This study examines how energy efficiency, renewable energy consumption, income inequality, carbon emissions, industrialization, urbanization, and gross fixed capital formation are associated with welfare‐focused sustainable development in the Nordic region. The analysis covers Denmark, Finland, Iceland, Norway, and Sweden over 2000–2024 using a balanced panel of 125 observations. Adjusted net national income per capita is used as the dependent variable because it provides a welfare‐based measure that goes beyond GDP and is better suited to capturing long‐run development in this context. Drawing on Ecological Modernization and Endogenous Green Growth theories, the study applies quantile regression alongside Panel‐Corrected Standard Errors, Driscoll–Kraay estimators, and System‐GMM. The findings show that energy efficiency, renewable energy consumption, and industrialization are positively associated with sustainable development, while carbon emissions, income inequality, and gross fixed capital formation display mixed or negative relationships across the distribution. Urbanization is positive across much of the distribution but becomes weaker at higher levels of sustainable development. The results offer practical relevance for policymakers, energy regulators, municipal authorities, industrial planners, and public investment institutions seeking to advance inclusive and low‐carbon development.
Zulfiquar Ali Antor, Mohammad Ridwan, Jeremy Ko et al.· Sustainable Development· 1 citation
This study examines the relationship between renewable energy use, industrialization, governance effectiveness, population growth, and technological innovation, and sovereign environmental, social, and governance (ESG) performance, used as a proxy for sustainable development, in China over the period 1996–2023. The analysis employs the Autoregressive Distributed Lag (ARDL) bounds testing approach to capture both short-run dynamics and long-run relationships among the variables. The findings indicate that population growth is negatively associated with ESG performance, whereas governance quality, renewable energy use, industrialization, and technological innovation are positively associated with improvements in ESG outcomes. To ensure robustness, the long-run estimates are validated using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR), and a series of diagnostic tests confirms the model’s stability and reliability. Granger causality results suggest unidirectional predictive relationships from renewable energy, industrialization, and population growth to ESG, as well as bidirectional predictive linkages between technological innovation and ESG. Overall, the findings highlight the importance of institutional quality, technological progress, and the energy transition in shaping China’s sovereign ESG performance.
Mohammad Ridwan, Jeremy Ko, Afsana Akther et al.· Discover Sustainability· 0 citations
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