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Journal of Econometric Methods

Ed. by Giacomini, Raffaella / Li, Tong

Mathematical Citation Quotient (MCQ) 2018: 0.06

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Quantile Regression with Clustered Data

Paulo M.D.C. Parente
  • Instituto Universitário de Lisboa (ISCTE-IUL), Business Research Unit (BRU-IUL), Lisboa, Portugal
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ João M.C. Santos Silva
  • Corresponding author
  • Department of Economics, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK; and CEMAPRE, Rua do Quelhas 6, 1200-781 Lisboa, Portugal
  • Email
  • Other articles by this author:
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Published Online: 2015-02-27 | DOI: https://doi.org/10.1515/jem-2014-0011


We study the properties of the quantile regression estimator when data are sampled from independent and identically distributed clusters, and show that the estimator is consistent and asymptotically normal even when there is intra-cluster correlation. A consistent estimator of the covariance matrix of the asymptotic distribution is provided, and we propose a specification test capable of detecting the presence of intra-cluster correlation. A small simulation study illustrates the finite sample performance of the test and of the covariance matrix estimator.

This article offers supplementary material which is provided at the end of the article.

Keywords: clustered standard errors; Moulton problem; panel data; specification testing

JEL Classifications:: C12; C21; C23


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About the article

Corresponding author: João M.C. Santos Silva, Department of Economics, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK; and CEMAPRE, Rua do Quelhas 6, 1200-781 Lisboa, Portugal, E-mail:

Published Online: 2015-02-27

Published in Print: 2016-01-01

Citation Information: Journal of Econometric Methods, Volume 5, Issue 1, Pages 1–15, ISSN (Online) 2156-6674, ISSN (Print) 2194-6345, DOI: https://doi.org/10.1515/jem-2014-0011.

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