Detecting corruption from outer space

Leonardo Baccini, Yushan Hu and Ben G. Li

Applied Economics Letters, 2025, vol. 32, issue 10, 1399-1404

Abstract: Moral hazards in local governance give rise to both corruption and data misreporting. We find that the latter, which is relatively easy to uncover, can be used to detect the former. Our study, using data from Chinese prefectures between 1993 and 2013, demonstrates that the difference between the GDP growth reported by local officials and the GDP growth inferred from nightlight luminosity can predict local corruption. This approach illustrates the effectiveness of integrating remote-sensing technology, non-causal correlation, and economic reasoning to uncover bureaucratic anomalies that originate from similar mechanisms.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/13504851.2024.2305235 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:apeclt:v:32:y:2025:i:10:p:1399-1404

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEL20

DOI: 10.1080/13504851.2024.2305235

Access Statistics for this article

Applied Economics Letters is currently edited by Anita Phillips

More articles in Applied Economics Letters from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().