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Digital assets represent newer technology and higher levels of intelligence in the context of global digitalization and intelligentization.With technology advancing and market demand changing asset replacement has become an indispensable step in the process of digital transformation.Asset replacement focuses on upgrading assets through technological progress to improve efficiency.It is different from fixed-asset investment which focuses more on expanding asset scale.The two types of investments are now presented in a composite form.Companies not only digitally upgrade their existing assets in reconstruction and technological transformation projects, but also extensively incorporate digital assets in new construction and expansion projects.The National Development and Reform Commission has announced actions to speed up the large-scale renewal of equipment and the trade-in of consumer goods, aiming to promoting high-quality development.Based on the actions, replaceable assets are defined as assets in the stock that should be renewed but remain un-renewed.To study the potential of asset replacement and its economic effects, the productive capital stock of digital hardware, digital software and non-digital assets of China's industries from 2001 to 2020 is measured.Industries are categorized based on the Statistical Classification of the Digital Economy and its Core Industries(2021) released by the National Bureau of Statistics.Replaceable assets are classified into three categories: buildings exceeding international standard of service life, non-building assets exceeding average service life, and digital assets accelerating replacement due to technological innovation supporting requirement.The scale of replaceable assets and its contribution to economic growth are estimated both in industial and national level.The differences in the contribution patterns of digital and non-digital assets to the economy are compared under production function model.The results show that: first, China's productive capital stock accounts for about 97% of non-digital asset types such as machinery, equipment, and buildings and the digital asset investment continues to increase.The proportion of capital stock exceeding average service lives of digital hardware are higher than that of other asset types.The time lag in the penetration of digital technology indicates great potential for asset replacement.Second, the scale of replaceable assets during the five-year period from 2020 to 2024 amounts to approximately 10.47 trillion to 16.87 trillion CNY,of which digital assets contribute more than 70%.Current asset depreciation methods cannot reflect the high-speed iteration of digital technology accurately.Third, the impact of digital capital on the output of industries is significant, with marginal output elasticity being about 20%.Digital assets are growing rapidly in scale and contributing more to economic growth than nondigital assets and labor.The finding reveals the structural transformation of factor returns, indicating that digital assets have become a significant driving force for economic growth.Large-scale asset replacement will lead to a totaled 17.94 trillion to 19.04 trillion CNY increase in comparable value-added during 2020 to 2024,of which digital assets contributed more than 96%.Based on the large-scale equipment renewals policies, China should build a structured docking mechanism for enterprise asset renewal, advance the digital integration and retrofitting of non-digital assets, accelerate the upgrade of digital assets, and further improve the tax support policies for asset digital transformation, to better promote high-quality development and the digital transformation of industries.
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(1)U.S.Bureau of Economic Analysis.Standard Fixed Assets Tables[EB/OL].(2024-10-02).https://www.bea.gov/itable/fixed-assets.
(2)31个数字经济行业与《数字经济统计分类》中32个数字经济中类对应。本文剔除了《数字经济统计分类》32个中类中的“0205其他数字产品服务业”,原因是该中类作为缺省类别,对应其他未列明数字产品服务业,目前在分类标准中没有对应的国民经济行业分类,因此该数字经济行业中类规模在本文中计为0,不纳入推算与分析。
(3)年龄—效率函数反映了单一资产老化时导致的生产能力损失,年龄—价格函数反映了单一资产老化时导致的价格下降。两者并不相同,只有在几何折旧的情况下,两者才具有相同的形式。
(4)本文选择范围上限5%作为残值率,资产折旧率会低于选择其他残值率的文献。
(5)本团队课题组研究成果,整理了2001—2020年共计20张序列投入产出表(42部门),包含现价投入产出表及可比价投入产出序列。
(6)由于版面问题未列示,需要数据者请与作者联系。
(7)下限与上限分别为几何效率模式下和双曲线效率模式下的测算结果。
(8)《数字经济统计分类》中采矿业、水电燃气生产和供应等部分工业行业被合并在其他数字效率提升业中,因此这部分行业的建筑资产也被记为非工业建筑,计入第二类可更新资产。
Basic Information:
DOI:10.20207/j.cnki.1007-3116.2025.0031
China Classification Code:TP399;F124;F222
Citation Information:
[1]XU Yingmei,CHEN Hongmin.Estimation of Scale and Analysis of Economic Effects of Industry Asset Replacement[J].Journal of Statistics and Information,2025,40(08):26-39.DOI:10.20207/j.cnki.1007-3116.2025.0031.
Fund Information:
国家社会科学基金一般项目“复杂网络视域下数字经济推动产业转型升级的统计研究”(21BTJ003)
2025-08-08
2025-08-08