Cluster Performance reconsidered: Structure, Linkages and Paths in the German Biotechnology Industry, 1996-2003

This paper addresses the evolution of biotechnology clusters in Germany between 1996 and 2003, paying particular attention to their respective composition in terms of venture capital, basic science institutions and biotechnology firms. Drawing upon the significance of co-location of "money and ideas", the literature stressing the importance of a cluster's openness and external linkages, and the path dependency debate, the paper aims to analyse how certain cluster characteristics correspond with its overall performance. After identifying different cluster types, we investigate their internal and external interconnectivity in comparative manner and draw on changes in cluster composition. Our results indicate that the structure, i.e. to which group the cluster belongs, and the openness towards external knowledge flows deliver merely unsystematic indications with regard to a cluster's overall success. Its ability to change composition towards a more balanced ratio of science and capital over time, on the other hand, turns out as a key explanatory factor. Hence, the dynamic perspective proves effective illuminating cluster growth and performance, where our explorative findings provide a promising avenue for further evolutionary research

The effect of immigration on convergence dynamics in the US

This paper analyzes the impact of immigration on the dynamics of the cross-sectional distribution of GSP per capita and per worker. To achieve this we combine different approaches: on the one hand, we establish via Instrumental Variable estimation the effect of the inflow of foreign- born workers on output per worker, employment and population; on the other hand, using the Distribution Dynamics approach, we reconstruct the consequences of migration flows on convergence dynamics across US states

Distribution Dynamics in the US. A spatial perspective.

It is quite common in cross-sectional convergence analyses that data exhibit strong spatial dependence. While the literature adopting the regression approach is now fully aware that neglecting this feature may lead to inaccurate results and has therefore suggested a number of statistical tools for addressing the issue, research is only at a very initial stage within the distribution dynamics approach. In particular, in the continuous state-space framework, a few authors opted for spatial pre-filtering the data in order to guarantee the statistical properties of the estimates. In this paper, we follow an alternative route that starts from the idea that spatial dependence is not just noise but can be a substantive element of the data generating process. In particular, we develop a tool that, building on a mean-bias adjustment procedure established in the literature, explicitly allows for spatial dependence in distribution dynamics analysis thus eliminating the need for pre-filtering. Using this tool, we then reconsider the evidence on convergence across US states

Living on thin abstractions: more power/economic knowledge

Debates over the role of knowledge and know-how as key economic assets in the contemporary economy, although far from new, are now increasingly couched in terms of a new-found economic immateriality which allows for their costless reproduction and widespread geographical dissemination. In the rush to tie down and reproduce economic know-how in abstract codifiable form, it has become almost baffling to argue that our stock of economic knowledge may rest upon affects as much as analysis, expressive symbolism as much as abstract symbolism. This paper is an attempt to think through how such 'elusive' economic knowledges may be grasped, yet neither formalized nor codified in abstract terms. It is also a plea to consider the geography of economic knowledge outside of the tacit - explicit distinction