Have Agricultural Derivatives and International Trade Boost the Brazilian Agricultural Sector? Empirical Evidence via Long-Run Non-Causality Test

This work analyzes long-run Granger causality relationships between Brazilian agricultural production, agricultural derivatives from the Brazilian Stock Exchange, international trade, interest rates, and nominal exchange rates. The methodology used is the long-run block Granger non-causality test proposed by Yamamoto and Kurozumi (2006) within a Vector Error Correction Model (VEC), for the period of 2001 to 2020. The generalized inverse procedure was applied to test for long-run Granger causality among the variables, with the degeneracy of the covariance matrix of the estimator detected through the test developed by Kurozumi (2003). The key findings confirm a long-run causal relationship from international trade to interest rates and agricultural derivatives, as well as from the latter two to the block consisting of international trade and agricultural output. The robustness analysis conducted validated the influence of derivatives on the economic growth of the agricultural sector over the past two decades.