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VIIRS Nighttime Lights in the Estimation of Cross-Sectional and Time-Series GDP

1
Department of Sociology, Quinnipiac University, Hamden, CT 06518, USA
2
Department of Economics, Yale University, New Haven, CT 06511, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(9), 1057; https://doi.org/10.3390/rs11091057
Received: 9 March 2019 / Revised: 17 April 2019 / Accepted: 24 April 2019 / Published: 5 May 2019
(This article belongs to the Collection Visible Infrared Imaging Radiometers and Applications)
This study extends previous applications of DMSP OLS nighttime lights data to examine the usefulness of newer VIIRS lights in the estimation of economic activity. Focusing on both US states and metropolitan statistical areas (MSAs), we found that the VIIRS lights are more useful in predicting cross-sectional GDP than predicting time-series GDP data. This result is similar to previous findings for DMSP OLS nighttime lights. Additionally, the present analysis shows that high-resolution VIIRS lights provide a better prediction for MSA GDP than for state GDP, which suggests that lights may be more closely related to urban sectors than rural sectors. The results also indicate the importance of considering biases that may arise from different aggregations (the modifiable areal unit problems, MAUP) in applications of nighttime lights in understanding socioeconomic phenomenon. View Full-Text
Keywords: VIIRS light; cross-sectional; time series; GDP; economic statistics VIIRS light; cross-sectional; time series; GDP; economic statistics
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Chen, X.; Nordhaus, W.D. VIIRS Nighttime Lights in the Estimation of Cross-Sectional and Time-Series GDP. Remote Sens. 2019, 11, 1057.

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