大数据试点政策能降低能源消耗强度吗？——基于国家级大数据综合试验区的准自然实验

doi:10.13776/j.cnki.resourcesindustries.20250916.001

摘要/Abstract

摘要： 能源消耗强度的高低是衡量国家经济发展优劣与否的一个重要标准，能源消耗强度越低，意味着我国经济产出越高效。大数据综合试验区试点地区作为国家重要战略布局，探究大数据综合试验区建设是否会促进我国能耗的降低，对于助力我国追赶数字经济浪潮、突破资源环境瓶颈制约、实现经济高质量发展具有重要意义。以2008—2022年中国30个省份面板数据为样本，采用双重差分模型分析大数据综合试验区试点政策对能源消耗强度的政策效应，并研究产业升级、研发投入对大数据试点政策与能源消耗强度可能产生的调节效应，从全要素生产率视角考察大数据试点政策对能源消耗强度的影响路径。结果表明：1）大数据试点政策有效地降低了能源消耗强度；2）机制检验发现，产业升级和研发投入强化了大数据试点政策对能源消耗强度的降低作用，大数据试点政策主要通过提升全要素生产率加强降低能源消耗强度的作用；3）异质性分析表明，大数据试点政策对于东部、西部地区及非资源型省份能源消耗强度的抑制作用更为明显。建议扩大试点范围，进一步促进地区大数据应用发展，积极引导大数据与能源领域融合创新，提高能源投入产出效率，推动经济高质量发展。

关键词: 国家级大数据综合试验区, 能源消耗强度, 产业升级, 研发投入, 全要素生产率

Abstract: Energy consuming intensity is an important indicator to mark a country's economic development quality; the lower intensity, the higher economic outputs. Big data comprehensive pilot zone, as national strategy, is key to testing if it can decrease China's energy consumption, catching up with digital economy, breaking resources environment bottleneck and realizing quality economic development. This paper uses 2008 to 2022 panel data of China's 30 provinces to establish a DID model which is employed to study the effectiveness of big data comprehensive pilot zone policy on energy consuming intensity, and to explore the possible adjusting effectiveness of industrial upgrade and research & development inputs on big data pilot policy and energy consuming intensity, and to test the impacting path from perspective of total factor productivity. Big data pilot policy effectively decreases energy consuming intensity, boosted by industrial upgrade and research & development inputs, mainly contributed by raising the total factor productivity. Heterogeneity analysis suggests that big data pilot policy constrains energy consuming intensity more in eastern, western and non-resources-based provinces. This paper presents suggestions on expanding pilot areas, combining big data application, combing big data with energy domain, improving energy input/output efficiency and driving quality economic development.

Key words: national big data comprehensive pilot zone, energy consuming intensity, industrial upgrade, research &, development input, total factor productivity

中图分类号:

F49
F206

马智胜, 王乐晴. 大数据试点政策能降低能源消耗强度吗？——基于国家级大数据综合试验区的准自然实验[J]. 资源与产业, 2025, 27(6): 1-15.

MA Zhisheng, WANG Leqing. CAN BIG DATA PILOT POLICY DECREASE ENERGY CONSUMING INTENSITY? BASED ON A QUASI-NATURAL EXPERIMENT OF NATIONAL BIG DATA COMPREHENSIVE PILOT ZONE[J]. Resources & Industries, 2025, 27(6): 1-15.

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