EconPapers    
Economics at your fingertips  
 

A Response to "Critique of an Article on Machine Learning in the Detection of Accounting Fraud"

Yang Bao, Bin Ke, Bin Li, Y. Julia Yu and Jie Zhang

Econ Journal Watch, 2021, vol. 18, issue 1, 71–78

Abstract: Stephen Walker (2021) raises two empirical issues about our article in the Journal of Accounting Research (Bao, Ke, Li, Yu, and Zhang 2020). The first one is about our treatment of missing values for the raw financial statement variables. The second one is about our treatment of serial fraud. Walker (2021) suggests an alternative approach to dealing with serial fraud and claims that inferences change significantly if his approach is adopted. We reexamine the impact of the two issues on our inferences and find no evidence that these two issues alter our paper’s inferences.

JEL-codes: C53 M41 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://econjwatch.org/File+download/1184/BaoEtAlMar2021.pdf?mimetype=pdf (application/pdf)
https://econjwatch.org/1232 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ejw:journl:v:18:y:2021:i:1:p:71-78

Access Statistics for this article

Econ Journal Watch is currently edited by Daniel Klein

More articles in Econ Journal Watch from Econ Journal Watch Contact information at EDIRC.
Bibliographic data for series maintained by Jason Briggeman ().

 
Page updated 2025-03-19
Handle: RePEc:ejw:journl:v:18:y:2021:i:1:p:71-78