Bootstrap specification tests for linear covariance stationary processes
This paper discusses goodness-of-fit tests for linear covariance stationary processes based on the empirical spectral distribution function. We can show that the limiting distribution of the tests are functionals of a Gaussian process, say, B ˜ ( ϑ ) with ϑ ∈ [ 0 , 1 ] . Since in general it is not e...
Gespeichert in:
| Veröffentlicht in: | Journal of econometrics 2006-08, Vol.133 (2), p.807-839 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 839 |
|---|---|
| container_issue | 2 |
| container_start_page | 807 |
| container_title | Journal of econometrics |
| container_volume | 133 |
| creator | Hidalgo, J. Kreiss, J.-P. |
| description | This paper discusses goodness-of-fit tests for linear covariance stationary processes based on the empirical spectral distribution function. We can show that the limiting distribution of the tests are functionals of a Gaussian process, say,
B
˜
(
ϑ
)
with
ϑ
∈
[
0
,
1
]
. Since in general it is not easy, if at all possible, to find a time deformation
g
(
ϑ
)
such that
B
˜
(
g
(
ϑ
)
)
is a Brownian (bridge) process, tests based on
B
˜
(
ϑ
)
will have limited value for the purpose of statistical inference. To circumvent the problem, we propose to bootstrap the test showing its validity. We also provide a Monte-Carlo experiment to examine the finite sample behaviour of the bootstrap. |
| doi_str_mv | 10.1016/j.jeconom.2005.06.015 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_36491497</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S030440760500134X</els_id><sourcerecordid>1147254811</sourcerecordid><originalsourceid>FETCH-LOGICAL-c527t-e5e2a97d3f41ee0acc76ac50777f234495b6e160db73ce6d651cc76cffddc51c3</originalsourceid><addsrcrecordid>eNqFkUGL1TAQx4Mo-Fz9CEIR9NaaNE3SnkQXdcUFL3oO2XSCKX1NzeQ92G_vdPtQ8GJgMnP4zeQ__zD2UvBGcKHfTs0EPi3p2LScq4brhgv1iB1Eb9pa94N6zA5c8q7uuNFP2TPEiRPY9fLAbj6kVLBkt1a4go8heldiWqoCWLAKKVdzXMDlyqezy9EtHiosD4zL99WakwdEwOfsSXAzwotLvmI_Pn38fn1T3377_OX6_W3tVWtKDQpaN5hRhk4AcOe90c4rbowJrey6Qd1pEJqPd0Z60KNWYkN8COPoqZZX7M0-l17-dSKR9hjRwzy7BdIJrdTdILrBEPjqH3BKp7yQNisGrXU76A1SO-RzQswQ7JrjkRazgtvNXDvZi7l2M9dybclc6vu692Ug1_40AZ0dPlvphJR031NQq6YUt5Jipei5sb0c7M9ypGmvL1IdejeHTC5H_Cul532vHlZ6t3NABp8jZIs-Av3IGDP4YscU_6P7N_tCrVg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>196662967</pqid></control><display><type>article</type><title>Bootstrap specification tests for linear covariance stationary processes</title><source>RePEc</source><source>Access via ScienceDirect (Elsevier)</source><creator>Hidalgo, J. ; Kreiss, J.-P.</creator><creatorcontrib>Hidalgo, J. ; Kreiss, J.-P.</creatorcontrib><description>This paper discusses goodness-of-fit tests for linear covariance stationary processes based on the empirical spectral distribution function. We can show that the limiting distribution of the tests are functionals of a Gaussian process, say,
B
˜
(
ϑ
)
with
ϑ
∈
[
0
,
1
]
. Since in general it is not easy, if at all possible, to find a time deformation
g
(
ϑ
)
such that
B
˜
(
g
(
ϑ
)
)
is a Brownian (bridge) process, tests based on
B
˜
(
ϑ
)
will have limited value for the purpose of statistical inference. To circumvent the problem, we propose to bootstrap the test showing its validity. We also provide a Monte-Carlo experiment to examine the finite sample behaviour of the bootstrap.</description><identifier>ISSN: 0304-4076</identifier><identifier>EISSN: 1872-6895</identifier><identifier>DOI: 10.1016/j.jeconom.2005.06.015</identifier><identifier>CODEN: JECMB6</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Applications ; Bootstrap mechanism ; Bootstrap method ; Bootstrap tests ; Brownian motion ; Covariance ; Economic theory ; Exact sciences and technology ; Gaussian process ; Gaussian processes ; Goodness-of-fit ; Inference from stochastic processes; time series analysis ; Insurance, economics, finance ; Linear models ; Linear processes ; Mathematics ; Monte Carlo simulation ; Normal distribution ; Probability and statistics ; Sciences and techniques of general use ; Spectral distribution ; Statistics ; Studies</subject><ispartof>Journal of econometrics, 2006-08, Vol.133 (2), p.807-839</ispartof><rights>2005 Elsevier B.V.