AI and Macroeconomic Modeling: Deep Reinforcement Learning in an RBC Model
Author | : Tohid Atashbar |
Publisher | : International Monetary Fund |
Total Pages | : 31 |
Release | : 2023-02-24 |
ISBN-10 | : 9798400235252 |
ISBN-13 | : |
Rating | : 4/5 (52 Downloads) |
Download or read book AI and Macroeconomic Modeling: Deep Reinforcement Learning in an RBC Model written by Tohid Atashbar and published by International Monetary Fund. This book was released on 2023-02-24 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study seeks to construct a basic reinforcement learning-based AI-macroeconomic simulator. We use a deep RL (DRL) approach (DDPG) in an RBC macroeconomic model. We set up two learning scenarios, one of which is deterministic without the technological shock and the other is stochastic. The objective of the deterministic environment is to compare the learning agent's behavior to a deterministic steady-state scenario. We demonstrate that in both deterministic and stochastic scenarios, the agent's choices are close to their optimal value. We also present cases of unstable learning behaviours. This AI-macro model may be enhanced in future research by adding additional variables or sectors to the model or by incorporating different DRL algorithms.