Against the backdrop of the coordinated advancement of the dual carbon goals and new-type urbanization, the traditional high-carbon development model has become a major constraint on urban green transformation. As a critical vehicle for digital technologies to empower low-carbon governance, smart cities have yet to receive a systematic evaluation of their long-term policy effects based on quasi-natural experiments. Using panel data from 280 prefecture-level cities from 2003 to 2023, this study takes the smart city pilot policy as a quasi-natural experiment. It adopts Interpretive Structural Modeling (ISM) to identify the key influencing factors and transmission paths of carbon emissions, and employs the progressive difference-in-differences (DID) model to assess the carbon emission reduction effects, dynamic evolutionary characteristics and urban heterogeneity of smart city construction. Furthermore, the mediation effect model is applied to clarify its underlying mechanisms. The empirical results show that smart city construction significantly curbs urban carbon emissions, and this finding remains valid after a series of robustness tests, including the parallel trend test, placebo test and PSM-DID. The emission reduction effect of the policy exhibits an obvious time lag: the effect is insignificant in the first and second years after policy implementation but turns significantly negative and continues to strengthen starting from the third year. Noticeable urban heterogeneity is also observed, with a more prominent emission reduction effect in eastern regions, central cities with high administrative ranks and large-sized cities. Mechanism analysis reveals that the conventional industrial pollution reduction pathway does not serve as the primary transmission channel. Instead, a suppression effect is identified, suggesting that smart cities achieve carbon abatement primarily through the digital empowerment of energy allocation efficiency—a pathway distinct from traditional end-of-pipe governance approaches. Unlike previous studies, this study combines ISM with a staggered DID framework to reveal the dynamic effects and transmission mechanisms of smart city policies.
China’s low-carbon city pilot program seeks to reconcile carbon emission reduction with economic growth and welfare improvement. This study examines whether low-carbon pilot policies (LCPPs) improve urban ecological welfare performance (EWP), the mechanisms through which these effects operate, and whether the polic...
Ge Sun, Ya-Ting Fu· Frontiers in Environmental S...· 0 citations
Promoting urban green and low-carbon transformation is essential for achieving carbon peaking and carbon neutrality, yet cities continue to face financing constraints, insufficient project identification, and weak incentives for green innovation. This study treats China’s climate investment and financing pilot program...
The rapid expansion of the digital economy coincides with escalating environmental challenges, making Green Data Centers (GDC) an important form of digital infrastructure with potential implications for environmental governance. However, existing studies mainly evaluate data centers from the perspectives of energy effi...
Jing-Bao Cao, Sheng-Hao Bi· Global NEST Journal· 0 citations
Enhancing urban ecological resilience (UER) is essential for achieving sustainable development in the context of global climate change. Using urban panel data and a difference-in-differences (DID) framework, this study empirically examines the effects of dual pilot policies combining new energy demonstration (NED) and...
Yin-Lu Zhang, Fen-Fen Wang, Qing-Feng Luo et al.· Urban Science· 0 citations
Whether digital governance can be converted into measurable disaster-mitigation performance is an important criterion for evaluating smart-city development. Taking China's national smart-city pilot program as a quasi-natural experiment, this study uses a balanced panel of 300 prefecture-level cities from 2009 to 2023 a...
Xian-Zhu Nie· Journal of Applied Economics...· 0 citations
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