The Impact of Agricultural Credit on Banana cultivation in Valle del Cauca, Colombia
DOI:
https://doi.org/10.22267/rcia.20234001.201Keywords:
financing, public policies, production, Propensity Score Matching, probit, selection biasAbstract
This study aimed to explore the use and effect of agricultural credit disbursed from banks and financial institutions on banana yield in farmers from Valle del Cauca (Colombia) using data from the National Agricultural Census (2014). Additionally, it evaluated whether the effect of credit differs according to the items in which the farmer prefers to invest. For this purpose, because credits are not granted randomly, this research used the Propensity Score Matching (PSM) methodology to manage selection bias. Initially, it was found through the probit model that having one's own agricultural machinery, using chemical fertilization to improve soil fertility, not belonging to an ethnic minority, and having some type of basic or higher education, increases the probability of obtaining an agricultural credit. On the other hand, the results suggest that credit has positive and significant effects on crop yield (6.2%), but the effect is greater if it is invested in land purchase and post-harvest processes, with an increase of 39% and 37% in yield, respectively. On the other hand, this study also suggests that, if credit is invested in items not related to agricultural activity, yields can be affected with a 10% reduction. Finally, it is recommended that a public policy be implemented to encourage greater participation of banana farmers in Valle del Cauca in agricultural credit programs, given their low participation (10%) despite the high acceptability rate (86%).
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