Pathways to sustainable transportation in G-20 countries: Unveiling the role of green technology, green energy, green finance and digital economy using panel data and machine learning analyses

Abstract

Achieving sustainability has become a global priority, with environmental sustainability gaining significant attention from policymakers due to its critical importance. While numerous studies have empirically examined the relationship between CO2 emissions and green initiatives, they often overlook sectoral differences. Since different sectors contribute unequally to carbon emissions, the environmental effectiveness of green solutions may vary across sectors. This study addresses this research gap by focusing on the transport sector, a major contributor to global CO2 emissions. This study investigates the role of green technology, green energy, green finance, digital economy, economic growth, and urbanization on transport sector CO2 emissions in G-20 economies from 2002 to 2022. Using panel quantile regression, the results reveal that green energy and economic growth reduce transport emissions in lower quantiles; while green energy, green finance, and urbanization enhance environmental quality in upper quantiles. However, green technology is associated with higher transport emissions across all quantiles. Moreover, we employ a simple regression tree model, a machine learning approach, to identify which countries are winners and losers in terms of predicted transport emissions. Our results predict a 13.72 % increase in transport emissions across G-20 nations, with Japan, Australia, Saudi Arabia, the United States, Argentina, Russia, South Africa, South Korea, France, Brazil, India, and Italy among the most affected. These findings recommends shifting to non-motorized vehicles and public transportation systems that enhance transport efficiency and mitigate environmental degradation through green transportation.