A Test of DMSP and VIIRS Night Lights Data for Estimating GDP and Spatial Inequality for Rural and Urban Areas

Night lights, as detected by satellites, are increasingly used by economists,
especially to proxy for economic activity in poor countries. Widely used data
from the Defense Meteorological Satellite Program (DMSP) have several flaws;
blurring, top-coding, lack of calibration, and variation in sensor amplification
that impairs comparability over time and space. These flaws are not present in
newer data from the Visible Infrared Imaging Radiometer Suite (VIIRS) that is
widely used in other disciplines. Economists have been slow to switch to these
better VIIRS data, perhaps because flaws in DMSP are rarely emphasized. We
show the relationship between night lights and Indonesian GDP at the second
sub-national level for 497 spatial units. The DMSP data are not a suitable proxy
for GDP outside of cities. Within the urban sector, the lights-GDP relationship
is twice as noisy using DMSP as using VIIRS. Spatial inequality is considerably
understated by the DMSP data. A Pareto adjustment to correct for top-coding in
DMSP data has a modest effect but still understates spatial inequality and misses
much of the intra-city heterogeneity in the brightness of lights for Jakarta.

Joint work with Susan Olivia and Geua Boe-Gibson.