</rights><rights>2006 INIST-CNRS</rights><rights>Copyright Elsevier Sequoia S.A. Aug 2006</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c527t-e5e2a97d3f41ee0acc76ac50777f234495b6e160db73ce6d651cc76cffddc51c3</citedby><cites>FETCH-LOGICAL-c527t-e5e2a97d3f41ee0acc76ac50777f234495b6e160db73ce6d651cc76cffddc51c3</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.2005.06.015$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>309,310,314,780,784,789,790,3550,4008,23930,23931,25140,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=18088597$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttp://econpapers.repec.org/article/eeeeconom/v_3a133_3ay_3a2006_3ai_3a2_3ap_3a807-839.htm$$DView record in RePEc$$Hfree_for_read</backlink></links><search><creatorcontrib>Hidalgo, J.</creatorcontrib><creatorcontrib>Kreiss, J.-P.</creatorcontrib><title>Bootstrap specification tests for linear covariance stationary processes</title><title>Journal of econometrics</title><description>This paper discusses goodness-of-fit tests for linear covariance stationary processes based on the empirical spectral distribution function. We can show that the limiting distribution of the tests are functionals of a Gaussian process, say,
B
˜
(
ϑ
)
with
ϑ
∈
[
0
,
1
]
. Since in general it is not easy, if at all possible, to find a time deformation
g
(
ϑ
)
such that
B
˜
(
g
(
ϑ
)
)
is a Brownian (bridge) process, tests based on
B
˜
(
ϑ
)
will have limited value for the purpose of statistical inference. To circumvent the problem, we propose to bootstrap the test showing its validity. We also provide a Monte-Carlo experiment to examine the finite sample behaviour of the bootstrap.</description><subject>Applications</subject><subject>Bootstrap mechanism</subject><subject>Bootstrap method</subject><subject>Bootstrap tests</subject><subject>Brownian motion</subject><subject>Covariance</subject><subject>Economic theory</subject><subject>Exact sciences and technology</subject><subject>Gaussian process</subject><subject>Gaussian processes</subject><subject>Goodness-of-fit</subject><subject>Inference from stochastic processes; time series analysis</subject><subject>Insurance, economics, finance</subject><subject>Linear models</subject><subject>Linear processes</subject><subject>Mathematics</subject><subject>Monte Carlo simulation</subject><subject>Normal distribution</subject><subject>Probability and statistics</subject><subject>Sciences and techniques of general use</subject><subject>Spectral distribution</subject><subject>Statistics</subject><subject>Studies</subject><issn>0304-4076</issn><issn>1872-6895</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>X2L</sourceid><recordid>eNqFkUGL1TAQx4Mo-Fz9CEIR9NaaNE3SnkQXdcUFL3oO2XSCKX1NzeQ92G_vdPtQ8GJgMnP4zeQ__zD2UvBGcKHfTs0EPi3p2LScq4brhgv1iB1Eb9pa94N6zA5c8q7uuNFP2TPEiRPY9fLAbj6kVLBkt1a4go8heldiWqoCWLAKKVdzXMDlyqezy9EtHiosD4zL99WakwdEwOfsSXAzwotLvmI_Pn38fn1T3377_OX6_W3tVWtKDQpaN5hRhk4AcOe90c4rbowJrey6Qd1pEJqPd0Z60KNWYkN8COPoqZZX7M0-l17-dSKR9hjRwzy7BdIJrdTdILrBEPjqH3BKp7yQNisGrXU76A1SO-RzQswQ7JrjkRazgtvNXDvZi7l2M9dybclc6vu692Ug1_40AZ0dPlvphJR031NQq6YUt5Jipei5sb0c7M9ypGmvL1IdejeHTC5H_Cul532vHlZ6t3NABp8jZIs-Av3IGDP4YscU_6P7N_tCrVg</recordid><startdate>20060801</startdate><enddate>20060801</enddate><creator>Hidalgo, J.</creator><creator>Kreiss, J.-P.</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>20060801</creationdate><title>Bootstrap specification tests for linear covariance stationary processes</title><author>Hidalgo, J. ; Kreiss, J.