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The Drivers of Income Inequality in Cities: A Spatial Bayesian Model Averaging Approach


  • Miriam Hortas-Rico
  • Vicente Rios


This study analyzes the drivers of urban income inequality. To that aim, we focus on the case of Spain and derive a novel data set of inequality metrics for a sample of municipalities over the period 2000-2006. Spatial Bayesian Model Averaging techniques are used in order to examine the empirical relevance of a large set of factors taking into account the role of spatial interactions. Our findings suggest that urban inequality is mainly explained by human capital, economic factors and local politics rather than amenities or demography. The results are robust to the use of different spatial functional forms and spatial weight matrices.

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  • Miriam Hortas-Rico & Vicente Rios, 2016. "The Drivers of Income Inequality in Cities: A Spatial Bayesian Model Averaging Approach," Studies on the Spanish Economy eee2016-26, FEDEA.
  • Handle: RePEc:fda:fdaeee:eee2016-26

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    Cited by:

    1. Steel, Mark F. J., 2017. "Model Averaging and its Use in Economics," MPRA Paper 81568, University Library of Munich, Germany.

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