Comportamento dos custos de produção e preços da soja OGM e convencional no Brasil em relação às variáveis econômicas

Abstract

Soy plays a central role in Brazilian agribusiness, a sector that accounted for approximately 25% of the country’s GDP and 48% of total exports in 2023. In the same year, soybean trade generated more than USD 60 billion in revenue, highlighting its economic significance. The formation of costs and prices in this sector is influenced by macroeconomic variables that directly affect profitability and competitiveness. Given this context, this study analyzed the impact of economic factors on production costs and pricing of genetically modified (GM) and conventional soybeans in the main producing regions of Brazil. The research adopted a quantitative approach, employing panel data regression models to examine the effects of the Exchange Rate, SELIC Rate, GDP, IPCA (Broad Consumer Price Index), and Country Risk on soybean costs and prices between 2014 and 2023. Data were obtained from secondary sources, including the National Supply Company (Conab), the Brazilian Institute of Geography and Statistics (IBGE), the Central Bank of Brazil, and the Institute of Applied Economic Research (IPEA). Econometric modeling was conducted using the Stata software, ensuring statistical robustness in the estimation of coefficients and model selection. The results indicate that the Exchange Rate was the most influential variable in the cost structure, particularly for imported inputs such as fertilizers and pesticides, with a more pronounced impact on genetically modified soybeans, due to their greater dependence on biotechnology and patented inputs. The SELIC Rate significantly affected financial costs, including administration and technical assistance, increasing financial burdens and restricting investments in the sector. GDP and IPCA had more indirect effects on costs, while Country Risk impacted longterm investments, such as the depreciation of machinery and agricultural infrastructure. The analysis of findings through the lens of Contingency Theory reinforces the need for adaptation in the agricultural sector to economic fluctuations, highlighting the importance of strategies such as currency hedging, supplier diversification, and agricultural credit policies to mitigate financial and exchange rate risks. The study contributes to a deeper understanding of the relationship between macroeconomics and agricultural costs, offering insights for producers, agribusiness managers, and policymakers. Future research may expand the analysis to other agricultural commodities, such as cotton and wheat, incorporate climate variables, and explore international comparisons, further enhancing the understanding of macroeconomic impacts on sector competitiveness.