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Bootstrap-Based Improvements for Inference with Clustered Errors

Author

Listed:
  • A. Colin Cameron

    (Department of Economics, University of California-Davis)

  • Jonah B. Gelbach

    (Department of Economics, University of Arizona)

  • Douglas L. Miller

    (Department of Economics, University of California-Davis)

Abstract

Researchers have increasingly realized the need to account for within-group dependence in estimating standard errors of regression parameter estimates. The usual solution is to calculate cluster-robust standard errors that permit heteroskedasticity and within-cluster error correlation, but presume that the number of clusters is large. Standard asymptotic tests can over-reject, however, with few (five to thirty) clusters. We investigate inference using cluster bootstrap-t procedures that provide asymptotic refinement. These procedures are evaluated using Monte Carlos, including the example of Bertrand, Duflo, and Mullainathan (2004). Rejection rates of 10% using standard methods can be reduced to the nominal size of 5% using our methods. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    • Handle: RePEc:tpr:restat:v:90:y:2008:i:3:p:414-427
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    1. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    2. Davidson, Russell & Flachaire, Emmanuel, 2008. "The wild bootstrap, tamed at last," Journal of Econometrics, Elsevier, vol. 146(1), pages 162-169, September.
    3. Chesher, Andrew & Austin, Gerard, 1991. "The finite-sample distributions of heteroskedasticity robust Wald statistics," Journal of Econometrics, Elsevier, vol. 47(1), pages 153-173, January.
    4. Franklin Satterthwaite, 1941. "Synthesis of variance," Psychometrika, Springer;The Psychometric Society, vol. 6(5), pages 309-316, October.
    5. Rothenberg, Thomas J, 1988. "Approximate Power Functions for Some Robust Tests of Regression Coefficients," Econometrica, Econometric Society, vol. 56(5), pages 997-1019, September.
    6. James G. MacKinnon, 2002. "Bootstrap inference in econometrics," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 35(4), pages 615-645, November.
    7. Stephen G. Donald & Kevin Lang, 2007. "Inference with Difference-in-Differences and Other Panel Data," The Review of Economics and Statistics, MIT Press, vol. 89(2), pages 221-233, May.
    8. Jonathan Gruber & James M. Poterba, 1993. "Tax Incentives and the Decision to Purchase Health Insurance: Evidence from the Self-Employed," NBER Working Papers 4435, National Bureau of Economic Research, Inc.
    9. Davidson, Russell & MacKinnon, James G., 1999. "The Size Distortion Of Bootstrap Tests," Econometric Theory, Cambridge University Press, vol. 15(3), pages 361-376, June.
    10. Greenwald, Bruce C., 1983. "A general analysis of bias in the estimated standard errors of least squares coefficients," Journal of Econometrics, Elsevier, vol. 22(3), pages 323-338, August.
    11. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053, September.
    12. David Brownstone & Robert Valletta, 2001. "The Bootstrap and Multiple Imputations: Harnessing Increased Computing Power for Improved Statistical Tests," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 129-141, Fall.
    13. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, Oxford University Press, vol. 119(1), pages 249-275.
    14. Moulton, Brent R., 1986. "Random group effects and the precision of regression estimates," Journal of Econometrics, Elsevier, vol. 32(3), pages 385-397, August.
    15. Kloek, T, 1981. "OLS Estimation in a Model Where a Microvariable Is Explained by Aggregates and Contemporaneous Disturbances Are Equicorrelated," Econometrica, Econometric Society, vol. 49(1), pages 205-207, January.
    16. Joshua D. Angrist & Victor Lavy, 2002. "The Effect of High School Matriculation Awards: Evidence from Randomized Trials," NBER Working Papers 9389, National Bureau of Economic Research, Inc.
    17. Joel L. Horowitz, 1996. "Bootstrap Methods in Econometrics: Theory and Numerical Performance," Econometrics 9602009, University Library of Munich, Germany, revised 05 Mar 1996.
    18. Arellano, M, 1987. "Computing Robust Standard Errors for Within-Groups Estimators," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 49(4), pages 431-434, November.
    19. 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.
    20. Jeffrey M. Wooldridge, 2003. "Cluster-Sample Methods in Applied Econometrics," American Economic Review, American Economic Association, vol. 93(2), pages 133-138, May.
    21. Horowitz, Joel L., 2001. "The Bootstrap," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.),Handbook of Econometrics, edition 1, volume 5, chapter 52, pages 3159-3228, Elsevier.
    22. Michael Baker & Nicole M. Fortin, 2001. "Occupational gender composition and wages in Canada, 1987-1988," Canadian Journal of Economics, Canadian Economics Association, vol. 34(2), pages 345-376, May.
    23. Jonathan Gruber & James Poterba, 1994. "Tax Incentives and the Decision to Purchase Health Insurance: Evidence from the Self-Employed," The Quarterly Journal of Economics, Oxford University Press, vol. 109(3), pages 701-733.
    24. Moulton, Brent R, 1990. "An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Unit," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 334-338, May.
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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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