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The exploratory analysis pursued in Chap. 3 has shown that the economic success of EU regions in an innovation-based model of sustainable economic growth depends on their capability to produce and access innovation. The uneven geographical distribution of R&D activities has been shown to be a localised source of competitive advantage for some areas rather than others.
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See Appendix A on data availability.
“The lifelong learning approach is an essential policy strategy for the development of citizenship, social cohesion, employment and for individual fulfilment” (European Commission 2002, p. 4). In the framework of the Lisbon Agenda’s objectives by means of lifelong learning the European Commission aims – among the other things – to ensure that people’s knowledge and skills match the changing demands of jobs and occupations, workplace organisation and working methods (2002, p. 5).
The European Commission made explicit the challenges created by ageing population when countries/regions have to rely upon the benefits of the knowledge based society, and presented the investment in human capital as a tool for counterbalancing the potential negative impact of ageing upon innovative performance. Where policies targeted towards human capital accumulation are implemented, “the future cohorts of older workers will benefit from higher levels of training, reducing the risk of a slower spread of new technologies that could be associated with ageing”. (European Commission 2006; p. 6).
For the technicalities of PCA see Appendix C.
Standardised in order to range from zero to one.
The calculation of this last variable is discussed in further detail in the section justifying its inclusion in the regression model.
As the time distance-matrix is calculated either at the NUTS1 or at the NUTS2 level, in order to make it coherent with our data which combine different Nuts levels we rely on the NUTS distance matrix using the NUTS 2 regions with the highest population density in order to represent the corresponding NUTS1 level for Belgium, Germany and the UK.
In the case of the New Member States data availability has prevented us from calculating the mean of the explanatory variables over the five year period (t-T-5) forcing us to use a shorter time span. For some EU 15 countries slightly differential time spans have been used according to data availability for each variable. The specification of each individual case would take up too much space.
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- The Role of Underlying Socio-Economic Conditions
- Springer Berlin Heidelberg
- Chapter 4