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| Registros recuperados : 166 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
18/12/2017 |
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Data da última atualização: |
18/12/2017 |
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Autoria: |
MORAES-OLIVEIRA, A. F. de; APARECIDO, L. E. de O.; FIGUEIRA, S. R. F. |
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Afiliação: |
Adriana Ferreira de Moraes-Oliveira, Universidade Estadual Paulista - Unesp/FCAV/DEAE; Lucas Eduardo de Oliveira Aparecido, Unesp/FCAV/DCE; Sérgio Rangel Fernandes Figueira, Universidade Estadual Paulista - Unesp/FCAV/DEAE. |
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Título: |
Economic and climatic models for estimating coffee supply. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Pesquisa Agropecuária Brasileira, Brasília, DF, v. 52, n. 12, p. 1158-1166, dez. 2017. |
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Idioma: |
Português |
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Notas: |
Título em português: Modelos econômicos e climáticos para estimativa da oferta cafeeira. |
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Conteúdo: |
The 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. |
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Palavras-Chave: |
Modelagem; Rural credit. |
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Thesagro: |
Clima; Coffea Arábica; Crédito rural; Econometria. |
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Thesaurus NAL: |
Climate; Econometrics; Models. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/169148/1/Economic-and-climatic-models.pdf
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Marc: |
LEADER 02129naa a2200265 a 4500
001 2082735
005 2017-12-18
008 2017 bl uuuu u00u1 u #d
100 1 $aMORAES-OLIVEIRA, A. F. de
245 $aEconomic and climatic models for estimating coffee supply.
260 $c2017
500 $aTítulo em português: Modelos econômicos e climáticos para estimativa da oferta cafeeira.
520 $aThe 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.
650 $aClimate
650 $aEconometrics
650 $aModels
650 $aClima
650 $aCoffea Arábica
650 $aCrédito rural
650 $aEconometria
653 $aModelagem
653 $aRural credit
700 1 $aAPARECIDO, L. E. de O.
700 1 $aFIGUEIRA, S. R. F.
773 $tPesquisa Agropecuária Brasileira, Brasília, DF$gv. 52, n. 12, p. 1158-1166, dez. 2017.
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Embrapa Unidades Centrais (AI-SEDE) |
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