Autoregressive vectors model in the analysis of the determinants of soybean production in Brazil
DOI:
https://doi.org/10.5902/2179460X40524Keywords:
Autoregressive models, Time series, Soybean ProductionAbstract
The general objective of this work was to identify what were the determinants of soybean production increase in Brazil, between 1980 and 2015. This work uses the Self-Regressive Vector (VAR) methodology for the estimation of empirical models. Allow the obtaining of evidence capable of clarifying the question about the determinant factors of the soybean productivity in this period. They pointed evidences of a greater relation between the soybean productivity increase and the physicochemical innovations. In addition, as the data reveal, there is idle capacity to expand soybean production, as well as increased productivity for the coming years. The empirical analysis suggests that, in fact, soybean productivity in Brazil is increasing, as occurred in the forecast test performed in this study.
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