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Quantile regression with clustered data

Author

Listed:
  • Paulo M.D.C. Parente

    (Department of Economics, University of Exeter)

  • Joao M.C. Santos Silva

    (Department of Economics, University of Essex and CEMAPRE)

Abstract

We show that the quantile regression estimator is consistent and asymptotically normal when the error terms are correlated within clusters but independent across clusters. A consistent estimator of the covariance matrix of the asymptotic distribution is provided and we propose a speci?cation test capable of detecting the presence of intra-cluster correlation. A small simulation study illustrates the ?nite sample performance of the test and of the covariance matrix estimator.

Suggested Citation

  • Paulo M.D.C. Parente & Joao M.C. Santos Silva, 2013. "Quantile regression with clustered data," Discussion Papers 1305, University of Exeter, Department of Economics.
  • Handle: RePEc:exe:wpaper:1305
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    References listed on IDEAS

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    7. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
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    10. J.A.F. Machado & P.M.D.C Parente & J.M.C. Santos Silva, 2011. "QREG2: Stata module to perform quantile regression with robust and clustered standard errors," Statistical Software Components S457369, Boston College Department of Economics, revised 02 Mar 2021.
    11. Buchinsky, Moshe, 1995. "Estimating the asymptotic covariance matrix for quantile regression models a Monte Carlo study," Journal of Econometrics, Elsevier, vol. 68(2), pages 303-338, August.
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    More about this item

    Keywords

    Clustered standard errors; Moulton Problem; Panel data; Specification testing.;
    All these keywords.

    JEL classification:

    • 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
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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