Jesus Fernandez Villaverde - University of Pennsylvania
“Financial Frictions and the Wealth Distribution”
Jesus Fernandez Villaverde
University of Pennsylvania, NBER, and CEPR
We postulate a nonlinear DSGE model with a financial sector and heterogeneous households.
In our model, the interaction between the supply of bonds by the financial sector
and the precautionary demand for bonds by households produces significant endogenous
aggregate risk. This risk induces an endogenous regime-switching process for output, the
risk-free rate, excess returns, debt, and leverage. The regime-switching generates i) multimodal
distributions of the variables above; ii) time-varying levels of volatility and skewness
for the same variables; and iii) super cycles of borrowing and deleveraging. All of these are
important properties of the data. In comparison, the representative household version of
the model cannot generate any of these features. Methodologically, we discuss how nonlinear
DSGE models with heterogeneous agents can be efficiently computed using machine
learning and how they can be estimated with a likelihood function, using inference with
diffusions.
Keywords: Heterogeneous agents; wealth distribution; financial frictions; continuous time;
machine learning; neural networks; structural estimation