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Kausalanalyse durch Matchingverfahren

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Author Info
Markus Gangl
Thomas A. DiPrete
Abstract

Having close linkages with the counterfactual concept of causality, nonparametric matching estimators have recently gained in popularity in the statistical and econometric literature on causal analysis. Introducing key concepts of the Rubin causal model (RCM), the paper discusses the implementation of counterfactual analyses by propensity score matching methods. We emphasize the suitability of the counterfactual framework for sociological questions as well as the assumptions underlying matching methods relative to standard regression analysis. We then illustrate the application of matching estimators in an analysis of the causal effect of unemployment on workers’ subsequent careers.

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File URL: http://www.diw.de/documents/publikationen/73/diw_01.c.41226.de/dp401.pdf
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Publisher Info
Paper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 401.

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Length: 30 p.
Date of creation: 2004
Date of revision:
Handle: RePEc:diw:diwwpp:dp401

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Related research
Keywords: Matching; Causality; Nonparametric estimators; Observational data; Rubin causal model; Counterfactual analysis;

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  1. Manski, C.F., 1990. "The Selection Problem," Working papers 90-12, Wisconsin Madison - Social Systems.
  2. 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, 08. [Downloadable!] (restricted)
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  3. Falk, Armin & Fehr, Ernst, 2003. "Why labour market experiments?," Labour Economics, Elsevier, vol. 10(4), pages 399-406, August. [Downloadable!] (restricted)
  4. Michael Lechner, 2002. "Program Heterogeneity And Propensity Score Matching: An Application To The Evaluation Of Active Labor Market Policies," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 205-220, May. [Downloadable!] (restricted)
  5. James J. Heckman, 1991. "Randomization and Social Policy Evaluation," NBER Technical Working Papers 0107, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  6. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February. [Downloadable!] (restricted)
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  7. Jeffrey Smith & Petra Todd, 2003. "Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?," University of Western Ontario, CIBC Human Capital and Productivity Project Working Papers 20035, University of Western Ontario, CIBC Human Capital and Productivity Project. [Downloadable!]
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  8. Ernst Fehr & Simon Gachter, 2000. "Cooperation and Punishment in Public Goods Experiments," American Economic Review, American Economic Association, vol. 90(4), pages 980-994, September. [Downloadable!] (restricted)
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  9. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267. [Downloadable!] (restricted)
  10. repec:att:wimass:199217 is not listed on IDEAS
  11. Lechner, Michael, 1999. "Earnings and Employment Effects of Continuous Off-the-Job Training in East Germany after Unification," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 74-90, January.
  12. Heckman, James J & Ichimura, Hidehiko & Todd, Petra, 1998. "Matching as an Econometric Evaluation Estimator," Review of Economic Studies, Blackwell Publishing, vol. 65(2), pages 261-94, April. [Downloadable!] (restricted)
  13. Jeffrey A. Smith & Petra E. Todd, 2001. "Reconciling Conflicting Evidence on the Performance of Propensity-Score Matching Methods," American Economic Review, American Economic Association, vol. 91(2), pages 112-118, May. [Downloadable!] (restricted)
  14. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-75, March. [Downloadable!] (restricted)
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  15. Rajeev H. Dehejia & Sadek Wahba, 1998. "Causal Effects in Non-Experimental Studies: Re-Evaluating the Evaluation of Training Programs," NBER Working Papers 6586, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  16. Heckman, James, 2001. "Accounting for Heterogeneity, Diversity and General Equilibrium in Evaluating Social Programmes," Economic Journal, Royal Economic Society, vol. 111(475), pages F654-99, November. [Downloadable!] (restricted)
  17. James Heckman & Justin L. Tobias & Edward Vytlacil, 2003. "Simple Estimators for Treatment Parameters in a Latent-Variable Framework," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 748-755, 06. [Downloadable!] (restricted)
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  18. Guido W. Imbens, 2003. "Nonparametric Estimation of Average Treatment Effects under Exogeneity: A Review," NBER Technical Working Papers 0294, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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