Measuring Inequality Using Geospatial Data
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Published by Oxford University Press on behalf of the World Bank
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The main challenge in studying
inequality is limited data availability, which is
particularly problematic in developing countries. This study
constructs a measure of light-based geospatial income
inequality (LGII) for 234 countries and 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. The
new LGII measure is significantly correlated with
cross-country variation in income inequality. Within
countries, the light-based inequality measure is also
correlated with measures of energy efficiency and the
quality of population data. Two applications of the data are
provided in the fields of health economics and international
finance. The results show that light- and income-based
inequality measures lead to similar results, but the
geospatial data offer a significant expansion of the number
of observations.
Palabras clave
NIGHTTIME LIGHTS, INEQUALITY, GRIDDED POPULATION
