Publicado dic 14, 2018



PLUMX
Almetrics
 
Dimensions
 

Google Scholar
 
Search GoogleScholar


Jorge Mora-Rivera http://orcid.org/0000-0003-0838-9551

Fernando García-Mora http://orcid.org/0000-0001-6858-4952

##plugins.themes.bootstrap3.article.details##

Resumen

El objetivo de este artículo es estimar el efecto que tiene el uso de las microfinanzas en la pobreza por ingresos de los hogares del sector rural mexicano. Empleando información de la Encuesta Coneval a Hogares Rurales de México 2013 (EnChor 2013) (Consejo Nacional de Evaluación de la Política de Desarrollo Social [Coneval], 2013) y técnicas de propensity score matching, los resultados de esta investigación muestran que el uso de los microcréditos contribuye a disminuir los niveles de pobreza de los hogares rurales en México. Estos hallazgos ponen de manifiesto la necesidad de crear políticas públicas que permitan incorporar a un mayor número de hogares pobres al mercado de las microfinanzas, lo cual incrementaría los niveles de vida de las personas que viven en este sector.

Keywords

micro-finances, poverty, rural households, matching, Mexicomicrofinanzas, pobreza, hogares rurales, matching, México

References
Abadie, A., e Imbens, G. W. (2011). Bias-corrected matching estimators for average treatment effects. Journal of Business and Economic Statistics, 29(1), 1-11. https://doi.org/10.1198/jbes.2009.07333
Angelucci, M., Karlan, D., y Zinman, J. (2015). Microcredit impacts: Evidence from a randomized microcredit program placement experiment by Compartamos Banco. American Economic Journal: Applied Economics, 7(1), 151-182. Recuperado de https://www.nber.org/papers/w19827
Asociación de Bancos de México. (2011). Anuario financiero de la banca en México 2011. Recuperado de https://www.abm.org.mx/anuario/anuario2011/pdf/compartamos-banco.pdf
Attanasio, O., Augsburg, B., de Haas, R., Fitzsimons, E., y Harmgart, H. (2015). The impacts of microfinance: Evidence from joint-liability lending in Mongolia. American Economic Journal: Applied Economics, 7(1), 90-122. http://dx.doi.org/10.2139/ssrn.1974414
Banco Mundial. (2017). Monitoring global poverty: Report of the Commission on Global Poverty. Washington: autor. Recuperado de https://openknowledge.worldbank.org/handle/10986/25141
Banerjee, A., Duflo, E., Glennerster, R., y Kinnan, C. (2015). The miracle of microfinance? Evidence from a randomized evaluation. American Economic Journal: Applied Economics, 7(1), 22-53. https://doi.org/10.3386/w18950
Banerjee, A. V., y Duflo, E. (2011). Poor economics: A radical rethinking of the way to fight global poverty. Public Affairs.
Banerjee, S. B., y Jackson, L. (2017). Microfinance and the business of poverty reduction: Critical perspectives from rural Bangladesh. Human Relations, 70(1), 63-91. https://doi.org/10.1177/0018726716640865
Bateman, M. (2011). Microfinance as a development and poverty reduction policy: Is it everything it’s cracked up to be? Londres: Overseas Development Institute.
Becker, S. O., e Ichino, A. (2002). Estimation of average treatment effects based on propensity scores. The Stata Journal, 2(4), 358-377. Recuperado de https://econpapers.repec.org/article/tsjstataj/v_3a2_3ay_3a2002_3ai_3a4_3ap_3a358-377.htm
Berhane, G., y Gardebroek, C. (2010). Does microfinance reduce rural poverty? Evidence based on household panel data from Northern Ethiopia. American Journal of Agricultural Economics, 93(1), 43-55. https://doi.org/10.1093/ajae/aaq126
Caliendo, M., y Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22(1), 31-72. Recuperado de https://www.iza.org/publications/dp/1588/some-practical-guidance-for-the-implementation-of-propensity-score-matching
Cameron, A. C., y Trivedi, P. K. (2010). Microeconometrics using Stata: Revised edition (2.a). Stata Press.
