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Broken or Fixed Effects?

Author

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  • Charles E. Gibbons
  • Juan Carlos Suárez Serrato
  • Michael B. Urbancic

Abstract

We replicate eight influential papers to provide empirical evidence that, in the presence of heterogeneous treatment effects, OLS with fixed effects (FE) is generally not a consistent estimator of the average treatment effect (ATE). We propose two alternative estimators that recover the ATE in the presence of group-specific heterogeneity. We document that heterogeneous treatment effects are common and the ATE is often statistically and economically different from the FE estimate. In all but one of our replications, there is statistically significant treatment effect heterogeneity and, in six, the ATEs are either economically or statistically different from the FE estimates.

Suggested Citation

  • Charles E. Gibbons & Juan Carlos Suárez Serrato & Michael B. Urbancic, 2014. "Broken or Fixed Effects?," NBER Working Papers 20342, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:20342
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    2. Kurt Schmidheiny & Sebastian Siegloch, 2023. "On event studies and distributed‐lags in two‐way fixed effects models: Identification, equivalence, and generalization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 695-713, August.
    3. Daniel Garrett & Andrey Ordin & James W Roberts & Juan Carlos Suárez Serrato, 2023. "Tax Advantages and Imperfect Competition in Auctions for Municipal Bonds," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(2), pages 815-851.
    4. Suárez Serrato, Juan Carlos & Zidar, Owen, 2018. "The structure of state corporate taxation and its impact on state tax revenues and economic activity," Journal of Public Economics, Elsevier, vol. 167(C), pages 158-176.
    5. Pedro Portugal, 2020. "The sources of wage variability in Portugal: a binge reading survey," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    6. Navdeep S. Sahni & Dan Zou & Pradeep K. Chintagunta, 2017. "Do Targeted Discount Offers Serve as Advertising? Evidence from 70 Field Experiments," Management Science, INFORMS, vol. 63(8), pages 2688-2705, August.
    7. Jeanine Miklós-Thal & Hannes Ullrich, 2016. "Career Prospects and Effort Incentives: Evidence from Professional Soccer," Management Science, INFORMS, vol. 62(6), pages 1645-1667, June.
    8. Leandro D’Aurizio & Domenico Depalo, 2016. "An Evaluation of the Policies on Repayment of Government’s Trade Debt in Italy," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 2(2), pages 167-196, July.
    9. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
    10. Słoczyński, Tymon, 2012. "New Evidence on Linear Regression and Treatment Effect Heterogeneity," MPRA Paper 39524, University Library of Munich, Germany.

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    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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