Fractional regression models for second stage DEA efficiency analyses
Autor(a) principal: | |
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Data de Publicação: | 2010 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.5/29324 |
Resumo: | Data envelopment analysis (DEA) is commonly used to measure the relative efficiency of decision-making units. Often, in a second stage, a regression model is estimated to relate DEA efficiency scores to exogenous factors. In this paper, we argue that the traditional linear or tobit approaches to second-stage DEA analysis do not constitute a reasonable data-generating process for DEA scores. Under the assumption that DEA scores can be treated as descriptive measures of the relative performance of units in the sample, we show that using fractional regression models is the most natural way of modeling bounded, proportional response variables such as DEA scores. We also propose generalizations of these models and, given that DEA scores take frequently the value of unity, examine the use of two-part models in this framework. Several tests suitable for assessing the specification of each alternative model are also discussed |
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Fractional regression models for second stage DEA efficiency analysesSecond-Stage DEAFractional DataSpecification TestsOne OutcomesTwo-Part ModelsData envelopment analysis (DEA) is commonly used to measure the relative efficiency of decision-making units. Often, in a second stage, a regression model is estimated to relate DEA efficiency scores to exogenous factors. In this paper, we argue that the traditional linear or tobit approaches to second-stage DEA analysis do not constitute a reasonable data-generating process for DEA scores. Under the assumption that DEA scores can be treated as descriptive measures of the relative performance of units in the sample, we show that using fractional regression models is the most natural way of modeling bounded, proportional response variables such as DEA scores. We also propose generalizations of these models and, given that DEA scores take frequently the value of unity, examine the use of two-part models in this framework. Several tests suitable for assessing the specification of each alternative model are also discussedSpringerRepositório da Universidade de LisboaRamalho, Esmeralda A.Ramalho, Joaquim J.S.Henriques, Pedro D.2023-11-08T09:44:35Z20102010-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/29324engRamalho, Esmeralda A.; Joaquim J.S. Ramalho and Pedro D. Henriques .(2010). “Fractional regression models for second stage DEA efficiency analyses”. Journal of Productivity Analysis, Vol. 34: pp. 239–255. (Search PDF in 2023).DOI: 10.1007/s11123-010-0184-0info: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:RCAAP2023-11-12T01:31:46Zoai:www.repository.utl.pt:10400.5/29324Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:37:59.709578Repositório 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 |
Fractional regression models for second stage DEA efficiency analyses |
title |
Fractional regression models for second stage DEA efficiency analyses |
spellingShingle |
Fractional regression models for second stage DEA efficiency analyses Ramalho, Esmeralda A. Second-Stage DEA Fractional Data Specification Tests One Outcomes Two-Part Models |
title_short |
Fractional regression models for second stage DEA efficiency analyses |
title_full |
Fractional regression models for second stage DEA efficiency analyses |
title_fullStr |
Fractional regression models for second stage DEA efficiency analyses |
title_full_unstemmed |
Fractional regression models for second stage DEA efficiency analyses |
title_sort |
Fractional regression models for second stage DEA efficiency analyses |
author |
Ramalho, Esmeralda A. |
author_facet |
Ramalho, Esmeralda A. Ramalho, Joaquim J.S. Henriques, Pedro D. |
author_role |
author |
author2 |
Ramalho, Joaquim J.S. Henriques, Pedro D. |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Ramalho, Esmeralda A. Ramalho, Joaquim J.S. Henriques, Pedro D. |
dc.subject.por.fl_str_mv |
Second-Stage DEA Fractional Data Specification Tests One Outcomes Two-Part Models |
topic |
Second-Stage DEA Fractional Data Specification Tests One Outcomes Two-Part Models |
description |
Data envelopment analysis (DEA) is commonly used to measure the relative efficiency of decision-making units. Often, in a second stage, a regression model is estimated to relate DEA efficiency scores to exogenous factors. In this paper, we argue that the traditional linear or tobit approaches to second-stage DEA analysis do not constitute a reasonable data-generating process for DEA scores. Under the assumption that DEA scores can be treated as descriptive measures of the relative performance of units in the sample, we show that using fractional regression models is the most natural way of modeling bounded, proportional response variables such as DEA scores. We also propose generalizations of these models and, given that DEA scores take frequently the value of unity, examine the use of two-part models in this framework. Several tests suitable for assessing the specification of each alternative model are also discussed |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010 2010-01-01T00:00:00Z 2023-11-08T09:44:35Z |
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/10400.5/29324 |
url |
http://hdl.handle.net/10400.5/29324 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Ramalho, Esmeralda A.; Joaquim J.S. Ramalho and Pedro D. Henriques .(2010). “Fractional regression models for second stage DEA efficiency analyses”. Journal of Productivity Analysis, Vol. 34: pp. 239–255. (Search PDF in 2023). DOI: 10.1007/s11123-010-0184-0 |
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 |
Springer |
publisher.none.fl_str_mv |
Springer |
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 |
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1799134938808713216 |