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

Matthias Breuer and Harm H. Schütt
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Harm H. Schütt: Tilburg University

Review of Accounting Studies, 2023, vol. 28, issue 2, No 10, 726-768

Abstract: Abstract 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.

Keywords: Bayes; Prediction; Accruals; Earnings management; Measurement uncertainty (search for similar items in EconPapers)
JEL-codes: C11 C53 M40 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11142-021-09654-0

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