The Propensity Score with Continuous Treatments
Keisuke Hirano, Guido W. Imbens
Abstract
Keisuke Hirano, Guido W. Imbens
Abstract
of the binary treatment propensity score, which we label the generalized propensity score (GPS). We demonstrate that the GPS has many of the attractive properties of the binary treatment propensity score. Just as in the binary treatment case, adjusting for this scalar function of the covariates removes all biases associated with dierences in the covariates. The GPS also has certain balancing properties that can be used to assess the adequacy of particular specications of the score. We discuss estimation and inference in a parametric
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of the binary treatment propensity score, which we label the generalized propensity score (GPS). We demonstrate that the GPS has many of the attractive properties of the binary treatment propensity score. Just as in the binary treatment case, adjusting for this scalar function of the covariates removes all biases associated with dierences in the covariates. The GPS also has certain balancing properties that can be used to assess the adequacy of particular specications of the score. We discuss estimation and inference in a parametric
Key concepts: Propensity score matching, Environmental science, Mathematics, Statistics