Nighttime Lights and County-Level Economic Activity in the United States: 2001 to 2019

John Gibson,Geua Boe-Gibson

doi:10.3390/rs13142741

Abstract

Nighttime lights (NTL) are a popular type of data for evaluating economic performance of regions and economic impacts of various shocks and interventions. Several validation studies use traditional statistics on economic activity like national or regional gross domestic product (GDP) as a benchmark to evaluate the usefulness of NTL data. Many of these studies rely on dated and imprecise Defense Meteorological Satellite Program (DMSP) data and use aggregated units such as nation-states or the first sub-national level. However, applied researchers who draw support from validation studies to justify their use of NTL data as a proxy for economic activity increasingly focus on smaller and lower level spatial units. This study uses a 2001–19 time-series of GDP for over 3100 U.S. counties as a benchmark to examine the performance of the recently released version 2 VIIRS nighttime lights (V.2 VNL) products as proxies for local economic activity. Contrasts were made between cross-sectional predictions for GDP differences between areas and time-series predictions of GDP changes within areas. Disaggregated GDP data for various industries were used to examine the types of economic activity best proxied by NTL data. Comparisons were also made with the predictive performance of earlier NTL data products and at different levels of spatial aggregation.

Highlights

Satellites have been observing the Earth at night for over 50 years, but it is especially since the digital archive of nighttime lights (NTL) was established in 1992 by the NationalOceanic and Atmospheric Administration (NOAA) that researchers have found an evergrowing set of use for these data
We started with country-level results for a comparison to a key study that found a GDPlights elasticity of 0.3 using the within estimator and Defense Meteorological Satellite Program (DMSP) data [7]
Unlike the country-level results in Table 1, which are subject to wide variation in statistical capacity between countries that make some gross domestic product (GDP) data more trustworthy than others, we considered that county-level GDP data produced by the Bureau of Economic Analysis (BEA) will provide a consistent level of reliability over time and space

Summary

Introduction

Satellites have been observing the Earth at night for over 50 years, but it is especially since the digital archive of nighttime lights (NTL) was established in 1992 by the NationalOceanic and Atmospheric Administration (NOAA) that researchers have found an evergrowing set of use for these data. Several key early studies by non-economists showed that NTL data from the Defense Meteorological Satellite Program (DMSP) could be used to estimate sub-national indicators of economic activity and per capita incomes [1,2,3,4,5]. In contrast to earlier studies focused on comparing regions, a theme in recent studies by economists is using NTL data to track fluctuations in local economic activity in response to various shocks such as disasters [10,11,12], or certain policy interventions [13,14]. This use of NTL as a proxy for changes in local economic activity, plus ongoing cross-sectional use as a proxy for variation in economic performance, raises the question of how predictive NTL data are for studying differences in economic activity between areas and the temporal changes in activity within areas

Methods

Results

Discussion

Conclusion