The spatio-temporal distribution of European R&D networks: Evidence using Eigenvector spatially filtered spatial interaction models

The focus of this study is on R&D networks in Europe, as captured by R&D joint ventures funded by the European Commission within the European Framework Programmes (FPs). The Framework Programmes are the main policy instrument to address the goal of an integrated and coherent European Research Area (ERA). The objective is to estimate the evolution of separation effects over the time period 1999-2006 that influence the probability of cross-region collaborations in the European network of R&D cooperation. Separation effects involve geographical, technological, cultural and institutional barriers. By this, the study builds on recent work by Scherngell and Barber (2009) that addresses this question from a static perspective, and follows recent numerous theoretical considerations pointing to the importance of analyzing the spatio-temporal dimension of R&D networks. We employ Poisson spatial interaction models taking into account spatial autocorrelation among flows by using Eigenfunction spatial filtering methods. The results show that geographical distance and country border effects gradually decrease over time when correcting for spatial autocorrelation of flows. Particularly, the estimator for geographical distance effects is underestimated, if spatial flow autocorrelation is not taken into account. From this perspective, the study provides empirical evidence for the contribution of the FPs to the realisation of ERA.