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Matching the gold standard: Comparing experimental and non-experimental evaluation techniques for a geographically targeted program

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  • Sudhanshu Handa
  • John Maluccio

Abstract

We compare non-experimental impact estimates based on matching methods with those from a randomized evaluation to determine whether the non-experimental 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.

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  • Sudhanshu Handa & John Maluccio, 2008. "Matching the gold standard: Comparing experimental and non-experimental evaluation techniques for a geographically targeted program," Middlebury College Working Paper Series 0813, Middlebury College, Department of Economics.
  • Handle: RePEc:mdl:mdlpap:0813
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    1. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    2. McKenzie, David & Gibson, John & Stillman, Steven, 2006. "How important is selection ? Experimental versus non-experimental measures of the income gains from migration," Policy Research Working Paper Series 3906, The World Bank.
    3. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    4. John A. Maluccio, 2009. "Household targeting in practice: The Nicaraguan Red de Protección Social," Journal of International Development, John Wiley & Sons, Ltd., vol. 21(1), pages 1-23.
    5. 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.
    6. Maluccio, John A. & Flores, Rafael, 2005. "Impact evaluation of a conditional cash transfer program: the Nicaraguan Red de Protección Social," Research reports 141, International Food Policy Research Institute (IFPRI).
    7. Menno Pradhan & Laura B. Rawlings, 2002. "The Impact and Targeting of Social Infrastructure Investments: Lessons from the Nicaraguan Social Fund," The World Bank Economic Review, World Bank, vol. 16(2), pages 275-295, August.
    8. 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.
    9. Jalan, Jyotsna & Ravallion, Martin, 2003. "Estimating the Benefit Incidence of an Antipoverty Program by Propensity-Score Matching," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 19-30, January.
    10. Godtland, Erin M & Sadoulet, Elisabeth & De Janvry, Alain & Murgai, Rinku & Ortiz, Oscar, 2004. "The Impact of Farmer Field Schools on Knowledge and Productivity: A Study of Potato Farmers in the Peruvian Andes," Economic Development and Cultural Change, University of Chicago Press, vol. 53(1), pages 63-92, October.
    11. Barbara Sianesi, 2004. "An Evaluation of the Swedish System of Active Labor Market Programs in the 1990s," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 133-155, February.
    12. Deaton, A. & Zaidi, S., 1999. "Guidelines for Constructing Consumption Aggregates for Welfare Analysis," Papers 192, Princeton, Woodrow Wilson School - Development Studies.
    13. Roberto Agodini & Mark Dynarski, 2004. "Are Experiments the Only Option? A Look at Dropout Prevention Programs," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 180-194, February.
    14. Charles Michalopoulos & Howard S. Bloom & Carolyn J. Hill, 2004. "Can Propensity-Score Methods Match the Findings from a Random Assignment Evaluation of Mandatory Welfare-to-Work Programs?," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 156-179, February.
    15. David McKenzie & John Gibson & Steven Stillman, 2010. "How Important Is Selection? Experimental vs. Non-Experimental Measures of the Income Gains from Migration," Journal of the European Economic Association, MIT Press, vol. 8(4), pages 913-945, June.
    16. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    17. Alberto Abadie & Guido W. Imbens, 2008. "On the Failure of the Bootstrap for Matching Estimators," Econometrica, Econometric Society, vol. 76(6), pages 1537-1557, November.
    18. Angus Deaton & Salman Zaidi, 2002. "Guidelines for Constructing Consumption Aggregates for Welfare Analysis," World Bank Publications, The World Bank, number 14101, April.
    19. James Heckman & Salvador Navarro-Lozano, 2004. "Using Matching, Instrumental Variables, and Control Functions to Estimate Economic Choice Models," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 30-57, February.
    20. 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.
    21. Friedlander, Daniel & Robins, Philip K, 1995. "Evaluating Program Evaluations: New Evidence on Commonly Used Nonexperimental Methods," American Economic Review, American Economic Association, vol. 85(4), pages 923-937, September.
    22. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Moving the Goalposts: Addressing Limited Overlap in the Estimation of Average Treatment Effects by Changing the Estimand," NBER Technical Working Papers 0330, National Bureau of Economic Research, Inc.
    23. Todd, Petra E., 2008. "Evaluating Social Programs with Endogenous Program Placement and Selection of the Treated," Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 60, pages 3847-3894, Elsevier.
    24. Barham, Tania & Maluccio, John A., 2009. "Eradicating diseases: The effect of conditional cash transfers on vaccination coverage in rural Nicaragua," Journal of Health Economics, Elsevier, vol. 28(3), pages 611-621, May.
    25. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    26. de Brauw, Alan & Hoddinott, John, 2011. "Must conditional cash transfer programs be conditioned to be effective? The impact of conditioning transfers on school enrollment in Mexico," Journal of Development Economics, Elsevier, vol. 96(2), pages 359-370, November.
    27. Thomas D. Cook & William R. Shadish & Vivian C. Wong, 2008. "Three conditions under which experiments and observational studies produce comparable causal estimates: New findings from within-study comparisons," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 27(4), pages 724-750.
    28. Roberto Agodini & Mark Dynarski, "undated". "Are Experiments the Only Option? A Look at Dropout Prevention Programs," Mathematica Policy Research Reports 51241adbf9fa4a26add6d54c5, Mathematica Policy Research.
    29. World Bank, 2003. "Nicaragua - Poverty Assessment : Raising Welfare and Reducing Vulnerability," World Bank Publications - Reports 14668, The World Bank Group.
    30. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    31. 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.
    32. Skoufias, Emmanuel, 2005. "PROGRESA and its impacts on the welfare of rural households in Mexico:," Research reports 139, International Food Policy Research Institute (IFPRI).
    33. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, January.
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    9. Hugh Sharma Waddington & Paul Fenton Villar & Jeffrey C. Valentine, 2023. "Can Non-Randomised Studies of Interventions Provide Unbiased Effect Estimates? A Systematic Review of Internal Replication Studies," Evaluation Review, , vol. 47(3), pages 563-593, June.
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    11. Smith, Lisa C. & Khan, Faheem & Frankenberger, Timothy R. & Wadud, A.K.M. Abdul, 2013. "Admissible Evidence in the Court of Development Evaluation? The Impact of CARE’s SHOUHARDO Project on Child Stunting in Bangladesh," World Development, Elsevier, vol. 41(C), pages 196-216.
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