{"id":"https://openalex.org/W4402636043","doi":"https://doi.org/10.1080/10618600.2024.2403705","title":"Bootstrap Inference for Linear Time-Varying Coefficient Models in Locally Stationary Time Series","display_name":"Bootstrap Inference for Linear Time-Varying Coefficient Models in Locally Stationary Time Series","publication_year":2024,"publication_date":"2024-09-19","ids":{"openalex":"https://openalex.org/W4402636043","doi":"https://doi.org/10.1080/10618600.2024.2403705"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2024.2403705","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2403705","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1080/10618600.2024.2403705","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055838773","display_name":"Yicong Lin","orcid":"https://orcid.org/0000-0002-9206-4137"},"institutions":[{"id":"https://openalex.org/I198488067","display_name":"Tinbergen Institute","ror":"https://ror.org/054xxtt73","country_code":"NL","type":"education","lineage":["https://openalex.org/I198488067"]},{"id":"https://openalex.org/I865915315","display_name":"Vrije Universiteit Amsterdam","ror":"https://ror.org/008xxew50","country_code":"NL","type":"education","lineage":["https://openalex.org/I865915315"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Yicong Lin","raw_affiliation_strings":["Department of Econometrics and Data Science, Vrije Universiteit Amsterdam","Tinbergen Institute","Vrije Universiteit Amsterdam"],"raw_orcid":"https://orcid.org/0000-0002-9206-4137","affiliations":[{"raw_affiliation_string":"Department of Econometrics and Data Science, Vrije Universiteit Amsterdam","institution_ids":["https://openalex.org/I865915315"]},{"raw_affiliation_string":"Tinbergen Institute","institution_ids":["https://openalex.org/I198488067"]},{"raw_affiliation_string":"Vrije Universiteit Amsterdam","institution_ids":["https://openalex.org/I865915315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102960285","display_name":"Mingxuan Song","orcid":"https://orcid.org/0009-0004-5979-9977"},"institutions":[{"id":"https://openalex.org/I865915315","display_name":"Vrije Universiteit Amsterdam","ror":"https://ror.org/008xxew50","country_code":"NL","type":"education","lineage":["https://openalex.org/I865915315"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Mingxuan Song","raw_affiliation_strings":["Department of Econometrics and Data Science, Vrije Universiteit Amsterdam","Vrije Universiteit Amsterdam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Econometrics and Data Science, Vrije Universiteit Amsterdam","institution_ids":["https://openalex.org/I865915315"]},{"raw_affiliation_string":"Vrije Universiteit Amsterdam","institution_ids":["https://openalex.org/I865915315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018542704","display_name":"Bernhard van der Sluis","orcid":"https://orcid.org/0000-0003-0369-9307"},"institutions":[{"id":"https://openalex.org/I913958620","display_name":"Erasmus University Rotterdam","ror":"https://ror.org/057w15z03","country_code":"NL","type":"education","lineage":["https://openalex.org/I913958620"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Bernhard van der Sluis","raw_affiliation_strings":["Department of Econometrics, Erasmus University Rotterdam","Erasmus University Rotterdam"],"raw_orcid":"https://orcid.org/0000-0003-0369-9307","affiliations":[{"raw_affiliation_string":"Department of Econometrics, Erasmus University Rotterdam","institution_ids":["https://openalex.org/I913958620"]},{"raw_affiliation_string":"Erasmus University Rotterdam","institution_ids":["https://openalex.org/I913958620"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5055838773"],"corresponding_institution_ids":["https://openalex.org/I198488067","https://openalex.org/I865915315"],"apc_list":null,"apc_paid":null,"fwci":4.3001,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.94869791,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"34","issue":"2","first_page":"654","last_page":"667"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11059","display_name":"Market Dynamics and Volatility","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11059","display_name":"Market Dynamics and Volatility","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10007","display_name":"Monetary Policy and Economic Impact","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/2000","display_name":"General Economics, Econometrics and Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.643741250038147},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6178238987922668},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5624222159385681},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.498563289642334},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4251770079135895},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.4249446392059326},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.41371771693229675},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.40018197894096375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.38460829854011536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24632880091667175}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.643741250038147},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6178238987922668},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5624222159385681},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.498563289642334},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4251770079135895},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.4249446392059326},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.41371771693229675},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.40018197894096375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38460829854011536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24632880091667175},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1080/10618600.2024.2403705","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2403705","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},{"id":"pmh:oai:pure.eur.nl:openaire/bf0acf22-b8d9-4e38-8260-dbe2235f4be8","is_oa":true,"landing_page_url":"https://pure.eur.nl/en/publications/bf0acf22-b8d9-4e38-8260-dbe2235f4be8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401266","display_name":"EUR Research Repository (Erasmus University Rotterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I913958620","host_organization_name":"Erasmus University Rotterdam","host_organization_lineage":["https://openalex.org/I913958620"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lin, Y, Song, M & van der Sluis, B 2025, 'Bootstrap inference for linear time-varying coefficient models in locally stationary time series', Journal of Computational and Graphical Statistics, vol. 34, no. 2, pp. 654-667. https://doi.org/10.1080/10618600.2024.2403705","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:research.vu.nl:openaire_cris_publications/84da16a7-1de3-4175-acf5-31ef5ba035ff","is_oa":true,"landing_page_url":"https://research.vu.nl/en/publications/84da16a7-1de3-4175-acf5-31ef5ba035ff","pdf_url":null,"source":{"id":"https://openalex.org/S4306401107","display_name":"VU Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I865915315","host_organization_name":"Vrije Universiteit Amsterdam","host_organization_lineage":["https://openalex.org/I865915315"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lin, Y, Song, M & van der Sluis, B 2025, 'Bootstrap inference for linear time-varying coefficient models in locally stationary time series', Journal of Computational and Graphical Statistics, vol. 34, no. 2, pp. 654-667. https://doi.org/10.1080/10618600.2024.2403705","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:research.vu.nl:openaire/84da16a7-1de3-4175-acf5-31ef5ba035ff","is_oa":true,"landing_page_url":"https://hdl.handle.net/1871.1/84da16a7-1de3-4175-acf5-31ef5ba035ff","pdf_url":null,"source":{"id":"https://openalex.org/S4306401107","display_name":"VU Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I865915315","host_organization_name":"Vrije Universiteit Amsterdam","host_organization_lineage":["https://openalex.org/I865915315"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Lin, Y, Song, M & van der Sluis, B 2025, 'Bootstrap inference for linear time-varying coefficient models in locally stationary time series', Journal of Computational and Graphical Statistics, vol. 34, no. 2, pp. 654-667. https://doi.org/10.1080/10618600.2024.2403705","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1080/10618600.2024.2403705","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10618600.2024.2403705","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1554737254","https://openalex.org/W1965254271","https://openalex.org/W1971846819","https://openalex.org/W2000647303","https://openalex.org/W2001288744","https://openalex.org/W2001992115","https://openalex.org/W2025607259","https://openalex.org/W2047694274","https://openalex.org/W2052828870","https://openalex.org/W2068019718","https://openalex.org/W2096850081","https://openalex.org/W2117380618","https://openalex.org/W2122524893","https://openalex.org/W2127275073","https://openalex.org/W2157852332","https://openalex.org/W2434015445","https://openalex.org/W2463486970","https://openalex.org/W2750106707","https://openalex.org/W2751213565","https://openalex.org/W2791603685","https://openalex.org/W2951823637","https://openalex.org/W2969132327","https://openalex.org/W3022346519","https://openalex.org/W3024235545","https://openalex.org/W3082177878","https://openalex.org/W3105105114","https://openalex.org/W3122904576","https://openalex.org/W3125754252","https://openalex.org/W3130827291","https://openalex.org/W3143236546","https://openalex.org/W3187488154","https://openalex.org/W4206856071","https://openalex.org/W4306958183","https://openalex.org/W4313594332","https://openalex.org/W4318815399","https://openalex.org/W4323351979","https://openalex.org/W4375851405","https://openalex.org/W4386035718","https://openalex.org/W4391123216","https://openalex.org/W4392840318"],"related_works":["https://openalex.org/W2055243143","https://openalex.org/W137830373","https://openalex.org/W3000984192","https://openalex.org/W2103073163","https://openalex.org/W4286952477","https://openalex.org/W4321348134","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660","https://openalex.org/W4387929287"],"abstract_inverted_index":{"Time-varying":[0],"coefficient":[1,13],"models":[2,17],"can":[3,83],"capture":[4],"evolving":[5],"relationships.":[6],"However,":[7,159],"constructing":[8],"asymptotic":[9],"confidence":[10,49],"bands":[11,50],"for":[12,77,94,178],"curves":[14],"in":[15,122,134],"these":[16,43],"is":[18,57],"challenging":[19],"due":[20],"to":[21,41,59,109,161],"slow":[22],"convergence":[23],"rates":[24],"and":[25,174],"the":[26,69,85,88,102,106,116,120,135,141,148],"presence":[27,149],"of":[28,87,105,119,150,169],"various":[29,110],"nuisance":[30,95],"parameters.":[31,96],"A":[32],"residual-based":[33],"sieve":[34],"bootstrap":[35,67,73],"method":[36],"has":[37],"recently":[38],"been":[39],"proposed":[40,142],"address":[42],"issues.":[44],"While":[45],"it":[46],"successfully":[47],"produces":[48],"with":[51,156],"accurate":[52],"empirical":[53],"coverage,":[54],"its":[55],"applicability":[56,118],"restricted":[58],"strictly":[60],"stationary":[61,79],"processes.":[62,80],"We":[63,129],"introduce":[64],"a":[65],"new":[66],"scheme,":[68],"local":[70],"blockwise":[71],"wild":[72],"(LBWB),":[74],"that":[75],"allows":[76],"locally":[78],"The":[81],"LBWB":[82,107,121],"replicate":[84],"distribution":[86],"parameter":[89],"estimates":[90],"while":[91],"automatically":[92],"accounting":[93],"An":[97],"extensive":[98],"simulation":[99],"study":[100],"reveals":[101],"superior":[103],"performance":[104],"compared":[108],"benchmark":[111],"approaches.":[112],"It":[113],"also":[114],"shows":[115],"potential":[117],"broader":[123],"scenarios,":[124],"including":[125],"time-varying":[126],"cointegrating":[127],"models.":[128],"then":[130],"examine":[131],"herding":[132,151,170],"effects":[133],"Chinese":[136],"renewable":[137],"energy":[138],"market":[139],"using":[140],"methods.":[143],"Our":[144],"findings":[145],"strongly":[146],"support":[147],"behaviors":[152],"before":[153],"2016,":[154],"aligning":[155],"earlier":[157],"studies.":[158],"contrary":[160],"previous":[162],"research,":[163],"we":[164],"find":[165],"no":[166],"significant":[167],"evidence":[168],"between":[171],"around":[172],"2018":[173],"2021.":[175],"Supplementary":[176],"materials":[177],"this":[179],"article":[180],"are":[181],"available":[182],"online.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-08T15:41:06.802602","created_date":"2025-10-10T00:00:00"}