Eficiência produtiva na agropecuária dos municípios do Rio Grande do Sul

Detalhes bibliográficos
Ano de defesa: 2014
Autor(a) principal: Ruberto, Isabel Von Grafen
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Santa Maria
BR
Administração
UFSM
Programa de Pós-Graduação em Administração
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://repositorio.ufsm.br/handle/1/4687
Resumo: The objective of this study was to evaluate the efficiency of agricultural production in the municipalities of Rio Grande do Sul and identify their determinants in 2006. Thus, the method of data envelopment analysis (DEA) with the product orientation, with constant returns to scale (CCR), and also with variable returns to scale (BCC) was used. The data used to calculate the performance indicators of the municipalities were obtained from the Brazilian Institute of Geography and Statistics (IBGE), referring to the last agricultural census (2006) the State of Rio Grande do Sul four input variables (inputs) were used, them being Land, Capital, Labour and Petrochemicals, and two output variables (outputs) , which are the values of livestock and agro-industrial production and summed the values o crop production. Analyzing the variables, it was found that the input has a negative relationship with efficiency, while output has positive relationship. CCR model in DEA efficient 13 municipalities (with indicator equal to 1.00) were identified, and found that most municipalities (30.77 %) have efficiency indicator between 0.11 and 0.20. You DEA BCC efficient 27 municipalities were identified, the majority (27.73 %) has no indicator of efficiency between 0.21 and 0.30. The Labour, Land, Capital and Petrochemicals variables are, respectively, those that determine the efficiency of the best cities in the state.