A data-driven framework for ESG prioritization: PCR-based insights for sustainable governance and growth

Environmental, social, and governance (ESG)-based investment strategies aim to integrate not only economic but also ethical and environmental dimensions into financial decision-making processes to promote sustainable economic growth. However, the relative effects of ESG criteria on economic growth have not been sufficiently examined in the existing literature, creating a significant research gap. Consequently, investment priorities and public policies cannot be determined effectively. The main objective of this study is to identify strategies that enable countries with limited resources to prioritize the ESG factors yielding the greatest benefit. The decision-making model proposed in this study is based on the principal component regression (PCR) approach, which minimizes multicollinearity issues. In this process, data from 155 countries for the year 2020 are taken into consideration. This study makes three main contributions to the literature: (1) a comparative examination of the relative effects of ESG factors on economic growth, (2) identifying how these effects differ across country groups, and (3) analyzing multicollinearity among ESG variables more accurately through the PCR method. The findings indicate that environmental burdens negatively affect growth in Asia, whereas education expenditures positively influence growth in developed economies.