Accounting for uncertainty: an application of Bayesian methods to accruals models

We provide an applied introduction to Bayesian estimation methods for empirical accounting research. To showcase the methods, we compare and contrast the estimation of accruals models via a Bayesian approach with the literature’s standard approach. The standard approach takes a given model of normal...

Full description

Saved in:
Bibliographic Details
Published in:Review of accounting studies 2023-06, Vol.28 (2), p.726-768
Main Authors: Breuer, Matthias, Schütt, Harm H.
Format: Article
Language:English
Subjects:
Accounting
Accounting/Auditing
Bayesian analysis
Business and Management
Corporate Finance
Public Finance
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We provide an applied introduction to Bayesian estimation methods for empirical accounting research. To showcase the methods, we compare and contrast the estimation of accruals models via a Bayesian approach with the literature’s standard approach. The standard approach takes a given model of normal accruals for granted and neglects any uncertainty about the model and its parameters. By contrast, our Bayesian approach allows incorporating parameter and model uncertainty into the estimation of normal accruals. This approach can increase power and reduce false positives in tests for opportunistic earnings management as a result of better estimates of normal accruals and more robust inferences. We advocate the greater use of Bayesian methods in accounting research, especially since they can now be easily implemented in popular statistical software packages.
ISSN:1380-6653
1573-7136
DOI:10.1007/s11142-021-09654-0