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

Abstract We provide an applied introduction to Bayesian estimation methods for empirical accounting research. To showcase the methods, we compare and contrast of accruals models via a approach with literature’s standard approach. The takes given model normal granted neglects any uncertainty about its parameters. By contrast, our allows incorporating parameter into accruals. This can increase power reduce false positives in tests opportunistic earnings management as result better estimates more robust inferences. advocate greater use research, especially since they now be easily implemented popular statistical software packages.