Quantile regression with clustered data
AbstractWe 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.
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Bibliographic InfoPaper provided by Exeter University, Department of Economics in its series Discussion Papers with number 1305.
Date of creation: 2013
Date of revision:
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Clustered standard errors; Moulton Problem; Panel data; Specification testing.;
Other versions of this item:
- 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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- Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
- Breusch, T S & Pagan, A R, 1980.
"The Lagrange Multiplier Test and Its Applications to Model Specification in Econometrics,"
Review of Economic Studies,
Wiley Blackwell, vol. 47(1), pages 239-53, January.
- Breusch, T.S. & Pagan, A.R., . "The Lagrange multiplier test and its applications to model specification in econometrics," CORE Discussion Papers RP -412, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
- Koenker,Roger, 2005.
Cambridge University Press, number 9780521608275.
- 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 15 Feb 2014.
- White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
- 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 431-34, November.
- William Rogers, 1993. "Quantile regression standard errors," Stata Technical Bulletin, StataCorp LP, vol. 2(9).
- Moulton, Brent R., 1986. "Random group effects and the precision of regression estimates," Journal of Econometrics, Elsevier, vol. 32(3), pages 385-397, August.
- 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.
- Jake Anders, 2014. "Does an aptitude test affect socioeconomic and gender gaps in attendance at an elite university?," DoQSS Working Papers 14-07, Department of Quantitative Social Science - Institute of Education, University of London.
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