We develop an empirical approach to examine static and dynamic knowledge externalities in the context of a regional total factor productivity relationship. Static externalities refer to current period scale or industry-size effects which have been labeled localization externalities or...

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....

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...

This paper presents a methodology for neural spatial interaction modelling. Particular emphasis is laid on design, estimation and performance issues in both cases, unconstrained and singly constrained spatial interaction. Families of classical neural network models, but also less classical ones...

The need to account for spatial autocorrelation is well known in spatial analysis. Many spatial statistics and spatial econometric texts detail the way spatial autocorrelation can be identified and modelled in the case of object and field data. The literature on spatial autocorrelation is much...

The focus in this paper is on knowledge spillovers between high-technology firms in Europe, as captured by patent citations. High-technology is defined to include the ISIC-sectors aerospace (ISIC 3845), electronics-telecommunication (ISIC 3832), computers and office equipment (ISIC 3825), and...

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...

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...