In this paper, we show how instrumental variable and matching estimators can be combined in order to identify a broader array of treatment effects. Instrumental variable estimators are known to estimate effects only for the compliers, which often represent only a small subset of the entire...

We investigate the finite sample properties of a large number of estimators for the average treatment effect on the treated that are suitable when adjustment for observable covariates is required, like inverse pro¬bability weighting, kernel and other variants of matching, as well as different...