Research on the impact of ultra-high voltage transmission on urban carbon neutral technology innovation: An empirical test based on double machine learning method

Abstract

Energy infrastructure is a pivotal driver in reshaping the development trajectory of low-carbon technology as global carbon neutrality and the significant alteration of energy systems. Its innovation-driven efficacy has not been thoroughly investigated. This paper examines the “ultra-high voltage (UHV) transmission project,” which encompasses 270 Chinese cities at the prefecture level and above, as a quasi-natural experiment from 2006 to 2023. The difference-in-differences model and double machine learning are integrated to provide a causal inference framework that systematically reveals the multifaceted mechanism of energy infrastructure's impact on carbon neutral technology innovation. The findings indicate that UHV transmission project significantly increased carbon neutral technology innovation in pilot cities, enabling the optimal allocation of energy across regions. This supports the hypothesis of a network effect-innovation response mechanism driven by the dynamic adaptation of energy infrastructure. Further mechanism tests identify three transmission paths: government green development attention, informal environmental regulation, and energy consumption structure. Heterogeneity analysis reveals that these effects vary by region: energy-rich areas utilize UHV networks to break the resource curse; old industrial bases utilize it for green transitions; and small and medium-sized cities benefit from collaborative innovation. UHV transmission project reduces regional development gaps and weakens conventional geographic advantages. The paper provides precise policy targets for the energy revolution and regional coordination to support carbon neutrality, while providing practical guidance for infrastructure investment decisions.