Implementing blopmatching in Stata
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Date
2021
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Abstract
The blopmatching estimator for average treatment effects in observational studies is a nonparametric matching estimator proposed by Diaz, Rau, and Rivera (2015, Review of Economics and Statistics 97: 803-812). This approach uses the solutions of linear programming problems to build the weighting schemes that are used to impute the missing potential outcomes. In this article, we describe blopmatch, a new command that implements these estimators.
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st0632, blopmatch, average treatment effects, matching, linear programming, synthetic covariate