Working Papers

Evolution of Income Inequality in the U.S.A. : A Calibration Tour of Datasets and Dynamic Models (Job Market Paper)

World Income Database (WID) and Survey of Consumer Finances (SCF) data exhibit different dynamics of fat-tailed income distributions in the U.S.A. In particular, the former dataset suggests much faster tail divergence (extreme growth in the gap between the wealthy and the rest of the population) than the latter. In this work, I show that the latter dataset is coherent with our understanding of economic dynamics, as well as other well known empirical facts about the U.S. Economy. To do so, I start reviewing the WID methodology of data imputation and extrapolation, which mostly uses complicated and computationally demanding continuous-time models. I show that the same patterns for top income inequality can be obtained more conveniently, and with less computational burden, using discrete time methods. Then, I develop a sound and extremely flexible economic model of income inequality and I use it to replicate the dynamics of income inequality as shown in the WID. However, even such a flexible model cannot simultaneously replicate the dynamics of both the body and tail of the income distribution. This is achieved by stipulating different driving parameters for the two parts of the distribution, and the values of calibrated parameters seem quite extreme. My model can, in fact, simultaneously calibrate income distribution body and tail dynamics for the SCF dataset, which exhibits less extreme divergence. This analysis suggests that WID tail divergence is likely exacerbated by the economic theory and the implicit assumptions behind its estimates.


The Evolution of Top Income Inequality in the United States

I develop a discrete time heterogeneous model of income distribution to show that class of models can match empirical evidence about the dynamics of inequality in the United States. While most of the existing literature only calibrates models on empirically observed tail of income distribution, I develop a calibration algorithm that takes advantage of recently released data about the entire distribution of income in the United States. I find that this model is able to match observed dynamics of top income inequality. Also, I find that fiscal policy seems to have limited impact on the performance of this model. At the same time, results suggest this class of simple random growth models that do not account for any form of economic policy changes will work well only in replicating the tail of income distribution.

Inequality, Elections and Redistribution: Structural Differences Between North America and Western Europe

The baseline Political Economy of Voting and Inequality says that countries with high levels of inequality will experience high taxation, which, in turn, is detrimental for economic growth. However, this does not happen when we compare data on inequality, taxation and economic growth between the United States, Northern Europe, and Southern Europe. Southern Europe seems to violate the theory, while the United States seems to follow its predictions closely. I develop an overlapping generations model of voting and inequality where individuals decide the general level of redistribution in one economy. Introducing social preferences allows the model to take into account regional differences in voting results and levels of taxation. I find that societies with Utilitarian social preferences will follow the baseline theory of voting and inequality, while those with Rawlsian social preferences will generally violate it. Countries of Northern and Southern Europe exhibit levels of taxation that are compatible with Rawlsian social preferences.

In Progress

Poverty Kills, But Does Inequality? Why are poor urban communities in unequal countries being hit harder by COVID-19.