Spillover-feedback effects of social, economic, and environmental footprints based on the “Belt and Road Initiative”

The Belt and Road Initiative (BRI) links China to markets and sources of raw materials around the world while stimulating economic growth in developing countries and leading to widespread and occasionally unexpected social and environmental impacts. Considering that few studies have focused on the trade-embodied social and environmental impacts and two-way impact mechanisms throughout the BRI, this study, for the first time, uses social–economic–environmental footprints and the corresponding indicators of ecological efficiency and environmental stress to methodically measure the spatial distribution and regional transfer among three major regions comprising China (CHN), countries along the Belt and Road countries except China (CBR), and the rest of world (REW) from the standpoint of spillover and feedback effects, to better coordinate sustainable development between environment, economy, and society of the BRI. The results indicated the importance of spillover-feedback effects. Its significance lies not in comparison with the multiplier effect or the rates to TF, but in the indication of the two-way influence between regions through the numerical value of spillover–feedback effects of different regions and different industries. We identified that CBR and REW displayed the highest regional correlation in environment–economic aspects, followed by CHN and REW. The biggest contribution to the total footprint stemmed from the multiplier effects, suggesting the possibility that initiatives (e.g., BRI) could reduce the multiplier effects through internal drive optimization to offset the negative impact of spillover-feedback effects between regions (e.g., pollution transfer). Regarding employment, the feedback effects in CBR were the highest, suggesting that the indirect response due to the world's final demand pulled the largest employment in CBR. Moreover, REW was the net exporter of WF, CF, and EF, while the net importer of VAF and TOF. Furthermore, if ecological efficiency and environmental stress indicators were not considered, the stress of regional water resource use and carbon emission will be underestimated to a certain extent. For example, I-AGR of CHN and CBR in water resources stress, and III-HIS and V-EGW of CHN in carbon emissions stress. Finally, the proportions of different industries should be considered to evade misestimating the level of cleaner production in various industries during policymaking. Elucidating these mechanisms is essential to support decision-making that leads to sustainable development.