Inequality and economic growth: Evidence from Argentina's provinces using spatial econometrics

This dissertation analyzes whether or not the spatial distribution of inequality in the provinces of Argentina affects real per capita economic growth. The primary objective is to decouple the effect of inequality into within inequality, which is the own province i level of inequality, and the spillover of inequality from the closest provinces to province i. Furthermore, another important objective is to decouple the influence of inequality into long-run and short-run effect.;To accomplish this, I based the analysis on a framework used by Partridge (2005), which starts considering a very simple model, called a "parsimonious" model with a few key variables. Building on that simple model I started adding a set of important control variables in order to get a more fully specified model, called "base" model. The main idea of using this methodology is that the "parsimonious" models, with only a few variables (income distribution and a few other control variables), not only reduces multicollinearity but also it is a test for robustness in the relationship between inequality and growth (Perotti, 1996; Panizza, 2002; Partridge, 2005).;In addition, following Partridge (2005), I considered that income distribution might have an entirely separate effect at the middle versus the tails of the distribution. Therefore, I decided to include the Gini that controls for the overall distribution, and the third Quantile share (Q3) that controls for middle-class consensus and the role of the median voter. The purpose of having two variables of income distribution is that when the Q3 is included in the model, the Gini controls for the overall distribution, especially at the tails, while Q3 controls for middle-class consensus and the role of the median voter.;Additionally, a key difference from Partridge (2005) framework, apart from the decoupled effect of inequality into within inequality, which is the own province i level of inequality, and the spillover of inequality from the closest provinces to province i, is the explicit consideration of possible spatial autocorrelation in the models. To achieve this, I used two of the simplest spatial specifications: the spatial lag and spatial error models.;In the dissertation I have found very robust evidence that the own province i inequality, and the inequality of the neighboring provinces of province i, affects negatively the economics growth of the provinces of Argentina in the period 1991-2002. Morerover, I have also found robust evidence that the third Quantile (Q3) affects negatively the economics growth, which is not consistent to the vibrancy of the middle class. The overall pattern of my results are not consistent with a long-run classical/incentive interpretation but to a political economy interpretation, in which the distortionary redistribution policies and social or political conflict are generated by the difference in inequality among provinces.