Financial Frictions and the Wealth Distribution

Abstract

This paper investigates how, in a heterogeneous agents model with financial frictions, idiosyncratic individual shocks interact with exogenous aggregate shocks to generate time-varying levels of leverage and endogenous aggregate risk. To do so, we show how such a model can be efficiently computed, despite its substantial nonlinearities, using tools from machine learning. We also illustrate how the model can be structurally estimated with a likelihood function, using tools from inference with diffusions. We document, first, the strong nonlinearities created by financial frictions. Second, we report the existence of multiple stochastic steady states with properties that differ from the deterministic steady state along important dimensions. Third, we illustrate how the generalized impulse response functions of the model are highly state-dependent. In particular, we find that the recovery after a negative aggregate shock is more sluggish when the economy is more leveraged. Fourth, we prove that wealth heterogeneity matters in this economy because of the asymmetric responses of household consumption decisions to aggregate shocks.

Keywords: Aggregate shocks, continuous-time, Heterogeneous Agents, Machine Learning, structural estimation

JEL Classification: C45, C63, E32, E44, G01, G11