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<p>The explicit impacts of digital economy often remain invisible in conventional national statistics, limiting opportunities for comprehensive social, economic, environmental, and interdisciplinary research. To enhance the visibility of digitalisation in macroeconomic statistics and address the growing demand for a robust research database, we proposed an innovative framework for digital supply and use tables (SUTs). Using the framework, we compiled a series of digital SUTs and input-output tables (IOTs) for China, consisting of 14 digital products, 40 digitalised conventional products, and 40 non-digitalised conventional products, and covering the period from 2000 to 2020. Building on conventional SUTs, our digital SUTs incorporate both digital products/industries and the digitalisation of conventional sectors. Importantly, our methodology is adaptable to other national and global digital SUTs and IOTs datasets, provided the necessary data is available.</p>

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Digital supply, use, and input-output tables for China from 2000 to 2020

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月28日

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  • Kailan Tian,
  • Kang Lin,
  • Yu Zhang,
  • Xiaolin Wang,
  • Wenze Chen,
  • Cuihong Yang

摘要

The explicit impacts of digital economy often remain invisible in conventional national statistics, limiting opportunities for comprehensive social, economic, environmental, and interdisciplinary research. To enhance the visibility of digitalisation in macroeconomic statistics and address the growing demand for a robust research database, we proposed an innovative framework for digital supply and use tables (SUTs). Using the framework, we compiled a series of digital SUTs and input-output tables (IOTs) for China, consisting of 14 digital products, 40 digitalised conventional products, and 40 non-digitalised conventional products, and covering the period from 2000 to 2020. Building on conventional SUTs, our digital SUTs incorporate both digital products/industries and the digitalisation of conventional sectors. Importantly, our methodology is adaptable to other national and global digital SUTs and IOTs datasets, provided the necessary data is available.