Spatiotemporal heterogeneities in the impact of the digital economy on carbon emission transfers in China

Abstract

This study investigates the spatiotemporal impacts of digital economic development on interprovincial carbon emissions transfer in China. Applying a proposed mixed geographically and temporally weighted spatial interaction panel regression (MGTWIPR) model, the study analyzes the annual carbon emissions data of 31 provincial administrative regions in China from 2015 to 2017. The results show that China's interprovincial carbon emissions transfers have apparent asymmetrical and imbalanced characteristics. The most significant transfers from the Yangtze River Delta (YRD) and Pearl River Delta (PRD) regions to north China and its surrounding areas follow a general pattern of carbon emissions transfer from developed to less developed regions. Improving digital economic development in origin regions promotes the exportation of carbon emissions to other areas. Conversely, enhancing digital economic development in destination regions would inhibit the import of carbon emissions to those regions. Additionally, from a spatial perspective, the impact of the origin region's digital economic development on carbon transfer is maximized in western China. Temporally, the influence of the origin region's digital economic development on carbon emissions transfers increases over time. This study integrates research regarding the digital economy and carbon emissions transfer, providing a novel perspective for digital economic studies. It also introduces a new research method for investigating the spatiotemporal heterogeneity of panel data. The results suggest the development of targeted strategies for regions with net carbon emissions exports and imports, emphasizing the role of digital technology in curbing carbon emissions to meet China's dual carbon goals.