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Abstract

In recent years, an important number of impact studies have attempted to examine the effect of credit on income poverty; however, many of these studies have not paid sufficient attention to the problems of endogeneity and selection bias. The few exceptional cases have employed econometric techniques that work at the village level. The problem is that the concept of village is inappropriate in the urban context where a large percentage of microfinance organisations in the developing world actually operate. This paper presents an econometric approach which controls for endogeneity and self-selection using data from a quasi-experiment designed at the household level, and conducted in three urban settlements in the surroundings of the Metropolitan area of Mexico City. The paper provides an estimation of the impact of credit, employing different equivalence scales in order to measure the sensitivity of the poverty impact to the intra-household distribution of welfare. We find a link between poverty impacts and lending technology. Group-based lending programmes are more effective in reducing the poverty gap but in doing so, they achieve insignificant impacts on the poverty incidence. By contrast, individual lending programmes reported significant and small impacts at the upper limits of deprivation but insignificant impacts on the poverty gap.



Item Type: MPRA Paper -

Institution: Department of Economics, University of Sheffield-

Original Title: The impact of credit on income poverty in urban Mexico. An endogeneity-corrected estimation-

Language: English-

Keywords: endogeneity; selection bias; microfinance; credit; income poverty; impact analysis; Mexico-

Subjects: O - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O19 - International Linkages to Development ; Role of International OrganizationsO - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O18 - Urban, Rural, Regional, and Transportation Analysis ; Housing ; InfrastructureO - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O17 - Formal and Informal Sectors ; Shadow Economy ; Institutional ArrangementsC - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data ; Data AccessO - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O16 - Financial Markets ; Saving and Capital Investment ; Corporate Finance and GovernanceC - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C24 - Truncated and Censored Models ; Switching Regression Models ; Threshold Regression Models-





Author: Niño-Zarazúa, Miguel

Source: https://mpra.ub.uni-muenchen.de/2367/



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