Entropy Regularized Belief Reporting

Fuente: arXiv
Saved in:
Bibliographic Details
Main Author: Suleymanov, Elchin
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866909932815646720
author Suleymanov, Elchin
author_facet Suleymanov, Elchin
contents This paper investigates a model of partition dependence, a widely reported experimental finding where the agent's reported beliefs depend on how the states are grouped. In the model, called Entropy Regularized Belief Reporting (ERBR), the agent is endowed with a latent benchmark prior that is unobserved by the analyst. When presented with a partition, the agent reports a prior that minimizes Kullback-Leibler divergence from the latent benchmark prior subject to entropy regularization. This captures the intuition that while the agent would like to report a prior that is close to her latent benchmark prior, she may also have a preference to remain noncommittal. I provide the structural properties of the model that allow for identification of the latent benchmark prior and apply the model to the experimental data from Benjamin et al. (2017).
format Preprint
id arxiv_https___arxiv_org_abs_2506_22649
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Entropy Regularized Belief Reporting
Suleymanov, Elchin
Theoretical Economics
This paper investigates a model of partition dependence, a widely reported experimental finding where the agent's reported beliefs depend on how the states are grouped. In the model, called Entropy Regularized Belief Reporting (ERBR), the agent is endowed with a latent benchmark prior that is unobserved by the analyst. When presented with a partition, the agent reports a prior that minimizes Kullback-Leibler divergence from the latent benchmark prior subject to entropy regularization. This captures the intuition that while the agent would like to report a prior that is close to her latent benchmark prior, she may also have a preference to remain noncommittal. I provide the structural properties of the model that allow for identification of the latent benchmark prior and apply the model to the experimental data from Benjamin et al. (2017).
title Entropy Regularized Belief Reporting
topic Theoretical Economics
url https://arxiv.org/abs/2506.22649