Recent research suggests that China’s Belt and Road Initiative (BRI) would improve the bilateral trade between China and its partners. This article uses detailed bilateral export data from 1990 to 2017 to investigate the impact of China’s BRI on its trade partners using neural network analysis techniques and structural gravity model estimations. Our main findings suggest that the BRI countries would raise exports by a modest 5.053%. This indicates that export and network upgrades should be considered from economic and policy perspectives. The results also show that neural networks is more robust compared with structural gravity framework.

The Belt and Road Initiative (BRI) intends to enhance China's international integration, strikingly by enhancing infrastructure and bolstering trade and investment links among the economies involved. Poor transport infrastructure and border restrictions are significant deterrents to trade expansion, economic growth, and bilateral trade. Using panel structural gravity model estimations, this study investigates the impact of Transportation infrastructure inheritances on bilateral trade across the Belt and Road member countries, particularly in Eastern Africa. The study considers the potential effect of the BRI roads, railways, and Information and Communication Technology (ICT) infrastructure network on the bilateral trade and economies of the Eastern African countries. The empirical analysis offers robust evidence that transport infrastructure promotes trade. The study found that transport infrastructure has a significant and positive effect on trade. These results imply that transport infrastructure exerts a strong effect on trade and growth in Eastern Africa. Policies for increasing access and affordability of transport infrastructure are highly recommended to promote trade and economic growth in the Eastern Africa sub‐region.

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This study investigates the relationship among CO2 emissions, human development index, and fossil energy usage. Essentially, the study was informed by the Sustainable Development Goal 7, which stipulates universal access to renewable and contemporary energy technologies. We employed the novel dynamic autoregressive-distributed lag (DARDL) simulations with a dataset spanning between1980 and 2020 from East Africa Community (EAC). The study revealed that human development, access to electricity, and trade have a strong correlation with carbon emissions in the long term, whereas fossil energy usage and economic growth have a negative connection with carbon emission. On the other hand, in the short run, human development and fossil energy usage have a positive correlation with carbon emission, while economic growth and foreign direct investment have a negative correlation with carbon emission. Thus, policies that are tailored to enhance the political environment in East Africa are crucial to ensuring realistic access to clean and modern electricity.