A REVIEW AND COMPARISON OF TESTS OF CROSS-SECTION INDEPENDENCE IN PANELS
In this paper we review and compare diagnostic tests of cross‐section independence in the disturbances of panel regression models. We examine tests based on the sample pairwise correlation coefficient or on its transformations, and tests based on the theory of spacings. The ultimate goal is to shed...
Gespeichert in:
Veröffentlicht in: | Journal of economic surveys 2009-07, Vol.23 (3), p.528-561 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 561 |
---|---|
container_issue | 3 |
container_start_page | 528 |
container_title | Journal of economic surveys |
container_volume | 23 |
creator | Moscone, Francesco Tosetti, Elisa |
description | In this paper we review and compare diagnostic tests of cross‐section independence in the disturbances of panel regression models. We examine tests based on the sample pairwise correlation coefficient or on its transformations, and tests based on the theory of spacings. The ultimate goal is to shed some light on the appropriate use of existing diagnostic tests for cross‐equation error correlation. Our discussion is supported by means of a set of Monte Carlo experiments and a small empirical study on health. Results show that tests based on the average of pairwise correlation coefficients work well when the alternative hypothesis is a factor model with non‐zero mean loadings. Tests based on spacings are powerful in identifying various forms of strong cross‐section dependence, but have low power when they are used to capture spatial correlation. |
doi_str_mv | 10.1111/j.1467-6419.2008.00571.x |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_37267277</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1743329711</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4711-5e905744df93219074924bf193b741829cb5202cbb3488d49a67f6d8cc3401e53</originalsourceid><addsrcrecordid>eNqNkDFPwzAQhS0EEqXwHyIGtoSz48T2wBClbhtUkqouMFpJ6kgthZa4FeXf41DEwISH853ufaenh5CHIcDu3a4CTGPmxxSLgADwACBiODicoN7v4hT1QETgAwd6ji6sXQEAY4z00DjxZvIpk89ekg-8tHiYJrNMFblXDL25VHPVNemsUMpXMp1nbpPlAzmVruSpdIM3TXI5UZforCnX1lz9_H30OJTzdOxPilGWJhO_pgxjPzLC-aN00YiQYAGMCkKrBouwYhRzIuoqIkDqqgop5wsqypg18YLXdUgBmyjso5vj3W27ed8bu9OvS1ub9bp8M5u91SEjMSOMOeH1H-Fqs2_fnDftcmIQxSx0In4U1e3G2tY0etsuX8v2U2PQXb56pbsYdRdjx3H9na8-OPTuiH4s1-bz35y-L6RyneP9I7-0O3P45cv2RTtnLNLP-Ujfx9OZ4iOqx-EXehWGwA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>200705673</pqid></control><display><type>article</type><title>A REVIEW AND COMPARISON OF TESTS OF CROSS-SECTION INDEPENDENCE IN PANELS</title><source>Wiley Online Library - AutoHoldings Journals</source><source>EBSCOhost Business Source Complete</source><creator>Moscone, Francesco ; Tosetti, Elisa</creator><creatorcontrib>Moscone, Francesco ; Tosetti, Elisa</creatorcontrib><description>In this paper we review and compare diagnostic tests of cross‐section independence in the disturbances of panel regression models. We examine tests based on the sample pairwise correlation coefficient or on its transformations, and tests based on the theory of spacings. The ultimate goal is to shed some light on the appropriate use of existing diagnostic tests for cross‐equation error correlation. Our discussion is supported by means of a set of Monte Carlo experiments and a small empirical study on health. Results show that tests based on the average of pairwise correlation coefficients work well when the alternative hypothesis is a factor model with non‐zero mean loadings. Tests based on spacings are powerful in identifying various forms of strong cross‐section dependence, but have low power when they are used to capture spatial correlation.</description><identifier>ISSN: 0950-0804</identifier><identifier>EISSN: 1467-6419</identifier><identifier>DOI: 10.1111/j.1467-6419.2008.00571.x</identifier><language>eng</language><publisher>Oxford, UK: Blackwell Publishing Ltd</publisher><subject>Cross-sectional analysis ; Diagnostic tests ; Economic theory ; Estimation ; Hypotheses ; Monte Carlo simulation ; Panel data ; Regression analysis ; Review articles ; Studies</subject><ispartof>Journal of economic surveys, 2009-07, Vol.23 (3), p.528-561</ispartof><rights>2009 The Authors. Journal compilation © 2009 Blackwell Publishing Ltd</rights><rights>Journal compilation © 2009 Blackwell Publishing Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4711-5e905744df93219074924bf193b741829cb5202cbb3488d49a67f6d8cc3401e53</citedby><cites>FETCH-LOGICAL-c4711-5e905744df93219074924bf193b741829cb5202cbb3488d49a67f6d8cc3401e53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fj.1467-6419.2008.00571.x$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fj.1467-6419.2008.00571.x$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>315,781,785,1418,27928,27929,45578,45579</link.rule.ids></links><search><creatorcontrib>Moscone, Francesco</creatorcontrib><creatorcontrib>Tosetti, Elisa</creatorcontrib><title>A REVIEW AND COMPARISON OF TESTS OF CROSS-SECTION INDEPENDENCE IN PANELS</title><title>Journal of economic surveys</title><description>In this paper we review and compare diagnostic tests of cross‐section independence in the disturbances of panel regression models. We examine tests based on the sample pairwise correlation coefficient or on its transformations, and tests based on the theory of spacings. The ultimate goal is to shed some light on the appropriate use of existing diagnostic tests for cross‐equation error correlation. Our discussion is supported by means of a set of Monte Carlo experiments and a small empirical study on health. Results show that tests based on the average of pairwise correlation coefficients work well when the alternative hypothesis is a factor model with non‐zero mean loadings. Tests based on spacings are powerful in identifying various forms of strong cross‐section dependence, but have low power when they are used to capture spatial correlation.