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Abstract
This paper explains the background to the notion of the 'geography of discontent' in the context of UK interregional inequalities and political shocks. The paper then examines how the geography of discontent has bound conflicting political and economic narratives together in ways, which makes the correcting for these regional imbalances all the more difficult, and results in ambiguity and a lack of clarity regarding the nature and form which Levelling Up processes should take.

The paper discusses the origins and emerging ideas of smart specialization, and in particular its translation from a non-spatial concept to an explicitly spatial and regional concept. This discussion is then set in the context of debates regarding the nature, rationale, and role of modern innovation policy, and the governance and institutional issues arising are then examined. We extend this discussion to discuss the experience of these issues in EU regions, and the arguments are then broadened to the potential lessons for other parts of the world which are aiming to enhance their innovation potential. ; Este artículo analiza los orígenes y las ideas emergentes de las estrategias de especialización inteligente, en particular su adaptación desde un óptica no espacial a una óptica explícitamente espacial y regional. Este análisis se enmarca en el contexto de los debates centrados en la naturaleza, objetivo y papel de las nuevas políticas de innovación, así como aspectos relacionados con su gobernanza y proceso institucional. El trabajo extiende la discusión, introduciendo aspectos basados en la experiencia de la implementación de estos procesos en varias regiones europeas, ofreciendo consejos basados en lecciones aprendidas para otras partes del mundo interesadas en implementar estos procesos con el fin de mejorar su potencial de innovación.

The paper discusses the origins and emerging ideas of smart specialization, and in particular its translation from a non-spatial concept to an explicitly spatial and regional concept. This discussion is then set in the context of debates regarding the nature, rationale, and role of modern innovation policy, and the governance and institutional issues arising are then examined. We extend this discussion to discuss the experience of these issues in EU regions, and the arguments are then broadened to the potential lessons for other parts of the world which are aiming to enhance their innovation potential.

This paper examines the arguments underpinning the smart specialisation concept, an idea which originally emerged from the sectoral growth literature, and one which has recently been applied with to the regional policy context. The shift from a sectoral to a regional context appears prima facie to be quite straightforward but this paper explains that translating the idea to a regional policy context is rather more complex that it at first appears and implies some changes in both interpretation and implications. The outcomes of this are that in a regional policy setting the smart specialisation logic is seen to be broadly consistent with the overall reforms of EU Cohesion Policy. However, in a regional policy setting there is no reason why ICTs should be prioritised over many forms of intangible capital, and the promotion of technological diversification via entrepreneurship may need to be related to specific sectors or activities.

The aim of this study is to investigate the relationship between a firm's R&D activities and its productivity using a unique micro data panel dataset and looking at sectoral peculiarities which may emerge; more specifically, we used an unbalanced longitudinal database consisting of 532 top European R&D investors over the six-year period 2000-2005. Our main findings can be summarised along the following lines: knowledge stock has a significant positive impact on a firm's productivity, with an overall elasticity of about 0.125; this general result is largely consistent with previous literature in terms of the sign, the significance and the estimated magnitude of the relevant coefficient. More interestingly, the coefficient increases monotonically when we move from the low-tech to the medium-high and high-tech sectors, ranging from a minimum of 0.05/0.07 to a maximum of 0.16/0.18. This outcome, in contrast with recently-renewed acceptance of low-tech sectors as a preferred target of R&D investment, suggests that firms in high-tech sectors are still far ahead in terms of the impact on productivity of their R&D investments, at least as regards top European R&D investors. -- R&D ; productivity ; knowledge stock ; panel data ; perpetual inventory method

AbstractThe literature has pointed to different causes to explain the productivity gap between the EU and the US in the last decades. This paper tests the hypothesis that the lower European productivity performance in comparison with the US can be explained not only by a lower level of corporate R&D investment but also by a lower capacity to translate R&D investment into productivity gains. The proposed microeconometric estimates are based on a unique longitudinal database covering the period 1990–2008 and comprising 1,809 US and EU companies for a total of 16,079 observations. Consistent with previous literature, we find robust evidence of a significant impact of R&D on productivity; however, using different estimation techniques, the R&D coefficients for the US firms always turn out to be significantly higher. To see to what extent these transatlantic differences in the R&D/productivity relationship may be related to the different sectoral structures in the US and the EU, we differentiated the analysis by sectors. The result is that bothin manufacturing, services and high‐tech manufacturing sectors US firms are more able to translate their R&D investments into productivity increases.

The importance of SMEs in Europe's innovation process can be seen in both the academic and the political arena. Adopted in June 2008, the 'Small Business Act' for Europe reflects the Commission's political will to recognise the central role of SMEs in the EU economy and was the first to put in place a comprehensive SME policy framework for the EU and its Member States. One of its main aims is to promote growth among SMEs by helping them to tackle problems that hamper their development. This kind of policy calls for a more in-depth look into the nature of the SME population in Europe. Several attempts have been made in recent years to draw taxonomies of firms, but mostly they do not control for size effects within the defined groups of firms. The purpose of this paper is to typify different groups of R&D-intensive SMEs distinguished according to their inputs into the innovation process. In particular, we draw attention to SMEs that contribute the most to the industrial R&D investment in the EU. To do so, we run a cluster analysis on a sample of top European R&D SME investors based on a unique dataset made up of the different waves of the European R&D Investment Scoreboard. The results show that several clusters of R&D-intensive SMEs can be defined by certain characteristics, but that the diversity between clusters calls for a more careful understanding before developing measures to support European R&D-intensive SMEs. For companies labelled as 'corporate laboratories' according to the cluster analysis, it would be legitimate to question support for R&D, as these firms do not seem to have significant problems in finding investors that believe in their business model. On the other hand, e.g. the 'Gazelles' do in fact grow, but struggle with the high capital investment needed to become and remain large. In this case, it seems it would be more effective to focus on the weaknesses (physical expansion) of these firms rather than supporting their strengths (knowledge, R&D).