Novel Avenues for Monetary Policy: Insights from Heterogeneous Agent Models

PhD Track master project by Simone Cigna, Isabel Figueiras, Antonio Giribaldi, and Franziska Schwingeler ’22

Editor’s note: This post is part of a series showcasing Barcelona School of Economics master projects. The project is a required component of all BSE Master’s programs.


This literature review focuses on the contribution of the heterogeneous agents framework to the empirical robustness of macroeconomic models. 

First, we focus on the transmission of monetary policy in an economy characterized by heterogeneous agents. We do this by analyzing both the quantitative HANK model and an analytical representation (THANK). 

Secondly, we illustrate the greater suitability of heterogeneous agent models for economic and welfare analysis in a developing country context. 

Finally, we analyze agent-based models as a potential avenue to address a higher degree of heterogeneity and complexity in the data.

HANK and THANK models

We see that the HANK model delivers a more accurate representation of the wealth and consumption distribution of households, but it still lacks important dimensions of household heterogeneity. For instance, the distribution of capital gains is crucial to match the empirical evidence on movements of capital and equity prices. 

The THANK model attempts to give a tractable representation of the HANK model, keeping a certain degree of idiosyncratic uncertainty. Yet, in contrast with the latter, it is not able to address issues related to wealth distribution and welfare.

The challenges of working with macroeconomic simulations

Even with heterogeneous agents, it is unclear whether macroeconomic simulations of the scaling up of micro-evaluations can really do more than making us aware and cautious of forces in general equilibrium that might alter the effects found in RCTs. 

Given the data-challenges in developing countries, the dimension of the informal economy, and in general the immense complexity that remains beyond what is captured in the models, the model predictions might still be inaccurate. 

The introduction of agent-based models attempts to represent more complex and richer economic dynamics. However, this enhancement comes with some drawbacks. First, researchers are left with almost arbitrary freedom in choosing the inputs of the models (e.g., behavioral equations governing agents’ behavior). Second, causal mechanisms in the model are unclear (“black box” critique).

Better models for complex, real-world economies

Despite these challenges, the introduction of the heterogeneous agents’ framework makes macroeconomic models more suitable to capture the complex dynamics in real-world economies.

We conclude that such development in the macroeconomic field is key to enhance the relevance of the models’ policy prescriptions and to improve the ability of their empirical performance.

Connect with the authors

Simone Cigna, Isabel Figueiras, Antonio Giribaldi, and Franziska Schwingeler ’22 are PhD students in Economics in the doctoral program organized jointly by Universitat Pompeu Fabra and the Barcelona School of Economics.

Author info is current as of May 2023.

About the BSE PhD Track Master’s Program