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Welfare programs and labor supply in developing countries: experimental evidence from Latin America

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This study looks at the effect of welfare programs on work incentives and the adult labor supply in developing countries. The analysis builds on the experimental evaluations of three programs implemented in rural areas: Mexico’s Programa Nacional de Educación, Salud y Alimentación (PROGRESA), Nicaragua’s Red de Protección Social, and Honduras’ Programa de Asignación Familiar. Comparable results for the three countries indicate that the effects that the programs have had on the labor supply of participating adults have been mostly negative but are nonetheless small and not statistically significant. However, the evidence does point to the presence of other effects on labor markets. In the case of PROGRESA, there is a small positive effect on the number of hours worked by female beneficiaries and a sizeable increase in wages among male beneficiaries and a resulting increase in household labor income. Moreover, PROGRESA seems to have reduced female labor-force participation in ineligible households. These results imply that large-scale interventions may have broader equilibrium effects.

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  1. Behrman and Todd (1999), Skoufias et al. (1999), Skoufias and Parker (2001) and Gertler (2004), among others, describe the original experimental evaluation strategy of Mexico’s PROGRESA on which the evaluations of RPS and PRAF were based.

  2. A more detailed description of the three programs is provided in Section 3.1 and in the Electronic Supplementary Material.

  3. Moreover, program overlap is less of a problem for program evaluation (Moffitt 2002) in the cases under study: PROGRESA consolidated several different programs in Mexico, while PRAF and RPS represented some of the first attempts made to provide widespread income support in Honduras and Nicaragua.

  4. Yang’s (2008) results for remittances in the Philippines do not point up any significant impacts of windfall income on the adult labor supply. However, the findings of Ardington et al. (2009) concerning migration from South Africa indicate that transfers may influence even more complex within-household interactions, thereby inducing unexpected labor-supply responses.

  5. The structure of each program is detailed in the Electronic Supplementary Material to this study. Further references may also be found in Todd (2004) for PROGRESA, Glewwe and Olinto (2004) for PRAF, and Maluccio and Flores (2005) for RPS.

  6. Baseline data were gathered between November 1997 and March 1998. The first, second, and third follow-ups correspond to November 1998, March 1999, and November 1999, respectively.

  7. These estimates are roughly in line with others given in the literature: Maluccio (2004) reports 4 % for PRAF, 18 % for RPS, and 20 % for PROGRESA, although, for the latter, Gertler (2004) computes the average transfer as one third of total household income.

  8. Since take-up was very high among eligible households, average treatment effects, and average treatment effects on the treated are roughly equivalent (Angelucci and De Giorgi 2009). For simplicity, the ATE terminology is adopted in the description of the results.

  9. Angelucci and De Giorgi (2009) exclude from their analysis a subset of those deemed ineligible in the initial phase of the program because of later changes in the eligibility rules. The analysis here follows Duflo et al. (2008) in exploiting only the primary assignment process regardless of changes in the program rules after the initial stage.

  10. BDM also propose a third correction that involves aggregating the data into group-year cells and estimating this model. However, only results from individual-level data are reported below.

  11. The working-paper version of this document (Alzua et al. 2010) presents the two sets of standard errors, with estimates following the suggestion of Cameron et al. (2008) of reporting bootstrapped CRVE-corrected standard errors.

  12. This is also apparent in a conditional framework, as discussed in the Electronic Supplementary Material in respect of the analysis of the random assignment process, which indicates that the resulting treatment and control localities have significant differences in some dimensions for the three programs.

  13. It is, thus, not possible to distinguish between inactivity and unemployment. This distinction is feasible for the RPS data, but in the interests of comparability, the results detailed below are reported for the same variable for the three programs.

  14. The tables report the effect by round of the evaluation survey and correspond to the difference between the round and the baseline (preprogram) levels. These effects are estimated jointly by multiple time and treatment interactions, not as separate regressions by follow-up period.

  15. Angelucci and De Giorgi (2009) similarly fail to find significant effects on hours worked for non-eligible individuals in PROGRESA.

  16. These additional results for RPS are presented in Table A4 in the Electronic Supplementary Material.

  17. Angelucci and De Giorgi (2009, see Table 5) report that PROGRESA’s average and indirect treatment effects on monthly adult equivalent labor earnings were not significant, based on results obtained by unconditional difference in differences estimation. However, they state in the notes to this table that they found a positive and significant (at the 10 % level) average treatment effect for the third-round estimate when they included conditioning variables in their regressions. This finding is compatible with the result reported in Table 11 in this study, which includes individual controls (for OLS regressions) and individual fixed effects (for FE regressions).


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This study is based on a background paper entitled, “Labor supply responses to conditional cash transfer programs. Experimental and non-experimental evidence from Latin America,” prepared for the Inter-American Development Bank. The authors wish to thank Santiago Levy for encouraging them to work on this study and Emanuel Skoufias for providing an early draft of his ongoing work. The authors also acknowledge financial support from the CEDLAS-IDRC research project on “Labor markets for inclusive growth in Latin America.” The editor, Erdal Tekin, and an anonymous referee provided valuable feedback. Comments by Felipe Barrera, Sami Berlinski, César Bouillon, Sebastián Galiani, Laura Guardia, Pablo Ibarrarán, Miguel Jaramillo, Julia Johannsen, Santiago Levy, Florencia López Boo, Craig McIntosh, Claudia Piras, Patrick Puhani, Graciana Rucci, Norbert Schady, Guilherme Sedlacek, Ana Santiago, and Yuri Soares are much appreciated. We also gratefully acknowledge the comments received from the participants at the 13th Annual Meeting of the Latin American and Caribbean Economic Association in Rio de Janeiro in 2008, at the AfrEA-NONIE-3ie Impact Evaluation Conference in Cairo, held in April 2009, and at annual conference of the North East Universities Development Consortium held in 2009. Andrés Ham and Nicolás Epele provided outstanding research assistance. The usual disclaimer applies.

The opinions expressed in this report are those of the authors and do not necessarily represent those of the institutions to which they belong.

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Correspondence to Guillermo Cruces.

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Alzúa, M.L., Cruces, G. & Ripani, L. Welfare programs and labor supply in developing countries: experimental evidence from Latin America. J Popul Econ 26, 1255–1284 (2013).

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