Gibson, John and Olivia, Susan and Boe-Gibson, Geua (2019): Which Night Lights Data Should we Use in Economics, and Where?
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Abstract
Popular DMSP night lights data are flawed by blurring, top-coding, and lack of calibration. Yet newer and better VIIRS data are rarely used in economics. We compare these two data sources for predicting Indonesian GDP at the second sub-national level. DMSP data are a bad proxy for GDP outside of cities. The city lights-GDP relationship is twice as noisy using DMSP as using VIIRS. Spatial inequality is considerably understated with DMSP data. A Pareto adjustment to correct for top-coding in DMSP data has a modest effect but still understates spatial inequality and misses key features of economic activity in Jakarta.
Item Type: | MPRA Paper |
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Original Title: | Which Night Lights Data Should we Use in Economics, and Where? |
Language: | English |
Keywords: | Night lights; inequality; GDP; DMSP; VIIRS; Indonesia |
Subjects: | O - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O15 - Human Resources ; Human Development ; Income Distribution ; Migration R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R12 - Size and Spatial Distributions of Regional Economic Activity |
Item ID: | 97582 |
Depositing User: | Prof John Gibson |
Date Deposited: | 19 Dec 2019 10:52 |
Last Modified: | 19 Dec 2019 10:52 |
References: | Abrahams, Alexei, Christopher Oram and Nancy Lozano-Gracia (2018) Deblurring DMSP night-time lights: A new method using Gaussian filters and frequencies of illumination. Remote Sensing of Environment 210(1): 242-258. Addison, Douglas, and Benjamin Stewart (2015) Night time lights revisited: The use of night time lights data as a proxy for economic variables. World Bank Policy Research Working Paper No. 7496. Andersson, Magnus, Ola Hall and Maria Archila (2019) How data poor countries remain data poor: Underestimation of human settlements in Burkina Faso as observed from night time lights data. Mimeo. Bickenbach, Frank, Eckhardt Bode, Peter Nunnenkamp, and Mareike Söder (2016) Night lights and regional GDP. Review of World Economics 152(2): 425-447. Bluhm, Richard, and Melanie Krause (2018) Top lights - bright cities and their contribution to economic development. CESifo Working Paper No. 7411. Chen, Xi, and William Nordhaus (2011) Using luminosity data as a proxy for economic statistics. Proceedings of the National Academy of Sciences 108(21): 8589-8594. Chen, Xi, and William Nordhaus (2015) A test of the new VIIRS lights data set: Population and economic output in Africa. Remote Sensing 7(4): 4937-4947. Chen, Xi, and William Nordhaus (2019) VIIRS night time lights in the estimation of cross-sectional and time-series GDP. Remote Sensing 11(9): 1057-1068. Doll, Christopher (2008) CIESIN Thematic Guide to Night-time Light Remote Sensing and its Applications. Center for International Earth Science Information Network, Columbia University, New York Elvidge, Christopher, Kimberly Baugh, Mikhail Zhizhin, and Feng-Chi Hsu (2013) Why VIIRS data are superior to DMSP for mapping night time lights. Proceedings of the Asia-Pacific Advanced Network 35(1): 62-69. Gibson, John, and David McKenzie (2014) The development impact of a best practice seasonal worker policy. Review of Economics and Statistics 96(2): 229-243. Gibson, John, Susan Olivia and Geua Boe-Gibson (2019) Night lights in economics: Sources and uses. Mimeo University of Oxford. Gibson, John, Gaurav Datt, Rinku Murgai and Martin Ravallion (2017) For India’s rural poor, growing towns matter more than growing cities. World Development 98(1): 413-429. Goldblatt, Ran, Kilian Heilmann and Yonatan Vaizman (2019) Can Medium-Resolution Satellite Imagery Measure Economic Activity at Small Geographies? Evidence from Landsat in Vietnam. The World Bank Economic Review. doi.org/10.1093/wber/lhz001 Henderson, Vernon, Adam Storeygard, and David Weil (2012) Measuring economic growth from outer space. American Economic Review 102(2): 994-1028. Hsu, Feng-Chi, Kimberly Baugh, Tilottama Ghosh, Mikhail Zhizhin, and Christopher Elvidge (2015) DMSP-OLS radiance calibrated night-time lights time series with inter-calibration. Remote Sensing 7(2): 1855-1876. Keola, Souknilanh, Magnus Andersson, and Ola Hall (2015) Monitoring economic development from space: Using night time light and land cover data to measure economic growth. World Development 66(1): 322-334. Kocornik-Mina, Adriana, Thomas McDermott, Guy Michaels, and Ferdinand Rauch (2019) Flooded cities. American Economic Journal: Applied Economics (forthcoming). Nordhaus, William. and Xi Chen (2015) A sharper image? Estimates of the precision of night time lights as a proxy for economic statistics. Journal of Economic Geography 15(1): 217-246. Tuttle, Benjamin, Sharolyn Anderson, Chris Elvidge, Tilottama Ghosh, Kim Baugh, and Paul Sutton (2014) Aladdin’s magic lamp: Active target calibration of the DMSP OLS. Remote Sensing 6(12): 12708-12722. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/97582 |