World cities are important nodes in the global networks of knowledge-based economies. As a result of the growing complexity of knowledge creation, firms increasingly organise their activities in business networks that operate across different spatial scales. On the global scale, new information...

This paper attempts to analyze the impact of knowledge and knowledge spillovers on regional total factor productivity (TFP) in Europe. Regional patent stocks are used as a proxy for knowledge, and TFP is measured in terms of a superlative index. We follow Fischer et. al (2008) by using a...

Spatial Filter for spatial autoregressive models like the spatial Durbin Model have seen a great interest in the recent literature. Pace et al. (2011) show that the spatial filtering methods developed by Griffith (2000) have desireable estimation properties for some parameters associated with...

Classical spatial autoregressive models share the same weakness as the classical linear regression models, namely it is not possible to estimate non-linear relationships between the dependent and independent variables. In the case of classical linear regression a semi-parametric approach can be...

This paper presents a comparative assessment of two distinct urban growth modeling approaches. The first urban model uses a traditional Cellular Automata methodology, based on Markov transition chains to prospect probabilities of future urban change. Drawing forth from non-linear cell dynamics,...

In this paper an attempt is made to assess the hypothesis of re- gional club-convergence, using a spatial panel analysis combined with B-Splines. In this context, a 'convergence-club' is conceived as a group of regions that in the long-run move towards steady-state equilib- rium, approximated in...