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.
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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:
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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, 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 non-experimental causal studies," Discussion Papers 0102-14, Columbia University, Department of Economics.
- C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
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- 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.:
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NBER Working Papers
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