Comportamento das variáveis dos custos de produção das culturas de café, cana-de-açúcar, milho e soja em relação ao preço de venda

• Ano de defesa: 2010
• Autor(a) principal: Duarte, Sérgio Lemos
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; BR; Programa de Pós-graduação em Administração; Ciências Sociais Aplicadas; UFU
• Palavras-chave em Português: Custos; Agronegócios; Custo industrial; Produtos agrícolas - Custos; Agribusiness; Administração rural; Costs; Farm managing; CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO
• Link de acesso: https://repositorio.ufu.br/handle/123456789/11931

The behavior of the production costs of coffee, sugar cane, corn and soybean in relation to sales price, can provide tools for management controls to agricultural producers. The objective of this study is to investigate how it was this behavior in these cultures, in relation to the selling price or gross revenue. For this, it was used the data s costs and gross revenues from the yearbook of Brazilian agriculture whose name is Agrianual and analyzed period was from 1999 to 2008. It has applied at the cost s variables, the statistical test of Kolmogorov- Smirnov (Lilliefors) in order to verify the normality of the data. Subsequently, it was calculated the correlation coefficient of Spearman for data whose distribution was not normal and the Pearson s correlation coefficient when data s distribution was normal. The objective of the correlation´s tests was to consider whether data were correlated linearly. After that, it was calculated the coefficient of determination, whose defines how a variable cost is explained by the variable gross revenue, and also obtained the linear regression equation in order to determine the dependency between variables with the standard error of estimate. The results showed that, for the formation s period of all analyzed cultures, the costs of "seedlings" and "planting material" were the variables that provided the better explanation for the price variable. At other times it was found that several variables in production costs were linearly correlated and could be predicted with the gross revenue, thus can providing the rural farmers, means to plan their budgets and a method for analysis of costs.