A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies

Detalhes bibliográficos
Autor(a) principal: Chen, Zhongfei
Data de Publicação: 2015
Outros Autores: Barros, Carlos Pestana, Borges, Maria Rosa
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.5/27006
Resumo: This paper analyses the technical efficiency of Chinese fossil-fuel electricity generation companies from 1999 to 2011, using a Bayesian stochastic frontier model. The results reveal that efficiency varies among the fossil-fuel electricity generation companies that were analysed. We also focus on the factors of size, location, government ownership and mixed sources of electricity generation for the fossil-fuel electricity generation companies, and also examine their effects on the efficiency of these companies. Policy implications are derived.
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spelling A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companiesFossil-fuel Electricity Generation CompaniesStochastic Frontier AnalysisEfficiencyThis paper analyses the technical efficiency of Chinese fossil-fuel electricity generation companies from 1999 to 2011, using a Bayesian stochastic frontier model. The results reveal that efficiency varies among the fossil-fuel electricity generation companies that were analysed. We also focus on the factors of size, location, government ownership and mixed sources of electricity generation for the fossil-fuel electricity generation companies, and also examine their effects on the efficiency of these companies. Policy implications are derived.ElsevierRepositório da Universidade de LisboaChen, ZhongfeiBarros, Carlos PestanaBorges, Maria Rosa2023-01-23T21:37:06Z20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/27006engChen, Zhongfei; Carlos Pestana Barros and Maria Rosa Borges .(2015). “A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies”. Energy Economics, Vol. 48 : pp. 136-144.0140 - 98830.1016/j.eneco.2014.12.020info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-11-20T19:27:55Zoai:repositorio.ul.pt:10400.5/27006Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-11-20T19:27:55Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies
title A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies
spellingShingle A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies
Chen, Zhongfei
Fossil-fuel Electricity Generation Companies
Stochastic Frontier Analysis
Efficiency
title_short A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies
title_full A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies
title_fullStr A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies
title_full_unstemmed A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies
title_sort A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies
author Chen, Zhongfei
author_facet Chen, Zhongfei
Barros, Carlos Pestana
Borges, Maria Rosa
author_role author
author2 Barros, Carlos Pestana
Borges, Maria Rosa
author2_role author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Chen, Zhongfei
Barros, Carlos Pestana
Borges, Maria Rosa
dc.subject.por.fl_str_mv Fossil-fuel Electricity Generation Companies
Stochastic Frontier Analysis
Efficiency
topic Fossil-fuel Electricity Generation Companies
Stochastic Frontier Analysis
Efficiency
description This paper analyses the technical efficiency of Chinese fossil-fuel electricity generation companies from 1999 to 2011, using a Bayesian stochastic frontier model. The results reveal that efficiency varies among the fossil-fuel electricity generation companies that were analysed. We also focus on the factors of size, location, government ownership and mixed sources of electricity generation for the fossil-fuel electricity generation companies, and also examine their effects on the efficiency of these companies. Policy implications are derived.
publishDate 2015
dc.date.none.fl_str_mv 2015
2015-01-01T00:00:00Z
2023-01-23T21:37:06Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/27006
url http://hdl.handle.net/10400.5/27006
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Chen, Zhongfei; Carlos Pestana Barros and Maria Rosa Borges .(2015). “A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies”. Energy Economics, Vol. 48 : pp. 136-144.
0140 - 9883
0.1016/j.eneco.2014.12.020
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv mluisa.alvim@gmail.com
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