Measuring Inequality Using Geospatial Data
研究利用卫星夜间灯光和人口网格数据，构建了1992-2013年234个国家/地区的光基地理空间收入不平等指标，通过校准灯光与繁荣关系匹配传统收入不平等测量，发现该指标与收入不平等显著相关，并应用于健康经济学和国际金融领域。
Abstract 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/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.