DOI: 10.5061/dryad.8w9ghx3rn
title: Data from: The spatiotemporal evolution and formation mechanism of the digital economic gap: Based on the case of China

description: 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.
description: A total of 263 cities in 30 provinces (cities or regions) in
 China were selected as the study subjects. Data were obtained from the
 <em>China Statistical Yearbook, China Science and Technology
 Statistical Yearbook</em>, 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. 
description: 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](mailto:jane333444@126.com)), Jinting Li
 ([1311028217@qq.com](mailto:1311028217@qq.com)), Daqian Huang
 ([1953836900@qq.com](mailto:1953836900@qq.com)), Jianhua Xiao
 ([1312655857@qq.com](mailto:1312655857@qq.com)) of Wuyi University. For
 any questions regarding the dataset, please send an email to Shujuan Wu
 [(jane333444@126.com)](mailto:\(jane333444@126.com\)) and Jinting Li
 ([1311028217@qq.com](mailto: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/](https://www.macrodatas.cn/)).