This research investigates the factors influencing carbon emission intensity in 94 countries during 2018 using two qualitative methods: necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA). The study covers variables related to economics, human geography, energy, and institutions, showing significant variations among them. The NCA model identifies economic complexity and fossil energy consumption as necessary conditions for high-carbon emission intensity. On the other hand, the fsQCA model reveals sufficient conditions for both high- and low-carbon emission intensity, presenting different causal combinations of variables. For high-carbon emission intensity, nine causal solutions are identified, emphasizing the roles of economic growth, urbanization, fossil energy consumption, and institutional quality. Reducing carbon emission intensity requires addressing economic complexity and reducing reliance on fossil energy consumption. Policymakers should focus on sustainable economic development, environmentally friendly urbanization, and transitioning to renewable energy sources. This research's originality lies in its qualitative approach, going beyond traditional regression methods to explore necessary and sufficient conditions for carbon emission intensity. It offers valuable insights into the complex interplay of variables, providing multiple causal configurations for both high- and low-carbon emission intensity.
Keywords: Carbon emission intensity; Ecological footprint; Fuzzy-set qualitative comparative analysis; Necessary condition analysis.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.