How agent-based models powered by HPC are enabling large scale economic simulations

The article discusses how agent-based models (ABMs) powered by high-performance computing (HPC) are enabling large-scale economic simulations, particularly for analyzing the effects of macroprudential policies. Macroprudential policies aim to mitigate systemic risks in the financial system.

Specifically, the article covers:

• The limitations of traditional economic models like DSGE in capturing agent heterogeneity and complex interactions
• An overview of ABMs and their ability to model diverse agents and emergent behaviors
• A case study on using ABMs to study the impact of macroprudential policies on the Polish economy, conducted by researchers from Oxford University and AWS
• The AWS cloud architecture used for running the ABM simulations, leveraging services like AWS Batch, ECS, EC2, and S3
• Key simulation results showing the redistributive effects of macroprudential policies across different income groups
• Potential future applications and developments of ABMs, such as expanding to other economic sectors and integrating with other modeling approaches