We consider identification and estimation of nonseparable sample selection models with censored selection rules. We employ a control function approach and discuss different objects of interest based on (1) local effects conditional on the control function, and (2) global effects obtained from...

Catastrophic wildfires in California have become more frequent in past decades, while insured losses per event have been rising substantially. On average, California ranks the highest among states in the U.S. in the number of fires as well as the number of acres burned each year. The study of...

In zahlreichen großen Datensätzen von wissenschaftlichem Interesse sind einige Variablen, wie z. B. die Lohnhöhe, top-coded oder rechtszensiert. Zur Analyse von Löhnen auf der Grundlage der IAB-Beschäftigtenstichprobe muss zunächst das Problem der, an der Beitragsbemessungsgrenze der...

The context of community-based interventions presents formidable problems for any evaluation analysis. Group-randomized studies do possess ideal properties in theory, but in practice, grouprandomization might not be a feasible alternative at all or group-randomized studies might be contaminated....

This paper proposes a nonparametric method for evaluating treatment effects in the presence of both treatment endogeneity and attrition/non-response bias, using two instrumental variables. Making use of a discrete instrument for the treatment and a continuous instrument for...

In this paper, we propose a new approach to estimating sample selection models that combines Generalized Tukey Lambda (GTL) distributions with copulas. The GTL distribution is a versatile univariate distribution that permits a wide range of skewness and thick- or thin-tailed behavior in the data...

We consider the estimation of a semiparametric location-scale model subject to endogenous selection, in the absence of an instrument or a large support regressor. Identification relies on the independence between the covariates and selection, for arbitrarily large values of the outcome. In this...

This paper develops a nonparametric methodology for treatment evaluation with multiple outcome periods under treatment endogeneity and missing outcomes. We use instrumental variables, pre-treatment characteristics, and short-term (or intermediate) outcomes to identify the average treatment...

The present paper develops a simple asymmetrical informational model that allows us to understand the individual´s willingness to participate in a strike. We develop and compare two signaling models of strikes: in one, firms are able to monitor and enforce hours and offer different workweeks to...

We partially identify population treatment effects in observational data under sample selection, without the benefit of random treatment assignment. We provide bounds both for the average and the quantile population treatment effects, combining assumptions for the selected and the non-selected...