On the computation of heterogeneous agent models and its applications

This thesis has two parts, each with a different subject. Part 1 studies the macroeconomic implications of alternative health care reforms. Part 2 studies the computation and simulation of dynamic competitive equilibria in models with heterogeneous agents and market frictions.;In 2007, 44.5 million non-elderly in the U.S did not have health insurance coverage. Empirical studies suggest that there are serious negative consequences associated with uninsurance. Consequently, there is wide agreement that reforming the current health care system is desirable and several proposals have been discussed among economists and in the political arena. However, little attention has been paid to quantify the macroeconomic consequences of reforming the health insurance system in the U.S. The objective of this section is to develop a theoretical framework to evaluate a broad set of health care reform plans. I build a model that is capable of reproducing a set of key facts of health expenditure and insurance demand patterns, as well as key macroeconomic conditions of the U.S. during the last decade. Then, I use this model to derive the macroeconomic implications of alternative reforms and alternative ways of funding these reforms.;The second part of this thesis studies the computation and simulation of dynamic competitive equilibria in models with heterogeneous agents and market frictions. This type of models have been of considerable interest in macroeconomics and finance to analyze the effects of various macroeconomic policies, the evolution of wealth and income distribution, and the variability of asset prices. However, there is no reliable algorithm available to compute their equilibria. We develop a theoretical framework for the computation and simulation of dynamic competitive markets economies with heterogeneous agents and market frictions. We apply these methods to some macroeconomic models and find important improvements over traditional methods.