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Modelling the Accruals Process and Assessing Unexpected Accruals

Authors: Cheng Y. Lai;

Modelling the Accruals Process and Assessing Unexpected Accruals

Abstract

This paper formalises the accruals process to model both normal and abnormal accruals under clean surplus accounting. Based on theoretically derived abnormal accruals, I assess the ability of unexpected accruals extracted from the empirical Jones-type models in detecting earnings management. These models include the original Jones (1991) model, the modified Jones model developed in Dechow et al. (1995), and the model in Ball and Shivakumar (2006) that incorporates conditional conservatism. My analysis reveals that unexpected accruals from these models generally do not fully reflect abnormal accruals. I show that a plausible explanation for this could be that abnormal and normal accruals are inherently correlated and they cannot be completely disentangled from each other.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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