D1.1-3 Statistical support to the European Innovation Scoreboard (EIS), and the updates and sensitivity and robustness analysis carried out on the European Commission’s Innovation Output Indicator and Adjusted Research Excellence Index not only provide users with new data and rankings, but also greater transparency about the methodological choices and statistical explanations for country performance and trends, and contribute to conceptual and statistical debates.
D1.4: A study about the feasibility of producing statistics on scale-up companies using micro-data from commercial sources indicated the possibility to identify companies of potential interest for studying scale-up activity, albeit only when applying strict restrictions in terms of firm age and size. We recognized a number of challenges to consider when using such data for policy monitoring purposes, related to cost and efforts, coverage, ownership structure, completeness and accuracy.
D2.1: This study was triggered by the lack of directly available, fully comparable aggregate statistics to assess how the EU28 performs in comparison with the US in terms of key business dynamics. To fill this gap, a aggregate statistics on recent trends in entrepreneurship and business demography for both macro-regions were built and analyzed in a systematic comparison using a wide range of sources. The outcomes highlight that the US “prefers the extremes”: hosts more non-employers as well as large-sized and exceptionally successful companies, while the EU hosts more micro-sized as well as high-growth enterprises. Small and medium enterprises were found to be similar in number per inhabitant in both macro-regions.
D2.2: The Open Innovation concept has pervaded the academic and policy debate, due to its potential to further stimulate the circulation of knowledge across business partners and institutions and, consequently, to increase their innovation potential. The contribution of this paper by Damioli, Ghisetti, Vertesy and Vezzulli is to unveil the economic returns associated to such a model, to answer the main question whether the productivity growth slowdown observed in the EU in recent years could be overcome through a more open and dynamic innovation environment. An empirical analysis conducted on sectoral data for 16 EU countries is provided, exploiting three waves of the Community Innovation Survey. Results confirm the role of Open Innovation in stimulating – even at the aggregate level – innovation, and, to a limited extent, to economic returns. However, when testing for the association between Open Innovation and economic growth, no robust effect emerges.
D3: This study addressed the internationalization of knowledge-intensive activities of multinational enterprises (MNEs) which triggered competition at multiple, interrelated geographical levels. It assessed the role of local, national and supranational factors influencing MNEs’ decisions about where to locate knowledge-intensive foreign direct investments. Socio-economic data was compiled for 277 comparable urban areas (cities and agglomerations home to half a million or more people) in 28 worldwide. We found that supranational integration blocs’ borders matter when firms decide the location of their knowledge-intensive activities. Both supranational and national borders play an important role in Europe, while national borders seem more relevant in North America -- supporting the role of EU policy instruments aimed at integrating Europe's research and innovation systems.
D: The paper by Katay, Mosberger and Tucci assessed the impact of European Union (EU) grants for research and innovation on profit-oriented firms’ productivity. Using a unique dataset on both successful and unsuccessful applicants to the EU’s 7th Framework Programme and balance-sheet data for firms from 46 countries, we show that the EU grants have had a positive impact on firms’ post-treatment productivity.
