Quasi-Bayes in Latent Variable Models

Fuente: arXiv
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Autor principal: Kankanala, Sid
Formato: Preprint
Publicado: 2023
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author Kankanala, Sid
author_facet Kankanala, Sid
contents Latent variable models are widely used to account for unobserved determinants of economic behavior. This paper introduces a quasi-Bayes approach to nonparametrically estimate a large class of latent variable models. As an application, we model U.S. individual log earnings from the Panel Study of Income Dynamics (PSID) as the sum of latent permanent and transitory components. Simulations illustrate the favorable performance of quasi-Bayes estimators relative to common alternatives.
format Preprint
id arxiv_https___arxiv_org_abs_2311_06831
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Quasi-Bayes in Latent Variable Models
Kankanala, Sid
Econometrics
Methodology
Latent variable models are widely used to account for unobserved determinants of economic behavior. This paper introduces a quasi-Bayes approach to nonparametrically estimate a large class of latent variable models. As an application, we model U.S. individual log earnings from the Panel Study of Income Dynamics (PSID) as the sum of latent permanent and transitory components. Simulations illustrate the favorable performance of quasi-Bayes estimators relative to common alternatives.
title Quasi-Bayes in Latent Variable Models
topic Econometrics
Methodology
url https://arxiv.org/abs/2311.06831