Consumption

Deep learning methods for solving dynamic economic models offer computational advantages but produce ‘black box’ solutions. This paper develops Economics Informed Neural Networks (EINNs) through a generalized method of moderation that embeds behavioral bounds directly into neural network architectures.

Consumer spending lies between pessimistic and optimistic extremes. This paper uses that fact to redefine the search space for optimal consumption rules.