Spatial Gini coefficient of countries along the Belt and the Road based on night light data (2017 national scale)

Based on the night light data from remote sensing, the research group used the method of Elvidge in 2009 and 2012 to reverse the incidence of poverty in the countries along the belt and the road. This data is comparable with Gini coefficient published by the World Bank and has the following four prominent advantages: (1) Computing units can be adjusted according to administrative boundaries, reflecting poverty disparities on the sub-regional scale of large countries that are difficult to achieve using statistic data; (2) The spatial Gini coefficient estimated based on night light data is less affected by subjective factors such as survey process, and is comparatively small. Objectively, and the comparability between countries is strong, which overcomes the difficult problem of unification between statistical calibers; (3) The survey and summary cycle limits the update speed at national and large sub-regional scales, while the method based on night light data estimation is convenient to update. (4) Night light data have many years of continuous interannual data from 1992 to 2017, which overcomes the difficulty of obtaining long time series indicators of poverty, such as the gap between the rich and the poor. In view of the above four outstanding advantages, the set of data can better support the research work and provide scientific data for finding out the basic situation of poverty along the "The Belt and the Road".