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Matching the Gold Standard: Comparing Experimental and Nonexperimental Evaluation Techniques for a Geographically Targeted Program

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  • Sudhanshu Handa
  • John A. Maluccio

Abstract

We compare nonexperimental impact estimates based on matching methods with those from a randomized evaluation to determine whether the nonexperimental approach can "match" the so-called gold standard. The social experiment we use was carried out to evaluate a geographically targeted conditional cash transfer antipoverty program in Nicaragua. The outcomes we assess include several components of household expenditure and a variety of children's health outcomes, including breast-feeding, vaccinations, and morbidity. We find that using each of the following improves performance of matching for these outcomes: (1) geographically proximate comparison samples, (2) stringent common support requirements, and (3) both geographic- and household-level matching variables. Even for a geographically targeted program, in which the selection is at the geographic, rather than at the individual or household level, and in which it is not possible to find comparison individuals or households in the program locales, matching can perform reasonably well. The results also suggest that the techniques may be more promising for evaluating the more easily measured individual-level binary outcomes than for outcomes that are more difficult to measure, such as expenditure. (c) 2010 by The University of Chicago. All rights reserved..

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Bibliographic Info

Article provided by University of Chicago Press in its journal Economic Development and Cultural Change.

Volume (Year): 58 (2010)
Issue (Month): 3 (04)
Pages: 415-447

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Handle: RePEc:ucp:ecdecc:v:58:y:2010:i:3:p:415-447

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  1. James J. Heckman & Salvador Navarro-Lozano, 2003. "Using Matching, Instrumental Variables and Control Functions to Estimate Economic Choice Models," NBER Working Papers 9497, National Bureau of Economic Research, Inc.
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  5. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," NBER Working Papers 6699, National Bureau of Economic Research, Inc.
  6. Jeffrey Smith & Petra Todd, 2003. "Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?," University of Western Ontario, CIBC Centre for Human Capital and Productivity Working Papers 20035, University of Western Ontario, CIBC Centre for Human Capital and Productivity.
  7. Alberto Abadie & David Drukker & Jane Leber Herr & Guido W. Imbens, 2004. "Implementing matching estimators for average treatment effects in Stata," Stata Journal, StataCorp LP, vol. 4(3), pages 290-311, September.
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  12. Daniel O. Gilligan & John Hoddinott, 2007. "Is There Persistence in the Impact of Emergency Food Aid? Evidence on Consumption, Food Security, and Assets in Rural Ethiopia," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(2), pages 225-242.
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  16. Jyotsna Jalan & Martin Ravallion, 2000. "Estimating the Benefit Incidence of an Antipoverty Program by Propensity Score Matching," Econometric Society World Congress 2000 Contributed Papers 0873, Econometric Society.
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  22. David I. Levine & Gary Painter, 2003. "The Schooling Costs of Teenage Out-of-Wedlock Childbearing: Analysis with a Within-School Propensity-Score-Matching Estimator," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 884-900, November.
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Cited by:
  1. Mathenge, Mary K. & Smale, Melinda & Olwande, John, 2012. "The Impact of Maize Hybrids on Income, Poverty, and Inequality among Smallholder Farmers in Kenya," Food Security International Development Working Papers 146931, Michigan State University, Department of Agricultural, Food, and Resource Economics.
  2. Bruno Martorano & Sudhanshu Handa & Carolyn Halpern & Harsha Thirumurthy & UNICEF Innocenti Research Centre, 2014. "Subjective Well-being, Risk Perceptions and Time Discounting: Evidence from a large-scale cash transfer programme," Innocenti Working Papers inwopa717, UNICEF Innocenti Research Centre.
  3. Henrik Hansen & Ninja Ritter Klejnstrup & Ole Winckler Andersen, 2011. "A Comparison of Model-based and Design-based Impact Evaluations of Interventions in Developing Countries," IFRO Working Paper 2011/16, University of Copenhagen, Department of Food and Resource Economics.

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