Does Digital Industrialization Improve Urban Energy Efficiency? Evidence from a Quasi-Natural Experiment in China

Big data-driven digital industrialization has become a critical driver of high-quality development in China, but its impacts on urban energy transition remain empirically uncertain and theoretically underexplored. This study addresses this gap using a quasi-natural experiment of China’s National Big Data Comprehensive Pilot Zones (NBDCPZ), panel data from 283 Chinese cities (2010–2023), and a combined DID-SDM (SDID) approach to estimate direct and spatial spillover effects while addressing SUTVA violations. Results show that digital industrialization reduces total urban energy consumption by 6% and improves energy efficiency, i.e. lowers unit GDP energy use. This net energy saving is achieved despite industrial output growth thanks to three key factors: industrial upgrade, green technology innovation, and reduced resource misallocation. Heterogeneity analysis reveals reductions in central China (9.8%), intra-regional pilot zones (9.0%), and large cities (7.0%), and also in non-resource-based cities and regions with advanced digital infrastructure. Crucially, there is significant spillover, where digital industrialization in one city can help neighboring cities cut energy consumption by 8.45%. This study contributes city-level causal evidence and quantitative insights, expands digital policy evaluation to energy consumption and efficiency, and integrates spatial dynamics into the digital-industrial-energy nexus. The findings offer guidance on synergizing digital transformation and low-carbon urban development.

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Publication Details

Journal
Chinese Journal of Urban and Environmental Studies
Published
2026-10-14
DOI
https://doi.org/10.1142/s2345748126500211
Primary Topic
Energy, Environment, Economic Growth
Type
article
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article

Does Digital Industrialization Improve Urban Energy Efficiency? Evidence from a Quasi-Natural Experiment in China

Yin Tang, tianlong guo
Chinese Journal of Urban and Environmental Studies
Energy, Environment, Economic Growth
article

Does Digital Industrialization Improve Urban Energy Efficiency? Evidence from a Quasi-Natural Experiment in China

Yin Tang, tianlong guo
article en

Abstract

Big data-driven digital industrialization has become a critical driver of high-quality development in China, but its impacts on urban energy transition remain empirically uncertain and theoretically underexplored. This study addresses this gap using a quasi-natural experiment of China’s National Big Data Comprehensive Pilot Zones (NBDCPZ), panel data from 283 Chinese cities (2010–2023), and a combined DID-SDM (SDID) approach to estimate direct and spatial spillover effects while addressing SUTVA violations. Results show that digital industrialization reduces total urban energy consumption by 6% and improves energy efficiency, i.e. lowers unit GDP energy use. This net energy saving is achieved despite industrial output growth thanks to three key factors: industrial upgrade, green technology innovation, and reduced resource misallocation. Heterogeneity analysis reveals reductions in central China (9.8%), intra-regional pilot zones (9.0%), and large cities (7.0%), and also in non-resource-based cities and regions with advanced digital infrastructure. Crucially, there is significant spillover, where digital industrialization in one city can help neighboring cities cut energy consumption by 8.45%. This study contributes city-level causal evidence and quantitative insights, expands digital policy evaluation to energy consumption and efficiency, and integrates spatial dynamics into the digital-industrial-energy nexus. The findings offer guidance on synergizing digital transformation and low-carbon urban development.

Chinese Journal of Urban and Environmental Studies
Chinese Academy of Social Sciences (CN), Qinghai University (CN)
Industry, innovation and infrastructure, Sustainable cities and communities, Affordable and clean energy, Climate action
Openalex Percentile: Top 8%
Energy, Environment, Economic Growth
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