-P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c527t-e5e2a97d3f41ee0acc76ac50777f234495b6e160db73ce6d651cc76cffddc51c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Applications</topic><topic>Bootstrap mechanism</topic><topic>Bootstrap method</topic><topic>Bootstrap tests</topic><topic>Brownian motion</topic><topic>Covariance</topic><topic>Economic theory</topic><topic>Exact sciences and technology</topic><topic>Gaussian process</topic><topic>Gaussian processes</topic><topic>Goodness-of-fit</topic><topic>Inference from stochastic processes; time series analysis</topic><topic>Insurance, economics, finance</topic><topic>Linear models</topic><topic>Linear processes</topic><topic>Mathematics</topic><topic>Monte Carlo simulation</topic><topic>Normal distribution</topic><topic>Probability and statistics</topic><topic>Sciences and techniques of general use</topic><topic>Spectral distribution</topic><topic>Statistics</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hidalgo, J.</creatorcontrib><creatorcontrib>Kreiss, J.-P.</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>Hidalgo, J.</au><au>Kreiss, J.-P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bootstrap specification tests for linear covariance stationary processes</atitle><jtitle>Journal of econometrics</jtitle><date>2006-08-01</date><risdate>2006</risdate><volume>133</volume><issue>2</issue><spage>807</spage><epage>839</epage><pages>807-839</pages><issn>0304-4076</issn><eissn>1872-6895</eissn><coden>JECMB6</coden><abstract>This paper discusses goodness-of-fit tests for linear covariance stationary processes based on the empirical spectral distribution function. We can show that the limiting distribution of the tests are functionals of a Gaussian process, say,
B
˜
(
ϑ
)
with
ϑ
∈
[
0
,
1
]
. Since in general it is not easy, if at all possible, to find a time deformation
g
(
ϑ
)
such that
B
˜
(
g
(
ϑ
)
)
is a Brownian (bridge) process, tests based on
B
˜
(
ϑ
)
will have limited value for the purpose of statistical inference. To circumvent the problem, we propose to bootstrap the test showing its validity. We also provide a Monte-Carlo experiment to examine the finite sample behaviour of the bootstrap.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.jeconom.2005.06.015</doi><tpages>33</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0304-4076 |
| ispartof | Journal of econometrics, 2006-08, Vol.133 (2), p.807-839 |
| issn | 0304-4076 1872-6895 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_36491497 |
| source | RePEc; Access via ScienceDirect (Elsevier) |
| subjects | Applications Bootstrap mechanism Bootstrap method Bootstrap tests Brownian motion Covariance Economic theory Exact sciences and technology Gaussian process Gaussian processes Goodness-of-fit Inference from stochastic processes time series analysis Insurance, economics, finance Linear models Linear processes Mathematics Monte Carlo simulation Normal distribution Probability and statistics Sciences and techniques of general use Spectral distribution Statistics Studies |
| title | Bootstrap specification tests for linear covariance stationary processes |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T20%3A20%3A52IST&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=Bootstrap%20specification%20tests%20for%20linear%20covariance%20stationary%20processes&rft.jtitle=Journal%20of%20econometrics&rft.au=Hidalgo,%20J.&rft.date=2006-08-01&rft.volume=133&rft.issue=2&rft.spage=807&rft.epage=839&rft.pages=807-839&rft.issn=0304-4076&rft.eissn=1872-6895&rft.coden=JECMB6&rft_id=info:doi/10.1016/j.jeconom.2005.06.015&rft_dat=%3Cproquest_cross%3E1147254811%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=196662967&rft_id=info:pmid/&rft_els_id=S030440760500134X&rfr_iscdi=true |