We consider estimation and inference on average treatment effects under unconfoundedness conditional the realizations of variable covariates. Given nonparametric smoothness and/or shape restrictions mean outcome variable, we derive estimators confidence intervals (CIs) that are optimal in finite samples when regression errors normal with known variance. In contrast to conventional CIs, our CIs ...

We consider smooth stochastic programs and develop a discrete-time optimal-control problem for adaptively selecting sample sizes in a class of algorithms based on sample average approximations (SAA). The control problem aims to minimize the expected computational cost to obtain a near-optimal solution of a stochastic program and is solved approximately using dynamic programming. The optimal-con...