class of indirect inference models. Our smoothing procedure makes use of importance sampling weights in estimation of the … auxiliary model on simulated data. The importance sampling weights are constructed from likelihood contributions implied by the …

in the presence of either sample selection or endogenous participation using maximum simulated likelihood. We allow for … the treatment to have an effect on both the sample selection or the participation rule and the main outcome. Applications …

countries adequately sample their entire student populations. In this research note, we show that larger exclusion and non … age group. However, accounting for sample selectivity does not alter existing research findings that tested academic …

In this paper, we propose a new approach to estimating sample selection models that combines Generalized Tukey Lambda … requisite for implementation of sample selection models in empirical research. Five applications ranging from wages and health …

" and of the bounding approach of Lee (2009). As a substitute for the instrument needed in sample selectivity correction … closer to point identification. We apply our sample selection correction in the context of a job-search experiment with low …

Sizeable gender differences in employment rates are observed in many countries. Sample selection into the workforce … densities in the presence of covariates which incorporates sample selection. We describe a simulation algorithm to implement … that when sample selection is taken into account gender wage gap widens, especially at the bottom of the wage distribution …

We examine instrumental variables estimation in situations where the instrument is only observed for a sub-sample …, which is fairly common in empirical research. Typically, researchers simply limit the analysis to the sub-sample where the …

the sample …