Advanced Search
MyIDEAS: Login

Bandwidth Selection and the Estimation of Treatment Effects with Unbalanced Data

Contents:

Author Info

  • Jose C. GALDO
  • Jeffrey SMITH
  • Dan BLACK

Abstract

This paper addresses the selection of smoothing parameters for estimating the average treatment effect on the treated using matching methods. Because precise estimation of the expected counterfactual is particularly important in regions containing the mass of the treated units, we define and implement weighted cross-validation approaches that improve over conventional methods by considering the location of the treated units in the selection of the smoothing parameters. We also implement a locally varying bandwidth method that uses larger bandwidths in areas where the mass of the treated units is located. A Monte Carlo study compares our proposed methods to the conventional unweighted method and to a related method inspired by BERGEMANN et al. [2005]. The Monte Carlo analysis indicates efficiency gains from all methods that take account of the location of the treated units. We also apply all five methods to bandwidth selection in the context of the data from LALONDE'S [1986] study of the performance of non-experimental estimators using the experimental data from the National Supported Work (NSW) Demonstration program as a benchmark. Overall, both the Monte Carlo analysis and the empirical application show feasible precision gains for the weighted cross-validation and the locally varying bandwidth approaches.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.jstor.org/stable/27917245
Download Restriction: no

Bibliographic Info

Article provided by ENSAE in its journal Annals of Economics and Statistics.

Volume (Year): (2008)
Issue (Month): 91-92 ()
Pages: 189-216

as in new window
Handle: RePEc:adr:anecst:y:2008:i:91-92:p:10

Contact details of provider:
Postal: 3, avenue Pierre Larousse, 92245 Malakoff Cedex
Phone: 01.41.17.51.55
Email:
Web page: http://annales.ensae.fr/
More information through EDIRC

Related research

Keywords:

Other versions of this item:

Find related papers by JEL classification:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January.
  2. 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.
  3. Wang-Sheng Lee, 2013. "Propensity score matching and variations on the balancing test," Empirical Economics, Springer, vol. 44(1), pages 47-80, February.
  4. Steven Lehrer & Gregory Kordas, 2013. "Matching using semiparametric propensity scores," Empirical Economics, Springer, vol. 44(1), pages 13-45, February.
  5. Rajeev H. Dehejia & Sadek Wahba, 1998. "Propensity Score Matching Methods for Non-experimental Causal Studies," NBER Working Papers 6829, National Bureau of Economic Research, Inc.
  6. Smith, Jeffrey & Todd, Petra, 2005. "Rejoinder," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 365-375.
  7. Speckesser, Stefan & Fitzenberger, Bernd & Bergemann, Annette, 2004. "Evaluating the Dynamic Employment Effects of Training Programs in East Germany Using Conditional Difference-in-Differences," ZEW Discussion Papers 04-41, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  8. Jianqing Fan & Theo Gasser & Irène Gijbels & Michael Brockmann & Joachim Engel, 1997. "Local Polynomial Regression: Optimal Kernels and Asymptotic Minimax Efficiency," Annals of the Institute of Statistical Mathematics, Springer, vol. 49(1), pages 79-99, March.
  9. Guido Imbens, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometric Society World Congress 2000 Contributed Papers 1166, Econometric Society.
  10. Dehejia, Rajeev, 2005. "Practical propensity score matching: a reply to Smith and Todd," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 355-364.
  11. 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.
  12. Hidehiko Ichimura & Oliver Linton, 2003. "Asymptotic expansions for some semiparametric program evaluation estimators," LSE Research Online Documents on Economics 2098, London School of Economics and Political Science, LSE Library.
  13. Heckman, J.J. & Hotz, V.J., 1988. "Choosing Among Alternative Nonexperimental Methods For Estimating The Impact Of Social Programs: The Case Of Manpower Training," University of Chicago - Economics Research Center 88-12, Chicago - Economics Research Center.
  14. 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.
  15. Dan A. Black & Jeffrey Smith, 2003. "How Robust is the Evidence on the Effects of College Quality? Evidence From Matching," University of Western Ontario, CIBC Centre for Human Capital and Productivity Working Papers 20033, University of Western Ontario, CIBC Centre for Human Capital and Productivity.
  16. 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.
  17. 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.
  18. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," NBER Working Papers 6699, 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. Heckman, James J & Ichimura, Hidehiko & Todd, Petra E, 1997. "Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Wiley Blackwell, vol. 64(4), pages 605-54, October.
  21. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
  22. 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.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Martin Huber & Michael Lechner & Conny Wunsch, 2010. "How to control for many covariates? Reliable estimators based on the propensity score," University of St. Gallen Department of Economics working paper series 2010 2010-30, Department of Economics, University of St. Gallen.
  2. Bernd Fitzenberger & Olga Orlanski & Aderonke Osikominu & Marie Paul, 2013. "Déjà Vu? Short-term training in Germany 1980–1992 and 2000–2003," Empirical Economics, Springer, vol. 44(1), pages 289-328, February.
  3. Chong, Alberto & Galdo, Jose C., 2006. "Does the Quality of Training Programs Matter? Evidence from Bidding Processes Data," IZA Discussion Papers 2202, Institute for the Study of Labor (IZA).
  4. Peter R. Mueser & Carolyn J. Heinrich & Kenneth R. Troske & Kyung-Seong Jeon & Daver C. Kahvecioglu, 2010. "New Estimates of Public Employment and Training Program Net Impacts: A Nonexperimental Evaluation of the Workforce Investment Act Program," Working Papers 1003, Department of Economics, University of Missouri.
  5. Steven Lehrer & Gregory Kordas, 2013. "Matching using semiparametric propensity scores," Empirical Economics, Springer, vol. 44(1), pages 13-45, February.
  6. Wang-Sheng Lee, 2013. "Propensity score matching and variations on the balancing test," Empirical Economics, Springer, vol. 44(1), pages 47-80, February.
  7. Collins, J. Michael, 2013. "The impacts of mandatory financial education: Evidence from a randomized field study," Journal of Economic Behavior & Organization, Elsevier, vol. 95(C), pages 146-158.
  8. Hans J. Baumgartner & Marco Caliendo, 2007. "Turning Unemployment into Self-Employment: Effectiveness and Efficiency of Two Start-Up Programmes," Discussion Papers of DIW Berlin 671, DIW Berlin, German Institute for Economic Research.
  9. Marco Caliendo, 2009. "Start-up subsidies in East Germany: finally, a policy that works?," International Journal of Manpower, Emerald Group Publishing, vol. 30(7), pages 625-647, November.
  10. Martin Biewen & Bernd Fitzenberger & Aderonke Osikominu & Marie Paul, 2012. "The effectiveness of public sponsored training revisited: The importance of data and methodological choices," ECON - Working Papers 091, Department of Economics - University of Zurich.
  11. Dorn, Sabrina & Egger, Peter, 2011. "On the Distribution of Exchange Rate Regime Treatment Effects on International Trade," CEPR Discussion Papers 8654, C.E.P.R. Discussion Papers.
  12. Hans J. Baumgartner & Marco Caliendo, 2008. "Turning Unemployment into Self-Employment: Effectiveness of Two Start-Up Programmes," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(3), pages 347-373, 06.
  13. Peter Z. Schochet & Ronald D'Amico & Jillian Berk & Nathan Wozny, 2012. "Methodological Notes Regarding the Impact Analysis," Mathematica Policy Research Reports 7734, Mathematica Policy Research.
  14. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:adr:anecst:y:2008:i:91-92:p:10. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Robert Gary-Bobo).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.