Chowdhury, M., Ghosh, D., y Wright, R. (2002). The impact of micro-credit on poverty: Evidence from Bangladesh. Progress in Development Studies, 5(4), 298-309. https://doi.org/10.1191/1464993405ps116oa
Consejo Nacional de Evaluación de la Política de Desarrollo Social [Coneval]. (2009). Metodología para la medición multidimensional de la pobreza en México. Ciudad de México: autor. Recuperado de https://www.coneval.org.mx/rw/resource/Metodologia_Medicion_Multidimensional.pdf
Consejo Nacional de Evaluación de la Política de Desarrollo Social [Coneval]. (2017a). Esquema General de Evaluación de la Cruzada Nacional Contra el Hambre, 2013-2018. Ciudad de México: autor. Recuperado de https://www.coneval.org.mx/Informes/Evaluacion/Cruzada %20contra %20el %20Hambre/ESQUEMA_GENERAL_DE_EVALUACION_DE_LA_CNCH_ %20F.pdf
Consejo Nacional de Evaluación de la Política de Desarrollo Social [Coneval]. (2017b). Medición de la pobreza en México y en las Entidades Federativas 2016. Ciudad de México: autor.
Crepón, B., Devoto, F., Duflo, E., y Pariente, W. (2015). Estimating the impact of microcredit on those who take it up: Evidence from a randomized experiment in Morocco. American Economic Journal: Applied Economics, 7(1), 123-150. https://doi.org/10.1257/app.20130535
Cuasquer, H., y Maldonado, R. (2011). Microfinanzas y microcrédito en Latinoamérica. Estudios de caso: Colombia, Ecuador, El Salvador, México y Paraguay. Centro de Estudios Monetarios Latinoamericanos: Asociación Regional de Bancos Centrales, Documento de Discusión n.o 2. Recuperado de https://ideas.repec.org/p/cml/docdsc/2.html
Esquivel, H. (2010). Medición del efecto de las microfinanzas en México. Comercio Exterior, 6(1), 9-27. Recuperado de http://revistas.bancomext.gob.mx/rce/magazines/134/1/09_ESQUIVEL_microfinanzas.pdf
Foster, J., Greer, J., y Thorbecke, E. (1984). A class of decomposable poverty measures. Econometrica, 52(3), 761-766. https://doi.org/10.2307/1913475
Fosu, A. K. (2017). Growth, inequality, and poverty reduction in developing countries: Recent global evidence. Research in Economics, 71(2), 306-336. https://doi.org/10.1016/j.rie.2016.05.005
George, A. (2006). Why the fight against poverty is failing: A contrarian view. Knowledge Knowledge@SMU (Singapore Management University). Recuperado de https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1022&context=ksmu
Ghalib, A., Malki, I., e Imai, K. (2015). Microfinance and household poverty reduction: Empirical evidence from rural Pakistan. Oxford Development Studies, 43(1), 84-104. https://doi.org/10.1080/13600818.2014.980228
Goetz, A. M., y Gupta, R. S. (1996). Who takes the credit? Gender, power, and control over loan use in rural credit programs in Bangladesh. World Development, 24(1), 45-63. https://doi.org/10.1016/0305-750X(95)00124-U
Imai, K., Arun, T., y Annim, S. (2010). Microfinance and household poverty reduction: New evidence from India. World Development, 38(12), 1760-1774. https://doi.org/10.1016/j.worlddev.2010.04.006
Imai, K., y Azam, S. (2012). Does microfinance reduce poverty in Bangladesh? New evidence from household panel data. The Journal of Development Studies, 48(5), 633-653. https://doi.org/10.1080/00220388.2012.661853
Imbens, G. W. (2000). The role of the propensity score in estimating dose-response functions. Biometrika, 87(3), 706-710. https://doi.org/10.3386/t0237
Karlan, D., y Zinman, J. (2009). Expanding microenterprise credit access: Using randomized supply decisions to estimate the impacts on Manila. Centre for Economic Policy Research (CEPR), Discussion Paper n.o DP7396. Recuperado de https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1469875
