Transcription of Implementing Propensity Score Matching Estimators with …
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Implementing Propensity Score Matching Estimators with …
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 Under some assumptions.
IMPLEMENTING PROPENSITY SCORE MATCHING ESTIMATORS WITH STATA Preparing the dataset Keep only one observation per individual Estimate the propensity score on the X’s e.g. via probit or logit and retrieve either the predicted probability or the index Necessary variables: the 1/0 dummy variable identifying the treated/controls the predicted ...
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