Crédito e produtividade rural no Brasil: uma análise por bioma e por setores familiares e patronais

Abstract

This study aims to assess the impacts of rural credit and productivity policies on family farming in the various Brazilian biomes. It is important to study, in Brazil, the perspectives and policies for the development of an economy with low emission of Greenhouse Gases, as well as the role of rural credit and productivity for this. The main objective is to identify the implications of i. the rural credit through the National Family Farming Strengthening Program (in Portuguese, Programa Nacional de Fortalecimento da Agricultura Familiar – Pronaf), and ii. the increases in productivity in the rural area. The impacts at the sectoral, regional, and macroeconomic levels are analyzed. The study is based on the theoretical framework of rural production in Brazil and the measurement of the effects of rural policies, as well as on the literature on climate change, rural sectors, and sustainable solutions to the rural productivity loss. Under these lights and under a strictly economic perspective, a rigorous analysis of the impacts of increases in rural credit and productivity, related to farmers in Brazilian territory – family and patronal farmers separately considered –, is carried out in this Dissertation. Such analysis uses a Computable General Equilibrium (CGE) model specially built for analysis of the rural sectors in the Brazilian biomes: TERM-Biomas. The methodology systematically considers interregional and intersectoral relations. The results of the simulation exercise regarding Pronaf are presented as a comparison of the variables of interest values in the simulation considering this specific rural credit with those in a base scenario without such program, according to the sectors and regions of occurrence. The shock occurs only on the family farming sectors of the model in recursive dynamics, directly impacting the production of these sectors. The main conclusion, given this simulation, is that, when compared to a base scenario, all regions of the model win, in the most varied magnitudes. Regions with greater participation in family farming production earn more than others. Up to the year 2020, some regions – predominantly from the Caatinga biome –show comparative losses. This was because, since traditionally family farming regions would have their demands for primary factors more drastically increased, investments and jobs migrate, for example, from those regions of Caatinga. When the results are analyzed in a wider timeframe, however, the results suggest general gains. The more vulnerable and specialized in family farming sectors are the regions, the greater are the gains. The production, the employment, and the investment levels are directly affected when analyzed by sector. The patronal farming sectors have their activities impacted as well, although to a lesser extent, in addition to some non-agrarian sectors indirectly affected, mainly those of fertilizers, pesticides, transport, and industrial and public utility services. The indirect effects are identified as important. When it comes to analyzing the results of productivity increases simulations in the Brazilian rural sectors, the analysis is in a comparative and static way, showing the expected variations in terms of annual percentage. In general, the productivity increases simulated, within the effects considered in the model, decrease the demand for primary factors. The simulations are performed by commodity. The findings are in line with what was expected by the hypotheses raised in this study and allow the following conclusion: when it comes to the theme addressed in this research, the advance comes in the study of specific rural policies and programs in Brazil using a methodology that allows the impact assessment. This Dissertation also improves the development of traditional CGE models for the Brazilian economy and fills important gaps when considering never used sectorial and regional aggregations, in a well-supported way in the literature and with important justifications for that. In sectoral terms, the progress made in considering the varied rural commodities in a disaggregated way in their family and patronal sectors is not trivial, but important. In regional terms, the consideration of climatic and geographic characteristics, for example, through the disaggregation of Brazilian States in different regions according to their biomes, is important and another step forward in CGE modeling in the field of study that this research covers.