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Review of Accounting Studies

Erschienen in:

01.09.2007

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

Erschienen in: Review of Accounting Studies | Ausgabe 2-3/2007

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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.

Vorheriger Artikel Another look at GAAP versus the Street: an empirical assessment of measurement error bias

Nächster Artikel Conservatism, growth, and return on investment

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I thank the authors for sending me their annual ERC estimates to allow me to re-create their Fig. 2.

Adding a constant to the GAAP ERC equal to the mean difference in ERCs over the 1995–2003 period and plotting the resulting measures together results in trend lines that are virtually indistinguishable.

Note that the large negative spike in the mean EPS_Diff in 2001 appears to be attributable to large analysts’ exclusions of one-time write-offs by many firms in 2001 as evidenced in the first chart of Fig. 2. This is consistent with anecdotal evidence that many firms had large write-offs in the wake of the economic downturn following September 11, 2001.

Note that while SFAS 154 has now changed the rules for changes in accounting principles, the authors sample period pre-dates this standard. Thus, changes in accounting principles were consistently reported as “below-the-line” items in the authors’ sample period.

BBCM collect the their sample of 5,736 quarterly earnings announcements using an electronic search string based on commonly used terms from actual press releases catalogued by Wallace (2002). Several other studies use hand-collected manager-adjusted earnings data (e.g., Allee, Bhattacharya, Black, & Christensen, 2007; Bhattacharya, Black, Christensen, & Larson, 2003; Bhattacharya, Black, Christensen, & Mergenthaler, 2004; Johnson & Schwartz, 2005; Lougee & Marquardt, 2004; Marques, 2006).

Note that when BBCM collected the initial sample, Compustat’s diluted EPS from operations (quarterly data item 181) was not readily available. Therefore, they rescaled the basic quarterly EPS from operations number (quarterly data item 177) by the diluted shares outstanding number from the annual Compustat database. Thus, it is a close approximation of data item 181.

Since manager-adjusted earnings metrics tend to exclude the same items as I/B/E/S, this earnings metric should be less affected by measurement error relative to other earnings metrics that are not constructed in a manner similar to the I/B/E/S actual EPS metric.

The difference between these two earnings metrics results from the fact that analysts often exclude recurring items that are always included in Data 177.

I note, however, that the random walk expectation appears to lead to a less skewed distribution as the 25th and 75th percentiles are equal in magnitude (−13 and +13 cents per share) for the random walk expectation but are not balanced for the analysts’ forecast expectation (−16 cents and +1 cents per share).

A random walk expectation is not a good expectation for manager-adjusted earnings numbers since most firms do not disclose adjusted numbers on a regular basis and even when they do, they don’t always exclude the same items (Bhattacharya et al., 2003). This lack of regular disclosures and of comparability suggests that a random walk “pro forma” expectation isn’t likely to be feasible or accurate.

It is important to note that not all of the reverse ERC coefficients are statistically significant. While the I/B/E/S ERCs are significant in all years except 1998 (which has the smallest sample size), the pro forma and Data 177 ERCs are only significantly significant in the years in which BBCM have the most data (2000 and 2001).

I thank the authors for sharing the coefficients from their regressions to allow me to construct this chart.

For example, given that there is a measurement error problem in using analysts’ forecasts as the expectation in the GAAP forecast error in Street versus GAAP comparisons, researchers could include the variance of past GAAP and Street forecast errors as a control variable in the respective GAAP or Street ERC regressions.

Abarbanell, J., & Lehavy, R. (2007). Letting the “tail wag the dog”: The debate over GAAP versus street earnings revisited. Contemporary Accounting Research, forthcoming.

Allee, K. D., Bhattacharya, N., Black, E. L., & Christensen, T. E. (2007). External validating of experimental evidence on pro forma reporting using archival data. Accounting Organizations and Society, 32, 201–222.CrossRef

Berger, P. G. (2005). Discussion of “Are investors misled by ‘pro forma’ earnings? Contemporary Accounting Research, 22(Winter), 965–976.

Bhattacharya, N., Black, E. L., Christensen, T. E., & Larson, C. R. (2003). Assessing the relative informativeness and permanence of pro forma earnings and GAAP operating earnings. Journal of Accounting and Economics, 36, 85–319.CrossRef

Bhattacharya, N., Black, E. L., Christensen, T. E., & Mergenthaler, R. D. (2004). Empirical evidence on recent trends in pro forma reporting. Accounting Horizons, 18(1), 27–43.

Bhattacharya, N., Black, E. L., Christensen, T. E., & Mergenthaler, R. D. (2007). Who trades on pro forma earnings? The Accounting Review, Forthcoming.

Bradshaw, M. T. (2003). A discussion of ‘Assessing the relative informativeness and permanence of pro forma earnings and GAAP operating earnings. Journal of Accounting and Economics, 36, 321–335.CrossRef

Bradshaw, M. T., & Sloan, R. G. (2002). GAAP versus the street: An empirical assessment of two alternative definitions of earnings. Journal of Accounting Research, 40, 41–66.CrossRef

Brown, L. D., & Sivakumar, K. (2003). Comparing the value relevance of two operating income measures. Review of Accounting Studies, 8(December), 561–572.

Cohen, D. A., Hann, R. N., & Ogneva, M. (2007). Another look at GAAP versus the street: An empirical assessment of measurement error bias. Review of Accounting Studies, Forthcoming.

Easton, P. (2003). Discussion of “The predictive value of expenses excluded from pro forma earnings.” Review of Accounting Studies, 8(June), 175–183.CrossRef

Johnson, B., & Schwartz, W. (2005). Are investors misled by “pro forma” earnings? Contemporary Accounting Research, 22, 915–963.CrossRef

Lougee, B. A., & Marquardt, C. A. (2004). Earnings informativeness and strategic disclosure: An empirical examination of ‘pro forma’ earnings. The Accounting Review, 78(July), 769–795.

Marques, A. (2006). SEC interventions and the frequency and usefulness of non-GAAP financial measures. Review of Accounting Studies, 11(December), 549–574.CrossRef

Wallace, W. (2002). Pro forma before and after the SEC’s warning: A quantification of reporting variances from GAAP. Morristown, NJ: FEI Research Foundation.

Titel: Discussion of “another look at GAAP versus the Street: an empirical assessment of measurement error bias”
Publikationsdatum: 01.09.2007
Erschienen in: Review of Accounting Studies / Ausgabe 2-3/2007
Print ISSN: 1380-6653
Elektronische ISSN: 1573-7136
DOI: https://doi.org/10.1007/s11142-007-9036-1

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