Abstract This study explores the development of a green taxonomy tailored to Qatar’s unique economic and environmental landscape. Green taxonomies guide sustainable finance by categorizing economic activities according to their environmental impact and alignment with global climate goals. This research provides a comprehensive framework for Qatar by analyzing global best practices, including those of the European Union (EU), China, the United Kingdom, South Africa, and Malaysia. The study employs a comparative methodology, examining the strengths and challenges of green taxonomies across different economic and regulatory contexts. Data were drawn from policy documents, existing taxonomies, and sustainability reports to identify transferable practices aligned with Qatar’s National Vision 2030 and international climate commitments. Findings reveal that successful green taxonomies integrate scientific rigor with flexibility to address national priorities. The EU's stringent classification and China’s project-specific approach provide valuable lessons, while South Africa and Malaysia highlight the importance of adaptability in emerging economies. Qatar’s taxonomy could balance international standards with local needs by leveraging its transitional role in natural gas and focusing on renewable energy, water conservation, and biodiversity protection. The originality of this study lies in its context-specific recommendations for Qatar, emphasizing the need to align local economic goals with global sustainability standards. By adopting these insights, Qatar can enhance its green finance ecosystem, attract international investment, and support its transition to a low-carbon economy. The study also offers transferable lessons for other hydrocarbon-dependent economies, particularly in the Gulf region, emphasizing phased threshold-setting, credible governance, data infrastructure, and transparent treatment of transitional activities. This study contributes to the growing literature on green finance in resource-dependent economies.
Mustafa et al. (Fri,) studied this question.