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<p>Taking China’s national green data center pilot (NGCP) as the research background, this study adopts the multi-period DID method to systematically examine the policy’s impacts on urban energy efficiency as well as its internal functioning mechanisms. The empirical outcomes indicate that the pilot program effectively and significantly improves urban energy utilization efficiency. Mechanistic examinations confirm three core transmission paths: green technological innovation stimulation, industrial agglomeration enhancement, and digital economy development. Furthermore, nonlinear estimation results prove that the policy’s marginal improvement effects differ at various energy efficiency development stages. Heterogeneity analysis indicates that the policy’s effect is contingent upon regional characteristics, such as resource availability, geographic location, and industrial structure, with notably stronger impacts observed in non-resource-dependent cities and regions possessing mature industrial bases. Moreover, spatial econometric analysis uncovers significant positive spatial spillovers from the policy, demonstrating its capacity to facilitate energy conservation and efficiency gains in neighboring urban areas not originally included in the strategic green data center framework.</p>

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The impact of data center green transformation on energy efficiency: a quasi-natural experiment based on national green data center pilot

  • 期刊论文

  • 发表日期：

    2026年6月16日

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  • Lianghu Wang,
  • Jun Shao

摘要

Taking China’s national green data center pilot (NGCP) as the research background, this study adopts the multi-period DID method to systematically examine the policy’s impacts on urban energy efficiency as well as its internal functioning mechanisms. The empirical outcomes indicate that the pilot program effectively and significantly improves urban energy utilization efficiency. Mechanistic examinations confirm three core transmission paths: green technological innovation stimulation, industrial agglomeration enhancement, and digital economy development. Furthermore, nonlinear estimation results prove that the policy’s marginal improvement effects differ at various energy efficiency development stages. Heterogeneity analysis indicates that the policy’s effect is contingent upon regional characteristics, such as resource availability, geographic location, and industrial structure, with notably stronger impacts observed in non-resource-dependent cities and regions possessing mature industrial bases. Moreover, spatial econometric analysis uncovers significant positive spatial spillovers from the policy, demonstrating its capacity to facilitate energy conservation and efficiency gains in neighboring urban areas not originally included in the strategic green data center framework.