UrbanStudyUrban Research Radar
Urban Society & Demography
Journal article

Using nighttime light data to assess the impact of AI pilot cities on government overtime in China

Published 22 Mar 2026 · Added to radar 5 Nov 2026

Source abstract

In an era of rapid urbanization and digital transformation, nighttime light data has emerged as a powerful proxy for measuring after-hours work. This study investigates whether the artificial intelligence (AI) pilot cities initiative, launched by the Ministry of Science and Technology in 2019, reduces overtime in Chinese government offices. Drawing on satellite-derived nighttime light data from more than 300 cities, it identifies changes in after-hours work behavior among government employees. Leveraging a quasi-natural experiment and a staggered difference-in-differences model, the findings show that AI implementation in pilot cities led to a 7.82% decline in nighttime overtime, which translates to approximately eight fewer overtime days per year. These estimates remain robust after accounting for potential alternative explanations including pandemic-induced remote work, other policy confounds, city heterogeneity, and selection bias. Overall, this research highlights the potential for AI initiatives to enhance efficiency in urban governance and reduce excessive work hours in public administration.

Abstract metadata supplied by the research index; wording belongs to the original source.

Structured record

Study objective (from source abstract)
This study investigates whether the artificial intelligence (AI) pilot cities initiative, launched by the Ministry of Science and Technology in 2019, reduces overtime in Chinese government offices.
Source-reported findings
  • Leveraging a quasi-natural experiment and a staggered difference-in-differences model, the findings show that AI implementation in pilot cities led to a 7.82% decline in nighttime overtime, which translates to approximately eight fewer overtime days per year.
Methods
difference-in-differences

Read the original ↗ DOI ↗