Shedding light on development: Leveraging the new nightlights data to measure economic progress

被引:0
|
作者
Jhamb, Prachi [1 ]
Ferreira, Susana [1 ]
Stephens, Patrick [2 ]
Sundaram, Mekala [3 ]
Wilson, Jonathan [4 ]
机构
[1] Univ Georgia, Dept Agr & Appl Econ, Athens, GA 30605 USA
[2] Oklahoma State Univ, Integrat Biol, Stillwater, OK USA
[3] Univ Georgia, Dept Infect Dis, Athens, GA USA
[4] Univ Georgia, Dept Pathol, Athens, GA USA
来源
PLOS ONE | 2025年 / 20卷 / 02期
基金
美国国家卫生研究院;
关键词
NIGHTTIME LIGHT; POVERTY;
D O I
10.1371/journal.pone.0318482
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Nightlights (NTL) have been widely used as a proxy for economic activity, despite known limitations in accuracy and comparability, particularly with outdated Defense Meteorological Satellite Program (DMSP) data. The emergence of newer and more precise Visible Infrared Imaging Radiometer Suite (VIIRS) data offers potential, yet challenges persist due to temporal and spatial disparities between the two datasets. Addressing this, we employ a novel harmonized NTL dataset (VIIRS + DMSP), which provides the longest and most consistent database available to date. We evaluate the association between newly available harmonized NTL data and various indicators of economic activity at the subnational level across 34 countries in sub-Saharan Africa from 2004 to 2019. Specifically, we analyze the accuracy of the new NTL data in predicting socio-economic outcomes obtained from two sources: 1) nationally representative surveys, i.e., the household Wealth Index published by Demographic and Health Surveys, and 2) indicators derived from administrative records such as the gridded Human Development Index and Gross Domestic Product per capita. Our findings suggest that even after controlling for population density, the harmonized NTL remain a strong predictor of the wealth index. However, while urban areas show a notable association between harmonized NTL and the wealth index, this relationship is less pronounced in rural areas. Furthermore, we observe that NTL can also significantly explain variations in both GDP per capita and HDI at subnational levels.
引用
收藏
页数:19
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