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2021 | OriginalPaper | Buchkapitel

Patterns of Knowledge Creation in European Regions: An Analysis by the Phases of the EU-Enlargements

verfasst von : Thomas Baumert

Erschienen in: Advances in Longitudinal Data Methods in Applied Economic Research

Verlag: Springer International Publishing

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Abstract

This chapter studies the determinants of regional knowledge production in Europe discriminating by the phases of the EU-enlargement (as a proxy for the degree of economic development). For this purpose, we combine factorial analysis with a regression model based on a knowledge production function. Our results evidence that there are clearly differentiated patterns in the knowledge production function of European regions according to the time of entrance of their corresponding countries into the EU: the less developed regions are, the more important the role of the Universities and of the Public administration in their Innovation Systems is; in more developed regions, however, the leading role is taken over by the Regional economic environment, the Sophistication of the (technological) demand as well as by the availability of financing in the form of Venture capital. We conclude that policy actions aimed to drive innovation should carefully consider the relative stage of development of the specific regional innovation system.

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The authors conclude that firm-specific factors are much more important than regional or national (i.e., systemic) ones.

This procedure allows to a certain extend to overcome the problem of cultural factors which, although usually pointed out as significant in theory, are seldom—one exception being the work by Varsakelis, 2001) included in empirical models. See for this Krammer (2009, p. 846).

For a succinct overview of the role of institutions on economic development, see Baumert (2020).

Exception made of the “new” German Länder which were automatically incorporated to the EU as a result of the Reunification.

ITU (2007, 2010).

As available on http://www.heritage.org/index/.

According to the following geographical classification (in brackets the number of regions):NUTS1: Belgium (3), Germany (16), Ireland (1), the United Kingdom (12), Slovenia (1), Bulgaria (2), and Romania (4); NUTS2: Denmark (1), Greece (13), Spain (17), France (22), Italy (20), the Netherlands (12), Austria (9), Portugal (5), Finland (6), Sweden (8), Czech Republic (8), Estonia (1), Cyprus (1), Latonia (1), Lithuania (1), Hungary (7), Malta (1), Poland (16), and Slovakia (4).

An attempt has been made to select, whenever the level of statistical disaggregation has allowed to do so, the NUTS level which corresponds to an administrative entity with real capability in the design and implementation of innovation policies.

We have intentionally left out the case of Croatia, who entered the EU in 2013, which allows only for a NUTS1 analysis (Croatian NUTS2 being a non administrative level, cf, the previous note) as, having to be modeled separately, would now allow for enough degrees of freedom. As a reminder: the UK was then still a full member of the EU.

The Kaiser-Meyer-Olkin test gives a value of 0.854 and the null hypothesis of the Barlett sphericity test can be rejected at the 99% level.

The patents statistics offered by EUROSTAT have the advantage of overcoming the “headquarter-effect” as patents are registered in the inventor’s region of residence.

For an in-depth discussion about the advantages and limitations of patens as measure of innovation, see Buesa et al. (2010, pp. 723–724).

It should be kept in mind, that the coefficients of a Tobit regression estimation have to be interpreted as the combination of (1) the change in K _it of those above the limit, weighted by the probability above the limit and (2) the change in the probability of being above the limit, weighted by the expected value of K _it if above.

The relation between B coefficients and BETA coefficients is \( {\mathrm{BETA}}_i={B}_i\times \frac{Sx_i}{Sy} \).

The regions of Belgium, the Netherlands, Luxembourg, France, Germany, the United Kingdom, Ireland, Italy, and Denmark.

The regions of Greece, Spain, and Portugal.

The regions of Austria, Finland, and Sweden.

The regions of Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Slovakia, and Slovenia.

The regions of Bulgaria and Romania.

We have so far, found no convincing explanation to this fact.

Of course, we cannot rule out the possibility that specific regions present such an atypical behavior in terms of innovative production, that they should be considered as outliers regarding their adscription group, better fitting another one that the one corresponding to the year of its EU-entrance. However, this does only reinforce our conclusion about the necessity of carefully studying the specific stage of development of a region before applying any innovation-policy measures.

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Titel: Patterns of Knowledge Creation in European Regions: An Analysis by the Phases of the EU-Enlargements
verfasst von: Thomas Baumert
Verlag: Springer International Publishing
Buch: Advances in Longitudinal Data Methods in Applied Economic Research
Print ISBN: 978-3-030-63969-3

Electronic ISBN: 978-3-030-63970-9

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-63970-9_23