2004•Wiley series in probability and statisticsRequires access

The Propensity Score with Continuous Treatments

Keisuke Hirano, Guido W. Imbens

Open publisher page 1,022 citations

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

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Available 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

Key concepts: Propensity score matching, Environmental science, Mathematics, Statistics

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