Impact Evaluation of the Brazilian crop insurance public program “Proagro Mais”

This research evaluates the impact of a public risk management tool that provides insurance to small-scale farmers. In particular, we analyze the “Farm Activity Guarantee Program for Smallholders” or Proagro Mais, which is one of the largest Brazilian public programs that uses crop insurance indemnity mechanisms. This program covers financial debts incurred by smallholders related to rural credit operations, and which payment was hampered by the occurrence of pests, diseases or climatological effects. The relevance of this research relies on the considerable size of the program, both in terms of number of operations and money invested to cover crop losses. We use a sample of small-scale corn producers from the State of Paraná, which included Proagro Mais beneficiaries and nonbeneficiaries. One should note that all growers in the sample contracted credits associated with their corn crop, but not all subscribed to the insurance Program. We use 2003 as the baseline since it is the year prior to the launch of Proagro Mais and then used 2005 as the endline considering the indemnity mechanism of the Program. The database used in this study was provided by the Federal Accounting Court of Brazil (TCU), and includes 25,877 corn growers that contracted with Proagro Mais between 2003 and 2005 (treatment group), and 68,312 growers who were not beneficiaries of that program in this same period (control group). The relevant variables include crop and growers characteristics such as area financed, complementary economic activities for additional income (dummy), education, and expected yield. We also added meteorological and regional variables from other public sources to control farm location. Our main objective is to evaluate the impact of Proagro Mais on the amount of credit per hectare granted to the beneficiaries of the Program. The methodology includes Propensity Score Matching (PSM) along with Difference-in-Difference (DID). We use longitudinal data and apply the conditional DID estimator proposed by Heckman et al. (1997), and the conditional DID estimator with repeated cross-sections, proposed by Blundell and Costa Dias (2000).The econometric estimates with both methods described above, show that the effect of the treatment on the tread was not positive. This suggests that after the yield loss period, the control group got a higher average amount of credit per hectare than Proagro Mais beneficiaries. Thus, the question that arises is whether there may be other agricultural risk management mechanisms more suited for smallholders than Proagro Mais, or whether the evaluated program could not achieve its main goal because it does not cover all risks faced by its beneficiaries. Therefore, this study could serve to promote discussions about the economic performance and efficiency of agricultural policy in Brazil.