surveys and other empirical studies. To control for a potential selection-bias we implement a doubly-robust estimator in the …

expectation function and the conditional density can be nonparametric kernel or series estimators or ML methods. Using doubly … robust influence function and cross-fitting, we give tractable primitive conditions under which the nuisance estimators do …

doubly robust influence function and cross-fitting, we give tractable primitive conditions under which the nuisance …

expectation function and the conditional density can be nonparametric kernel or series estimators or ML methods. Using doubly … robust influence function and cross-fitting, we give tractable primitive conditions under which the nuisance estimators do …