Estimation and inference for policy relevant treatment effects

The policy relevant treatment effect (PRTE) measures the average effect of switching from a status-quo policy to a counterfactual policy under consideration. Estimation of the PRTE involves estimation of multiple preliminary parameters, including propensity scores, conditional expectation functions...

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Bibliographic Details
Published in:Journal of econometrics 2023-06, Vol.234 (2), p.394-450
Main Authors: Sasaki, Yuya, Ura, Takuya
Format: Article
Language:English
Subjects:
Double debiased estimation
Orthogonal score
Policy relevant treatment effects
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Summary:The policy relevant treatment effect (PRTE) measures the average effect of switching from a status-quo policy to a counterfactual policy under consideration. Estimation of the PRTE involves estimation of multiple preliminary parameters, including propensity scores, conditional expectation functions of the outcome and covariates given the propensity score, and marginal treatment effects. These preliminary estimators can affect the asymptotic distribution of the PRTE estimator in complicated and intractable manners. In this light, we propose an orthogonal score for double debiased estimation of the PRTE, whereby the asymptotic distribution of the PRTE estimator is obtained without any influence of preliminary parameter estimators as far as they satisfy mild requirements of convergence rates. To our knowledge, this paper is the first to develop limit distribution theories for inference about the PRTE.
ISSN:0304-4076
1872-6895
DOI:10.1016/j.jeconom.2021.03.015