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; (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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Paper provided by Columbia University, Department of Economics in its series Discussion Papers with number
1998_02.
Find related papers by JEL classification: 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 - - - Microeconomic Data C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
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