{"id":"https://openalex.org/W3113933862","doi":"https://doi.org/10.1007/s10287-020-00382-5","title":"Including news data in forecasting macro economic performance of China","display_name":"Including news data in forecasting macro economic performance of China","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https://openalex.org/W3113933862","doi":"https://doi.org/10.1007/s10287-020-00382-5","mag":"3113933862"},"language":"en","primary_location":{"id":"doi:10.1007/s10287-020-00382-5","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10287-020-00382-5","pdf_url":null,"source":{"id":"https://openalex.org/S28822639","display_name":"Computational Management Science","issn_l":"1619-697X","issn":["1619-697X","1619-6988"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Management Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024279851","display_name":"Asger Lunde","orcid":"https://orcid.org/0000-0002-0805-0892"},"institutions":[{"id":"https://openalex.org/I180519160","display_name":"Copenhagen Business School","ror":"https://ror.org/04sppb023","country_code":"DK","type":"education","lineage":["https://openalex.org/I180519160"]},{"id":"https://openalex.org/I204337017","display_name":"Aarhus University","ror":"https://ror.org/01aj84f44","country_code":"DK","type":"education","lineage":["https://openalex.org/I204337017"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Asger Lunde","raw_affiliation_strings":["CREATES, Department of Economics and Business Economics, Aarhus University, Fuglesangs All\u00e9 4, 8210, Aarhus V, Denmark","Copenhagen Economics, Langebrogade 1B, 1411, Copenhagen K, Denmark"],"raw_orcid":"https://orcid.org/0000-0002-0805-0892","affiliations":[{"raw_affiliation_string":"CREATES, Department of Economics and Business Economics, Aarhus University, Fuglesangs All\u00e9 4, 8210, Aarhus V, Denmark","institution_ids":["https://openalex.org/I204337017"]},{"raw_affiliation_string":"Copenhagen Economics, Langebrogade 1B, 1411, Copenhagen K, Denmark","institution_ids":["https://openalex.org/I180519160"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051406373","display_name":"Miha Torkar","orcid":"https://orcid.org/0000-0002-1118-1391"},"institutions":[{"id":"https://openalex.org/I3006985408","display_name":"Jo\u017eef Stefan Institute","ror":"https://ror.org/05060sz93","country_code":"SI","type":"facility","lineage":["https://openalex.org/I3006985408"]},{"id":"https://openalex.org/I4210113529","display_name":"Jo\u017eef Stefan International Postgraduate School","ror":"https://ror.org/01hdkb925","country_code":"SI","type":"education","lineage":["https://openalex.org/I4210113529"]}],"countries":["SI"],"is_corresponding":false,"raw_author_name":"Miha Torkar","raw_affiliation_strings":["Artificial Intelligence Laboratory, Jozef Stefan Institute, Jamova cesta 39, 1000, Ljubljana, Slovenia","Jozef Stefan International Postgraduate School, Jamova cesta 39, 1000, Ljubljana, Slovenia"],"raw_orcid":"https://orcid.org/0000-0002-1118-1391","affiliations":[{"raw_affiliation_string":"Artificial Intelligence Laboratory, Jozef Stefan Institute, Jamova cesta 39, 1000, Ljubljana, Slovenia","institution_ids":["https://openalex.org/I3006985408"]},{"raw_affiliation_string":"Jozef Stefan International Postgraduate School, Jamova cesta 39, 1000, Ljubljana, Slovenia","institution_ids":["https://openalex.org/I4210113529"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5024279851"],"corresponding_institution_ids":["https://openalex.org/I180519160","https://openalex.org/I204337017"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":null,"fwci":0.9167,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.87430053,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"17","issue":"4","first_page":"585","last_page":"611"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11059","display_name":"Market Dynamics and Volatility","score":0.995199978351593,"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":0.995199978351593,"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/T10007","display_name":"Monetary Policy and Economic Impact","score":0.9933000206947327,"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"}},{"id":"https://openalex.org/T12368","display_name":"Grey System Theory Applications","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dynamic-factor","display_name":"Dynamic factor","score":0.7788287401199341},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.6821846961975098},{"id":"https://openalex.org/keywords/univariate","display_name":"Univariate","score":0.6534289121627808},{"id":"https://openalex.org/keywords/vector-autoregression","display_name":"Vector autoregression","score":0.5731556415557861},{"id":"https://openalex.org/keywords/gross-domestic-product","display_name":"Gross domestic product","score":0.48300158977508545},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.48222339153289795},{"id":"https://openalex.org/keywords/factor-analysis","display_name":"Factor analysis","score":0.46268144249916077},{"id":"https://openalex.org/keywords/consensus-forecast","display_name":"Consensus forecast","score":0.45600709319114685},{"id":"https://openalex.org/keywords/china","display_name":"China","score":0.45514681935310364},{"id":"https://openalex.org/keywords/macro","display_name":"Macro","score":0.4531916677951813},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.4460158348083496},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4284690320491791},{"id":"https://openalex.org/keywords/economic-forecasting","display_name":"Economic