Heterogenous Macro-Finance Model: A Mean-field Game Approach

TL;DR

This paper models the dynamics of capital and wealth among heterogeneous agents in a frictional economy using mean-field game theory, revealing how interactions and constraints influence behaviors during economic cycles.

Contribution

It introduces a mean-field game framework to analyze heterogeneous agent interactions, capturing realistic behaviors in booms and busts without complex numerical methods.

Findings

Experts accumulate capital in good times and reverse quickly in bad times.

Financial friction amplifies mean-field effects, causing capital fire sales.

Heterogeneous groups exhibit slow recovery and FOMO behaviors.

Abstract

We investigate the full dynamics of capital allocation and wealth distribution of heterogeneous agents in a frictional economy during booms and busts using tools from mean-field games. Two groups in our models, namely the expert and the household, are interconnected within and between their classes through the law of capital processes and are bound by financial constraints. Such a mean-field interaction explains why experts accumulate a lot of capital in the good times and reverse their behavior quickly in the bad times even in the absence of aggregate macro-shocks. When common noises from the market are involved, financial friction amplifies the mean-field effect and leads to capital fire sales by experts. In addition, the implicit interlink between and within heterogeneous groups demonstrates the slow economic recovery and characterizes the deviating and fear-of-missing-out (FOMO) behaviors of households compared to their counterparts. Our model also gives a fairly explicit representation of the equilibrium solution without exploiting complicated numerical approaches.