Estimation of threshold parameters in (generalized) threshold regression models is typically performed by maximizing the corresponding profile likelihood function. Also, certain Bayesian techniques based on non-informative priors are developed and widely used. This article draws attention to...

The threshold vector error correction model is a popular tool for the analysis of spatial price transmission and market integration. In the literature, the profile likelihood estimator is the preferred choice for estimating this model. Yet, in certain settings this estimator performs poorly. In...

We present a unifying view on various statistical estimation techniques including penalization, variational, and thresholding methods. These estimators are analyzed in the context of statistical linear inverse problems including nonparametric and change point regression, and high-dimensional...

In contrast to conventional model selection criteria, the Focused Information Criterion (FIC) allows for purpose-specific choice of models. This accommodates the idea that one kind of model might be highly appropriate for inferences on a particular parameter, but not for another. Ever since its...

This paper is concerned with testing rationality restrictions using quantile regression methods. Specifically, we consider negative semidefiniteness of the Slutsky matrix, arguably the core restriction implied by utility maximization. We consider a heterogeneous population characterized by a...

We focus on the construction of confidence corridors for multivariate nonparametric generalized quantile regression functions. This construction is based on asymptotic results for the maximal deviation between a suitable nonparametric estimator and the true function of interest which follow...

In contrast to conventional model selection criteria, the Focused Information Criterion (FIC) allows for purpose-specific choice of models. This accommodates the idea that one kind of model might be highly appropriate for inferences on a particular parameter, but not for another. Ever since its...