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National innovation systems, economic complexity, and economic growth: country panel analysis using the US patent data

Author

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  • Keun Lee

    (Seoul National University)

  • Jongho Lee

    (Yonsei University)

Abstract

This study examines the impacts of national innovation systems (NIS) and economic complexity index (ECI) on economic growth. A composite index of NIS is developed by using US patent data as a weighted sum of three, four or five variables among the following: concentration of assignees, localization, originality, diversification, and cycle time of technologies. Growth regressions confirm the significant and robust impacts of NIS3a, NIS4a, and NIS5 indices on economic growth. The common feature of these NIS indices is that they have the same component variables as their ingredients, and these are originality, cycle time, and technological diversification. NIS3a is the most parsimonious and powerful among all indices. The robustness of ECI is questionable because ECI loses significance after adding government expenditure and terms of trade variables into the regression model. Results confirm the overall importance of NIS in economic growth and justify policy efforts to improve NIS. This research is one of the first to generate a robust NIS index by using patent data only without many data requirements and free from the problem of cross-country comparability of underlying variables.

Suggested Citation

  • Keun Lee & Jongho Lee, 2020. "National innovation systems, economic complexity, and economic growth: country panel analysis using the US patent data," Journal of Evolutionary Economics, Springer, vol. 30(4), pages 897-928, September.
    • Handle: RePEc:spr:joevec:v:30:y:2020:i:4:d:10.1007_s00191-019-00612-3
    DOI: 10.1007/s00191-019-00612-3
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    3. Simon Ndicu & Dianah Ngui & Laura Barasa, 2024. "Technological Catch-Up, Innovation, and Productivity Analysis of National Innovation Systems in Developing Countries in Africa 2010–2018," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 7941-7967, June.
    4. Agnieszka Kleszcz & Krzysztof Rusek, 2022. "Has EU accession boosted patents performance in the EU-13? -- A critical evaluation using causal impact analysis with Bayesian structural time-series models," Papers 2201.09878, arXiv.org.
    5. Agnieszka Kleszcz & Krzysztof Rusek, 2022. "Has EU Accession Boosted Patent Performance in the EU-13? A Critical Evaluation Using Causal Impact Analysis with Bayesian Structural Time-Series Models," Forecasting, MDPI, vol. 4(4), pages 1-16, October.
    6. Chan-Yuan Wong & Keun Lee, 2022. "Evolution of innovation systems of two industrial districts in East Asia: transformation and upgrade from a peripheral system and the role of the core firms, Samsung and TSMC," Journal of Evolutionary Economics, Springer, vol. 32(3), pages 955-990, July.
    7. Chen, Wei & Song, Hongti, 2024. "National innovation system: Measurement of overall effectiveness and analysis of influencing factors," Technology in Society, Elsevier, vol. 77(C).
    8. Caliari, Thiago & Ribeiro, Leonardo Costa & Pietrobelli, Carlo & Vezzani, Antonio, 2023. "Global value chains and sectoral innovation systems: An analysis of the aerospace industry," Structural Change and Economic Dynamics, Elsevier, vol. 65(C), pages 36-48.
    9. Jongho Lee & Keun Lee, 2021. "Is the fourth industrial revolution a continuation of the third industrial revolution or something new under the sun? Analyzing technological regimes using US patent data [Vertical integration and ," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(1), pages 137-159.
    10. Jinhee Kim & Keun Lee, 2022. "Varieties of Regional Innovation Systems around the World and Catch-up by Latecomers," Papers in Evolutionary Economic Geography (PEEG) 2219, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Oct 2022.
    11. Fakhimi, MohammadAmin & Miremadi, Iman, 2022. "The impact of technological and social capabilities on innovation performance: a technological catch-up perspective," Technology in Society, Elsevier, vol. 68(C).
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    More about this item

    Keywords

    National innovation systems; Economic complexity; Economic growth; Patents; Index;
    All these keywords.

    JEL classification:

    • B52 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Historical; Institutional; Evolutionary; Modern Monetary Theory;
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

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