Most sample selection models assume that the errors are independent of the regressors. Under this assumption, all quantile and mean functions are parallel, which implies that quantile estimators cannot reveal any (per definition non-existing) heterogeneity. However, quantile estimators are...

Standard tests are generally not applicable in panel data models with selection. The paper shows how the Hausman specification test and the Sargan–Hansen test for overidentifying restrictions can be generalized to panel data models with unobserved heterogeneity and sample selection.

We introduce a framework to test for exogeneity of a variable in a regression based on cross-sectional data. By sorting data with respect to a function (sorting score) of known exogeneous variables it is possible to utilize a battery of tools originally develped to detecting model...

This paper proposes tests for instrument validity in sample selection models with non-randomly censored outcomes. Such models commonly invoke an exclusion restriction (i.e., the availability of an instrument affecting selection, but not the outcome) and additive separability of the errors in the...

We introduce a framework to test for exogeneity of a variable in a regression based on cross-sectional data. By sorting data with respect to a function (sorting score) of known exogeneous variables it is possible to utilize a battery of tools originally develped to detecting model...

We introduce a framework to test for exogeneity of a variable in a regression based on cross-sectional data. By sorting data with respect to a function (sorting score) of known exogeneous variables it is possible to utilize a battery of tools originally develped to detecting model...

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...

In this paper, I assess the employment and income effect of divorce for women in West Germany between 2000 and 2005. With newly available administrative data that allows me to adopt a causal approach, I find strong negative employment effects with respect to marginal employment and strong...

This paper presents a simple approach to deal with sample selection in models with multiplicative errors. Models for non-negative limited dependent variables such as counts fit this framework. The approach builds on a specification of the conditional mean of the outcome only and is, therefore,...

This paper develops methods of Bayesian inference in a sample selection model. The main feature of this model is that the outcome variable is only partially observed. We first present a Gibbs sampling algorithm for a model in which the selection and outcome errors are normally distributed. The...