Name and affiliations of the session organisers
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Carlo Corradini (University of Reading)
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Enrico Vanino (University of Sheffield)
- in collaboration with the UK Office for National Statistics (ONS)
A large literature has looked at the importance of different policy tools to spur private R&D investment and innovation. However, there are concerns that many of these instruments are highly imbalanced and follow a “picking-the-winner” strategy, targeting and supporting businesses already intensive in R&D activities, leading to a vicious circle that widens the productivity gap between industry leaders and laggards and reinforces regional productivity inequalities.
The public R&D support for leading regions is usually motivated by the fact that there would be higher returns to public investment by exploiting agglomeration effects and creating positive knowledge externalities, which are more challenging to leverage in regions with low innovation intensity. However, these arguments are based on measures that mostly capture a limited portion of innovation activities, underrepresenting the many different forms of innovation that are particularly important in less technology-intensive and lagging-behind industries and regions.
As a consequence, there is a need to build a more comprehensive picture of regional specialisations and capabilities, encompassing private R&D and technology development as well as capturing aspects of hidden innovation which may be particularly relevant for lagging-behind regions. Accordingly, further research is necessary to better understand the fundamental role of public R&D support, particularly in stimulating innovation and growth among the underrepresented segments of the business population operating in low-tech industries and regions. This will help to develop new policies to promote knowledge spillovers across public and private R&D intensive organisations and stimulate overall innovation, including a more effective support for small and low-tech businesses in lagging-behind regions.
This special session – organised in collaboration with the UK Office for National Statistics (ONS) – will welcome contributions linked, but not only limited, to the following topics: