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Impact evaluation of multiple overlapping programs under a conditional independence assumption

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  • Cuong, Nguyen Viet

Abstract

Under the assumption on conditional independence between potential outcomes and program assignment, program impacts measured by the Average Treatment Effect (ATE) and the Average Treatment Effect on Treated (ATT) can be identified and estimated using cross-section regression or propensity score matching (PSM). Traditional impact literature often deals with the impact evaluation of a single program. In reality, one can participate in several programs simultaneously and the programs may be correlated. This paper discusses cross-section regression and PSM methods in this general context. It is shown that under the PSM method, impact of a program of interest can be measured as a weighted average of program impacts on groups with different program statuses. Estimation of impacts of multiple overlapping programs is illustrated using Monte Carlo simulation and an empirical example of impact measurement of international and internal remittances in Vietnam.

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Bibliographic Info

Article provided by Elsevier in its journal Research in Economics.

Volume (Year): 63 (2009)
Issue (Month): 1 (March)
Pages: 27-54

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Handle: RePEc:eee:reecon:v:63:y:2009:i:1:p:27-54

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Web page: http://www.elsevier.com/locate/inca/622941

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Keywords: Treatment effect Impact evaluation Multiple programs Matching Propensity score;

References

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  1. Guido W. Imbens, 1999. "The Role of the Propensity Score in Estimating Dose-Response Functions," NBER Technical Working Papers 0237, National Bureau of Economic Research, Inc.
  2. Stark, Oded & Taylor, J Edward & Yitzhaki, Shlomo, 1986. "Remittances and Inequality," Economic Journal, Royal Economic Society, vol. 96(383), pages 722-40, September.
  3. Markus Fr–lich, 2004. "Programme Evaluation with Multiple Treatments," Journal of Economic Surveys, Wiley Blackwell, vol. 18(2), pages 181-224, 04.
  4. Stark, Oded & Taylor, J. Edward & Yitzhaki, Shlomo, 1988. "Migration, remittances and inequality : A sensitivity analysis using the extended Gini index," Journal of Development Economics, Elsevier, vol. 28(3), pages 309-322, May.
  5. Adams, Richard H, Jr, 1989. "Worker Remittances and Inequality in Rural Egypt," Economic Development and Cultural Change, University of Chicago Press, vol. 38(1), pages 45-71, October.
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Cited by:
  1. Nguyen Viet, Cuong, 2012. "Selection of Control Variables in Propensity Score Matching: Evidence from a Simulation Study," MPRA Paper 36377, University Library of Munich, Germany.

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