Measuring and Explaining Patterns of Spatial Income Inequality from Outer Space: Evidence from Africa

Anthony Mveyange

doi:10.1596/1813-9450-8484

Abstract

This paper argues for night--lights data as an alternative data source for measuring spatial inequalities in Africa, where the paucity of subnational income data is persistent. The analysis compares the statistical relationships between income and lights-based measures of spatial income inequality in South Africa and shows that night-lights are a decent proxy for spatial income inequality. Further analysis of the patterns of lights-based spatial income inequality across 48 countries in Africa broadly reveals rising patterns between 1992 and 2013. Following the climate-economy literature, the analysis also reveals that temperature and precipitation changes significantly increased spatial inequality in the long-run and the effects penetrated through income and agriculture channels across countries in the continent. These findings provide important lessons for policy discussions about how to measure, explain the patterns of, and mitigate the potential drivers of spatial inequality in Africa.

Highlights

Increasing gaps in spatial income inequality are likely to undo the economic growth benefits that Africa has enjoyed in recent years
The gaps can negatively affect the economic and political wellbeing of countries (Kim, 2008), in addition to potentially dwarfing the prospects for successful implementation of the structural transformation strategies that Africa has championed in recent years (OECD, 2015)
I begin the analysis with a closer look at the relationship between income and lights–based inequality measures using data from South Africa

Summary

Introduction

Increasing gaps in spatial income inequality are likely to undo the economic growth benefits that Africa has enjoyed in recent years. The gaps can negatively affect the economic and political wellbeing of countries (Kim, 2008), in addition to potentially dwarfing the prospects for successful implementation of the structural transformation strategies that Africa has championed in recent years (OECD, 2015). While these widening gaps have had, and continue to receive, a considerable amount of attention in Africa (OECD, 2015), measuring and explaining spatial inequality has remained elusive. While measuring and explaining spatial inequality is important, the resounding question that remains unanswered for Africa is how we can credibly measure and explain the patterns of spatial inequality amid lingering data challenges

Results

Discussion

Conclusion