Planes, Trains, and Automobiles: What Drives Human-Made Light?

Dickinson, Jeffrey (2020): Planes, Trains, and Automobiles: What Drives Human-Made Light?

Abstract

This paper expands on our understanding of the lights-income relationship by linking the newest generation of nighttime satellite images derived from the Visible Infrared Imaging Radiometry Suite, VIIRS, to nationwide, panel data on population and income from 2012-2018 for both Brazil and the United States including 3,104 US counties, and 5,570 munic\'ipios. I leverage the quality and frequency of those data sources and the VIIRS lights images to decompose the links between population changes, GDP changes, and nighttime lights changes at the county and munic\'ipio level. I find decreasing marginal effects of GDP on nighttime light as well as decreasing marginal effects of population on nighttime light, a result which holds across many specifications and that is robust to sub-sample analysis and placebo tests. Interactions among controls also appear to be present. Using sub-sample analysis, I also find that nighttime light does a poor job of capturing less-wealthy areas. Finally, I use a between-county estimator to identify the effects of time-invariant infrastructure features on night-time light. Roads, rail, ports, airports, and border crossings I find to be strong contributors to increases in light.

• Item Type: MPRA Paper
• Language: English
• Keywords: night-time light, GDP, population, infrastructure, regional development
• Subjects: C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C82 - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data ; Data Access; O - Economic Development, Innovation, Technological Change, and Growth > O5 - Economywide Country Studies > O51 - U.S. ; Canada; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R10 - General; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R11 - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R12 - Size and Spatial Distributions of Regional Economic Activity

References

Aysheshim, K., Hinson, J. R., and Panek, S. D. (2020). A primer on local area gross domesticproduct methodology. Survey of Current Business, 100(3):1–13.

Bleakley, H. and Lin, J. (2012). Portage and path dependence. The quarterly journal of economics, 127(2):587–644.11

Carlowicz, M. (2012). Out of the blue and into the black: New views of the earth at night. [Online; posted 5-December-2012].

Chen, X. and Nordhaus, W. D. (2011). Using luminosity data as a proxy for economic statistics. Proceedings of the National Academy of Sciences, 108(21):8589–8594.

Donaldson, D. and Storeygard, A. (2016). The view from above: Applications of satellite datain economics. Journal of Economic Perspectives, 30(4):171–98.

Elvidge, C. D., Baugh, K., Zhizhin, M., Hsu, F. C., and Ghosh, T. (2017). Viirs night-timelights. International Journal of Remote Sensing, 38(21):5860–5879.

Frick, S. A., Rodrıguez-Pose, A., and Wong, M. D. (2019). Toward economically dynamic special economic zones in emerging countries. Economic Geography, 95(1):30–64.

Henderson, J. V., Storeygard, A., and Weil, D. N. (2012). Measuring economic growth fromouter space. American economic review, 102(2):994–1028.

Hodler, R. and Raschky, P. A. (2014). Regional favoritism. The Quarterly Journal of Economics,129(2):995–1033.

Hu, Y. and Yao, J. (2019). Illuminating economic growth. Technical report, InternationalMonetary Fund.

Kocornik-Mina, A., McDermott, T. K., Michaels, G., and Rauch, F. (2020). Flooded cities.American Economic Journal: Applied Economics, 12(2):35–66.

Levin, N. and Zhang, Q. (2017). A global analysis of factors controlling viirs nighttime light levels from densely populated areas.Remote sensing of environment, 190:366–382.

Mellander, C., Lobo, J., Stolarick, K., and Matheson, Z. (2015). Night-time light data: A good proxy measure for economic activity? PloS one, 10(10)