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Technological Attraction of FDI flows in Knowledge-Intensive Services: a Regional Innovation System Perspective for Spain

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2011

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Instituto Complutense de Estudios Internacionales (ICEI)
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An increasing body of literature has been generated regarding the role that services play in innovation systems, in which special attention has been paid recently to Knowledge-Intensive (Business) Services – KIS & KIBS. As not only developed nations but also emerging economies and regions embedded in this country-level unit of analysis show an economic structure strongly based in the tertiary sector, it is mandatory for policymaking processes to better evaluate and understand the idiosyncrasies of these innovation-generating services and its relationships with National, Sectoral and Regional Innovation Systems. Thus, this article aims at approaching the dynamics of Foreign Direct Investment (Inward and Outward flows) in KIS in Spain considering the Regional (NUTS 2) level of analysis and taking into account their interactions with the innovative environment of two specific regions (Madrid and Andalusia) by testing a regressive model built upon technological and innovation systems’ variables. The novelty of our approach is to propose a model based on innovation-driven determinants of FDI attraction where: a) the size of innovation systems is approximated by GERD (controlled by GDP) and by a Human Resources variable (Researchers in R&D); and b) technological heterogeneity is measured according to the technological gap between region/country (using a Patent Index proxy). This approach, although novel to our understanding is based on a broad set of references on FDI (Investment Development Path, Asset Augmenting Strategies), internationalization and Innovation Systems (Knowledge Generation, Absorptive Capacity). Preliminary results do not indicate that Innovation Systems affect relevantly the FDI flows for the analyzed regions/countries, suggesting that FDI behaves generally according to a market seeking logic, rather than asset seeking. Improvements for econometric estimations are suggested.

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