ABSTRACT
This article discusses the links between human development, innovation and economic growth. After a brief theoretical preamble, I present a framework bringing together the relationships between those processes in a circular causation diagram. I then examine these relationships using data on 266 European regions covering the period 2000–2015. I test two econometric models: one based on panel (3SLS), the other on spatial analysis (SAR). The first helps me explore, in more detail, the relationship between innovation, human development and income. The results indicate a mutually reinforcing relationship between them. The associations between human development and innovation, and GDP and innovation are found to be particularly strong. The spatial analysis further confirms the existence of virtuous circles and the presence of spatial interrelationships, both in terms of spillover and feedback effects. Consequently, I argue, these variables should be promoted simultaneously. I highlight two points that seem especially worthy of being developed in future work: the importance of setting human development as the ultimate goal of innovation policy, and the need to formulate macroeconomic policies fostering innovation and human development.
Disclosure statement
No potential conflict of interest was reported by the author.
Notes
1 Upper secondary, post-secondary non-tertiary, first and second stage of tertiary education (levels 3–6).
2 Persons with tertiary education (ISCED) and/or employed in science and technology. Human Resources in Science and Technology (HRST) are people who fulfil one or other of the following conditions:
- successfully completed education at the third level in an S&T field of study,
- not formally qualified as above but employed in an S&T occupation where the above qualifications are normally required.
3 Upper secondary, post-secondary non-tertiary, first and second stage of tertiary education (levels 3–6)
4 The word “centroid” in the literature on geographic information systems indicates a weighted average of the vertices of a polygon that approximates the centre of the polygon (see Waller and Gotway Citation2004, 44–45).
5 These are provided by the dataset “Nomenclature of Territorial Units for Statistics (NUTS) 2010 – European Commission, Eurostat/GISCO”, which represents the regions for levels 1, 2 and 3 of the Nomenclature of Territorial Units for Statistics (NUTS) for 2010.
6 Regressions were also made with delays of 3 and 5 years which overall confirmed the results obtained.
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Notes on contributors
Michele Capriati
Michele Capriati is Professor of Political Economics, Department of Political Sciences, University of Bari (Italy). His main interests are in: Human Development and Capabilities Approach. Innovation, development and growth of regional and local systems. Organisational capabilities and innovation.