Spatial Inequality in Latin America (1895–2010): Convergence and Clusters in a Long-Run Approach

Economic development in Latin America from the end of the nineteenth century shows highly diverse patterns across countries and periods. Argentina, for instance, experienced rapid growth until World War I, following an export-led model, and a relative decline afterwards, whereas economic growth in Brazil and Mexico was faster in the second half of the twentieth century, in both cases driven by state-led industrialization policies. Others as Chile and Peru were blessed with different mining cycles, while experienced industrialization expansion led by the state at mid-twentieth century. In this chapter, benefiting from the work done in the previous chapters, we provide a first attempt to analyse regional growth (at a subnational level), emphasizing the interaction between first- and second-nature forces, namely the localization of natural resources, trade policies, agglomeration forces and economic policies in shaping the regional income inequality of Latin American countries from the end of the nineteenth and twentieth centuries. Following the work done by Badia-Miró et al. (Journal of Interdisciplinary History, 49(1), 117–139, 2018), we will test existence of sigma and beta convergence, and the evolution of the Theil index and its decomposition. Finally, we check statistically the existence of a group of richer or poorer regions, considering spatial clustering analysis. To do that we run a simple test to obtain local Moran’s I coefficient for all the regions, which consider a statistical relationship between the regional income per capita of any region and its neighbourhood. We are especially interested in detecting the existence of this groups across national borders and its persistence in the long run, according to the changes in commodity cycles, industrial and trade policies and regional integration. Besides, we are also interested in the role played by the administrative capitals of the countries and the economic linkages to neighbouring regions.