2 Moreover, medium <strong>and</strong> large farmers are more likely to be served by unsubsidized credit, especially with the current lower interest rates in the Brazilian ec<strong>on</strong>omy. <str<strong>on</strong>g>The</str<strong>on</strong>g> analysis in this work also indicates that credit for larger producers is associated with higher levels <str<strong>on</strong>g>of</str<strong>on</strong>g> deforestati<strong>on</strong>. This highlights the need for other instruments <strong>and</strong> policies to help c<strong>on</strong>serve Brazil’s natural capital, especially because the large producers occupy most <str<strong>on</strong>g>of</str<strong>on</strong>g> the agricultural l<strong>and</strong>. THREE DIMENSIONS OF THE RURAL CREDIT ANALYSIS This analysis evaluates the impacts <str<strong>on</strong>g>of</str<strong>on</strong>g> rural credit from three perspectives: credit lines (PRONAF, PRONAMP, <str<strong>on</strong>g>Rural</str<strong>on</strong>g> Savings, <strong>and</strong> Compulsory Resources), 3 producer types (individuals <strong>and</strong> firms) <strong>and</strong> credit uses (working capital, investments <strong>and</strong> trade). 4 Figure 1 shows the number <str<strong>on</strong>g>of</str<strong>on</strong>g> credit c<strong>on</strong>tracts, the credit amounts, <strong>and</strong> the distributi<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> area covered by the credit c<strong>on</strong>tracts in each category for each <str<strong>on</strong>g>of</str<strong>on</strong>g> these three perspectives. <str<strong>on</strong>g>The</str<strong>on</strong>g> analysis by credit line focuses <strong>on</strong> the four largest programs <strong>and</strong> funding sources: PRONAF, PRONAMP, <str<strong>on</strong>g>Rural</str<strong>on</strong>g> Savings (Restricted), <strong>and</strong> Compulsory Resources. Figure 1 shows that these four credit lines account for 91% <str<strong>on</strong>g>of</str<strong>on</strong>g> the number <str<strong>on</strong>g>of</str<strong>on</strong>g> c<strong>on</strong>tracts, 64% <str<strong>on</strong>g>of</str<strong>on</strong>g> the credit amount, <strong>and</strong> 84% <str<strong>on</strong>g>of</str<strong>on</strong>g> the area that receives rural credit in Brazil. Notice that the difference in the distributi<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> the number <str<strong>on</strong>g>of</str<strong>on</strong>g> c<strong>on</strong>tracts <strong>and</strong> credit amounts dem<strong>on</strong>strates how unequal the size <str<strong>on</strong>g>of</str<strong>on</strong>g> the c<strong>on</strong>tracts is across categories. For instance, PRONAF, which is the primary credit source for small farmers, represents 74% <str<strong>on</strong>g>of</str<strong>on</strong>g> the number <str<strong>on</strong>g>of</str<strong>on</strong>g> c<strong>on</strong>tracts, but <strong>on</strong>ly 14% <str<strong>on</strong>g>of</str<strong>on</strong>g> the credit amount <strong>and</strong> 16% <str<strong>on</strong>g>of</str<strong>on</strong>g> the area. <str<strong>on</strong>g>The</str<strong>on</strong>g> next dimensi<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> analysis focuses <strong>on</strong> the types <str<strong>on</strong>g>of</str<strong>on</strong>g> producers: individuals <strong>and</strong> firms. <str<strong>on</strong>g>The</str<strong>on</strong>g> high costs <str<strong>on</strong>g>of</str<strong>on</strong>g> starting a new business in Brazil <strong>and</strong> a special tax regime encourage agricultural producers to organize <strong>and</strong> present themselves to the tax authority as individuals rather than firms. Again, the unequal allocati<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> resources across categories st<strong>and</strong>s out: while <strong>on</strong>ly 1% <str<strong>on</strong>g>of</str<strong>on</strong>g> producers are firms, they account for 29% <str<strong>on</strong>g>of</str<strong>on</strong>g> the credit amount <strong>and</strong> 85% <str<strong>on</strong>g>of</str<strong>on</strong>g> the area that receives credit (see Figure 1). Finally, the analysis looks at the use <str<strong>on</strong>g>of</str<strong>on</strong>g> credit. <str<strong>on</strong>g>The</str<strong>on</strong>g> rural credit policy in Brazil supports three major uses <str<strong>on</strong>g>of</str<strong>on</strong>g> credit: working capital, investment, <strong>and</strong> trade. Working capital makes up the major use <str<strong>on</strong>g>of</str<strong>on</strong>g> credit c<strong>on</strong>sidering credit amounts. Figure 1 also shows the credit use for investment is still quite limited in terms <str<strong>on</strong>g>of</str<strong>on</strong>g> amount (23%) <strong>and</strong> covered area (7%) compared to working capital (57% <strong>and</strong> 93%, respectively). 3 <str<strong>on</strong>g>The</str<strong>on</strong>g> PRONAF program is the Nati<strong>on</strong>al Program for Family Farming (Programa Naci<strong>on</strong>al de Fortalecimento da Agricultura Familiar). <str<strong>on</strong>g>The</str<strong>on</strong>g> PRONAMP program is the Nati<strong>on</strong>al Program to Support Medium Producers (Programa Naci<strong>on</strong>al de Apoio ao Médio Produtor <str<strong>on</strong>g>Rural</str<strong>on</strong>g>). <str<strong>on</strong>g>Rural</str<strong>on</strong>g> Savings – Restricted (Poupança <str<strong>on</strong>g>Rural</str<strong>on</strong>g> - C<strong>on</strong>trolados) <strong>and</strong> Compulsory Resources (Recursos Obrigatórios - MCR 6.2) are funding sources with their own financing c<strong>on</strong>diti<strong>on</strong>s. <str<strong>on</strong>g>The</str<strong>on</strong>g> analysis c<strong>on</strong>siders loans from <str<strong>on</strong>g>Rural</str<strong>on</strong>g> Savings-Restricted <strong>and</strong> Compulsory Resources that are not linked to specific rural credit programs. 4 Although “industry” is also a category for “uses <str<strong>on</strong>g>of</str<strong>on</strong>g> capital” in 2017, it is a small <strong>on</strong>e c<strong>on</strong>sidering the number <str<strong>on</strong>g>of</str<strong>on</strong>g> c<strong>on</strong>tracts <strong>and</strong> the credit amounts. Besides that, it <strong>on</strong>ly appears in recent years. <str<strong>on</strong>g>The</str<strong>on</strong>g>refore, an ec<strong>on</strong>ometric analysis using panel data for the period 2002- 2017 is not possible.
3 Figure 1: <str<strong>on</strong>g>The</str<strong>on</strong>g> Distributi<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>Rural</str<strong>on</strong>g> <str<strong>on</strong>g>Credit</str<strong>on</strong>g> in <str<strong>on</strong>g>Credit</str<strong>on</strong>g> Lines, Producer Types <strong>and</strong> Types <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>Credit</str<strong>on</strong>g> in 2017 Source: Climate Policy Initiative with data from the Brazilian Central Bank