Quantifying carbon emissions through financial development in Ghana: empirical evidence from novel dynamic ARDL and KRLS techniques

The critical issue of environmental degradation emphasises the urgent need for coordinated actions to safeguard and restore the planet's fragile ecological balance. This study examines the relationship between financial development and carbon emissions in Ghana from 1990 to 2020, focusing on the roles of natural resource rents and economic sustainability. Utilizing time-series data from the World Bank and applying a dynamic autoregressive distributed lag (ARDL) model and kernel-based regularized least squares (KRLS) machine learning technique, the findings indicate that financial development significantly increases carbon emissions in both the short- and long-term. At the same time, natural resource rents have a negligible impact on emissions in the short term but contribute to increased emissions in the long run. Conversely, economic sustainability consistently reduces carbon emissions in the short- and long-run. Our findings highlight the need for policymakers to prioritize green financing initiatives, promote financial products that support renewable energy, and implement stricter regulations on natural resource exploitation. Additionally, incentives for financial institutions to invest in environmentally-sustainable projects are vital for achieving Ghana's carbon neutrality goals.