¿Cómo influye la diversificación de los ingresos rurales en la eficiencia técnica agrícola de los pequeños agricultores? Evidencia de Colombia

dc.audienceInvestigador
dc.coverageColombia
dc.creatorPolo Murcia, Sonia Mercedes
dc.creatorTeran Chaves, Cesar Augusto
dc.date2024-01-19T13:01:18Z
dc.date2024-01-19T13:01:18Z
dc.date2022
dc.date2022
dc.date.accessioned2026-06-27T04:34:46Z
dc.descriptionEn este estudio se estima el efecto del ingreso rural no agrícola (IRNA) sobre la eficiencia técnica (ET) de los hogares de pequeños productores agropecuarios en cuatro regiones de Colombia. Se utiliza el enfoque estocástico de meta-frontera que permite considerar la heterogeneidad regional. Los resultados sugieren que los hogares rurales en todas las regiones utilizan la tecnología disponible de manera subóptima. En la meta-frontera los resultados evidencian un efecto negativo y significativo sobre la ET; el efecto se debilita conforme aumenta la participación del IRNA en el ingreso total del hogar, la ET puede disminuir entre 8.8% y 43% (significancia del 5%).
dc.formatapplication/pdf
dc.formatapplication/pdf
dc.identifierhttps://estudiosrurales.unq.edu.ar/index.php/ER/article/view/441
dc.identifier2250-4001
dc.identifierhttp://hdl.handle.net/20.500.12324/38774
dc.identifier10.48160/22504001er25.441
dc.identifierreponame:Biblioteca Digital Agropecuaria de Colombia
dc.identifierinstname:Corporación colombiana de investigación agropecuaria AGROSAVIA
dc.identifier.urihttp://hdl.handle.net/123456789/32013
dc.languagespa
dc.publisherUniversidad Nacional de Quilmes
dc.relationEstudios Rurales
dc.relation12
dc.relation25
dc.relation1
dc.relation19
dc.relationAbdulai, A., & Huffman, W. (2000). Structural Adjustment and Economic Efficiency of Rice Farmers in Northern Ghana. Economic Development and Cultural Change, 48(3), 503–520. https://doi.org/10.1086/452608
dc.relationAl-Amin, A. A., & Hossain, M. (2019). Impact of non-farm income on welfare in rural Bangladesh: Multilevel mixed effects regression approach. World Development Perspectives, 13, 95–102. https://doi.org/10.1016/j.wdp.2019 .02.014
dc.relationAlem, H., Lien, G., Hardaker, J. B., & Guttormsen, A. (2018). Regional differences in technical efficiency and technological gap of Norwegian dairy farms: a stochastic meta-frontier model. Applied Economics, 51(4), 409– 421. https://doi.org/10.1080/00036846.2018.1502867
dc.relationAlmeida, A. N., & Bravo-Ureta, B. E. (2019). Agricultural productivity, shadow wages and off-farm labor decisions in Nicaragua. Economic Systems, 43(1), 99–110. https://doi.org/10.1016/j.ecosys.2018.09.002
dc.relationAmare, M., & Shiferaw, B. (2017). Nonfarm employment, agricultural intensification, and productivity change: empirical findings from Uganda. Agricultural Economics, 48(S1), 59–72. https://doi.org/10.1111/agec.12386
dc.relationBojnec, T., & Latruffe, L. (2009). Determinants of technical efficiency of Slovenian farms. Post-Communist Economies, 21(1), 117–124. https://doi.org/10.1080/14631370802663737
dc.relationDethier, J. J., & Effenberger, A. (2012). Agriculture and development: A brief review of the literature. Economic Systems, 36(2), 175–205. https://doi.org/10.1016/j.ecosys.2011.09.003
dc.relationDepartamento Administrativo Nacional de Estadística (DANE). 2014. Uso, cobertura y tenencia del suelo: 3er censo nacional agropecuario 2014. (Consultado en línea el 27 de abril de 2020).
dc.relationGoodwin, B. K., & Mishra, A. K. (2004). Farming Efficiency and the Determinants of Multiple Job Holding by Farm Operators. American Journal of Agricultural Economics, 86(3), 722–729. https://doi.org/10.1111/j.0002-9092 .2004.00614.x
dc.relationHeckman, J. J. (1978). Dummy Endogenous Variables in a Simultaneous Equation System. Econometrica, 46(4), 931. https://doi.org/10.2307/1909757
dc.relationHuang, C. J., Huang, T. H., & Liu, N. H. (2014). A new approach to estimating the metafrontier production function based on a stochastic frontier framework. Journal of Productivity Analysis, 42(3), 241–254. https://doi.org/10 .1007/s11123-014-0402-2
dc.relationKilic, T., Carletto, C., Miluka, J., & Savastano, S. (2009). Rural nonfarm income and its impact on agriculture: evidence from Albania. Agricultural Economics, 40(2), 139–160. https://doi.org/10.1111/j.1574-0862.2009.00366.x
dc.relationKumbhakar, S. C., Lien, G., & Hardaker, J. B. (2012). Technical efficiency in competing panel data models: a study of Norwegian grain farming. Journal of Productivity Analysis, 41(2), 321–337. https://doi.org/10.1007/s1112 3-012-0303-1
dc.relationLien, G., Kumbhakar, S. C., & Hardaker, J. B. (2010). Determinants of off-farm work and its effects on farm performance: the case of Norwegian grain farmers. Agricultural Economics, 41(6), 577–586. https://doi.org/1 0.1111/j.1574-0862.2010.00473.x
dc.relationLien, G., Kumbhakar, S. C., & Alem, H. (2018). Endogeneity, heterogeneity, and determinants of inefficiency in Norwegian crop-producing farms. International Journal of Production Economics, 201, 53–61. https://doi.org/ 10.1016/j.ijpe.2018.04.023
