Mitigating energy intensity stands as a core linchpin for fulfilling China’s “dual carbon” strategic goals and facilitating the low-carbon green transition of the economic system. Against the backdrop of the in-depth convergence of the digital economy and the real economy, a critical unresolved research question persists: whether and through what pathways digital government construction can improve energy utilization efficiency by enabling the development of emerging strategic industries. Against this background, this study systematically investigates the combined effects and intrinsic transmission mechanisms between digital government construction, the high-quality development of the low-altitude economy (hereafter referred to as LAE), and regional energy intensity. Specifically, this study addresses four core research gaps: first, whether digital government construction can exert a direct curbing effect on energy intensity; second, what functional role the high-quality development of the LAE plays in this causal relationship; third, whether spatial spillover effects exist between the two core factors on regional energy intensity; and fourth, whether the industrial, market, and policy dimensions of LAE development have heterogeneous influences in the above transmission mechanism. To answer the above research questions, this study constructs a unified analytical framework that incorporates digital government construction, high-quality LAE development, and regional energy intensity. We employ panel data covering 30 provinces in China from 2012 to 2022, taking the institutional reform of provincial big data management authorities as a quasi-natural experiment to identify the policy effects of digital government construction. Meanwhile, we build a comprehensive evaluation system to quantify the high-quality development level of the LAE from three core dimensions: industrial development, market maturity, and policy support. On this basis, the spatial difference-in-differences (SDID) model and double machine learning (DML) model are adopted to carry out systematic empirical tests. The empirical results reveal the following core findings: First, both digital government construction and the high-quality development of the LAE have a significant direct inhibitory effect on regional energy intensity. Second, the spatial spillover effects of the two factors present pronounced heterogeneous characteristics: the radiation effect of digital government construction on adjacent regions depends on the dual premise of geographical proximity and economic development similarity, while the technology spillover effect of LAE development can be effectively realized under the single condition of economic similarity. Third, the high-quality development of the LAE plays a significant mediating role in the causal chain of digital government construction affecting regional energy intensity, and this transmission mechanism remains statistically robust after a series of robustness tests, including algorithm replacement, adjustment of sample splitting ratios, and exclusion of interference from concurrent policy shocks. Fourth, further decomposition tests of the transmission path demonstrate that the industrial dimension plays the most core and fundamental role, acting as the “material basis” for transforming the governance efficiency of digital government into actual energy-saving effects, while the market and policy dimensions function as key supporting collaborative mechanisms, whose transmission intensity is highly dependent on the foundation of industrial development. This study unpacks the intrinsic transmission mechanism through which digital government construction enables the LAE to curb regional energy intensity, offering solid theoretical underpinnings and actionable policy implications for emerging market economies to advance energy “dual control” targets and foster the development of new quality productive forces.
Lang et al. (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: