Deep Equilibrium Nets

80 Pages Posted: 10 Jun 2019 Last revised: 20 Jul 2021

See all articles by Marlon Azinovic

Marlon Azinovic

University of Zurich

Luca Gaegauf

University of Zurich

Simon Scheidegger

University of Lausanne - School of Economics and Business Administration (HEC-Lausanne)

Date Written: May 24, 2019

Abstract

We introduce deep equilibrium nets---a deep learning-based method to compute approximate functional rational expectations equilibria of economic models featuring a substantial amount of heterogeneity, significant uncertainty, and occasionally binding constraints.
Deep equilibrium nets are neural networks that directly approximate all equilibrium functions and that are trained in an unsupervised fashion to satisfy all equilibrium conditions along simulated paths of the economy. Since the neural network approximates the equilibrium functions directly, simulating the economy is computationally cheap, and training data can be generated at virtually zero cost.
We demonstrate that deep equilibrium nets can solve rich and economically relevant models accurately by applying them to solve three different models, all featuring a very high-dimensional state space. Specifically, we solve two overlapping generations models with aggregate and idiosyncratic uncertainty, illiquid capital, a one-period bond, and occasionally binding constraints. Additionally, we solve a Bewley-style model with a continuum of agents, aggregate and idiosyncratic risk, borrowing constraints, and recursive preferences.

Keywords: computational economics, deep learning, deep neural networks, global solution method, life-cycle, occasionally binding constraints, overlapping generations

JEL Classification: C61, C63, C68, E21

Suggested Citation

Azinovic, Marlon and Gaegauf, Luca and Scheidegger, Simon, Deep Equilibrium Nets (May 24, 2019). Available at SSRN: https://ssrn.com/abstract=3393482 or http://dx.doi.org/10.2139/ssrn.3393482

Marlon Azinovic

University of Zurich ( email )

Rämistrasse 71
Zürich, CH-8006
Switzerland

Luca Gaegauf

University of Zurich ( email )

Rämistrasse 71
Zürich, CH-8006
Switzerland

Simon Scheidegger (Contact Author)

University of Lausanne - School of Economics and Business Administration (HEC-Lausanne) ( email )

Unil Dorigny, Batiment Internef
Lausanne, 1015
Switzerland

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