Semiparametric inference in multivariate fractionally cointegrated systems
A semiparametric multivariate fractionally cointegrated system is considered, integration orders possibly being unknown and I ( 0 ) unobservable inputs having nonparametric spectral density. Two estimates of the vector of cointegrating parameters ν are considered. One involves inverse spectral weigh...
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| Veröffentlicht in: | Journal of econometrics 2010-08, Vol.157 (2), p.492-511 |
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| container_title | Journal of econometrics |
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| creator | Hualde, J. Robinson, P.M. |
| description | A semiparametric multivariate fractionally cointegrated system is considered, integration orders possibly being unknown and
I
(
0
)
unobservable inputs having nonparametric spectral density. Two estimates of the vector of cointegrating parameters
ν
are considered. One involves inverse spectral weighting and the other is unweighted but uses a spectral estimate at frequency zero. Both corresponding Wald statistics for testing linear restrictions on
ν
are shown to have a standard null
χ
2
limit distribution under quite general conditions. Notably, this outcome is irrespective of whether cointegrating relations are “strong” (when the difference between integration orders of observables and cointegrating errors exceeds 1/2), or “weak” (when that difference is less than 1/2), or when both cases are involved. Finite-sample properties are examined in a Monte Carlo study and an empirical example is presented. |
| doi_str_mv | 10.1016/j.jeconom.2010.04.002 |
| format | Article |
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I
(
0
)
unobservable inputs having nonparametric spectral density. Two estimates of the vector of cointegrating parameters
ν
are considered. One involves inverse spectral weighting and the other is unweighted but uses a spectral estimate at frequency zero. Both corresponding Wald statistics for testing linear restrictions on
ν
are shown to have a standard null
χ
2
limit distribution under quite general conditions. Notably, this outcome is irrespective of whether cointegrating relations are “strong” (when the difference between integration orders of observables and cointegrating errors exceeds 1/2), or “weak” (when that difference is less than 1/2), or when both cases are involved. Finite-sample properties are examined in a Monte Carlo study and an empirical example is presented.</description><identifier>ISSN: 0304-4076</identifier><identifier>EISSN: 1872-6895</identifier><identifier>DOI: 10.1016/j.jeconom.2010.04.002</identifier><identifier>CODEN: JECMB6</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Applications ; Cointegration ; Cointegration analysis ; Distribution theory ; Econometrics ; Estimating techniques ; Estimation ; Exact sciences and technology ; Fractional cointegration ; Fractional cointegration Semiparametric model Unknown integration orders Standard inference ; Insurance, economics, finance ; Limit theorems ; Linear models ; Mathematical analysis ; Mathematics ; Measure and integration ; Monte Carlo simulation ; Parameter estimation ; Probability and statistics ; Probability theory and stochastic processes ; Sciences and techniques of general use ; Semiparametric model ; Standard inference ; Stationarity ; Statistical inference ; Statistics ; Studies ; Time series ; Unknown integration orders</subject><ispartof>Journal of econometrics, 2010-08, Vol.157 (2), p.492-511</ispartof><rights>2010 Elsevier B.V.</rights><rights>2015 INIST-CNRS</rights><rights>Copyright Elsevier Sequoia S.A. Aug 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c576t-46215318b89ebd0af29c370d3632066674661f6ea0f41465b83825983a81198c3</citedby><cites>FETCH-LOGICAL-c576t-46215318b89ebd0af29c370d3632066674661f6ea0f41465b83825983a81198c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jeconom.2010.04.002$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,778,782,3539,3996,27911,27912,45982</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23015233$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttp://econpapers.repec.org/article/eeeeconom/v_3a157_3ay_3a2010_3ai_3a2_3ap_3a492-511.htm$$DView record in RePEc$$Hfree_for_read</backlink></links><search><creatorcontrib>Hualde, J.</creatorcontrib><creatorcontrib>Robinson, P.M.</creatorcontrib><title>Semiparametric inference in multivariate fractionally cointegrated systems</title><title>Journal of econometrics</title><description>A semiparametric multivariate fractionally cointegrated system is considered, integration orders possibly being unknown and
I
(
0
)
unobservable inputs having nonparametric spectral density. Two estimates of the vector of cointegrating parameters
ν
are considered. One involves inverse spectral weighting and the other is unweighted but uses a spectral estimate at frequency zero. Both corresponding Wald statistics for testing linear restrictions on
ν
are shown to have a standard null
χ
2
