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How to control for many covariates? Reliable estimators based on the propensity score

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  • Martin Huber

    ()

  • Michael Lechner

    ()

  • Conny Wunsch

    ()

Abstract

We investigate the finite sample properties of a large number of estimators for the average treatment effect on the treated that are suitable when adjustment for observable covariates is required, like inverse pro¬bability weighting, kernel and other variants of matching, as well as different parametric models. The simulation design used is based on real data usually employed for the evaluation of labour market programmes in Germany. We vary several dimensions of the design that are of practical importance, like sample size, the type of the outcome variable, and aspects of the selection process. We find that trimming individual observations with too much weight as well as the choice of tuning parameters is important for all estimators. The key conclusion from our simulations is that a particular radius matching estimator combined with regression performs best overall, in particular when robustness to misspecifications of the propensity score is considered an important property.

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Bibliographic Info

Paper provided by Department of Economics, University of St. Gallen in its series University of St. Gallen Department of Economics working paper series 2010 with number 2010-30.

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Length: 62 pages
Date of creation: Oct 2010
Date of revision:
Handle: RePEc:usg:dp2010:2010-30

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Keywords: Propensity score matching; kernel matching; inverse probability weighting; selection on observables; empirical Monte Carlo study; finite sample properties;

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References

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  1. Jochen Kluve & Boris Augurzky, 2005. "Assessing the performance of matching algorithms when selection into treatment is strong," RWI Discussion Papers 0021, Rheinisch-Westfälisches Institut für Wirtschaftsforschung.
  2. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2004. "Dealing with Limited Overlap in Estimation of Average Treatment Effects," Working Papers 0716, University of Miami, Department of Economics, revised 12 Jun 2007.
  3. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
  4. Galdo, Jose C. & Smith, Jeffrey A. & Black, Dan A., 2007. "Bandwidth Selection and the Estimation of Treatment Effects with Unbalanced Data," IZA Discussion Papers 3095, Institute for the Study of Labor (IZA).
  5. Flores, Carlos A. & Mitnik, Oscar A., 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," IZA Discussion Papers 4451, Institute for the Study of Labor (IZA).
  6. Zhao, Zhong, 2008. "Sensitivity of propensity score methods to the specifications," Economics Letters, Elsevier, vol. 98(3), pages 309-319, March.
  7. Richard Blundell & Monica Costa Dias & Costas Meghir & John Van Reenen, 2004. "Evaluating the Employment Impact of a Mandatory Job Search Program," Journal of the European Economic Association, MIT Press, vol. 2(4), pages 569-606, 06.
  8. Conny Wunsch & Michael Lechner, 2007. "What Did All the Money Do? On the General Ineffectiveness of Recent West German Labour Market Programmes," University of St. Gallen Department of Economics working paper series 2007 2007-19, Department of Economics, University of St. Gallen.
  9. Newey, Whitney K., 1984. "A method of moments interpretation of sequential estimators," Economics Letters, Elsevier, vol. 14(2-3), pages 201-206.
  10. Michael Lechner, 2000. "An Evaluation of Public-Sector-Sponsored Continuous Vocational Training Programs in East Germany," Journal of Human Resources, University of Wisconsin Press, vol. 35(2), pages 347-375.
  11. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-in-Differences Estimates?," The Quarterly Journal of Economics, MIT Press, vol. 119(1), pages 249-275, February.
  12. Stefanie Behncke & Markus Frölich & Michael Lechner, 2008. "A Caseworker Like Me - Does The Similarity Between Unemployed And Caseworker Increase Job Placements?," University of St. Gallen Department of Economics working paper series 2008 2008-08, Department of Economics, University of St. Gallen.
  13. Guido Imbens & Jeffrey Wooldridge, 2008. "Recent developments in the econometrics of program evaluation," CeMMAP working papers CWP24/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  14. Zhong Zhao, 2004. "Using Matching to Estimate Treatment Effects: Data Requirements, Matching Metrics, and Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 91-107, February.
