| 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. |
| Keywords: |
Brazil, impact evaluation, agricultural risk management policy, Agricultural and Food Policy, Research Methods/ Statistical Methods, Risk and Uncertainty, Q18, C54, Q12, G22, |