Smart specialisation in the tangled web of European inter-regional trade

Abstract

It aims to provide evidence-based scientific support to the European policy-making process. The scientific output expressed does not imply a policy position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use which might be made of this publication.

Capacity-building barriers to S3 implementation: an empirical framework for catch-up regions

“…There is a growing recognition that our S3 understanding has to shift attention from theory (design) to practice (implementation); for example, see the work of (Gianelle et al 2014;Capello and Kroll 2016;McCann, Van Oort, and Goddard 2016). At a theoretical level, the value of S3 has been well embedded in the regional innovation agenda (OECD 2013b;McCann, Van Oort, and Goddard 2016), concentrating both policymaking and academic interest.…”

“…During the last seven years (2010-2017), a rapidly expanding literature has informed S3 theoretical underpinnings, aiming to explain how its dynamics could gradually support European regions expand and diversify into new economic activities (Foray 2014;Asheim and Grillitsch 2015;McCann 2015). The paradox, however, is that while S3 has been accepted as a tool for regional turnaround, its practical realisation in the regional context is still fuzzy (Gianelle et al 2014;McCann, Van Oort, and Goddard 2016).…”

Exploring Brexit with dynamic spatial panel models: some possible outcomes for employment across the EU regions

“…The data come from the PBL (the Netherlands Environmental Assessment Agency) 7 who developed a new methodology which is close to that of Simini et al (2012). Details of the methodology are given in Thissen et al (2013Thissen et al ( , 2013a, see also Gianelle (2014). The method follows a top-down approach and therefore is consistent with the national accounts of the different countries.…”

Italexit, is it another Brexit?

“…Simini et al (2012) argue that parameter-free methodologies can outperform sophisticated parameter estimations, stay closer to the actual data and are far less data demanding. Details of the PBL methodology are given in Thissen et al (2013a, b, c), see also Gianelle et al (2014).…”