This book reviews recent approaches for partial identification of average treatment effects with instrumental variables in the program evaluation literature, including Manski’s bounds, bounds based on threshold crossing models, and bounds based on the Local Average Treatment Effect (LATE)...

We employ quantile regression fixed effects models to estimate the income-pollution relationship on <italic>NO</italic> _{<italic>x</italic>} (nitrogen oxide) and <italic>SO</italic> ₂ (sulfur dioxide) using U.S. data. Conditional median results suggest that conditional mean methods provide too optimistic estimates about emissions reduction for...</italic>

In many observational studies, the treatment may not be binary or categorical but rather continuous, so the focus is on estimating a continuous dose– response function. In this article, we propose a set of programs that semiparametrically estimate the dose–response function of a continuous...

We semiparametrically estimate average causal effects of different lengths of exposure to academic and vocational instruction in the Job Corps (JC) under the assumption that selection into different lengths is based on a rich set of observed covariates and time-invariant factors. We find that...

We review and extend nonparametric partial identification results for average and quantile treatment effects in the presence of sample selection. These methods are applied to assessing the wage effects of Job Corps, United States’ largest job-training program targeting disadvantaged youth....