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A Comparative Analysis Of National Innovation Performance: The Baltic States In The Eu Context

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  • Tiiu Paas
  • Helen Poltimäe

Abstract

This paper bridges two approaches to assess national innovation performance based on European Innovation Scoreboard (EIS) composite indicators and the analysis of the factors that may be behind these indicators. The main focus of the study is on analysing the innovation performance of the Baltic States – small countries with similar post-socialist path dependence. Our aim is to explore what factors have been most influential in developing the different levels of innovation performance in these countries, and whether these differences are also captured by innovation measurement indicators. Our analysis shows that the inability to sufficiently capture the quality of human capital, the small economy effect (i.e. high dependence on single enterprises in a sector) and data availability issues represent remarkable measurement problems. The measurement results may also be biased as a result of self-reporting indicators. This conclusion was confirmed by comparing the EIS evaluations with the results of our assessment via factor analysis. The results are robust. Estonian innovation performance seems to be ahead of the other two Baltic countries; the main causes have been the successful attraction of foreign investment, favourable tax policy and possible positive spillover effects from the Nordic neighbourhood, particularly Finland and Sweden.

Suggested Citation

  • Tiiu Paas & Helen Poltimäe, 2010. "A Comparative Analysis Of National Innovation Performance: The Baltic States In The Eu Context," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 78, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    • Handle: RePEc:mtk:febawb:78
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    References listed on IDEAS

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    1. Jan Fagerberg, 2003. "Innovation: A Guide to the Literature," Working Papers on Innovation Studies 20031012, Centre for Technology, Innovation and Culture, University of Oslo.
    2. Andres Rodriguez-Pose & Riccardo regstdcenzi, 2008. "Research and Development, Spillovers, Innovation Systems, and the Genesis of Regional Growth in Europe," Regional Studies, Taylor & Francis Journals, vol. 42(1), pages 51-67.
    3. A. Rodriguez-Pose & Riccardo Crescenzi, 2006. "R&D, spillovers, innovatoin systems and the genesis of regional growth in Europe," Departmental Working Papers of Economics - University 'Roma Tre' 0067, Department of Economics - University Roma Tre.
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    Cited by:

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    2. Elias G. Carayannis & Evangelos Grigoroudis, 2016. "Using multiobjective mathematical programming to link national competitiveness, productivity, and innovation," Annals of Operations Research, Springer, vol. 247(2), pages 635-655, December.
    3. Elias Carayannis & Luc Hens & Polyxeni Nicolopoulou-Stamati, 2017. "TRANS-DISCIPLINARITY AND GROWTH: Nature and Characteristics of Trans-disciplinary Training Programs on the Human-Environment Interphase," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 8(1), pages 1-22, March.
    4. Elias Carayannis & Evangelos Grigoroudis, 2016. "Quadruple Innovation Helix and Smart Specialization: Knowledge Production and National Competitiveness," Foresight and STI Governance, National Research University Higher School of Economics, vol. 10(1), pages 31-42.
    5. Satı, Zümrüt Ecevit, 2024. "Comparison of the criteria affecting the digital innovation performance of the European Union (EU) member and candidate countries with the entropy weight-TOPSIS method and investigation of its importance for SMEs," Technological Forecasting and Social Change, Elsevier, vol. 200(C).

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    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • I2 - Health, Education, and Welfare - - Education

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