Knowledge and technological change are often assumed to be the driving forces for long run economic growth. Regions with a higher level of knowledge compared to other regions exhibit a higher per-capita income on average. Agglomeration effects can lead to a steady increase of income and widen...

The new growth theory considers knowledge to be a decisive engine of economic growth. More precisely, knowledge is not used solely to the benefit of its originator, but generates positive side effects also for others, provided they have the capability to understand the transferred knowledge...

Understanding the way in which knowledge is technically produced and transferred, and how its diffusion path can be characterized is of fundamental importance for the performance of an economy. Although this fact seems to be plausible ex ante, the relevant literature so far has paid less...

The aim of this paper is to introduce a new model selection mechanism for cross sectional spatial models. This method is more fexible than the approach proposed by Florax et al. (2003) since it controls for spatial dependence as well as for spatial heterogeneity. In particular, Bayesian and...

In this paper, we investigate the relationship between market dynamics, dynamic resource management and environmental policy. In contrast to static market entry games, this paper draws attention to the effects of market dynamics on resource dynamics et vice versa, because (1) we show that...

De Paoli, Scott, and Weeken (2010, Asset pricing implications of a New Keynesian model. Journal of Economic Dynamics and Control 34, 2056-73) study equity and bonds prices in a New Keynesian model with sticky nominal prices. This note argues that their model generates a behavior of the labor...

The aim of this paper is to introduce a new model selection mechanism for cross sectional spatial models. This method is more flexible than the approach proposed by Florax et al. (2003) since it controls for spatial dependence as well as for spatial heterogeneity. In particular, Bayesian and...

Bootstrapping methods have so far been rarely used to evaluate spatial data sets. Based on an extensive Monte Carlo study we find that also for spatial, cross-sectional data, the wild bootstrap test proposed by Davidson and Flachaire (2008) based on restricted residuals clearly outperforms...