We introduce deep equilibrium nets (DEQNs)—a deep learning‐based method to compute
approximate functional rational expectations equilibria of economic models featuring a …

Dynamic programming (DP) is a powerful tool for solving a wide class of sequential decision-
making problems under uncertainty. In principle, it enables us to compute optimal decision …

We contrast machine learning (ML) and structural econometrics (SE), focusing on areas
where ML can advance the goals of SE. Our views have been informed and inspired by the …

This article clarifies the connections between certain algorithms to develop artificial
intelligence (AI) and the econometrics of dynamic structural models, with concrete examples …

Can reputation replace legal commitment for an institution making periodic
announcements? Near the limiting case of ideal patience, results of Fudenberg and Levine …

Solving dynamic economic models that capture salient real-world heterogeneity and non-
linearity requires the approximation of high-dimensional functions. As their dimensionality …

I develop a new computational framework called Actively Learned and Informed Equilibrium
Nets (ALIENs) to solve continuous time economic models with endogenous state variables …

Can reputation replace legal commitment for an institution making periodic public
announcements? Near the limiting case of ideal patience, results of Fudenberg and Levine …

The analysis of dynamic economic models routinely leads to the mathematical problem of
determining an unknown function for which no closed-form solution exists. Economists must …

This paper introduces the concept of``self-justified equilibria" as a tractable alternative to
rational expectations equilibria in stochastic general equilibrium models with heterogeneous …