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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.