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Quantile Regression with Clustered Data

Parente, Paulo M D C and Santos Silva, Joao M C (2015) 'Quantile Regression with Clustered Data.' Journal of Econometric Methods. ISSN 2156-6674

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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.

Item Type: Article
Uncontrolled Keywords: clustered standard errors; Moulton problem; panel data; specification testing
Subjects: H Social Sciences > HB Economic Theory
Divisions: Faculty of Social Sciences > Economics, Department of
Depositing User: Jim Jamieson
Date Deposited: 04 Sep 2015 15:15
Last Modified: 04 Sep 2015 15:15

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