Discussion of “another look at GAAP versus the Street: an empirical assessment of measurement error bias”

Discussion of “another look at GAAP versus the Street: an empirical assessment of measurement... Cohen, Hann, and Ogneva [(2007) Review of Accounting Studies, Forthcoming] provide evidence on how measurement error affects inferences this literature. In particular, they provide a theoretical framework for understanding (1) the source of differences in market reactions to GAAP and Street earnings and (2) why we observe a divergence over time between ERCs based on these two earnings metrics. Moreover, they present empirical evidence on practical solutions researchers can use to mitigate the effects of measurement error. I discuss the implications of their results and provide new empirical evidence to highlight how their results apply to future research. In particular, I use a large sample of manager-adjusted “pro forma” earnings numbers voluntarily disclosed in quarterly earnings press releases to provide additional evidence about the implications of their research. Descriptive statistics based on these data illustrate the degree of measurement error in different earnings metrics. The results suggest that additional research is needed to determine the extent to which a random walk earnings expectation and reverse regression can mitigate the effects of measurement error. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Accounting Studies Springer Journals

Discussion of “another look at GAAP versus the Street: an empirical assessment of measurement error bias”

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Publisher
Kluwer Academic Publishers-Plenum Publishers
Copyright
Copyright © 2007 by Springer Science+Business Media, LLC
Subject
Business and Management; Accounting/Auditing; Corporate Finance; Public Finance
ISSN
1380-6653
eISSN
1573-7136
D.O.I.
10.1007/s11142-007-9036-1
Publisher site
See Article on Publisher Site

Abstract

Cohen, Hann, and Ogneva [(2007) Review of Accounting Studies, Forthcoming] provide evidence on how measurement error affects inferences this literature. In particular, they provide a theoretical framework for understanding (1) the source of differences in market reactions to GAAP and Street earnings and (2) why we observe a divergence over time between ERCs based on these two earnings metrics. Moreover, they present empirical evidence on practical solutions researchers can use to mitigate the effects of measurement error. I discuss the implications of their results and provide new empirical evidence to highlight how their results apply to future research. In particular, I use a large sample of manager-adjusted “pro forma” earnings numbers voluntarily disclosed in quarterly earnings press releases to provide additional evidence about the implications of their research. Descriptive statistics based on these data illustrate the degree of measurement error in different earnings metrics. The results suggest that additional research is needed to determine the extent to which a random walk earnings expectation and reverse regression can mitigate the effects of measurement error.

Journal

Review of Accounting StudiesSpringer Journals

Published: Apr 11, 2007

References

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