Better Night Lights Data, For Longer

John Gibson

Oxford Bulletin of Economics and Statistics, 2021, vol. 83, issue 3, 770-791

Abstract: Night lights data are increasingly used in applied economics, almost always from the Defense Meteorological Satellite Program (DMSP). These data are old, with production ending in 2013, and are flawed by blurring, lack of calibration and top‐coding. These inaccuracies in DMSP data cause mean‐reverting errors. This paper shows newer and better VIIRS night lights data have 80% higher predictive power for real GDP in a cross‐section of 269 European NUTS2 regions. Spatial inequality is greatly understated with DMSP data, especially for the most densely populated regions. A Pareto correction for top‐coding of DMSP data has a modest effect.

Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Downloads: (external link)
https://doi.org/10.1111/obes.12417

Related works:
Working Paper: Better Night Lights Data, For Longer (2020)
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:bla:obuest:v:83:y:2021:i:3:p:770-791

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0305-9049

Access Statistics for this article

Oxford Bulletin of Economics and Statistics is currently edited by Christopher Adam, Anindya Banerjee, Christopher Bowdler, David Hendry, Adriaan Kalwij, John Knight and Jonathan Temple

More articles in Oxford Bulletin of Economics and Statistics from Department of Economics, University of Oxford Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().