贝叶斯推理对会计研究有何启示?

IF 2.3 Q2 BUSINESS, FINANCE Journal of Financial Reporting Pub Date : 2023-08-18 DOI:10.2308/jfr-2021-002
H. Schütt
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引用次数: 0

摘要

贝叶斯统计是一个框架,它将新数据与现有形式的信息结合起来,产生比单独使用数据更精确的推断。它最大的实际优势是它在合并先验信息和信念、建模异质性、建模潜在构造和组合多个数据源方面提供的灵活性。本文有两个目标:向会计研究人员介绍贝叶斯推理,并将其与经典的频率推理区分开来,并展示贝叶斯建模何时可以改善会计研究人员感兴趣的许多应用中的推理。数据可用性:数据可从文本中描述的公共来源获得。JEL分类:C11;C53;类型;M40。
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What Can Bayesian Inference Do for Accounting Research?
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.
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来源期刊
Journal of Financial Reporting
Journal of Financial Reporting BUSINESS, FINANCE-
自引率
6.70%
发文量
19
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