Análise da eficiência técnica agropecuária das microrregiões do estado do Paraná nos anos de 2006 e 2017
Ano de defesa: | 2022 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | , , |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Estadual do Oeste do Paraná
Toledo |
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Desenvolvimento Regional e Agronegócio
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Departamento: |
Centro de Ciências Sociais Aplicadas
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País: |
Brasil
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Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
Link de acesso: | https://tede.unioeste.br/handle/tede/6458 |
Resumo: | Agriculture plays an important role in the economy of Paraná and Brazil. Studying the technical efficiency of this sector becomes essential to improve competitive performance and also improve the use of inputs used in production. In this way, the work analyzed the technical efficiency of the 39 micro-regions of Paraná in the years 2006 and 2017, through the Agricultural Censuses. The data indicated that there was an increase in the fleet of machines and implements and a decrease in the number of people employed in the field. The useful area of the establishments remained the same during the period, while the value of production increased, indicating a vertical growth. The DEA-CCR model from the perspective of inputs, it emerged that, in 2006, there were nine technically efficient micro-regions and, for the year 2017, this number dropped to two, indicating a change in the productive paradigm of the State, since the methodology is comparative and depicts only one year at a time. Through the DEA-Malmquist model, it was possible to compare the technical efficiency of the years 2006 and 2017, which presented an evolution in only two micro-regions, Floraí and Goioerê, a very small number for a State so vigorous in the agricultural sector, indicating that the new technologies, but they are not technically oriented and do not have adequate education to optimize their use. Thus serving as an alert for the entire production chain. |