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...

Unlike the time series literature the spatial econometric literature has not really dealt with the issue of the parameter space. This paper shows that current parameter space concepts for spatial econometric DGPs are inadequate. It proves that the parameter space proposed by Kelejian and Prucha...

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,...

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,...

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...

The speed of income convergence in Europe remains one of the hot topics in regional economics. Recently Bayesian Model Averaging (BMA) applied to spatial autoregressive models seems to have gained more popularity. BMA averages over some predetermined number of so called top models, ranked by the...

This paper focuses on several estimation methods for SAR- models in case of missing observations in the dependent variable. First, we show with an example and then in general, how missing observations can change the model and thus resulting in the failure of the 'traditional' estimation methods....