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The impact of a Hausman pretest, applied to panel data, on the coverage probability of confidence intervals

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  • Kabaila, Paul
  • Mainzer, Rheanna
  • Farchione, Davide

Abstract

In the analysis of panel data that includes a time-varying covariate, a Hausman pretest is commonly used to decide whether subsequent inference is made using the random effects model or the fixed effects model. We consider the effect of this pretest on the coverage probability of a confidence interval for the slope parameter. We prove three new finite sample theorems that make it easy to assess, for a wide variety of circumstances, the effect of the Hausman pretest on the minimum coverage probability of this confidence interval.

Suggested Citation

  • Kabaila, Paul & Mainzer, Rheanna & Farchione, Davide, 2015. "The impact of a Hausman pretest, applied to panel data, on the coverage probability of confidence intervals," Economics Letters, Elsevier, vol. 131(C), pages 12-15.
    • Handle: RePEc:eee:ecolet:v:131:y:2015:i:c:p:12-15
    DOI: 10.1016/j.econlet.2015.03.031
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    References listed on IDEAS

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    1. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-1398, November.
    2. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    3. Maddala, G S, 1971. "The Use of Variance Components Models in Pooling Cross Section and Time Series Data," Econometrica, Econometric Society, vol. 39(2), pages 341-358, March.
    4. Guggenberger, Patrik, 2010. "The impact of a Hausman pretest on the size of a hypothesis test: The panel data case," Journal of Econometrics, Elsevier, vol. 156(2), pages 337-343, June.
    5. Guggenberger, Patrik, 2010. "The Impact Of A Hausman Pretest On The Asymptotic Size Of A Hypothesis Test," Econometric Theory, Cambridge University Press, vol. 26(2), pages 369-382, April.
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    Citations

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    Cited by:

    1. Nils Grashof, 2020. "Sinking or swimming in the cluster labour pool? A firm-specific analysis of the effect of specialized labour," Jena Economics Research Papers 2020-006, Friedrich-Schiller-University Jena.
    2. Firmin DOKO TCHATOKA & Jean-Marie DUFOUR, 2016. "Exogeneity Tests, Incomplete Models, Weak Identification and Non-Gaussian Distributions : Invariance and Finite-Sample Distributional Theory," Cahiers de recherche 14-2016, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    3. Bartolucci, Francesco & Bacci, Silvia & Pigini, Claudia, 2017. "Misspecification test for random effects in generalized linear finite-mixture models for clustered binary and ordered data," Econometrics and Statistics, Elsevier, vol. 3(C), pages 112-131.
    4. Paul Kabaila & Rheanna Mainzer & Davide Farchione, 2017. "Conditional assessment of the impact of a Hausman pretest on confidence intervals," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 71(4), pages 240-262, November.
    5. Wang, Yun & Zhang, Yonghui & Zhou, Qiankun, 2016. "A Stein-like estimator for linear panel data models," Economics Letters, Elsevier, vol. 141(C), pages 156-161.
    6. Paul Kabaila & Davide Farchione & Samer Alhelli & Nathan Bragg, 2021. "The effect of a Durbin–Watson pretest on confidence intervals in regression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(1), pages 4-23, February.
    7. Doko Tchatoka, Firmin & Wang, Wenjie, 2021. "Uniform Inference after Pretesting for Exogeneity with Heteroskedastic Data," MPRA Paper 106408, University Library of Munich, Germany.
    8. Doko Tchatoka, Firmin & Wang, Wenjie, 2020. "Uniform Inference after Pretesting for Exogeneity," MPRA Paper 99243, University Library of Munich, Germany.
    9. Doko Tchatoka, Firmin & Dufour, Jean-Marie, 2020. "Exogeneity tests, incomplete models, weak identification and non-Gaussian distributions: Invariance and finite-sample distributional theory," Journal of Econometrics, Elsevier, vol. 218(2), pages 390-418.

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    More about this item

    Keywords

    Coverage probability; Fixed effects model; Hausman specification test; Panel data; Random effects model;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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