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Causal analysis of SDG achievements

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  • Yu, Tiffany Hui-Kuang
  • Huarng, Kun-Huang

Abstract

The United Nations Sustainable Development Goals (SDGs) set common targets for countries all over the world for their economy and society. This research uses popular indices as antecedents (independent variables) to analyze the causal complexity of SDG achievements (outcome or dependent variable). For the antecedents, Inclusive Internet Index measures digital technology, Corruption Perception Index measures transparency and integrity, Global Innovation Index measures innovation, Global Entrepreneurship Monitor measures entrepreneurship, GDP measures economic growth, and Global Findex measures financial technology (fintech). It takes fuzzy set/Qualitative Comparative Analysis (fsQCA) as the research method and applies it to data spanning the years 2020 (30 common countries) and 2021 (28 common countries), respectively. The results show multiple relationships for both 2020 and 2021, and each relationship consists of multiple antecedents. In addition, the causal relationships of the two calendar years appear similar. Implications are discussed herein, and following the research results, countries with different competitive advantages can choose the proper causal relationship to facilitate their own SDG achievements.

Suggested Citation

  • Yu, Tiffany Hui-Kuang & Huarng, Kun-Huang, 2024. "Causal analysis of SDG achievements," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    • Handle: RePEc:eee:tefoso:v:198:y:2024:i:c:s0040162523006625
    DOI: 10.1016/j.techfore.2023.122977
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