Villa, Juan M. and Niño-Zarazúa, Miguel (2018) 'Poverty dynamics and graduation from conditional cash transfers: a transition model for Mexico’s Progresa-Oportunidades-Prospera program.' Journal of Economic Inequality, 17 (2). pp. 219-251.
|
Text
- Published Version
Available under License Creative Commons Attribution 4.0 (CC-BY 4.0). Download (764kB) | Preview |
Abstract
The effects of conditional cash transfers (CCTs) on poverty and well-being have been widely studied. However, there is limited knowledge on how a CCT should respond to the dynamics of poverty. How should program administrators treat beneficiaries that exit poverty in period t-1, but exhibit a high probability of falling into poverty in period t? This is a relevant, yet unanswered question. This paper provides an analysis of the implications of poverty dynamics in the implementation of graduation strategies of CCTs, taking Mexico’s Progresa-Oportunidades-Prospera (POP) program as reference case. We propose a Markovian transition model that allows to control for unobserved heterogeneity, state dependence, and attrition. The model provides a framework for a generic graduation condition that can be applied to cash transfer programs that follow well-defined eligibility income thresholds. Overall, we find that only one-third of program beneficiaries that were poor in 2002 exhibited low probabilities of becoming poor in 2009–12 and therefore could be regarded as true ‘graduates’ of the program. We also find that the ‘recertification’ process of POP—which takes place every three years—would be more efficient if it took place every 3.7 and 5.1 years in urban and rural areas, respectively.
Item Type: | Journal Article |
---|---|
SOAS Departments & Centres: | Departments and Subunits > Department of Economics |
ISSN: | 15691721 |
Copyright Statement: | ©UNU-WIDER 2018 |
DOI (Digital Object Identifier): | https://doi.org/10.1007/s10888-018-9399-5 |
Date Deposited: | 22 Jan 2022 14:21 |
URI: | https://eprints.soas.ac.uk/id/eprint/36552 |
Funders: | Other |
Altmetric Data
Statistics
Accesses by country - last 12 months | Accesses by referrer - last 12 months |