To analyze data obtained by non-random sampling in the presence of cross-sectional dependence, estimation of a sample selection model with a spatial lag of a latent dependent variable or a spatial error in both the selection and outcome equations is considered. Since there is no estimation...

The identification of parameters in a nonseparable single-index models with correlated random effects is considered in the context of panel data with a fixed number of time periods. The identification assumption is based on the correlated random-effect structure: the distribution of individual...

An important and widely used class of semiparametric models is formed by the varying-coefficient models. Although the varying coefficients are traditionally assumed to be smooth functions, the varying-coefficient model is considered here with the coefficient functions containing a finite set of...

This paper extends an existing outlier-robust estimator of linear dynamic panel data models with fixed effects, which is based on the median ratio of two consecutive pairs of first-differenced data. To improve its precision and robust properties, a general procedure based on many pairwise...

The secured borrowing based on sell/buy-backs agreements is studied, specifically considering both: quantity and price. The empirical evidence presented in this paper suggests that, after controlling for specific individual characteristics, group-specific effects (defined by belonging or not to...

The panel-data regression models are frequently applied to micro-level data, which often suffer from data contamination, erroneous observations, or unobserved heterogeneity. Despite the adverse effects of outliers on classical estimation methods, there are only a few robust estimation methods...

A new class of robust regression estimators is proposed that forms an alternative to traditional robust one-step estimators and that achieves the √n rate of convergence irrespective of the initial estimator under a wide range of distributional assumptions. The proposed reweighted least trimmed...

To accommodate the inhomogenous character of financial time series over longer time periods, standard parametric models can be extended by allowing their coefficients to vary over time. Focusing on conditional heteroscedasticity models, we discuss various strategies to identify and estimate...

The spatial survival models typically impose frailties, which characterize unobserved heterogeneity, to be spatially correlated. This specification relies highly on a predeterminate covariance structure of the errors. However, the spatial effect may not only exist in the unobserved errors, but...

High breakdown-point regression estimators protect against large errors and data contamination. We adapt and generalize the concept of trimming used by many of these robust estimators so that it can be employed in the context of the generalized method of moments. The proposed generalized method...