A relação de variáveis econômicas nos custos e preço do café commodity nas principais cidades produtoras do Brasil

• Ano de defesa: 2024
• Autor(a) principal: Borges Junior, Derotides Resende
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; Brasil; Programa de Pós-graduação em Ciências Contábeis
• Palavras-chave em Português: café; variável econômica; preço; custo; CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO::CIENCIAS CONTABEIS; Contabilidade; Controladoria; Café - Cultivo; ODS::ODS 8. Trabalho decente e crescimento econômico - Promover o crescimento econômico sustentado, inclusivo e sustentável, emprego pleno e produtivo, e trabalho decente para todos.
• Link de acesso: https://repositorio.ufu.br/handle/123456789/43313; http://doi.org/10.14393/ufu.di.2024.234

Brazil plays a crucial role in global coffee production and exports. According to data from the Ministry of Agriculture, Livestock and Supply from 2022, the country is the largest producer and exporter of coffee globally, in addition to occupying the second position in world consumption of this product. Furthermore, coffee is an essential component of the Brazilian trade balance. Its exports generate revenue in foreign currency, balancing the country's external accounts. Fluctuations in exchange rates, global prices of agricultural commodities, as well as variables such as GDP, interest rates, inflation and country risk, can significantly impact producers' profit margins. In this context, contingency theory becomes relevant. It allows us to understand how these variables interact and relate to the price and cost of coffee, helping to analyze these complexities and make strategic decisions for the coffee sector. To achieve the outlined objective, it was necessary to answer the research question: What is the relationship between economic variables and the cost and price of commodity coffee in the main producing cities in Brazil? A rigorous investigation was conducted using descriptive statistical analysis, including correlation and multiple linear regression, in the main coffee producing cities. The purpose of choosing multiple linear regression was to identify variables that present statistically significant relationships in the context of the commodity coffee market. The time series examined covered the period from 2014 to 2022. In summary, the results of this research corroborate the interdependence between the variables and the prices and costs associated with commodity coffee. Notably, the most impacted dependent variables are price, labor costs, fertilizers and pesticides, which represent more than fifty percent of the coffee farmer's costs. The findings of this research have social relevance, benefiting coffee producers by improving productivity and the strategy to deal with economic variables. Effective planning, rigorous control and continuous monitoring of agricultural activity, combined with careful cost management, will provide valuable information for making informed and assertive decisions. Thus, these conclusions contribute to a deeper understanding of the factors that influence the dynamics of this essential market for the global economy.