Measuring Inequality using Geospatial Data
Jaqueson Galimberti (),
Stefan Pichler () and
Regina Pleninger ()
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Regina Pleninger: ETH Zurich, Switzerland
No 21-493, KOF Working papers from KOF Swiss Economic Institute, ETH Zurich
The main challenge in studying economic inequality is limited data availability, which is particularly problematic in developing countries. We construct a measure of economic inequality for 234 countries/territories from 1992 to 2013 using satellite data on night lights and gridded population data. Key methodological innovations include the use of varying levels of data aggregation, and a calibration of the lights-prosperity relationship to match traditional inequality measures based on income data. We obtain a measure that is significantly correlated with cross-country variation in income inequality. We provide three applications of the data in the fields of health economics and international finance. Our results show that light- and income-based inequality measures lead to similar results in terms of cross-country correlations, but not for the dynamics of inequality within countries. Namely, we find that the light-based inequality measure can capture more enduring features of economic activity that are not directly captured by income.
Keywords: : Nighttime lights; inequality; gridded population (search for similar items in EconPapers)
JEL-codes: D63 E01 I14 O11 O47 O57 (search for similar items in EconPapers)
Pages: 56 pages
New Economics Papers: this item is included in nep-big, nep-geo and nep-mac
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Working Paper: Measuring Inequality using Geospatial Data (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:kof:wpskof:21-493
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