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This study employs a rigorous econometric approach to investigate the intricate interrelationships among environmental, social, and governance (ESG) factors and their impact on GDP growth and the attainment of Sustainable Development Goals (SDGs) in East Asia-Pacific and South Asian countries. Utilizing panel data spanning the period from 2003 to 2021 sourced from the World Bank, our study diverges from previous research by adopting a comprehensive and inclusive stance in selecting relevant variables. Robust econometric methods, including cross-sectional dependence tests, unit root tests, Granger causality tests, and cointegration analyses, have been applied to scrutinize these relationships. The findings substantiate the significant long-run associations between ESG factors, GDP growth, and SDGs. This research emphasizes the distinctive aspect of meticulously assessing the interconnections of each country. Notably, this study innovates by considering environmental, social, and governance indicators alongside GDP growth to comprehensively evaluate their impact on SDGs. The application of advanced econometric methodologies confirms cross-sectional dependence, a long-run symmetric relationship, and stationary variables with high significance. Autoregressive Distributed Lag (ARDL) estimates revealed a positive long-run association between governance factors (GOVNf) and SDGs, indicating a negative relationship between environmental factors (ENVf) and SDGs. To further test the robustness of the findings we used AMG and CCEMG estimations. The study establishes significant relationships between environmental, social, and governance factors, GDP growth, and SDGs, providing valuable insights for policymakers and researchers alike.
Gazi et al. (Fri,) studied this question.