  The policy relevant treatment effect (PRTE) measures the average effect of
switching from a status-quo policy to a counterfactual policy. 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.
