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

• 成果类型: Article
• 署名作者: Breuer, Matthias; Schutt, Harm H.
• 署名单位: Columbia University; Tilburg University
• 刊物名称: REVIEW OF ACCOUNTING STUDIES
• ISSN/ISSBN: 1380-6653
• DOI: 10.1007/s11142-021-09654-0
• 发表日期: 2023
• 页码: 726-768
• 关键词: earnings management; real activities; QUALITY; errors

摘要

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.