Learning and Equilibrium under Model Misspecification

Fuente: arXiv
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Main Authors: Esponda, Ignacio, Pouzo, Demian
Format: Preprint
Published: 2026
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author Esponda, Ignacio
Pouzo, Demian
author_facet Esponda, Ignacio
Pouzo, Demian
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2601_09891
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Learning and Equilibrium under Model Misspecification
Esponda, Ignacio
Pouzo, Demian
Theoretical Economics
Statistics Theory
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.
title Learning and Equilibrium under Model Misspecification
topic Theoretical Economics
Statistics Theory
url https://arxiv.org/abs/2601.09891