dc.relationLiu, Z., & Zhuang, J. (2000). Determinants of Technical Efficiency in Post-Collective Chinese Agriculture: Evidence from Farm-Level Data. Journal of Comparative Economics, 28(3), 545–564. https://doi.org/10.1006/jcec.200 0.1666
dc.relationMathenge, M. K., & Tschirley, D. L. (2015). Off-farm labor market decisions and agricultural shocks among rural households in Kenya. Agricultural Economics, 46(5), 603–616. https://doi.org/10.1111/agec.12157
dc.relationMelo-Becerra, L. A., & Orozco-Gallo, A. J. (2016). Technical efficiency for Colombian small crop and livestock farmers: A stochastic metafrontier approach for different production systems. Journal of Productivity Analysis, 47(1), 1–16. https://doi.org/10.1007/s11123-016-0487-x
dc.relationPfeiffer, L., López-Feldman, A., & Taylor, J. E. (2009). Is off-farm income reforming the farm? Evidence from Mexico. Agricultural Economics, 40(2), 125–138. https://doi.org/10.1111/j.1574-0862.2009.00365.x
dc.relationPhimister, E., & Roberts, D. (2006). e Effect of Off-farm Work on the Intensity of Agricultural Production. Environmental and Resource Economics, 34(4), 493–515. https://doi.org/10.1007/s10640-006-0012-1
dc.relationPurdy, B. M., Langemeier, M. R., & Featherstone, A. M. (1997). Financial Performance, Risk, and Specialization. Journal of Agricultural and Applied Economics, 29(1), 149–161. https://doi.org/10.1017/s107407080000763x
dc.relationSemykina, A., & Wooldridge, J. M. (2010). Estimating panel data models in the presence of endogeneity and selection. Journal of Econometrics, 157(2), 375–380. https://doi.org/10.1016/j.jeconom.2010.03.039
dc.relationShi, X., Heerink, N., & Qu, F. (2007). Choices between different off-farm employment sub-categories: An empirical analysis for Jiangxi Province, China. China Economic Review, 18(4), 438–455. https://doi.org/10.1016/j.chie co.2006.08.001
dc.relationShittu, A. M. (2014). Off-farm labour supply and production efficiency of farm household in rural Southwest Nigeria. Agricultural and Food Economics, 2(1). https://doi.org/10.1186/s40100-014-0008-z
dc.relationSkevas, T., Lansink, A. O., & Stefanou, S. E. (2012). Measuring technical efficiency in the presence of pesticide spillovers and production uncertainty: e case of Dutch arable farms. European Journal of Operational Research, 223(2), 550–559. https://doi.org/10.1016/j.ejor.2012.06.034
dc.relationSipiläinen, T., Kumbhakar, S. C., & Lien, G. (2013). Performance of dairy farms in Finland and Norway from 1991 to 2008. European Review of Agricultural Economics, 41(1), 63–86. https://doi.org/10.1093/erae/jbt012
dc.relationVella, F., & Verbeek, M. (1999). Two-step estimation of panel data models with censored endogenous variables and selection bias. Journal of Econometrics, 90(2), 239–263. https://doi.org/10.1016/s0304-4076(98)00043-8
dc.relationWan, J., Li, R., Wang, W., Liu, Z., & Chen, B. (2016b). Income Diversification: A Strategy for Rural Region Risk Management. Sustainability, 8(10), 1064. https://doi.org/10.3390/su8101064
dc.relationWei SI. (2011). Productivity growth, technical efficiency, and technical change in China’s soybean production. Aican Journal Of Agricultural Research, 6(25). https://doi.org/10.5897/ajar11.1080
dc.relationWoldeyohanes, T., Heckelei, T., & Surry, Y. (2016). Effect of off-farm income on smallholder commercialization: panel evidence from rural households in Ethiopia. Agricultural Economics, 48(2), 207–218. https://doi.org/10 .1111/agec.12327
dc.relationWooldridge, J. M. (2015). Control Function Methods in Applied Econometrics. Journal of Human Resources, 50(2), 420–445. https://doi.org/10.3368/jhr.50.2.420
dc.relationZhang, L., Su, W., Eriksson, T., & Liu, C. (2016). How Off-farm Employment Affects Technical Efficiency of China’s Farms: e Case of Jiangsu. China & World Economy, 24(3), 37–51. https://doi.org/10.1111/cwe.12157
dc.rightsAttribution-ShareAlike 4.0 International
dc.rightshttp://creativecommons.org/licenses/by-sa/4.0/
dc.sourceEstudios Rurales; Vol. 12, Núm,. 25 (2022): Estudios Rurales (Enero-Junio);p. 1 -19.
dc.subjectEconomía de la producción - E16
dc.subjectPequeños agricultores
dc.subjectDiversificación económica
dc.subjectRenta
dc.subjectTecnología
dc.subjectTransversal
dc.subjecthttp://aims.fao.org/aos/agrovoc/c_14343
dc.subjecthttp://aims.fao.org/aos/agrovoc/c_ee2962b7
dc.subjecthttp://aims.fao.org/aos/agrovoc/c_3820
dc.subjecthttp://aims.fao.org/aos/agrovoc/c_7644
dc.thumbnailhttps://repository.agrosavia.co/bitstreams/43c92f3e-6209-4f2a-8707-4600d5b71d33/download
dc.title¿Cómo influye la diversificación de los ingresos rurales en la eficiencia técnica agrícola de los pequeños agricultores? Evidencia de Colombia
dc.titleHow Rural Income Diversification Influence AgriculturalTechnical Efficiency Of Smallholder Farmers? Evidence From Colombia
dc.typeArtículo científico

Archivos

Colecciones