How Major Events Reconfigure Technology–Energy Risk Spillovers in China: Implications for Energy Security

The rapid expansion of artificial intelligence is tightening the interdependence between digital infrastructure and energy systems, making the linkages between technology and energy increasingly important for understanding energy security. This study examines how major events reshape risk spillovers between China’s technology and energy sectors, with particular attention to the asymmetric effects of policy shocks, external technological shocks, and domestic technological breakthroughs. Focusing on four events, namely the announcement of the carbon peaking and carbon neutrality goals, the launch of the East Data and West Computing project, the release of ChatGPT 3.5, and the release of DeepSeek R1, the study explores whether different shocks alter risk transmission between sectors in distinct ways. Using interval data for 16 representative listed firms from 2021 to 2025, the analysis combines firm-level spillover networks with sector-level robustness tests. The results suggest that policy-driven events are associated with stronger systemic connectedness and changes in the direction of predictive spillovers between the technology and energy sectors, although the Dual Carbon result is sensitive to the selected event window, whereas ChatGPT 3.5 is associated with short-term risk decoupling under the baseline specification, although this result also shows some sensitivity to the event horizon. DeepSeek R1 shows the largest baseline increase in overall spillovers and a relatively stable positive pattern across alternative event windows. The precision of the estimated changes also varies across events. The findings suggest that domestic advances in large language models are not only innovation milestones, but also potential sources of persistent pressure on energy security.