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Ciencia e investigación agraria

versión On-line ISSN 0718-1620

Resumen

DONOSO, Guillermo; MELO, Oscar  y  NEGRETE, Eduardo. Participation determinants and impact assessment of the Institute of Agricultural Development (INDAP) credit program. Cienc. Inv. Agr. [online]. 2010, vol.37, n.2, pp.87-99. ISSN 0718-1620.  http://dx.doi.org/10.4067/S0718-16202010000200009.

This research estimates the impact of INDAP's Credit Program on the per hectare agricultural income of small agricultural producers. To accomplish this, a Treatment Effects Model (TEM) is employed to simultaneously estímate producer incomes and program participation functions, correcting for the potential presence of selectivity bias through the correlation between the errors of both functions. The results indicate that farmers of greater age present a higher disposition to participate in the program, but their interest decreases as their age increases. Additionally, producers who are acquainted with and evaluate the financial cost of credits as well as those producers whose income comes mainly from their land, who are landowners, present a greater family size and work greater land surfaces, present a greater disposition to participate. The results also indicate the existence of selection bias due to the nonrandom participation of farmers in the program. A negative correlation between the error terms of the per hectare agricultural income and participation function is observed. This implies that Ordinary Least Squares (OLS) underestimates the true effect of the program, because it omits the different initial situations between the treated and control group, situation corrected by the TEM estimation. In addition, the results indicate that there exists a positive and significant difference in the per hectare agricultural income between both groups in favor of the participants of the Credit Programs of INDAP, thus the Credit Program presents a positive impact on producer income levels.

Palabras clave : Program impact estimation; selection bias; rural finance; treatment effects model.

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