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Impacto del crédito sobre el agro en Colombia: evidencia del nuevo Censo nacional agropecuario

In: Superando barreras: el impacto del crédito en el sector agrario en Colombia

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  • Juan José Echavarría

Abstract

En este trabajo se utilizan los microdatos del Censo nacional agropecuario (CNA) de 2014, cuya cobertura operativa fue del 98,9% y llegó a 1.101 de los 1.122 municipios del país (DANE, 2014), con información sobre las características de la Unidad de producción agropecuaria (UPA)1 y sobre las condiciones socioeconómicas del productor. También, se utiliza información proveniente del Fondo para el Financiamiento del Sector Agropecuario (Finagro) sobre las características de los créditos desde 2009 y del Banco Agrario sobre aceptaciones y rechazos (esta última para el año 2013).Se evalúa el impacto del crédito sobre el rendimiento de los cultivos y sobre el nivel de pobreza medido por el índice de pobreza multidimensional (IPM), considerando tanto el crédito total como las fuentes alternativas incluidas en el CNA: Banco Agrario, bancos privados, cooperativas, particulares o prestamistas, programas del Gobierno, y almacenes de insumos agrícolas y agroindustria. Para realizar la estimación se implementa la metodología de propensity score matching (PSM), propuesta por Rosenbaum y Rubin (1983), la cual permite conformar grupos de tratamiento y control comparables, reduciendo así el sesgo de selección que puede surgir cuando la asignación del crédito no es aleatoria. Los resultados para el conjunto completo de información se comparan con aquellos de monocultivos, con el fin de evaluar la importancia relativa de las desviaciones de crédito hacia otros fines o cultivos diferentes al estipulado originalmente en el préstamo. También, se contrastan los resultados para cultivos transitorios, anuales y permanentes. La primera sección del capítulo presenta una breve revisión de la literatura relacionada con el impacto del crédito en la producción, la productividad y la pobreza; la segunda considera las fuentes de información y algunas estadísticas descriptivas; la tercera discute la metodología de PSM empleada; la cuarta presenta resultados relacionados con el soporte común, el balanceo y el impacto del crédito sobre el rendimiento de los cultivos y sobre la pobreza; y la quinta concluye.

Suggested Citation

  • Juan José Echavarría, 2018. "Impacto del crédito sobre el agro en Colombia: evidencia del nuevo Censo nacional agropecuario," Chapters, in: Mauricio Villamizar-Villegas & Sara Restrepo-Tamayo & Juan David Hernández-Leal (ed.), Superando barreras: el impacto del crédito en el sector agrario en Colombia, chapter 2, pages 41-72, Banco de la Republica de Colombia.
    • Handle: RePEc:bdr:bdrcap:2018-12-41-72
    DOI: 10.32468/Ebook.664-385-6
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    1. Aparicio, Gabriela & Bobicì, Vida & De Olloqui, Fernando & Fernández Díez, María Carmen & Gerardino, María Paula & Mitnik, Oscar A. & Vargas, Sebastián, 2021. "Liquidity or Capital?: The Impacts of Easing Credit Constraints in Rural Mexico," IDB Publications (Working Papers) 11332, Inter-American Development Bank.
    2. Fabio José De La Hoz Aguilar, 2019. "Sector rural colombiano: crédito y actividad agrícola," Documentos de trabajo 17633, Escuela de Gobierno - Universidad de los Andes.

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    More about this item

    Keywords

    Crédito; Rendimiento; Pobreza; Crédito agrícola; Propensity score matching; Credit; Financial performance; Poverty; Agricultural credit; Propensity score matching;
    All these keywords.

    JEL classification:

    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance

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