Nguyen Viet, Cuong (2008): Impact Evaluation of Multiple Overlapping Programs using Difference-in-differences with Matching.
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Difference-in-differences with matching is a popular method in impact evaluation. Traditional impact evaluation methods including difference-in-differences with matching often deal with impact measurement of a single binary program. Imbens (1999) and Lechner (2001) extend the matching method to the case of multiple mutually exclusive programs. Frölich (2002) discusses different impact evaluation methods in the similar context. In reality, one can participate in several programs simultaneously and the programs may be overlapping. This paper discusses the method of difference-in-differences with matching in a general context of multiple overlapping programs. The method is applied to measure impacts of formal and informal credit in Vietnam using panel data from two Vietnam Household Living Standard Surveys in 2002 and 2004.
|Item Type:||MPRA Paper|
|Original Title:||Impact Evaluation of Multiple Overlapping Programs using Difference-in-differences with Matching|
|English Title:||Impact Evaluation of Multiple Overlapping Programs using Difference-in-differences with Matching|
|Keywords:||Treatment effect, impact evaluation, multiple programs, difference-in-differences, matching, propensity score.|
|Subjects:||C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C23 - Models with Panel Data; Longitudinal Data; Spatial Time Series
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C21 - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
|Depositing User:||Cuong Nguyen Viet|
|Date Deposited:||10. Sep 2010 17:17|
|Last Modified:||14. Feb 2013 15:14|
Cochran, W. G. (1968). The effectiveness of Adjustment by Subclassification in Removing Bias in Observational Studies. Biometrics 24, 295-313. Cochran, W. G. and S. P. Chambers (1965). The Planning of Observational Studies of Human Population. Journal of the Royal Statistical Society. Series A (General), Vol. 128, No. 2. (1965), pp. 234-266. Conning, J. and Christopher U. (2005). Rural Financial Markets in Developing Countries, Economic Growth Center, Yale University, Center Discussion Paper No. 914. Dawid, A. P. (1979). Conditional Independence in Statistical Theory. J. R. Statist. Soc., 41, No. 1: 1-31. Dehejia, R. H. and Wahba S. (1998). Propensity Score Matching Methods for Non Experimental Causal Studies. NBER Working Paper 6829, Cambridge, Mass. Frölich, M. (2002). Program Evaluation with Multiple Treatments. Discussion Paper 2002-17, Department of Economics, University of St. Gallen. Heckman, J., Lalonde, R., and Smith, J., (1999). The Economics and Econometrics of Active Labor Market Programs. Handbook of Labor Economics, Volume 3, Ashenfelter, A. and D. Card, eds., Amsterdam: Elsevier Science. Heckman, J., Ichimura H. and Todd P. (1997). Matching as an Econometric Evaluation Estimators: Evidence from Evaluating a Job Training Programme. Review of Economic Studies, 64 (4), 605- 654. Imbens, G. (1999). The Role of the Propensity Score in Estimating Dose-Response Functions NBER Technical Working Paper 237. Lechner, M. (2001). Identification And Estimation of Causal Effects of Multiple Treatments under the Conditional Independence Assumption (In Lechner, M. and Pfeiffer, F. (Eds.), Econometric Evaluation of Labour Market Policies. Heidelberg: Physica-Verlag.) Quandt, R. (1972). Methods for Estimating Switching Regressions. Journal of the American Statistical Association, 67(338):306-310. Rosenbaum, P. and Rubin R. (1983). The Central Role of the Propensity Score in Observational Studies for Causal Effects. Biometrika, 70 (1), 41-55. Rubin, D. (1974). Estimating Causal Effects of Treatments in Randomized and Non-Randomized Studies. Journal of Educational Psychology, 66:688-701. Rubin, D. (1977). Assignment to a Treatment Group on the Basis of a Covariate. Journal of Educational Statistics, 2 (1), 1-26. Rubin, D. (1979). Using Multivariate Sampling and Regression Adjustment to Control Bias in Observational Studies. Journal of the American Statistical Association, 74: 318–328. Rubin, D. (1980). Bias Reduction Using Mahalanobis-Metric Matching. Biometrics, 36 (2): 293–298. Zeller, M., A. Diagne, and C. Mataya (1997). Market Access by Smallholder Farmers in Malawi: Implications for Technology Adoption, Agricultural Productivity, And Crop Income. Agricultural Economics, 19 (1 – 2): 219 – 229.