Proposed Research on the Relationships Between Innovation Competitiveness and Export Competitiveness in Central and Eastern European Countries
Proposed Research on the Relationships Between Innovation Competitiveness and Export Competitiveness in Central and Eastern European Countries

Summary/Abstract: Research background: In the contemporary world, innovations are the driving force of economic development and new products, designs, trademarks and creative projects are of key importance to everyday economic decisions. Both economic theories and empirical research concern relations between innovations and foreign trade. This article belongs to this research trend and is devoted to an analysis of relations between innovations and export competitiveness in selected Central and Eastern European countries. Purpose: The paper is aimed at assessing the impact of innovation competitiveness on export competitiveness in selected countries of Central and Eastern Europe. Research methodology: The paper contains an analysis with the use of standardised innovation competitiveness and export competitiveness indices. Countries and industry sectors are analysed in terms of the frequency of occurrence of these indices with various combinations of their signs. The impact of innovation competitiveness on export competitiveness has been tested using dynamic models of panel data. Results: The conducted research indicates that technological advantage usually has a considerable positive impact on the trade competitiveness of Central and Eastern European countries but the strength of the impact depends on the branch of industry. Generally, the influence of technological competitiveness on trade competitiveness is stronger in highly and moderately technologically advanced industries than in industries characterised by low technological advancement. Novelty: The evaluation of the influence of innovation competitiveness on export competitiveness in Central and Eastern European countries using standardised competitiveness indices and a dynamic model of panel data is an added value in the paper.

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