forecasting","score":0.4173862934112549},{"id":"https://openalex.org/keywords/economic-indicator","display_name":"Economic indicator","score":0.4155060052871704},{"id":"https://openalex.org/keywords/macroeconomics","display_name":"Macroeconomics","score":0.20162618160247803},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.19326156377792358},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.08327987790107727},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.07880821824073792}],"concepts":[{"id":"https://openalex.org/C155702961","wikidata":"https://www.wikidata.org/wiki/Q5318975","display_name":"Dynamic factor","level":2,"score":0.7788287401199341},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6821846961975098},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.6534289121627808},{"id":"https://openalex.org/C133029050","wikidata":"https://www.wikidata.org/wiki/Q385593","display_name":"Vector autoregression","level":2,"score":0.5731556415557861},{"id":"https://openalex.org/C114350782","wikidata":"https://www.wikidata.org/wiki/Q12638","display_name":"Gross domestic product","level":2,"score":0.48300158977508545},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.48222339153289795},{"id":"https://openalex.org/C10879293","wikidata":"https://www.wikidata.org/wiki/Q726474","display_name":"Factor analysis","level":2,"score":0.46268144249916077},{"id":"https://openalex.org/C120954023","wikidata":"https://www.wikidata.org/wiki/Q1127277","display_name":"Consensus forecast","level":2,"score":0.45600709319114685},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.45514681935310364},{"id":"https://openalex.org/C166955791","wikidata":"https://www.wikidata.org/wiki/Q629579","display_name":"Macro","level":2,"score":0.4531916677951813},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.4460158348083496},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4284690320491791},{"id":"https://openalex.org/C163068380","wikidata":"https://www.wikidata.org/wiki/Q3409313","display_name":"Economic forecasting","level":2,"score":0.4173862934112549},{"id":"https://openalex.org/C202353208","wikidata":"https://www.wikidata.org/wiki/Q1167393","display_name":"Economic indicator","level":2,"score":0.4155060052871704},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.20162618160247803},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.19326156377792358},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.08327987790107727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.07880821824073792},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s10287-020-00382-5","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10287-020-00382-5","pdf_url":null,"source":{"id":"https://openalex.org/S28822639","display_name":"Computational Management Science","issn_l":"1619-697X","issn":["1619-697X","1619-6988"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Management Science","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:spr:comgts:v:17:y:2020:i:4:d:10.1007_s10287-020-00382-5","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s10287-020-00382-5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:pure.atira.dk:publications/31b10f43-30f9-462b-b9fe-66f552d8a03b","is_oa":false,"landing_page_url":"https://pure.au.dk/portal/en/publications/31b10f43-30f9-462b-b9fe-66f552d8a03b","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Lunde, A & Torkar, M 2020, 'Including news data in forecasting macro economic performance of China', Computational Management Science, vol. 17, no. 4, pp. 585-611. https://doi.org/10.1007/s10287-020-00382-5","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W576960269","https://openalex.org/W648159467","https://openalex.org/W983095797","https://openalex.org/W1528512439","https://openalex.org/W1553858487","https://openalex.org/W1558252355","https://openalex.org/W1600708916","https://openalex.org/W1906850749","https://openalex.org/W1930476495","https://openalex.org/W1970487353","https://openalex.org/W2038601479","https://openalex.org/W2057539574","https://openalex.org/W2071171951","https://openalex.org/W2079563517","https://openalex.org/W2103958279","https://openalex.org/W2121160688","https://openalex.org/W2122966827","https://openalex.org/W2130704303","https://openalex.org/W2135046866","https://openalex.org/W2142025725","https://openalex.org/W2170202041","https://openalex.org/W2250453270","https://openalex.org/W2479138064","https://openalex.org/W2507060692","https://openalex.org/W2529086294","https://openalex.org/W2576301137","https://openalex.org/W2891565894","https://openalex.org/W2904984718","https://openalex.org/W3023770749","https://openalex.org/W3121185769","https://openalex.org/W3121468423","https://openalex.org/W3122870226","https://openalex.org/W3125070724","https://openalex.org/W3125950889","https://openalex.org/W4206563096","https://openalex.org/W4214661678","https://openalex.org/W4256642473","https://openalex.org/W4256645166"],"related_works":["https://openalex.org/W3123219359","https://openalex.org/W2142896437","https://openalex.org/W3125209858","https://openalex.org/W2152481464","https://openalex.org/W3146396974","https://openalex.org/W2183346404","https://openalex.org/W2589952369","https://openalex.org/W3125309971","https://openalex.org/W4241031265","https://openalex.org/W4367859310"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
