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Bias and Measurement Error in Discretionary Accrual Models

Authors: Glen Arthur Hansen;

Bias and Measurement Error in Discretionary Accrual Models

Abstract

This paper examines bias and measurement error in discretionary accrual models. This is important because the empirical evidence supporting the conclusions from many earnings management studies is based entirely on estimates from these models. Models of discretionary accruals are actually models of expected and unexpected accruals. Therefore for most earnings management studies, unexpected accruals that arise for reasons other than managerial discretion over financial reporting represent measurement error in discretionary accruals. This study proposes that unexpected accruals will arise from large structural changes such as acquisitions and divestitures. Since most earnings management studies examine managerial discretion over financial reporting these unexpected accruals represent measurement error. I find that structural changes are associated with the direction and magnitude of discretionary accrual estimates. Also, the measurement error associated with these structural changes is correlated with the level of earnings. Since the level of earnings is often used by researchers to partition earnings management incentives (or is correlated with the partitioning variable). This suggests that the empirical results from many earnings management studies are biased.

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citations
The total number of citations received by all articles of the researcher of interest.
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!
9
Average
Top 10%
Average
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