treatrew: A user-written command for estimating average treatment effects by reweighting on the propensity score
Giovanni Cerulli
Ceris-CNR
National Research Council of Italy
Institute for Economic Research on Firms and Growth
Rome, Italy
[email protected]
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Abstract. Reweighting is a popular statistical technique to deal with inference
in the presence of a nonrandom sample, and various reweighting estimators
have been proposed in the literature. This article presents the user-written command
treatrew, which implements reweighting on the propensity-score estimator
as proposed by Rosenbaum and Rubin (1983, Biometrika 70: 41–55) in their seminal
article. The main contribution of this command lies in providing analytical
standard errors for the average treatment effects in the whole population, in the
subpopulation of the treated, and in that of the untreated. Standard errors are calculated
using the approximation suggested by Wooldridge (2010, 920–930, Econometric
Analysis of Cross Section and Panel Data [MIT Press]), but bootstrapped
standard errors can also be easily computed. Because an implementation of this
estimator with analytic standard errors and nonnormalized weights is missing in
Stata, this article and the accompanying ado-file aim to provide the community
with an easy-to-use method for reweighting on the propensity-score. The estimator
proves to be a valuable tool for estimating average treatment effects under
selection on observables.
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Giovanni Cerulli
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treatrew, treatment models, reweighting, propensity score, average treatment effects, ATE, ATET, ATENT
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