Abstract
ABSTRACT
Bayesian statistics is a framework for combining new data with existing forms of information to yield more precise inferences than are possible using the data alone. Its greatest practical advantages are the flexibility it offers in incorporating prior information and beliefs, modeling heterogeneity, modeling latent constructs, and combining multiple data sources. There are two goals of this paper: to introduce accounting researchers to Bayesian inference and distinguish it from classical frequentist inference and to showcase when Bayesian modeling can improve inferences in many applications that are of interest to accounting researchers.
Data Availability: Data are available from the public sources described in the text.
JEL Classifications: C11; C53; G17; M40.
Publisher
American Accounting Association
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