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Configural analysis of innovation for exploring economic growth

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  • Yu, Tiffany Hui-Kuang
  • Huarng, Kun-Huang
  • Lai, Yun Ting

Abstract

This research analyzes and forecasts the causal combinations of innovation for economic growth, utilizing yearly data from Organization for Economic Co-operation and Development (OECD) countries. Employing the method of fuzzy sets/Qualitative Comparative Analysis (fsQCA), the two causal combinations from the estimation are 1) Institute, Human Capital and Research, Infrastructure, and Market Sophistication as well as 2) Human Capital and Research, Infrastructure, Market Sophistication, and Business Sophistication. This study proposes a time series method to forecast fsQCA results that offer performances demonstrating strong predictive validities.

Suggested Citation

  • Yu, Tiffany Hui-Kuang & Huarng, Kun-Huang & Lai, Yun Ting, 2021. "Configural analysis of innovation for exploring economic growth," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    • Handle: RePEc:eee:tefoso:v:172:y:2021:i:c:s0040162521004510
    DOI: 10.1016/j.techfore.2021.121019
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    Cited by:

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    5. Bigerna, Simona & D'Errico, Maria Chiara & Polinori, Paolo, 2022. "Understanding the green-growth: which pathways cities undertake in their climate programs," MPRA Paper 114156, University Library of Munich, Germany.
    6. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang, 2022. "Causal complexity analysis for fintech adoption at the country level," Journal of Business Research, Elsevier, vol. 153(C), pages 228-234.

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