Resources sustainability and energy transition in China: Asymmetric role of digital trade and policy uncertainty using QARDL

Abstract

This research explores the influence of economic policy uncertainty, energy transition, and digital trade on China's resources (material) footprints. Moreover, we control the effect of economic growth and industrialization in dealing with the association between the variables of interest from Q1-2000 to Q4-2020. The association between the variables has been examined through Quantile Autoregressive Distributed Lag (QARDL) model, which determines the change in the primary dependent variable (i.e., material footprints) over lower, medium, and higher order quantiles. The initial findings confirm the non-normal trends in the data with the stationarity properties. The results show that economic policy uncertainty is causing more damage in creating a higher resource footprint. Contrarily, energy transition, and digital trade tend to reduce resources burden. More specifically, the impact of policy uncertainty on material footprints is higher at higher-order quantiles and lower at lower-order quantiles. Similarly, energy transition significantly reduces the material footprints across all the quantiles. Considering the role of digital trade, it is found that except for the 0.10th quantile, trade facilities are suitable for reducing material footprints in China.