Mingli Chen, Andreas Joseph, Michael Kumhof, Xinlei Pan, Xuan Zhou
arXiv 19 Apr 2021 · Econometrics · 10 citations (OpenAlex)
arXiv:2104.09368 · PDF · DOI · OpenAlex · Extracted main text
We propose using deep reinforcement learning to solve dynamic stochastic general equilibrium models. Agents are represented by deep artificial neural networks and learn to solve their dynamic optimisation problem by interacting with the model environment, of which they have no a priori knowledge. Deep reinforcement learning offers a flexible yet principled way to model bounded rationality within this general class of models. We apply our proposed approach to a classical model from the adaptive learning literature in macroeconomics which looks at the interaction of monetary and fiscal policy. We find that, contrary to adaptive learning, the artificially intelligent household can solve the model in all policy regimes.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Evans \ Honkapohja (2005) `Policy interaction, expectations and the liquidity trap', Review of Economic Dynamics 8, 303–323 | 1.000 | 5 | 3 | 100% |
| 2 | Haarnoja, Zhou, Abbeel \ Levine (2018) `Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor', arXiv-eprint 1801.01290 | 0.941 | 6 | 4 | 83% |
| 3 | Evans \ Honkapohja (2001) Learning and Expectations in Macroeconomics, Princeton University Press | 0.874 | 5 | 2 | 100% |
| 4 | Benhabib, Schmitt-Grohe \ Uribe (2001) `The perils of taylor rules', Journal of Economic Theory 91, 40–69 | 0.811 | 4 | 2 | 100% |
| 5 | Sutton \ Barto (2018) Reinforcement Learning: An Introduction, second edn, The MIT Press | 0.811 | 4 | 2 | 100% |
| 6 | Sargent (1993) `Bounded rationality in macroeconomics: The arne ryde memorial lectures', OUP Catalogue | 0.811 | 4 | 2 | 100% |
| 7 | Eusepi \ Preston (2018) `The science of monetary policy: An imperfect knowledge perspective', Journal of Economic Literature 56(1), 3–59 | 0.737 | 3 | 2 | 100% |
| 8 | Goodfellow, Bengio, Courville \ Bengio (2016) Deep learning, Vol. 1, MIT press Cambridge | 0.737 | 3 | 2 | 100% |
| 9 | Benhabib, Schmitt-Grohe \ Uribe (2001) `Monetary policy and multiple equilibria', The American Economic Review 96 | 0.644 | 2 | 2 | 100% |
| 10 | Eusepi (2007) `Learnability and monetary policy: A global perspective', Journal of Monetary Economics 54, 1115–1131 | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 23 scored citations.