The synergistic advancement of “Digital China” and “Beautiful China” represents a pivotal national strategy for achieving high-quality economic development and a low-carbon transition. To illuminate the intrinsic mechanisms linking the digital economy (DE) to urban carbon emission performance (CEP), this study develops a novel two-sector theoretical framework. Leveraging panel data from 278 Chinese prefecture-level cities (2011–2023), we employ a comprehensive evaluation method to gauge DE development and utilize calibrated nighttime light data with downscaling inversion techniques to estimate city-level CEP. Our empirical analysis integrates static panel fixed effects, panel threshold, and moderating effects models. Key findings reveal that the digital economy demonstrably enhances urban carbon emission performance, although this positive effect exhibits a threshold characteristic linked to the maturity of digital infrastructure; beyond a specific developmental stage, the marginal benefits diminish. Crucially, this enhancement operates primarily through the twin engines of fostering technological innovation and driving industrial structure upgrading, with the former playing a dominant role. The impact of DE on CEP displays significant heterogeneity, proving stronger in northern cities, resource-dependent cities, and those characterized by higher levels of inclusive finance or lower fiscal expenditure intensities. Furthermore, the effectiveness of DE in reducing carbon emissions is dynamically moderated by policy environments: flexible economic growth targets amplify its carbon reduction efficacy, while environmental target constraints, particularly direct binding mandates, exert a more pronounced moderating influence. This research provides crucial theoretical insights and actionable policy pathways for harmonizing the “Dual Carbon” goals with the overarching Digital China strategy.
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Shan Yan
Wen Zhong
Zhiqing Yan
Sustainability
Jiangxi University of Science and Technology
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Yan et al. (Tue,) studied this question.
synapsesocial.com/papers/689e03e9d61984b91e13d127 — DOI: https://doi.org/10.3390/su17167277