Inference-in-residuals as an Estimation Method for Earnings Management

Christodoulou, D; Ma, L; Vasnev, A

Inference-in-residuals as an Estimation Method for Earnings Management

Christodoulou, D Ma, L

Vasnev, A

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Publication Type:: Journal Article
Citation:: Abacus, 2018, 54 (2), pp. 154 - 180
Issue Date:: 2018-06-01

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Field	Value	Language
dc.contributor.author	Christodoulou, D	en_US
dc.contributor.author	Ma, L https://orcid.org/0000-0003-1115-5051	en_US
dc.contributor.author	Vasnev, A	en_US
dc.date.issued	2018-06-01	en_US
dc.identifier.citation	Abacus, 2018, 54 (2), pp. 154 - 180	en_US
dc.identifier.issn	0001-3072	en_US
dc.identifier.uri	http://hdl.handle.net/10453/130418
dc.description.abstract	© 2018 Accounting Foundation, The University of Sydney The paper tests the assumptions underlying the inference-in-residuals method as an estimation framework for detecting and classifying suspects of earnings management. We derive several systematic biases that are shown to confound inference-in-residuals and, depending on the data, could render the method a futile exercise. This is not a matter of model specification, but a limitation of the statistical method. Also, it is shown that the method of using estimated residuals in a second stage regression on economic determinants of earnings management suffers considerably, especially when residuals are estimated by industry classification in the first stage.	en_US
dc.relation.ispartof	Abacus	en_US
dc.relation.isbasedon	10.1111/abac.12121	en_US
dc.subject.classification	Accounting	en_US
dc.title	Inference-in-residuals as an Estimation Method for Earnings Management	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	54	en_US
utslib.for	1501 Accounting, Auditing and Accountability	en_US
utslib.for	1502 Banking, Finance and Investment	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Accounting Discipline
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	54	en_US

Abstract:

© 2018 Accounting Foundation, The University of Sydney The paper tests the assumptions underlying the inference-in-residuals method as an estimation framework for detecting and classifying suspects of earnings management. We derive several systematic biases that are shown to confound inference-in-residuals and, depending on the data, could render the method a futile exercise. This is not a matter of model specification, but a limitation of the statistical method. Also, it is shown that the method of using estimated residuals in a second stage regression on economic determinants of earnings management suffers considerably, especially when residuals are estimated by industry classification in the first stage.

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http://hdl.handle.net/10453/130418