Covariate selection for non-parametric estimation of treatment effects
In observational studies, the non-parametric estimation of a binary treatment effect is often performed by matching each treated individual with a control unit which is similar in observed characteristics (covariates). In practical applications, the reservoir of covariates available may be extensive and the question arises which covariates should be matched for. The current practice consists in matching for covariates which are not balanced for the treated and the control groups, i.e. covariates affecting the treatment assignment. This paper develops a theory based on graphical models, whose results emphasize the need for methods looking both at how the covariates affect the treatment assignment and the outcome. Furthermore, we propose identification algorithms to select at minimal set of covariates to match for. An application to the estimation of the effect of a social program is used to illustrate the implementation of such algorithms.
|Date of creation:||25 Jan 2005|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (+46) 18 - 471 70 70
Fax: (+46) 18 - 471 70 71
Web page: http://www.ifau.se/
More information through EDIRC
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.:
- Alberto Abadie & Guido W. Imbens, 2002. "Simple and Bias-Corrected Matching Estimators for Average Treatment Effects," NBER Technical Working Papers 0283, National Bureau of Economic Research, Inc.
- 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.
- Heckman, James & Navarro-Lozano, Salvador, 2003.
"Using matching, instrumental variables and control functions to estimate economic choice models,"
Working Paper Series
2003:4, IFAU - Institute for Evaluation of Labour Market and Education Policy.
- 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, February.
- Heckman, James J. & Navarro, Salvador, 2003. "Using Matching, Instrumental Variables and Control Functions to Estimate Economic Choice Models," IZA Discussion Papers 768, Institute for the Study of Labor (IZA).
- James J. Heckman & Salvador Navarro-Lozano, 2003. "Using Matching, Instrumental Variables and Control Functions to Estimate Economic Choice Models," NBER Working Papers 9497, National Bureau of Economic Research, Inc.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
- Su, Liangjun & White, Halbert, 2003.
"Testing Conditional Independence Via Empirical Likelihood,"
University of California at San Diego, Economics Working Paper Series
qt35v8g0fm, Department of Economics, UC San Diego.
- Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
When requesting a correction, please mention this item's handle: RePEc:hhs:ifauwp:2005_004. 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: (Margareta Wicklander)
If references are entirely missing, you can add them using this form.