Assessing the significance of covariates in output oriented data envelopment analysis with two stage regression models.
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/993719 |
Resumo: | We propose alternative regression models to assess the effects of covariates in output oriented DEA scores. We use probability choice models combined with specifications related to the gamma and to the truncated normal families of distributions. These specifications imply different two stage regression models and alternative quasi maximum likelihood estimators. We apply these methods to assess the significance of technical effects ? type of unit, processes improvement and technology impact ? affecting DEA efficiency scores computed to agricultural research production in Brazil, measured through Embrapa. We favor models taking into account the whole sample of efficiency scores and not only the inefficient units. In our application we conclude that type of unit and processes improvement are significant effects, with the latter effect negatively associated to the efficiency of the units classified into the type of unit considered more efficient. |
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Assessing the significance of covariates in output oriented data envelopment analysis with two stage regression models.Melhoria de processoModelo de regressãoFatoriais fracionáriosMétodo estatísticoPesquisa agrícolaData analysisRegression analysisAgricultural researchWe propose alternative regression models to assess the effects of covariates in output oriented DEA scores. We use probability choice models combined with specifications related to the gamma and to the truncated normal families of distributions. These specifications imply different two stage regression models and alternative quasi maximum likelihood estimators. We apply these methods to assess the significance of technical effects ? type of unit, processes improvement and technology impact ? affecting DEA efficiency scores computed to agricultural research production in Brazil, measured through Embrapa. We favor models taking into account the whole sample of efficiency scores and not only the inefficient units. In our application we conclude that type of unit and processes improvement are significant effects, with the latter effect negatively associated to the efficiency of the units classified into the type of unit considered more efficient.GERALDO DA SILVA E SOUZA, SGE; ELIANE GONCALVES GOMES, SGE.SOUZA, G. da S. eGOMES, E. G.2014-08-29T11:11:11Z2014-08-29T11:11:11Z2014-08-2920142014-08-29T11:11:11Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleWSEAS Transactions on Systems, v. 13, p. 440-449, 2014.http://www.alice.cnptia.embrapa.br/alice/handle/doc/993719enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2017-08-16T00:47:03Zoai:www.alice.cnptia.embrapa.br:doc/993719Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-08-16T00:47:03falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-08-16T00:47:03Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Assessing the significance of covariates in output oriented data envelopment analysis with two stage regression models. |
title |
Assessing the significance of covariates in output oriented data envelopment analysis with two stage regression models. |
spellingShingle |
Assessing the significance of covariates in output oriented data envelopment analysis with two stage regression models. SOUZA, G. da S. e Melhoria de processo Modelo de regressão Fatoriais fracionários Método estatístico Pesquisa agrícola Data analysis Regression analysis Agricultural research |
title_short |
Assessing the significance of covariates in output oriented data envelopment analysis with two stage regression models. |
title_full |
Assessing the significance of covariates in output oriented data envelopment analysis with two stage regression models. |
title_fullStr |
Assessing the significance of covariates in output oriented data envelopment analysis with two stage regression models. |
title_full_unstemmed |
Assessing the significance of covariates in output oriented data envelopment analysis with two stage regression models. |
title_sort |
Assessing the significance of covariates in output oriented data envelopment analysis with two stage regression models. |
author |
SOUZA, G. da S. e |
author_facet |
SOUZA, G. da S. e GOMES, E. G. |
author_role |
author |
author2 |
GOMES, E. G. |
author2_role |
author |
dc.contributor.none.fl_str_mv |
GERALDO DA SILVA E SOUZA, SGE; ELIANE GONCALVES GOMES, SGE. |
dc.contributor.author.fl_str_mv |
SOUZA, G. da S. e GOMES, E. G. |
dc.subject.por.fl_str_mv |
Melhoria de processo Modelo de regressão Fatoriais fracionários Método estatístico Pesquisa agrícola Data analysis Regression analysis Agricultural research |
topic |
Melhoria de processo Modelo de regressão Fatoriais fracionários Método estatístico Pesquisa agrícola Data analysis Regression analysis Agricultural research |
description |
We propose alternative regression models to assess the effects of covariates in output oriented DEA scores. We use probability choice models combined with specifications related to the gamma and to the truncated normal families of distributions. These specifications imply different two stage regression models and alternative quasi maximum likelihood estimators. We apply these methods to assess the significance of technical effects ? type of unit, processes improvement and technology impact ? affecting DEA efficiency scores computed to agricultural research production in Brazil, measured through Embrapa. We favor models taking into account the whole sample of efficiency scores and not only the inefficient units. In our application we conclude that type of unit and processes improvement are significant effects, with the latter effect negatively associated to the efficiency of the units classified into the type of unit considered more efficient. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-08-29T11:11:11Z 2014-08-29T11:11:11Z 2014-08-29 2014 2014-08-29T11:11:11Z |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
WSEAS Transactions on Systems, v. 13, p. 440-449, 2014. http://www.alice.cnptia.embrapa.br/alice/handle/doc/993719 |
identifier_str_mv |
WSEAS Transactions on Systems, v. 13, p. 440-449, 2014. |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/993719 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
collection |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
repository.name.fl_str_mv |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
_version_ |
1794503393648050176 |