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...

This paper considers identification and estimation of ceteris paribus effects of con- tinuous regressors in nonseparable panel models with time homogeneity. The effects of interest are derivatives of the average and quantile structural functions of the model. We find that these derivatives are...

We investigate to what extent convergence in production levels per worker has been achieved in Germany since unification. To this end, we model the distribution of GDP per employee across German districts using two-component normal mixtures. While in the first year after unification, the two...

We investigate to what extent convergence in production levels per worker has been achieved in Germany since unification. To this end, we model the distribution of GDP per employee across German districts using two-component normal mixtures. While in the first year after unification, the two...

We analyze the cross-national distribution of GDP per capita and its evolution from 1970 to 2003. We argue that peaks are not a suitable measure for distinct growth regimes, because the number of peaks is not invariant under strictly monotonic transformations of the data (e.g. original vs. log...