Unveiling the drivers of climate change: the impact of economic indicators, renewable energy consumption and human development through a panel ardl approach

This study investigates the impact of renewable energy consumption, GDP, industrialization, and the Human Development Index (HDI) on carbon emissions in selected Asian countries from 1997 to 2023. Utilizing panel data from the World Development Indicators (WDI) and supplementary sources, the research employs a Panel Autoregressive Distributed Lag (ARDL) model to analyze both short- and long-term dynamics within the framework of the Environmental Kuznets Curve (EKC) hypothesis, which posits an inverted U-shaped relationship between economic growth and environmental degradation. The study explores whether human development and renewable energy adoption can disrupt the conventional trajectory where economic expansion leads to higher emissions. The methodology consists of unit root tests to assess staionarity followed by cointegration and error correction analysis. Findings show GDP and renewable energy use significantly impact short-run emissions while industrialization and HDI have minimal impact. In the long run a 1% increase in GDP equals a 0.017% increase in emissions, which highlights the carbon-intensive nature of economic growth. In contrast, when the usage of renewable energy doubles, emissions decrease by 0.029%, making clean and renewable energy a crucial part of the global agenda to combat climate change. Industrialisation also has a positive long-term relationship with emissions, but not statistically significant over time whereas a 1 unit increase in HDI increases emissions by 0.014%, which may indicate a trade-off between development and environmental sustainability. These findings contribute to the understanding of the dynamics between economic growth, human development and emission reduction pathways in Asia.