Shining (New) Light on Regional Inequality, Convergence and Development

点击翻译按钮获取中文摘要

Rapid economic growth in emerging and developing countries brought down global income inequality over the last decades, but also spurred increasing regional inequalities within countries. Uneven growth implies that not all geographic regions or ethnicities benefit equally from growing prosperity and global integration at the country level. The resulting interregional differences can have profound interactions with society and politics, in particular when they are associated with distributional disputes or civil conflict. Hence, understanding the level, the evolution and the causes of spatial inequalities are important research areas to which this project contributes.The proposed project breaks new ground in analyzing regional inequalities and regional development across the globe. While previous studies were constrained by the limited availability of reliable regional accounts (which are usually only available in richer countries with high statistical capacity), our project works with satellite data of nighttime luminosity instead. Night lights have proved to be a reliable indicator of economic activity at the local level. Put simply, regions with a higher income per capita look brighter from outer space (e.g. see Henderson et al. 2012). Satellite data have many advantages: they cover the whole world, are objective and comparable across regions. Thanks to the high resolution of the raster data, they can also be flexibly aggregated and thus free us from the confines of administrative regions.The project analyses regional inequality, regional convergence and their root causes using satellite data on nighttime luminosity. It consists of three related research questions that are to be studied jointly in Hannover, Hamburg and Braunschweig. i) The first challenge is the construction of a consistent data set of nighttime luminosity and light inequality at different spatial resolutions. The task involves developing procedures to correct measurement errors, studying suitable inequality measures, and examining how the level of spatial aggregation influences the results. A key goal is to establish a best-practice standard for users of the lights data and to facilitate its adoption by the broader community. ii) The new data will then be used to investigate regional convergence within countries. The aim is to identify growth clusters using a new spatially explicit measure of club-convergence and describe their success strategies. iii) Finally, whether regions converge and inequalities decline ultimately depends on geographical, social and political economy factors. Our new data put us in a position to rephrase the so-called Geography Hypothesis. We conjecture that exogenous geographical factors determine regional inequalities, which in turn have negative repercussions on national development. Special attention will be paid to the role of political institutions, which are likely to mitigate the influence of regional inequalities on development.