Learning and Equilibrium under Model Misspecification
Theoretical Economics
2026-01-16 v1 Statistics Theory
Statistics Theory
Abstract
This chapter develops a unified framework for studying misspecified learning situations in which agents optimize and update beliefs within an incorrect model of their environment. We review the statistical foundations of learning from misspecified models and extend these insights to environments with endogenous, action-dependent data, including both single agent and strategic settings.
Cite
@article{arxiv.2601.09891,
title = {Learning and Equilibrium under Model Misspecification},
author = {Ignacio Esponda and Demian Pouzo},
journal= {arXiv preprint arXiv:2601.09891},
year = {2026}
}