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Economic Impact of Smart Specialization and Research in Advanced Adaptive Systems in a Monetary Union

  • Dimitrios Kyriakou
Chapter

Abstract

Tensions in the eurozone have brought back to the surface issues/criteria related to its solidity and optimality. We will suggest that technology and research can help buttress a monetary union, through their impact on trade and specialization and production structures. This applies to advanced adaptive systems, such as robotic systems that can be used in wide arrays of sectors to enhance performance and competitiveness. It can open the way for European economies to compete internationally by emphasizing their strong card, technology, as opposed to competing on labor cost. It can mitigate the tensions caused by divergent performances between members of a monetary union, through promoting convergence toward higher technological plateaus. This emphasis on technoeconomic convergence has a counterpart, in terms of technology and innovation policies, which can hardly compete globally on the basis of labor costs. The sovereign debt crisis has increased pressure on countries to redress structural problems in their economies, while preserving the margin for public investment in knowledge-based capital, in a “smart way,” contributing to productivity growth and competitiveness. Smart specialization, the concept and the associated policy process, aims to do just that, fostering growth potential in a context of rapid technological change and globalization. The rationale for smart specialization stresses the role of policymakers, knowledge-based institutions, and entrepreneurs in shaping specialization and competitiveness. Horizontal key enabling technologies, such as robotic technologies, play a particularly essential role in boosting existing strengths, as well as revealing new economic opportunities in sectors at various levels of technological sophistication.

Keywords

Exchange Rate Fiscal Policy Real Exchange Rate Monetary Union Flexible Exchange Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  1. 1.Institute for Prospective Technological StudiesSevilleSpain

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