Journal Articles


Lessmann, C. and A. Seidel (2017): Regional inequality, convergence, and its determinants – A view from outer space, European Economic Review 92, 110-132.

Abstract: This paper provides a new dataset of regional income inequalities within countries based on satellite nighttime light data. First, we empirically study the relationship between luminosity data and regional incomes for those countries for which regional income data are available. Second, we use our estimation results for an out-of-sample prediction of regional incomes based on the luminosity data. These results enable us to investigate regional income differentials in developing countries that lack official income data. Third, we calculate commonly used measures of regional inequality within countries based on predicted incomes. An investigation of changes in the dispersion of regional incomes over time reveals that approximately 67-70% of all countries experience sigma-convergence. Forth, we study different major determinants of within-country changes in inequality, i.e., the determinants of the convergence process. We find evidence for an N-shaped relationship between development and regional inequality. Resources, mobility, trade openness, aid, federalism and human capital are also very important.


The complete data set on regional inequalities could be downloaded at the datorium of gesis - Leibniz Institute of the Social Sciences.



Working Papers


Lessmann, C. and A. Steinkraus (2017): The geography of natural resources, ethnic inequality and development, CESifo Working Paper No. 6302.

Abstract: We study whether the spatial distribution of natural resources across different ethnic groups within countries impede spatial inequality, national economic performance, and the incidence of armed conflict. By providing a theoretical rent-seeking model and analysing a set of geo-coded data for mines, night-time light emissions, local populations and ethnic homelands, we show that the distribution of resources is a major driving factor of ethnic income inequality and, thus, induces rent-seeking behaviour. Consequently, we extend the perspective of the resource curse to explain cross-country differences in economic performance and the onset of civil conflicts. We show that the inequality in the spatial distribution of resource endowments within countries drives the curse of natural resources, not the resources per se.


Bluhm, R. and M. Krause (2016): Top lights – Bright spots and their contribution to economic development, mimeo, University of Hanover and Hamburg University

Abstract: Satellite data on nighttime luminosity are an increasingly popular proxy for economic activity, but their utility for analyzing comparative development across the globe is severely limited by top-coding. The commonly used satellites do not accurately capture the brightness of large and densely populated cities. As a result, they underestimate differences between urban and rural regions, as well as developed and developing countries. Our main contribution is to propose a new and easy-to-use procedure to correct for top-coding of the lights data. We show that, like top incomes, top lights are Pareto distributed. On this basis, we derive simple formulas for the top-adjusted mean and spatial Gini coefficient. Furthermore, we develop simulation methods to correct the data at the pixel level. Our top-coding correction raises the worldwide Gini coefficient of spatial inequality in lights by about 9 percentage points. This rather large increase underlines the importance of big cities for global economic activity. We present further applications to show that top-coding affects estimates of the income elasticity of light, urban-rural differences, and regional or ethnic inequalities.


Bluhm, R. and M. H. L. Wong (2017): Neighborhood disputes? Spatial inequalities and civil conflict in Africa, mimeo, University of Hanover.

Abstract: High levels of spatial inequality are associated with slow growth and civil conflict in developing countries, yet we know very little about whether these findings are driven by localized tensions or nation-wide grievances. In this paper we develop novel measures of local spatial inequalities which can be applied to neighborhoods of varying sizes. Using geographic information systems, we use these measures to capture economic differences between neighboring ethnic groups and administrative regions in Africa. We show that greater ethnic inequalities are robustly associated with a higher propensity of experiencing civil conflict within a particular region, while spatial inequalities among first-level administrative regions are not. Interestingly, once comparisons include groups living further away this association strengthens, while reducing the size of the neighborhood often weakens the estimated effect. We also show that the effect of local between-group inequality on conflict varies with the historical formation of language groups.




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