An Evaluation of the Performance of Regression Discontinuity Design on PROGRESA

By H. Buddelmeyer, Emmanuel Skoufias. 2004

168 citations recorded by the source corpus.

While providing the most reliable method of evaluating social programs, randomized experiments in developing and developed countries alike are accompanied by political risks and ethical issues that jeopardize the chances of adopting them. In this paper the authors use a unique data set from rural Mexico collected for the purposes of evaluating the impact of the PROGRESA poverty alleviation program to examine the performance of a quasi-experimental estimator, the Regression Discontinuity Design (RDD). Using as a benchmark the impact estimates based on the experimental nature of the sample, we examine how estimates differ when we use the RDD as the estimator for evaluating program impact on two key indicators: child school attendance and child work. Overall the performance of the RDD was remarkably good. The RDD estimates of program impact agreed with the experimental estimates in 10 out of the 12 possible cases. The two cases in which the RDD method failed to reveal any significant program impact on the school attendance of boys and girls were in the first year of the program (round 3). RDD estimates comparable to the experimental estimates were obtained when we used as a comparison group children from non-eligible households in the control localities.

Subfields: Safety Research, Sociology and Political Science, Soil Science

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Citations in the corpus

Analyzing Regression-Discontinuity Designs With Multiple Assignment Variables (2013, unknown): “…Goldberger (2008) in 1972, the design has been shown empirically to produce effects akin to an experiment’s (Aiken, West, Schwalm, Carroll, & Hsuing, 1998; Berk, Barnes, Ahlman, & Kurtz, 2010; Black, Galdo, & Smith, 2007; Buddelmeyer & Skoufias, 2004; Shadish, Galindo, Wong, Steiner, & Cook, 2011).”
Regression-Discontinuity Analysis: A Survey of Recent Developments in Economics (2008, methodology): “The RD approach was adopted to evaluate the impacts of a US anti-discrimination law (Hahn et al., 1999), an anti-poverty program in Mexico (Buddelmeyer and Skoufias, 2004), expansions in government-provided health insurance to low-income © 2008 Federal Reserve Bank of New York Copyright Journal comp”
Testing for Manipulation in the Regression Discontinuity Design When the Running Variable Is Discrete (2016, unknown): “Estimates from RD designs agree with their close cousins, randomized experiments, in numerous withinstudy comparisons where both methods are available (Buddelmeyer and Skoufias, 2003; Black et al., 2007; Cook and Wong, 2008).”
Quantile Treatment Effects in the Regression Discontinuity Design: Process Results and Gini Coefficient (2010, background): “Koenker and Bassett (1978) propose a parametric estimator for conditional quantile functions while Chaudhuri (1991) suggests a nonparametric estimator.”
Three conditions under which experiments and observational studies produce comparable causal estimates: New findings from within‐study comparisons (2008, background): “In Buddelmeyer and Skoufias (2003), the sample sizes were similar but so high that each design had very high power anyway—9,575 experimental and 9,183 RD cases.”
The Heterogeneous Impact of Conditional Cash Transfers (2013, background): “22 But, analyzing Progresa data, Buddelmeyer and Skoufias (2004) find inconsistent results.”
Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs (2014, methodology): “Buddelmeyer and Skoufias (2004) were the first to note the RD features of this social program.”
Educational Impacts and Cost-Effectiveness of Conditional Cash Transfer Programs in Developing Countries: A Meta-Analysis (2017, unknown): “Second, evidence by Buddelmeyer and Skoufias (2004) suggests that in the context of Mexico’s PROGRESA program, RDD methods may approximate well benchmark estimates using experimental data.18 Third, according to the WWC review protocol, RDD studies can, at best, meet standards with reservations,…”
PROGRESA and Its Impacts on the Welfare of Rural Households in Mexico (2005, background): “See Buddelmeyer and Skoufias (2004) for an evaluation of the impact of PROGRESA on”
Testing the Accuracy of Regression Discontinuity Analysis Using Experimental Benchmarks (2009, methodology): “Although this exercise, pioneered by LaLonde (1986), has become widespread as a means of analyzing the adequacy of a variety of statistical methods used to analyze observational data, it has rarely been used to assess and guide RD analysis (Buddelmeyer and Skoufias 2003; Black, Galdo, and Smith 2005”
Weak Identification in Fuzzy Regression Discontinuity Designs (2016, background): “A few examples include Hahn, Todd, and Van der Klaauw (1999, 2001); Porter (2003); Buddelmeyer and Skoufias (2004); McCrary (2008); Frölich (2007); Frölich and Melly (2008); Otsu, Xu, and Matsushita (2015); Imbens and Kalyanaraman (2012); Calonico, Cattaneo, and Titiunik (2014); Arai and Ichimura…”