, Elsevier, vol. 91(C).
    3. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2019. "A Distributional Framework for Matched Employer Employee Data," Econometrica, Econometric Society, vol. 87(3), pages 699-739, May.
    4. Evan K. Rose & Jonathan T. Schellenberg & Yotam Shem-Tov, 2022. "The Effects of Teacher Quality on Adult Criminal Justice Contact," NBER Working Papers 30274, National Bureau of Economic Research, Inc.
    5. Marianne Bertrand & Sendhil Mullainathan, 2004. "Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination," American Economic Review, American Economic Association, vol. 94(4), pages 991-1013, September.
    6. Stacy Berg Dale & Alan B. Krueger, 2002. "Estimating the Payoff to Attending a More Selective College: An Application of Selection on Observables and Unobservables," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1491-1527.
    7. Raj Chetty & John N. Friedman & Nathaniel Hendren & Maggie R. Jones & Sonya R. Porter, 2018. "The Opportunity Atlas: Mapping the Childhood Roots of Social Mobility," Working Papers 18-42, Center for Economic Studies, U.S. Census Bureau.
    8. Patrick Kline & Evan K. Rose & Christopher R. Walters, 2024. "A Discrimination Report Card," American Economic Review, American Economic Association, vol. 114(8), pages 2472-2525, August.
    9. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
    10. David Card & Jörg Heining & Patrick Kline, 2013. "Workplace Heterogeneity and the Rise of West German Wage Inequality," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(3), pages 967-1015.
    11. Felipe Goncalves & Steven Mello, 2021. "A Few Bad Apples? Racial Bias in Policing," American Economic Review, American Economic Association, vol. 111(5), pages 1406-1441, May.
    12. Manski, Charles F., 2000. "Identification problems and decisions under ambiguity: Empirical analysis of treatment response and normative analysis of treatment choice," Journal of Econometrics, Elsevier, vol. 95(2), pages 415-442, April.
    13. Bonhomme, Stéphane & Denis, Angela, 2024. "Estimating heterogeneous effects: Applications to labor economics," Labour Economics, Elsevier, vol. 91(C).
    14. David Card & Ana Rute Cardoso & Patrick Kline, 2016. "Bargaining, Sorting, and the Gender Wage Gap: Quantifying the Impact of Firms on the Relative Pay of Women," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(2), pages 633-686.
    15. MacKinnon, James G. & White, Halbert, 1985. "Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties," Journal of Econometrics, Elsevier, vol. 29(3), pages 305-325, September.
    16. Roger Koenker & Ivan Mizera, 2014. "Convex Optimization, Shape Constraints, Compound Decisions, and Empirical Bayes Rules," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 674-685, June.
    17. Alberto Abadie & Maximilian Kasy, 2019. "Choosing Among Regularized Estimators in Empirical Economics: The Risk of Machine Learning," The Review of Economics and Statistics, MIT Press, vol. 101(5), pages 743-762, December.
    18. Jason Abaluck & Mauricio Caceres Bravo & Peter Hull: & Amanda Starc, 2021. "Mortality Effects and Choice Across Private Health Insurance Plans," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(3), pages 1557-1610.
    19. Atila Abdulkadiroğlu & Joshua D. Angrist & Susan M. Dynarski & Thomas J. Kane & Parag A. Pathak, 2011. "Accountability and Flexibility in Public Schools: Evidence from Boston's Charters And Pilots," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(2), pages 699-748.
    20. repec:mpr:mprres:6857 is not listed on IDEAS
    21. John D. Storey, 2002. "A direct approach to false discovery rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 479-498, August.
    22. John D. Storey & Jonathan E. Taylor & David Siegmund, 2004. "Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 187-205, February.
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    Keywords

    empirical Bayes; labor economics; value-added; shrinkage; Bayesian methods; multiple testing;
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