John Gibson, Professor of Economics at the University of Waikato, New Zealand, visited the Collaborative Research Center 1342 on Thursday, October 26, 2023, for a Jour Fixe in the winter term 2023/24. In his talk "Big Data gone bad: Effects of measurement errors in popular DMSP night-time lights in empirical political economy," he spoke about the uses and abuses of night-time light satellite data in the social sciences to measure economic activity and assess local inequality.
Abstract:
Economists and other social science researchers increasingly use satellite-detected night-time lights, as one of the most popular “big data” sources. The most widely used series of night-time lights data are from the Defense Meteorological Satellite Program (DMSP), which was initiated in the 1960s to observe clouds to aid US Air Force weather forecasts. Initial use of these data by social science researchers was as a proxy for economic activity at the national or aggregated regional level but increasingly these data are used to evaluate local impacts of interventions and to estimate local inequality. When measurement errors in these data were originally considered it was in a framework that just required that the errors were independent of errors in conventional economic statistics. However, more recent studies use DMSP data directly as a proxy and so the nature of their measurement error becomes important because under certain circumstances these errors could cause bias that distorts conclusions.
This talk provides two such examples: first, when estimating local inequality in China and the United States the level of inequality is understated and a misleading trend is introduced, because of spatially mean-reverting errors in the DMSP data. Second, in a difference-in-differences evaluation of the impact of a sanction on North Korea the sanction impact is understated due to mean-reverting errors and bottom-coding in the DMSP data. These errors reflect some of the inherent limitations of DMSP data. Where possible, applied economists and other social scientists should switch to using newer, more accurate, night-time lights data that were designed for research purposes, even if that means they have to work with shorter time-series.
See also: Popular Big Data on Night-Time Lights Underestimate Inequality
John Gibson is Professor of Economics at the University of Waikato, Hamilton, New Zealand. He also is the Editor-in-Chief of the Asian Development Review, and non-resident Visiting Fellow at the Asian Development Bank Institute in Tokyo. His research, inter alia, focuses on economic development and social inequality. Since receiving his PhD from Stanford University, he has worked in numerous countries including Cambodia, China, Papua New Guinea, Thailand, and Vietnam.
Publications:
Using multi-source nighttime lights data to proxy for county-level economic activity in China from 2012 to 2019 (2022), with X Zhang, Remote Sensing.
Which night lights data should we use in economics, and where? (2021), with S Olivia, G Boe-Gibson, C Li, Journal of Development Economics.
Better night lights data, for longer (2021), Oxford Bulletin of Economics and Statistics.
How important is selection? Experimental vs. non-experimental measures of the income gains from migration (2010), with D McKenzie, S Stillman, Journal of the European Economic Association.
Contact:
Dr. Armin Müller
CRC 1342: Global Dynamics of Social Policy, Research IV and China Global Center
Campus Ring 1
28759 Bremen
Phone: +49 421 200-3473
E-Mail: armmueller@constructor.university
