Highly non-elliptical posterior distributions may occur in several econometric models, in particular, when the likelihood information is allowed to dominate and data information is weak. We explain the issue of highly non-elliptical posteriors in a model for the effect of education on income...

This paper features an analysis of major currency exchange rate movements in relation to the US dollar, as constituted in US dollar terms. Euro, British pound, Chinese yuan, and Japanese yen are modelled using a variety of non-linear models, including smooth transition regression models,...

Innovation research has become an important topic in regional science analysis. Yet the modelling base of much innovation research is still feeble. This paper aims to map out the research potential of recent approaches in quantitative complexity analysis, in particular Neural Networks (NNs)...

In this paper, a set of neural network (NN) models is developed to compute short-term forecasts of regional employment patterns in Germany. NNs are modern statistical tools based on learning algorithms that are able to process large amounts of data. NNs are enjoying increasing interest in...

The present paper aims to analyse interregional freight transport movements in Europe in order to forecast spatio-temporal patterns of new transport economic scenarios.In view of the high dimension of our data-base on transport flows, two different approaches are compared, viz. the logit model...

A major problem in applying neural networks is specifying the sizeof the network. Even for moderately sized networks the number ofparameters may become large compared to the number of data. In thispaper network performance is examined while reducing the size of thenetwork through the use of...