Kasali, T., Ahmad, S., y Ean, L. (2015). Does microfinance operation have effect on poverty alleviation in Nigeria? European Journal of Contemporary Economics and Management, 2(2), 54-69. http://dx.doi.org/10.19044/elp.v2no2a4
Khandker, S. (2005). Microfinance and poverty: Evidence using panel data from Bangladesh. The World Bank Economic Review, 19(2), 263-286. Recuperado de http://documents.worldbank.org/curated/en/284801468013215718/Microfinance-and-poverty-evidence-using-panel-data-from-Bangladesh
Khandker, S., y Samad, H. A. (2018). Bangladesh’s achievement in poverty reduction: The role of microfinance revisited. En Y. Sawada, M. Mahmud y N. Kitano (eds.), Economic and social development of Bangladesh (pp. 177-198). Japón: Palgrave MacMillan.
MkNelly, B., y Dunford, C. (1998). Impact of credit with education on mothers and their young children’s nutrition: Lower Pra Rural Bank credit with education program in Ghana. Freedom from Hunger, Research Paper n.o 4. Recuperado de https://www.freedomfromhunger.org/impact-credit-education-mothers-and-their-young-children %E2 %80 %99s-nutrition-lower-pra-rural-bank-0
MkNelly, B., y Dunford, C. (1999). Impacto de crédito con educación en las madres y en la nutrición de sus niños pequeños: programa Crecer de crédito con educación en Bolivia. Freedom from Hunger, Trabajo de Investigación n.o 5. Recuperado de https://www.freedomfromhunger.org/sites/default/files/R5_Bolivia_Impact_Study_Exec_Summary_8-99-spa.pdf
Morduch, J. (1998). Does microfinance really help the poor? New evidence from flagship programs in Bangladesh. Princeton University, Woodrow Wilson School of Public and International Affairs, Research Program in Development Studies, Working Paper n.o 198. Recuperado de https://wagner.nyu.edu/impact/research/publications/does-microfinance-really-help-poor-new-evidence-flagship-programs
Patel, R., Patel, M., y Patel, N. (2018). Impact of microfinance on poor women: Lessons from North Gujarat. Prabandhan: Indian Journal of Management, 11(2). https://doi.org/10.17010/pijom/2018/v11i2/121393
Pitt, M., y Khandker, S. (1998). The impact of group-based credit programs on poor households in Bangladesh: Does the gender of participants matter? Journal of Political Economy, 106(5), 958-996. https://doi.org/10.1086/250037
Rosenbaum, P., y Rubin, D. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41-55.
Rosenbaum, P., y Rubin, D. (1985). Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. The American Statistician, (39), 33-38. https://doi.org/10.1093/biomet/70.1.41
Rubin, D. B. (1973). Matching to remove bias in observational studies. Biometrics, 29(1), 159-183. https://doi.org/10.2307/2529684
Sani, A., Khan, M. S., Ahmed, H. R. N., y Aziz, B. (2017). Role of micro finance institutions in poverty reduction. Imperial Journal of Interdisciplinary Research, 3(2), 209-212. Recuperado de https://www.onlinejournal.in/IJIRV3I2/036.pdf
Sultana, H. Y., Jamal, M. A., y Najaf, D.-E. (2017). Impact of microfinance on women empowerment through poverty alleviation: An assessment of socioeconomic conditions in Chennai City of Tamil Nadu. Asian Journal for Poverty Studies, 3(2), 175-183. Recuperado de https://ejournal.unib.ac.id/index.php/ajps/article/view/2785
Tarozzi, A., Desai, J., y Johnson, K. (2015). The impacts of microcredit: Evidence from Ethiopia. American Economic Journal: Applied Economics, 7(1), 54-89. https://doi.org/10.1257/app.20130475
Todd, P. E. (2010). Matching estimators. En S. N. Durlauf y L. E. Blume (eds.), Microeconometrics, (pp. 108-121). Reino Unido: Palgrave MacMillan.
Cómo citar
Mora-Rivera, J., & García-Mora, F. (2018). Microfinanzas y pobreza rural en México: un análisis con técnicas de propensity score matching. Cuadernos De Desarrollo Rural, 15(82), 1–19. https://doi.org/10.11144/Javeriana.cdr15-82.mprm
Sección
Artículos Investigación