Quantile regression with clustered data

Bibliographic Details
Main Author: Parente, P. M. D. C.
Publication Date: 2016
Other Authors: Silva, J. M. C. S.
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10071/12175
Summary: 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.
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spelling Quantile regression with clustered dataClustered standard errorsMoulton problemPanel dataSpecification testingWe 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.De Gruyter2016-12-06T18:07:54Z2016-01-01T00:00:00Z20162019-04-23T10:30:39Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/12175eng2156-667410.1515/jem-2014-0011Parente, P. M. D. C.Silva, J. M. C. S.info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-07-07T03:52:25Zoai:repositorio.iscte-iul.pt:10071/12175Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T18:33:11.805457Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Quantile regression with clustered data
title Quantile regression with clustered data
spellingShingle Quantile regression with clustered data
Parente, P. M. D. C.
Clustered standard errors
Moulton problem
Panel data
Specification testing
title_short Quantile regression with clustered data
title_full Quantile regression with clustered data
title_fullStr Quantile regression with clustered data
title_full_unstemmed Quantile regression with clustered data
title_sort Quantile regression with clustered data
author Parente, P. M. D. C.
author_facet Parente, P. M. D. C.
Silva, J. M. C. S.
author_role author
author2 Silva, J. M. C. S.
author2_role author
dc.contributor.author.fl_str_mv Parente, P. M. D. C.
Silva, J. M. C. S.
dc.subject.por.fl_str_mv Clustered standard errors
Moulton problem
Panel data
Specification testing
topic Clustered standard errors
Moulton problem
Panel data
Specification testing
description 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.
publishDate 2016
dc.date.none.fl_str_mv 2016-12-06T18:07:54Z
2016-01-01T00:00:00Z
2016
2019-04-23T10:30:39Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10071/12175
url http://hdl.handle.net/10071/12175
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2156-6674
10.1515/jem-2014-0011
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv De Gruyter
publisher.none.fl_str_mv De Gruyter
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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