Propensity Score Matching Methods for Non-Experimental Causal Studies
AbstractThis paper considers causal inference and sample selection bias in non-experimental settings in which: (i) few units in the non-experimental comparison group are comparable to the treatment units; (ii) selecting a subset of comparison units similar to the treatment units is difficult because units must be compared across a high-dimentional set of pretreatment characteristics. We propose the use of propensity score matching methods, and implement them using data from the NSW experiment.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoPaper provided by Columbia University, Department of Economics in its series Discussion Papers with number 1998_02.
Length: 26 pages
Date of creation: 1998
Date of revision:
Contact details of provider:
Postal: 1022 International Affairs Building, 420 West 118th Street, New York, NY 10027
Phone: (212) 854-3680
Fax: (212) 854-8059
Web page: http://www.econ.columbia.edu/
More information through EDIRC
MATCHING ; EVALUATION ; ECONOMIC MODELS;
Other versions of this item:
- 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, 2002. "Propensity score matching methods for non-experimental causal studies," Discussion Papers 0102-14, Columbia University, Department of Economics.
- 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.
- C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
- C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
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.:
- 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.
- Daniel Friedlander & David H. Greenberg & Philip K. Robins, 1997. "Evaluating Government Training Programs for the Economically Disadvantaged," Journal of Economic Literature, American Economic Association, vol. 35(4), pages 1809-1855, December.
- Ashenfelter, Orley C, 1978. "Estimating the Effect of Training Programs on Earnings," The Review of Economics and Statistics, MIT Press, vol. 60(1), pages 47-57, February.
- Orley Ashenfelter & David Card, 1984.
"Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs,"
NBER Working Papers
1489, National Bureau of Economic Research, Inc.
- Ashenfelter, Orley & Card, David, 1985. "Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs," The Review of Economics and Statistics, MIT Press, vol. 67(4), pages 648-60, November.
- Orley Ashenfelter & David Card, 1984. "Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs," Working Papers 554, Princeton University, Department of Economics, Industrial Relations Section..
- Czajka, John L, et al, 1992. "Projecting from Advance Data Using Propensity Modeling: An Application to Income and Tax Statistics," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 117-31, April.
Blog mentionsAs found by EconAcademics.org, the blog aggregator for Economics research:CitEc Project, subscribe to its RSS feed for this item.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading lists or Wikipedia pages:
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Discussion Paper Coordinator).
If references are entirely missing, you can add them using this form.