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

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.