A large part of the recent literature on program evaluation has focused on estimation of the average effect of the treatment under assumptions of unconfoundedness or ignorability following the seminal work by Rubin (1974) and Rosenbaum and Rubin (1983). In many cases however, researchers are...

Estimation of average treatment effects under unconfoundedness or exogenous treatment assignment is often hampered by lack of overlap in the covariate distributions. This lack of overlap can lead to imprecise estimates and can make commonly used estimators sensitive to the choice of...

Estimation of average treatment effects under unconfounded or ignorable treatment assignment is often hampered by lack of overlap in the covariate distributions between treatment groups. This lack of overlap can lead to imprecise estimates, and can make commonly used estimators sensitive to the...

In this paper we develop two nonparametric tests of treatment effect heterogeneity. The first test is for the null hypothesis that the treatment has a zero average effect for all subpopulations defined by covariates. The second test is for the null hypothesis that the average effect conditional...

We investigate the problem of predicting the average effect of a new training program using experiences with previous implementations. There are two principal complications in doing so. First, the population in which the new program will be implemented may differ from the population in which the...

As part of recent reforms of the welfare programs in the U.S., many states and localities have refocused their Welfare-to-Work programs from an emphasis on human capital acquisition (i.e., providing basic education and vocational training) to an emphasis on "work-first," (i.e., moving welfare...

In this paper, we explore ways of combining experimental data and non-experimental methods to estimate the differential effects of components of training programs. We show how data from a multi-site experimental evaluation in which subjects are randomly assigned to any treatment versus a control...

We propose regression based estimators for beta representations of dynamic asset pricing models with an affine pricing kernel specification. We allow for state variables that are cross sectional pricing factors, forecasting variables for the price of risk, and factors that are both. The...

With the aim of improving the quality of asymptotic distributional approximations for nonlinear functionals of nonparametric estimators, this article revisits the large-sample properties of an important member of that class, namely a kernel-based weighted average derivative estimator. Asymptotic...