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Journal of Accounting and Economics Vol. 69 No. 2-3 2020

Using a hidden Markov model to measure earnings quality

Kai Du1,2; Steven J. Huddart2; Lingzhou Xue2; Yifan Zhang2

1 United States Securities and Exchange Commission · 2 Pennsylvania State University

open access

Abstract

We propose and validate a new measure of earnings quality based on a hidden Markov model. This measure, termed earnings fidelity, captures how faithful earnings signals are in revealing the true economic state of the firm. We estimate the measure using a Markov chain Monte Carlo procedure in a Bayesian hierarchical framework that accommodates cross-sectional heterogeneity. Earnings fidelity is positively associated with the forward earnings response coefficient. It significantly outperforms existing measures of quality in predicting two external indicators of low-quality accounting: restatements and Securities and Exchange Commission comment letters.

DOI
10.1016/j.jacceco.2019.101281
Volume
69
Issue
2-3
Pages
101281
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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