Using a Hidden Markov Model to Measure Earnings Quality

Journal of Accounting and Economics, Forthcoming

57 Pages Posted: 8 May 2018 Last revised: 22 Dec 2019

See all articles by Kai Du

Kai Du

Pennsylvania State University - Department of Accounting

Steven J. Huddart

Pennsylvania State University, University Park - Department of Accounting

Lingzhou Xue

Pennsylvania State University - Department of Statistics

Yifan Zhang

Pennsylvania State University - Department of Marketing

Date Written: October 1, 2019

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.

Keywords: Hidden Markov model; Bayesian hierarchical framework; MCMC methods; Earnings quality; Earnings fidelity

JEL Classification: C11, C13, M41, M43

Suggested Citation

Du, Kai and Huddart, Steven J. and Xue, Lingzhou and Zhang, Yifan, Using a Hidden Markov Model to Measure Earnings Quality (October 1, 2019). Journal of Accounting and Economics, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3166423 or http://dx.doi.org/10.2139/ssrn.3166423

Kai Du (Contact Author)

Pennsylvania State University - Department of Accounting ( email )

University Park, PA 16802-3306
United States

HOME PAGE: http://directory.smeal.psu.edu/kxd30

Steven J. Huddart

Pennsylvania State University, University Park - Department of Accounting ( email )

University Park, PA 16802-3603
United States
814-863-0448 (Phone)

HOME PAGE: http://directory.smeal.psu.edu/sjh11

Lingzhou Xue

Pennsylvania State University - Department of Statistics ( email )

326 Thomas Building
University Park, PA 16802
United States

Yifan Zhang

Pennsylvania State University - Department of Marketing ( email )

University Park, PA 16802-3306
United States

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