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Spooky Boundaries at a Distance: Exploring Transversality and Stability with Deep Learning

In the long run, we are all dead. Nonetheless, even when investigating short-run dynamics, models require boundary conditions on long-run, forward-looking behavior. In this paper, we show how deep learning approximations can automatically fulfill these conditions.

Exploiting Symmetry in High-Dimensional Dynamic Programming

We provide a new method for solving high-dimensional dynamic programming problems, and recursive competitive equilibria with a large (but finite) number of heterogenous agents.