</description><subject>Cross-sectional analysis</subject><subject>Diagnostic tests</subject><subject>Economic theory</subject><subject>Estimation</subject><subject>Hypotheses</subject><subject>Monte Carlo simulation</subject><subject>Panel data</subject><subject>Regression analysis</subject><subject>Review articles</subject><subject>Studies</subject><issn>0950-0804</issn><issn>1467-6419</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><recordid>eNqNkDFPwzAQhS0EEqXwHyIGtoSz48T2wBClbhtUkqouMFpJ6kgthZa4FeXf41DEwISH853ufaenh5CHIcDu3a4CTGPmxxSLgADwACBiODicoN7v4hT1QETgAwd6ji6sXQEAY4z00DjxZvIpk89ekg-8tHiYJrNMFblXDL25VHPVNemsUMpXMp1nbpPlAzmVruSpdIM3TXI5UZforCnX1lz9_H30OJTzdOxPilGWJhO_pgxjPzLC-aN00YiQYAGMCkKrBouwYhRzIuoqIkDqqgop5wsqypg18YLXdUgBmyjso5vj3W27ed8bu9OvS1ub9bp8M5u91SEjMSOMOeH1H-Fqs2_fnDftcmIQxSx0In4U1e3G2tY0etsuX8v2U2PQXb56pbsYdRdjx3H9na8-OPTuiH4s1-bz35y-L6RyneP9I7-0O3P45cv2RTtnLNLP-Ujfx9OZ4iOqx-EXehWGwA</recordid><startdate>200907</startdate><enddate>200907</enddate><creator>Moscone, Francesco</creator><creator>Tosetti, Elisa</creator><general>Blackwell Publishing Ltd</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope></search><sort><creationdate>200907</creationdate><title>A REVIEW AND COMPARISON OF TESTS OF CROSS-SECTION INDEPENDENCE IN PANELS</title><author>Moscone, Francesco ; Tosetti, Elisa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4711-5e905744df93219074924bf193b741829cb5202cbb3488d49a67f6d8cc3401e53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Cross-sectional analysis</topic><topic>Diagnostic tests</topic><topic>Economic theory</topic><topic>Estimation</topic><topic>Hypotheses</topic><topic>Monte Carlo simulation</topic><topic>Panel data</topic><topic>Regression analysis</topic><topic>Review articles</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Moscone, Francesco</creatorcontrib><creatorcontrib>Tosetti, Elisa</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><jtitle>Journal of economic surveys</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Moscone, Francesco</au><au>Tosetti, Elisa</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A REVIEW AND COMPARISON OF TESTS OF CROSS-SECTION INDEPENDENCE IN PANELS</atitle><jtitle>Journal of economic surveys</jtitle><date>2009-07</date><risdate>2009</risdate><volume>23</volume><issue>3</issue><spage>528</spage><epage>561</epage><pages>528-561</pages><issn>0950-0804</issn><eissn>1467-6419</eissn><abstract>In this paper we review and compare diagnostic tests of cross‐section independence in the disturbances of panel regression models. We examine tests based on the sample pairwise correlation coefficient or on its transformations, and tests based on the theory of spacings. The ultimate goal is to shed some light on the appropriate use of existing diagnostic tests for cross‐equation error correlation. Our discussion is supported by means of a set of Monte Carlo experiments and a small empirical study on health. Results show that tests based on the average of pairwise correlation coefficients work well when the alternative hypothesis is a factor model with non‐zero mean loadings. Tests based on spacings are powerful in identifying various forms of strong cross‐section dependence, but have low power when they are used to capture spatial correlation.</abstract><cop>Oxford, UK</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1111/j.1467-6419.2008.00571.x</doi><tpages>34</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0950-0804 |
ispartof | Journal of economic surveys, 2009-07, Vol.23 (3), p.528-561 |
issn | 0950-0804 1467-6419 |
language | eng |
recordid | cdi_proquest_miscellaneous_37267277 |
source | Wiley Online Library - AutoHoldings Journals; EBSCOhost Business Source Complete |
subjects | Cross-sectional analysis Diagnostic tests Economic theory Estimation Hypotheses Monte Carlo simulation Panel data Regression analysis Review articles Studies |
title | A REVIEW AND COMPARISON OF TESTS OF CROSS-SECTION INDEPENDENCE IN PANELS |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-17T04%3A25%3A17IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20REVIEW%20AND%20COMPARISON%20OF%20TESTS%20OF%20CROSS-SECTION%20INDEPENDENCE%20IN%20PANELS&rft.jtitle=Journal%20of%20economic%20surveys&rft.au=Moscone,%20Francesco&rft.date=2009-07&rft.volume=23&rft.issue=3&rft.spage=528&rft.epage=561&rft.pages=528-561&rft.issn=0950-0804&rft.eissn=1467-6419&rft_id=info:doi/10.1111/j.1467-6419.2008.00571.x&rft_dat=%3Cproquest_cross%3E1743329711%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=200705673&rft_id=info:pmid/&rfr_iscdi=true |