  15. Behncke, Stefanie & Frölich, Markus & Lechner, Michael, 2007. "Unemployed and Their Caseworkers: Should They Be Friends or Foes?," CEPR Discussion Papers 6558, C.E.P.R. Discussion Papers.
  16. Peter Hall & Jeff Racine & Qi Li, 2004. "Cross-Validation and the Estimation of Conditional Probability Densities," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1015-1026, December.
  17. Hujer, Reinhard & Caliendo, Marco & Thomsen, Stephan Lothar, 2003. "New Evidence on the Effects of Job Creation Schemes in Germany - A Matching Approach with Threefold Heterogeneity," IZA Discussion Papers 750, Institute for the Study of Labor (IZA).
  18. Dehejia, Rajeev, 2005. "Practical propensity score matching: a reply to Smith and Todd," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 355-364.
  19. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, 07.
  20. 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.
  21. Frölich, Markus, 2002. "Nonparametric IV Estimation of Local Average Treatment Effects with Covariates," IZA Discussion Papers 588, Institute for the Study of Labor (IZA).
  22. Dehejia, R.H. & Wahba, S., 1998. "Propensity Score Matching Methods for Non-Experimental Causal Studies," Discussion Papers 1998_02, Columbia University, Department of Economics.
  23. Lechner, Michael, 2009. "Long-run labour market and health effects of individual sports activities," Journal of Health Economics, Elsevier, vol. 28(4), pages 839-854, July.
  24. Blundell, Richard & Costa Dias, Monica, 2008. "Alternative Approaches to Evaluation in Empirical Microeconomics," IZA Discussion Papers 3800, Institute for the Study of Labor (IZA).
  25. Heckman, James J & Ichimura, Hidehiko & Todd, Petra, 1998. "Matching as an Econometric Evaluation Estimator," Review of Economic Studies, Wiley Blackwell, vol. 65(2), pages 261-94, April.
  26. 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.
  27. Zhao, Zhong, 2006. "Matching Estimators and the Data from the National Supported Work Demonstration Again," IZA Discussion Papers 2375, Institute for the Study of Labor (IZA).
  28. Martin Huber, 2011. "Testing for covariate balance using quantile regression and resampling methods," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2881-2899, February.
  29. Ahmed Khwaja & Gabriel Picone & Martin Salm & Justin G. Trogdon, 2011. "A comparison of treatment effects estimators using a structural model of AMI treatment choices and severity of illness information from hospital charts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 825-853, 08.
  30. Marco Caliendo & Reinhard Hujer & Stephan L. Thomsen, 2006. "Sectoral Heterogeneity in the Employment Effects of Job Creation Schemes in Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 226(2), pages 139-179, March.
  31. Wooldridge, Jeffrey M., 2007. "Inverse probability weighted estimation for general missing data problems," Journal of Econometrics, Elsevier, vol. 141(2), pages 1281-1301, December.
  32. Michael Gerfin & Michael Lechner, 2002. "A Microeconometric Evaluation of the Active Labour Market Policy in Switzerland," Economic Journal, Royal Economic Society, vol. 112(482), pages 854-893, October.
  33. Alberto Abadie & Guido W. Imbens, 2009. "Matching on the Estimated Propensity Score," NBER Working Papers 15301, National Bureau of Economic Research, Inc.
  34. Alberto Abadie, 2005. "Semiparametric Difference-in-Differences Estimators," Review of Economic Studies, Oxford University Press, vol. 72(1), pages 1-19.
  35. DiNardo, John & Fortin, Nicole M & Lemieux, Thomas, 1996. "Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach," Econometrica, Econometric Society, vol. 64(5), pages 1001-44, September.
  36. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-20, September.
  37. Millimet, Daniel L. & Tchernis, Rusty, 2009. "On the Specification of Propensity Scores, With Applications to the Analysis of Trade Policies," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(3), pages 397-415.
  38. Markus Frölich, 2004. "Finite-Sample Properties of Propensity-Score Matching and Weighting Estimators," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 77-90, February.
  39. Hujer, Reinhard & Thomsen, Stephan L., 2010. "How do the employment effects of job creation schemes differ with respect to the foregoing unemployment duration?," Labour Economics, Elsevier, vol. 17(1), pages 38-51, January.
  40. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492 National Bureau of Economic Research, Inc.
  41. 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.
  42. Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, vol. 66(2), pages 315-332, March.
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