Identifying key natural gas drivers towards China's carbon neutrality through a novel temporal shrinkage framework

Natural gas (NG) plays a critical short-term role but must be gradually phased out in the long term to achieve China's ambitious dual carbon goals (DCGs), making it essential to identify key drivers that reconcile these divergent temporal demands. This study employs a novel temporal shrinkage framework that integrates big data analytics (LASSO/ALASSO) with advanced time-series modelling (ECM), proposing the long-run model (sequentially combining LASSO/ALASSO and ECM) and the short-run model (simultaneously incorporating both ECM and LASSO/ALASSO). The long-run model first identifies the key drivers in the NG market—temperature, thermal coal and HH gas prices, piped NG and LNG imports, NG market liberalisation, and NG infrastructure-related factors—and analyses their long-term effects. The short-run model then preliminarily assesses the short-term effects of these drivers while further exploring more comprehensive short-run dynamics by identifying additional drivers, such as ESG, global oil price, coking coal price, LNG and PNG import prices, and economic indicators. Our findings offer policymakers insights into these drivers, enabling the formulation of initiatives that balance short- and long-term effects to advance DCGs for China's sustainable development.