This note intends to shed a broader light on this matter through the spatial analysis of spillover effects within and between départements induced by these clusters. It also seeks to measure the clusters' ability to develop B2B (business-to-business) networks and assess their effects on companies' economic performance and their R&D spending. At the time of the realisation of this work, the available data had ended in 2015.
Results obtained in other studies confirmed the impact of clusters on companies' R&D spending: one euro of public subsidy received under this policy would have generated an average of 2.5 additional euros in R&D spending by beneficiary small and medium enterprises (SMEs). On the other hand, as in previous works, the analysis confirms the absence of measurable positive effects on R&D spending by medium-sized and large firms.
The analysis also seeks to measure the clusters' contribution to the structuring of innovation networks in which large companies could play a decisive role. The results obtained are contrasted. On the positive side, relations appear to be increasingly diversified within clusters, and their overall cohesion is progressing over time. On the negative side, the number of collaborations is declining. It cannot be ruled out that this might result from an increase in inter-cluster collaborations or the number of SMEs belonging to clusters, nor can it be excluded that it goes hand in hand with an improvement of these collaborations' quality. Still, the analysis does not allow us to conclude on this point.
From the point of view of spatial effects, a greater number of companies joining a cluster triggers a better dynamic of R&D spending within the territory where the cluster is located. On the other hand, no solid evidence of positive synergies with neighbouring territories has been demonstrated.
Overall, the analysis confirms that public policy in favour of competitiveness clusters has had positive e ects on companies, networks, and territories. Still, these effects remain diffcult to measure precisely, given the methodological fragilities related to the object of study.
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