Transcription of Implementing Propensity Score Matching Estimators with STATA
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Implementing Propensity Score Matching Estimators with STATA
1 Implementing Propensity Score Matching Estimatorswith STATAB arbara SianesiUniversity College LondonandInstitute for Fiscal StudiesE-mail: forUK STATA Users group , VII MeetingLondon, May 2001 2 BACKGROUND: THE EVALUATION PROBLEMPOTENTIAL-OUTCOME APPROACHE valuating the causal effect of some treatment on some outcome Yexperienced by units in the population of the outcome of unit i if i were exposed to the treatmentY0i the outcome of unit i if i were not exposed to the treatmentDi {0, 1} indicator of the treatment actually received by unit iYi = Y0i + Di (Y1i Y0i) the actually observed outcome of unit iX the set of pre-treatment characteristicsCAUSAL EFFECT FOR UNIT iY1i Y0iTHE FUNDAMENTAL PROBLEM OF CAUSAL INFERENCE impossible to observe the individual treatment effect impossible to make causal inference without making generallyuntestable assumptions3 U
comparison group: ywy iijj jC pi = ∈ ∑ 0 where: • C0(pi) is the set of neighbours of treated i in the control group • wij ∈[0, 1] with wij jC p∈ i ∑ = 0 1 is the weight on control j in forming a comparison with treated i Two broad groups of matching estimators individual neighbourhood weights
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