Propensity Score Matching Methods for Non-experimental Causal Studies
This 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, and (ii) selecting a subset of comparison units similar to the treatment units is difficult because units must be compared across a high-dimensional set of pre-treatment characteristics. We propose the use of propensity score matching methods and implement them using data from the NSW experiment. Following Lalonde (1986), we pair the experimental treated units with non-experimental comparison units from the CPS and PSID and compare the estimates of the treatment effect obtained using our methods to the benchmark results from the experiment. We show that the methods succeed in focusing attention on the small subset of the comparison units comparable to the treated units and, hence, in alleviating the bias due to systematic differences between the treated and comparison units.
|Date of creation:||Dec 1998|
|Date of revision:|
|Publication status:||published as Dehejia, Rajeev H. and Sadek Wahba. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," Review of Economics and Statistics, 2002, v84(1,Feb), 151-161.|
|Contact details of provider:|| Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.|
Web page: http://www.nber.org
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