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Abstract
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.