Can the Digital Economy Promote the Upgrading of Urban Environmental Quality?

Int J Environ Res Public Health. 2023 Jan 27;20(3):2243. doi: 10.3390/ijerph20032243.

Abstract

As the core of economic development, the digital economy plays an essential role in promoting urban environmental quality. In this study, we constructed a comprehensive indicator system using two dimensions, i.e., the internet and digital finance, to measure the development situation of the urban digital economy, and we used principal component analysis to assess it. From the three perspectives of ecological environment state, ecological environment pollution degree, and ecological environment governance ability, the entropy method was used to measure the quality of the urban environment. On the basis of panel data from 275 cities (prefecture-level and above) in China from 2011 to 2019, we empirically analyzed the impact of the digital economy on urban environmental quality using the two-way fixed effect model and spatial Dubin model. The research shows that the digital economy significantly promotes urban environmental quality upgrades. This conclusion still holds when considering endogeneity. This effect is mainly achieved by promoting technological innovation, optimizing the industrial structure, and enhancing market competition. Further research demonstrated that the digital economy does not significantly impact the improvement of environmental quality in small- and medium-sized cities, but has a positive effect on environmental quality upgrading in large cities. The development of the digital economy promoted urban environmental quality upgrading in the region. However, the development of the digital economy has no significant impact on environmental quality upgrading in surrounding areas.

Keywords: digital economy; endogeneity; entropy method; spatial Dubin model; urban environmental quality.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Cities
  • Economic Development*
  • Entropy
  • Environment*

Grants and funding

This research was funded by the National Natural Science Foundation of China (grant number: 72073071), and Regional Programs of the National Natural Science Foundation of China (grant number: 71963016).