This paper adopts a spatial econometric perspective to analyse regional convergence of per capita income in Europe in 1995 to 2000 and, moreover, relaxes the assumption of a single steady-state growth path which appears to be out of tune with reality of empirical dynamics. The two-club spatial...

Innovation networks of manufacturers are currently receiving much attention as a competitive strategy. The contribution represents a response to the growing recognition that there are very important reasons why we need a better understanding of the relationship between innovation and networking....

Building a feedforward computational neural network model (CNN) involves two distinct tasks: determination of the network topology and weight estimation. The specification of a problem adequate network topology is a key issue and the primary focus of this contribution. Up to now, this issue has...

The paper sheds some light on the issue of geographically mediated knowledge spillovers from university research activities to regional knowledge production in the high tech sector in Austria. Knowledge spillovers occur because knowledge created by university is typically not contained within...

Fundamental to regional science is the subject of spatial interaction. GeoComputation - a new research paradigm that represents the convergence of the disciplines of computer science, geographic information science, mathematics and statistics - has brought many scholars back to spatial...

The modelling of univariate time series is a subject of great importance in a variety of fields, in regional science and economics, and beyond. Time series modelling involves three major stages:model identification, model%0D estimation and diagnostic checking. This current paper focuses its...

Although there is a substantial body of literature on labour market analysis, most of it ignores the spatial dimension of the labour market. A spatial perspective in analysing labour market processes is important for several reasons. FIRST, labour markets are by no means as homogeneous as...