Publication: Deep Equilibrium Nets
Deep Equilibrium Nets
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Azinovic, M., Gaegauf, L., & Scheidegger, S. (2022). Deep Equilibrium Nets. International Economic Review, 63(4), 1471–1525. https://doi.org/10.1111/iere.12575
Abstract
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Abstract
We introduce deep equilibrium nets (DEQNs)—a deep learning‐based method to compute approximate functional rational expectations equilibria of economic models featuring a significant amount of heterogeneity, uncertainty, and occasionally binding constraints. DEQNs are neural networks trained in an unsupervised fashion to satisfy all equilibrium conditions along simulated paths of the economy. Since DEQNs approximate the equilibrium functions directly, simulating the economy is computationally cheap, and training data can be generated a
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- Azinovic, Marlon
- Gaegauf, Luca
- Scheidegger, Simon
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Azinovic, M., Gaegauf, L., & Scheidegger, S. (2022). Deep Equilibrium Nets. International Economic Review, 63(4), 1471–1525. https://doi.org/10.1111/iere.12575
