A new frontier in understanding the dynamics of environmental sustainability in the context of finance and low carbon energy investment: Evidence from artificial intelligence and Fourier approach

Nuclear and renewable (low-carbon) energy research and development is crucial for a sustainable future, transitioning away from fossil fuels. However, adequate financial sources are imperative to stimulate this transition. Financial institutions, particularly banking institutions, play a critical role in fulfilling the financial needs for green energy transition. This study investigates the effects of banking sector development, low-carbon energy investments, economic growth, and trade openness on environmental sustainability. Notably, novel Fourier asymmetric ARDL and artificial intelligence-based neural network methods are used for empirical analysis. The Fourier approach captures nonlinearities in the banking sector development and environment relationship. It is found that the negative shocks of banking sector development and economic growth reduce environmental sustainability. However, the positive effects of low-carbon energy investments and trade openness on environmental quality offer a promising path toward a more sustainable future. The Japanese government should accelerate low-carbon energy investments to accelerate the transition from fossil energy to green energy sources. This transition holds the potential to significantly improve Japan's environmental sustainability and contribute to the achievement of Sustainable Development Goal 7. In addition, since the decline of the banking sector's development in Japan undermines environmental sustainability, financial planning should be implemented to progress this sector.