limit distribution under quite general conditions. Notably, this outcome is irrespective of whether cointegrating relations are “strong” (when the difference between integration orders of observables and cointegrating errors exceeds 1/2), or “weak” (when that difference is less than 1/2), or when both cases are involved. Finite-sample properties are examined in a Monte Carlo study and an empirical example is presented.</description><subject>Applications</subject><subject>Cointegration</subject><subject>Cointegration analysis</subject><subject>Distribution theory</subject><subject>Econometrics</subject><subject>Estimating techniques</subject><subject>Estimation</subject><subject>Exact sciences and technology</subject><subject>Fractional cointegration</subject><subject>Fractional cointegration Semiparametric model Unknown integration orders Standard inference</subject><subject>Insurance, economics, finance</subject><subject>Limit theorems</subject><subject>Linear models</subject><subject>Mathematical analysis</subject><subject>Mathematics</subject><subject>Measure and integration</subject><subject>Monte Carlo simulation</subject><subject>Parameter estimation</subject><subject>Probability and statistics</subject><subject>Probability theory and stochastic processes</subject><subject>Sciences and techniques of general use</subject><subject>Semiparametric model</subject><subject>Standard inference</subject><subject>Stationarity</subject><subject>Statistical inference</subject><subject>Statistics</subject><subject>Studies</subject><subject>Time series</subject><subject>Unknown integration orders</subject><issn>0304-4076</issn><issn>1872-6895</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>X2L</sourceid><recordid>eNqFkU1r3DAQhkVpodu0P6FgAqEnb0aflk-hhH4mkEPas9DK41bGthxJu7D_vtp6yaGXCkYzSM87jF4R8p7ClgJV18N2QBfmMG0ZlDMQWwD2gmyoblitdCtfkg1wELWARr0mb1IaAEAKzTfk-yNOfrHRTpijd5Wfe4w4OyxVNe3H7A82epux6qN12YfZjuOxcsHPGX_FctFV6ZgyTuktedXbMeG7c74gPz9_-nH7tb5_-PLt9uN97WSjci0Uo5JTvdMt7jqwPWsdb6DjijNQSjVCKdortNALKpTcaa6ZbDW3mtJWO35BPqx9lxie9piymXxyOI52xrBPppGSSilbKOTlP-QQ9rG8IBnJNLCGC1EguUIuhpQi9maJfrLxaCiYk79mMGd_zclfA8IUf4vubtVFXNA9i7CsFT4Ybqlsyn4s8VfKrT-VJZYSomVGUmp-56l0uzqPapOzYzF7dj49d2UcqGScF-5m5bA4fPAYTXL-9F-dj-iy6YL_z9x_AMQrq5k</recordid><startdate>20100801</startdate><enddate>20100801</enddate><creator>Hualde, J.</creator><creator>Robinson, P.M.</creator><general>Elsevier B.V</general><general>Elsevier</general><general>Elsevier Sequoia S.A</general><scope>IQODW</scope><scope>DKI</scope><scope>X2L</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope></search><sort><creationdate>20100801</creationdate><title>Semiparametric inference in multivariate fractionally cointegrated systems</title><author>Hualde, J. ; Robinson, P.M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c576t-46215318b89ebd0af29c370d3632066674661f6ea0f41465b83825983a81198c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Applications</topic><topic>Cointegration</topic><topic>Cointegration analysis</topic><topic>Distribution theory</topic><topic>Econometrics</topic><topic>Estimating techniques</topic><topic>Estimation</topic><topic>Exact sciences and technology</topic><topic>Fractional cointegration</topic><topic>Fractional cointegration Semiparametric model Unknown integration orders Standard inference</topic><topic>Insurance, economics, finance</topic><topic>Limit theorems</topic><topic>Linear models</topic><topic>Mathematical analysis</topic><topic>Mathematics</topic><topic>Measure and integration</topic><topic>Monte Carlo simulation</topic><topic>Parameter estimation</topic><topic>Probability and statistics</topic><topic>Probability theory and stochastic processes</topic><topic>Sciences and techniques of general use</topic><topic>Semiparametric model</topic><topic>Standard inference</topic><topic>Stationarity</topic><topic>Statistical inference</topic><topic>Statistics</topic><topic>Studies</topic><topic>Time series</topic><topic>Unknown integration orders</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hualde, J.</creatorcontrib><creatorcontrib>Robinson, P.M.</creatorcontrib><collection>Pascal-Francis</collection><collection>RePEc IDEAS</collection><collection>RePEc</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 econometrics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hualde, J.</au><au>Robinson, P.M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Semiparametric inference in multivariate fractionally cointegrated systems</atitle><jtitle>Journal of econometrics</jtitle><date>2010-08-01</date><risdate>2010</risdate><volume>157</volume><issue>2</issue><spage>492</spage><epage>511</epage><pages>492-511</pages><issn>0304-4076</issn><eissn>1872-6895</eissn><coden>JECMB6</coden><abstract>A semiparametric multivariate fractionally cointegrated system is considered, integration orders possibly being unknown and
I
(
0
)
unobservable inputs having nonparametric spectral density. Two estimates of the vector of cointegrating parameters
ν
are considered. One involves inverse spectral weighting and the other is unweighted but uses a spectral estimate at frequency zero. Both corresponding Wald statistics for testing linear restrictions on
ν
are shown to have a standard null
χ
2
limit distribution under quite general conditions. Notably, this outcome is irrespective of whether cointegrating relations are “strong” (when the difference between integration orders of observables and cointegrating errors exceeds 1/2), or “weak” (when that difference is less than 1/2), or when both cases are involved. Finite-sample properties are examined in a Monte Carlo study and an empirical example is presented.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.jeconom.2010.04.002</doi><tpages>20</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Journal of econometrics, 2010-08, Vol.157 (2), p.492-511 |
| issn | 0304-4076 1872-6895 |
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| source | RePEc; ScienceDirect Journals (5 years ago - present) |
| subjects | Applications Cointegration Cointegration analysis Distribution theory Econometrics Estimating techniques Estimation Exact sciences and technology Fractional cointegration Fractional cointegration Semiparametric model Unknown integration orders Standard inference Insurance, economics, finance Limit theorems Linear models Mathematical analysis Mathematics Measure and integration Monte Carlo simulation Parameter estimation Probability and statistics Probability theory and stochastic processes Sciences and techniques of general use Semiparametric model Standard inference Stationarity Statistical inference Statistics Studies Time series Unknown integration orders |
| title | Semiparametric inference in multivariate fractionally cointegrated systems |
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