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Data from: The spatiotemporal evolution and formation mechanism of the digital economic gap: Based on the case of China

Cite this dataset

Wu, Shujuan; Li, Jinting; Huang, Daqian; Xiao, Jianhua (2024). Data from: The spatiotemporal evolution and formation mechanism of the digital economic gap: Based on the case of China [Dataset]. Dryad. https://doi.org/10.5061/dryad.8w9ghx3rn

Abstract

We analyzed the formation mechanism of digital economic gap (DEG), measured the DEGs at four levels (the gaps in information and communication technology accessibility, application skill, digital economic outcome, and efficiency), and explored its spatiotemporal evolution in China by using DEA–Malmquist index method, Gini Coefficent method, Kernel density, and Geodetector. Data from 263 cities in China between 2011 and 2019 were collected. The results demonstrated that (1) The four levels of DEGs showed different trends. The first-, second- and third- level DEGs showed ceiling effects, and the fourth-level DEG oscillated upward. (2) The distribution location of the four levels of DEGs varied. The first- and second-level DEGs shifted at a stable low degree. The third-level DEG increased steadily and polarized. The fourth-level DEG increased steadily and formed a multi-polarization trend, with one strong polar. (3) The long-term transfer trend of the DEGs at four levels changed little, and showed a phenomenon of “club convergence”. (4) As for the formation of DEGs, the first-level DEG was influenced by most factors and was education- and policy-driven; the second-level DEG was profit-driven; the third-level DEG was profit- and education-driven; the fourth-level DEG was human resource-driven.

README

The dataset -- data.dta (city = 263, year = 8) -- was compiled from the peer-reviewed literature. This was from study sites in 263 cities, China.

The dataset was compiled by co-authors Shujuan Wu (jane333444@126.com), Jinting Li (1311028217@qq.com), Daqian Huang (1953836900@qq.com), Jianhua Xiao (1312655857@qq.com) of Wuyi University.

For any questions regarding the dataset, please send an email to Shujuan Wu (jane333444@126.com) and Jinting Li (1311028217@qq.com).


Filename: data.dta

◈year: The year of the data

◈city: City No.

◈region: The No. Of the region

◈rndexp: R&D expenditure (10000 Yuan)

◈exgebudget:Total financial expenditure (10000 Yuan)

◈fixass:  Fixed asset investment (10000 Yuan)

◈fstdeg: First-level of digital economy (/)

◈library: The collection of books in public libraries per capita (1000 volumes or pieces )

◈ ictlabor: The proportion of information transmission, computer services, and software professionals in urban units (%)

◈digpatent: The number of digital patent authorizations per capita. (DE patents include Internet technology, Internet of Things technology, big data technology, AI technology, mobile Internet technology, virtual reality technology, and related products and services.) (case/ person)

◈telpen: The fixed telephone mainline penetration rate (%)

◈mobrate: The mobile phone penetration rate (%)

◈netrate: The Internet penetration rate (%)

◈secdeg: Second-level of DE (/)

◈ thddeg: Third-level of DE (/)

◈netuser: Internet user No. (person)

◈netpro: The proportion of information transmission, computer services, and software professionals in urban units (%)

◈netout: Total telecom business per capita (%)

◈ fthdeg: Fourth-level of DE (/)

◈ digpol: Regional DE intensity gap (/)

◈digattn: DE Baidu attention index gap (/)

◈eduexp: Education investment level (10000 CN Yuan)

◈profit: Enterprise profit margin (10000 CN Yuan)

◈flowasset:  Regional current asset amount (10000 CN Yuan)

◈lending: Regional loan amount (10000 CN Yuan)

◈ scilab: Regional research human resource (Person)

◈ sallab: Regional sales human resource (Person)

Data derived from the following sources, are compatible with the CC0 waiver required by Dryad.

The sources are: China Statistical Yearbook, China Science and Technology Statistical Yearbook, provincial and city statistical yearbooks, the White Paper on China City DE Index, and the Mark Data website (https://www.macrodatas.cn/).

Methods

A total of 263 cities in 30 provinces (cities or regions) in China were selected as the study subjects. Data were obtained from the China Statistical Yearbook, China Science and Technology Statistical Yearbook, Provincial and City Statistical Yearbooks, White Paper on China City DE Index, and the Mark Data website (https://www.macrodatas.cn/). The expedition period for this study was from 2011 to 2019. 

Funding

The 2021 General Project of Guangdong Philosophy and Social Sciences Planning under Grant, Award: GD21CYJ28

The 13th Five-year plan of Educational Science in Guangdong Province, Award: 2020GXJK105

The Ministry of Education Humanities and Social Science Research Planning Fund Project, Award: 21YJA630097