Murilo José Borges

The empirical study about rural credit and its relationship with the growth of agricultural product is a relatively new subject in academic research in Brazil and is the central objective of this thesis. For this, three articles were built. The first aims to evaluate the impact that total rural credit and its modalities have on the agricultural product, from 1999 to 2018. To estimate the model, we used the autoregressive vectors (VAR) methodology and the causality of Granger It was observed that rural credit has undergone several changes in recent decades and its expansion occurred more than proportionally in relation to the agricultural product. It was concluded that the impact of total rural credit on agricultural output, expressed via elasticity, was 0.20%. As for the Granger causality tests, the results indicate that there is a temporal precedence of rural credit to the agricultural product and, therefore, unidirectionally, rural credit causes, in Granger's sense, Agricultural GDP. The second aims to analyze the determinants and the decomposition of rural credit from the perspective of the heterogeneities of the federation units from 2009 to 2017. To estimate the model, we used the panel data methodology with fixed, random effects and with autocorrelation correction and heteroscedasticity. The coefficients showed the expected signs and the decomposition of rural credit was reasonably different between the states with the highest and lowest participation in the volume of rural credit granted. The determinants of default, variation in planted area and agricultural yield are the components with the greatest impact on the volume of rural credit granted. On the other hand, the variables bank branches by planted area and agribusiness commercial openness coefficient exert less influence on rural credit. Finally, the third objective is to analyze the relationship between agricultural product and the financial system in Brazil, between 1999 and 2018. In addition, the specific objective is to define the optimal relationship between agricultural product and rural credit granted. To this end, the methodology used is the Error Corrected Vector Auto Regression (VEC) and the Ordinary Least Squares (OLS) method. It is concluded that for the studied period the results are in accordance with the studies that show that the relationship between financial system development and economic growth depends on the type of proxy used to measure financial system development. Thus, among the selected variables, the agricultural product responds positively and more intensely to shocks in the proxies financiais intermediation/GDP and rural credit/agricultural GDP. Regarding the optimal relationship between agricultural product and rural credit, the estimated value of rural credit that maximizes agricultural product was approximately R$ 58 billion per quarter.