Economic and climatic models for estimating coffee supply

dc.contributor.authorde Moraes-Oliveira, Adriana Ferreira [UNESP]
dc.contributor.authorAparecido, Lucas Eduardo de Oliveira [UNESP]
dc.contributor.authorFigueira, Sérgio Rangel Fernandes [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-12-11T17:17:03Z
dc.date.available2018-12-11T17:17:03Z
dc.date.issued2017-12-01
dc.description.abstractThe objective of this work was to estimate the coffee supply by calibrating statistical models with economic and climatic variables for the main producing regions of the state of São Paulo, Brazil. The regions were Batatais, Caconde, Cássia dos Coqueiros, Cristais Paulista, Espírito Santo do Pinhal, Marília, Mococa, and Osvaldo Cruz. Data on coffee supply, economic variables (rural credit, rural agricultural credit, and production value), and climatic variables (air temperature, rainfall, potential evapotranspiration, water deficit, and water surplus) for each region, during the period from 2000-2014, were used. The models were calibrated using multiple linear regression, and all possible combinations were tested for selecting the variables. Coffee supply was the dependent variable, and the other ones were considered independent. The accuracy and precision of the models were assessed by the mean absolute percentage error and the adjusted coefficient of determination, respectively. The variables that most affect coffee supply are production value and air temperature. Coffee supply can be estimated with multiple linear regressions using economic and climatic variables. The most accurate models are those calibrated to estimate coffee supply for the regions of Cássia dos Coqueiros and Osvaldo Cruz.en
dc.description.affiliationUniversidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias Departamento de Economia Administração e Educação, Via de Acesso Prof. Paulo Donato Castellane, s/no
dc.description.affiliationUnesp Faculdade de Ciências Agrárias e Veterinárias Departamento de Ciências Exatas, Via de Acesso Prof. Paulo Donato Castellane, s/no
dc.description.affiliationUnespUniversidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias Departamento de Economia Administração e Educação, Via de Acesso Prof. Paulo Donato Castellane, s/no
dc.description.affiliationUnespUnesp Faculdade de Ciências Agrárias e Veterinárias Departamento de Ciências Exatas, Via de Acesso Prof. Paulo Donato Castellane, s/no
dc.format.extent1158-1166
dc.identifierhttp://dx.doi.org/10.1590/S0100-204X2017001200004
dc.identifier.citationPesquisa Agropecuaria Brasileira, v. 52, n. 12, p. 1158-1166, 2017.
dc.identifier.doi10.1590/S0100-204X2017001200004
dc.identifier.fileS0100-204X2017001201158.pdf
dc.identifier.issn1678-3921
dc.identifier.issn0100-204X
dc.identifier.scieloS0100-204X2017001201158
dc.identifier.scopus2-s2.0-85038855650
dc.identifier.urihttp://hdl.handle.net/11449/175679
dc.language.isoeng
dc.relation.ispartofPesquisa Agropecuaria Brasileira
dc.relation.ispartofsjr0,469
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectClimate
dc.subjectCoffea arabica
dc.subjectEconometrics
dc.subjectModelling
dc.subjectRural credit
dc.titleEconomic and climatic models for estimating coffee supplyen
dc.typeArtigo
unesp.departmentCiências Exatas - FCAVpt
unesp.departmentEconomia, Administração e Educação - FCAVpt

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