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

Area of Science:

• Remote Sensing
• Geospatial Analysis
• Development Economics

Background:

• Nightlights (NTL) are crucial proxies for economic activity, but historical data (DMSP) have accuracy limitations.
• Newer satellite data (VIIRS) offer improvements but face temporal and spatial integration challenges.
• A novel harmonized NTL dataset (VIIRS + DMSP) provides a consistent, long-term database.

Purpose of the Study:

• To evaluate the predictive power of harmonized NTL data for socio-economic indicators in sub-Saharan Africa.
• To assess NTL accuracy using household wealth data from surveys and administrative records (GDP, HDI).
• To analyze NTL associations with economic activity at the subnational level across 34 countries (2004-2019).

Main Methods:

• Utilized a novel harmonized nightlight dataset (VIIRS + DMSP).
• Analyzed associations between harmonized NTL and subnational economic indicators (Wealth Index, GDP per capita, HDI).
• Controlled for population density in statistical models.

Main Results:

• Harmonized NTL data strongly predict the wealth index, even after controlling for population density.
• The association between NTL and wealth is significant in urban areas, with a less pronounced relationship in rural settings.
• NTL data significantly explain variations in subnational GDP per capita and Human Development Index.

Conclusions:

• The harmonized NTL dataset offers a reliable and consistent measure of economic activity at subnational levels.
• NTL data are valuable tools for understanding socio-economic disparities and development trends in sub-Saharan Africa.
• Future research can leverage this harmonized dataset for more accurate economic activity assessments.