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Radius matching on the propensity score with bias adjustment: finite sample behaviour, tuning parameters and software implementation

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  • Huber, Martin

    ()

  • Lechner, Michael

    ()

  • Steinmayr, Andreas

    ()

Abstract

Using a simulation design that is based on empirical data, a recent study by Huber, Lechner and Wunsch (2012) finds that distance-weighted radius matching with bias adjustment as proposed in Lechner, Miquel and Wunsch (2011) is competitive among a broad range of propensity score-based estimators used to correct for mean differences due to observable covariates. In this paper, we further investigate the finite sample behaviour of radius matching with respect to various tuning parameters. The results are intended to help the practitioner to choose suitable values of these parameters when using this method, which has been implemented as "radiusmatch" command in the software packages GAUSS, STATA and the R package "radiusmatching".

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Bibliographic Info

Paper provided by University of St. Gallen, School of Economics and Political Science in its series Economics Working Paper Series with number 1226.

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Length: 40 pages
Date of creation: Dec 2012
Date of revision:
Handle: RePEc:usg:econwp:2012:26

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Related research

Keywords: Propensity score matching; radius matching; selection on observables; empirical Monte Carlo study; finite sample properties;

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References

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  1. Lechner, Michael & Wunsch, Conny, 2006. "Are Training Programs More Effective When Unemployment Is High?," IZA Discussion Papers 2355, Institute for the Study of Labor (IZA).
  2. Behncke, Stefanie & Frölich, Markus & Lechner, Michael, 2008. "A Caseworker Like Me - Does the Similarity between unemployed and Caseworker Increase Job Placements?," CEPR Discussion Papers, C.E.P.R. Discussion Papers 6784, C.E.P.R. Discussion Papers.
  3. Michael Lechner & Conny Wunsch, 2009. "Active labour market policy in East Germany," The Economics of Transition, The European Bank for Reconstruction and Development, The European Bank for Reconstruction and Development, vol. 17(4), pages 661-702, October.
  4. James G. MacKinnon, 2006. "Bootstrap Methods in Econometrics," Working Papers, Queen's University, Department of Economics 1028, Queen's University, Department of Economics.
  5. Guido M. Imbens & Jeffrey M. Wooldridge, 2008. "Recent Developments in the Econometrics of Program Evaluation," NBER Working Papers 14251, National Bureau of Economic Research, Inc.
  6. 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.
  7. Joffe, Marshall M. & Ten Have, Thomas R. & Feldman, Harold I. & Kimmel, Stephen E., 2004. "Model Selection, Confounder Control, and Marginal Structural Models: Review and New Applications," The American Statistician, American Statistical Association, American Statistical Association, vol. 58, pages 272-279, November.
  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, Department of Economics, University of St. Gallen 2007-19, Department of Economics, University of St. Gallen.
  9. Michael Lechner & Ruth Miquel & Conny Wunsch, 2011. "Long‐Run Effects Of Public Sector Sponsored Training In West Germany," Journal of the European Economic Association, European Economic Association, European Economic Association, vol. 9(4), pages 742-784, 08.
  10. Stefanie Behncke & Markus Frˆlich & Michael Lechner, 2010. "Unemployed and their caseworkers: should they be friends or foes?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(1), pages 67-92.
  11. Hotz, V. Joseph & Crump, Richard K. & Mitnik, Oscar A. & Imbens, Guido, 2009. "Dealing with Limited Overlap in Estimation of Average Treatment Effects," Scholarly Articles 3007645, Harvard University Department of Economics.
  12. 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.
  13. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, Econometric Society, vol. 66(5), pages 1017-1098, September.
  14. Heckman, James J & Ichimura, Hidehiko & Todd, Petra, 1998. "Matching as an Econometric Evaluation Estimator," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 65(2), pages 261-94, April.
  15. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2009. "Does Leaving Welfare Improve Health? Evidence for Germany," CEPR Discussion Papers, C.E.P.R. Discussion Papers 7421, C.E.P.R. Discussion Papers.
  16. Frolich, Markus, 2007. "Nonparametric IV estimation of local average treatment effects with covariates," Journal of Econometrics, Elsevier, Elsevier, vol. 139(1), pages 35-75, July.
  17. Guido Imbens, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometric Society World Congress 2000 Contributed Papers, Econometric Society 1166, Econometric Society.
  18. Bryan S. Graham & Cristine Campos de Xavier Pinto & Daniel Egel, 2008. "Inverse Probability Tilting for Moment Condition Models with Missing Data," NBER Working Papers 13981, National Bureau of Economic Research, Inc.
  19. 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.
  20. Busso, Matias & DiNardo, John & McCrary, Justin, 2009. "New Evidence on the Finite Sample Properties of Propensity Score Matching and Reweighting Estimators," IZA Discussion Papers 3998, Institute for the Study of Labor (IZA).
  21. Martin Huber, 2010. "Identification of average treatment effects in social experiments under different forms of attrition," University of St. Gallen Department of Economics working paper series 2010, Department of Economics, University of St. Gallen 2010-22, Department of Economics, University of St. Gallen.
  22. Lechner, Michael, 2009. "Long-run labour market and health effects of individual sports activities," Journal of Health Economics, Elsevier, Elsevier, vol. 28(4), pages 839-854, July.
  23. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, Elsevier, vol. 175(1), pages 1-21.
  24. 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.
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Citations

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Cited by:
  1. Lechner, Michael & Sari, Nazmi, 2014. "Labor Market Effects of Sports and Exercise: Evidence from Canadian Panel Data," IZA Discussion Papers 7931, Institute for the Study of Labor (IZA).
  2. Adrian Hille & Jürgen Schupp, 2013. "How Learning a Musical Instrument Affects the Development of Skills," SOEPpapers on Multidisciplinary Panel Data Research 591, DIW Berlin, The German Socio-Economic Panel (SOEP).
  3. Lechner, Michael & Strittmatter, Anthony, 2014. "Practical Procedures to Deal with Common Support Problems in Matching Estimation," Economics Working Paper Series 1410, University of St. Gallen, School of Economics and Political Science.
  4. Downward, Paul & Lechner, Michael, 2013. "Heterogeneous sports participation and labour market outcomes in England," CEPR Discussion Papers, C.E.P.R. Discussion Papers 9701, C.E.P.R. Discussion Papers.
  5. Denisova-Schmidt, Elena & Huber, Martin, 2014. "Regional Differences in Perceived Corruption among Ukrainian Firms," Economics Working Paper Series 1407, University of St. Gallen, School of Economics and Political Science.

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