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ABSTRACT  Over the last two decades many European governments have pursued ambitious research and development (R&D) policies with the aim of fostering innovation and economic growth in peripheral regions of Europe. The question is whether these policies are paying off. Arguments such as the need to reach a minimum threshold of research, the existence of important distance decay effects in the diffusion of technological spillovers, the presence of increasing returns to scale in R&D investments, or the unavailability of the necessary socio‐economic conditions in these regions to generate innovation seem to cast doubts about the possible returns of these sort of policies. This paper addresses this question. A two‐step analysis is used in order to first identify the impact of R&D investment of the private, public, and higher education sectors on innovation (measured as the number of patent applications per million population). The influence of innovation and innovation growth on economic growth is then addressed. The results indicate that R&D investment, as a whole, and higher education R&D investment in peripheral regions of the EU, in particular, are positively associated with innovation. The existence and strength of this association are, however, contingent upon region‐specific socio‐economic characteristics, which affect the capacity of each region to transform R&D investment into innovation and, eventually, innovation into economic growth.

With this paper we depict a typology of regions, capturing the diversity of regional innovation systems (RISs) across the EU-25. Following the RIS literature, we select twenty-one variables related to the ability of a region to generate and absorb knowledge, and its capacity to transform research and development into innovation and economic growth. On the basis of the results of principal components and cluster analyses, we identify seven types of RIS where the 186 regions group together according to their sectoral specialisation, technological and economic capacity, and performance. By allowing us to identify similar and more advanced regions, the paper facilitates comparisons and benchmarking between similar regions, thus enabling more accurate policy learning. For each group a number of policy recommendations are suggested, contingent on their local specific characteristics. In short, the contribution of this paper is twofold. Firstly, it provides the first RIS typology for the EU-25 regions completed using a large number of variables. Secondly, the conclusions obtained from the analysis may be used to lead policy makers' actions in the field of regional innovation policy in the EU.