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Do managers use earnings guidance to influence street earnings exclusions?

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Abstract

Despite the apparent importance of “street earnings” to investors, we know relatively little about the process through which this earnings metric is determined. The limited evidence in the extant literature provides analyst-centric explanations, suggesting that analysts’ abilities and incentives influence which line items forecast-tracking services exclude from GAAP earnings to arrive at street earnings. We propose an alternative explanation: managers actively influence analysts’ forecast exclusion decisions via earnings guidance. We test this explanation by examining how earnings guidance influences two aspects of analysts’ exclusions: (1) special item exclusions (i.e., nonrecurring items) and (2) incremental exclusions (i.e., recurring items). We find that for firms with no special items in the previous year, when managers guide, analysts exclude almost all current-year special items, whereas when managers do not guide, the proportion that analysts exclude is significantly lower. More importantly, we that analysts’ incremental exclusions are significantly higher when managers guide than when they do not guide. Overall, our evidence suggests that managers play an active role in influencing the composition of street earnings via earnings guidance.

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Notes

  1. Some studies have used the terms “pro forma earnings” and “street earnings” interchangeably (e.g., Bradshaw and Sloan 2002). We use the term “street earnings” to refer to the non-GAAP realized earnings numbers reported by analyst forecast tracking services and “pro forma earnings” to refer to the non-GAAP realized earnings disclosed by managers (e.g., Gu and Chen 2004; Bhattacharya et al. 2007).

  2. Although analysts occasionally include certain nonrecurring income items, for brevity we use the term “exclusion” to refer to both expense (loss) exclusions and income (gain) inclusions.

  3. First Call notes: “The estimates have been adjusted to exclude any unusual items that a majority of the contributing analysts deem non-operating and/or nonrecurring” and “The values in the Actuals table have been adjusted to exclude any unusual items that a majority of the contributing analysts deem non-operating and/or nonrecurring” (First Call Historical Database User Guide, pp. 8–9).

  4. See Amazon’s press release on Oct. 22, 2009 and eBay’s press release on Oct. 21, 2009.

  5. Regulation G requires the reconciliation of pro forma earnings and GAAP earnings, but is silent about whether pro forma guidance needs to be reconciled with GAAP earnings guidance. Some firms provide both GAAP and pro forma guidance either for informative or opportunistic reasons.

  6. We infer this information from the actual analysts’ consensus estimate available from a Thomson Reuters research report for each company. Market Watch (October 21, 2009) provides additional confirmation.

  7. For example, see Akamai’s earnings guidance press release dated Feb. 4, 2009, where managers describe their rationale for excluding depreciation and amortization expense as follows: “Adjusted EBITDA also excludes depreciation and amortization expense, which is based on the company’s estimate of the useful life of tangible and intangible assets. These estimates could vary from actual performance of the asset, are based on historic cost incurred to build out the company’s deployed network, and may not be indicative of current or future capital expenditures.” Similar justifications are routinely offered by companies seeking to exclude other recurring expenses.

  8. They hand-collect a subsample of pro forma earnings at the earnings announcement to determine where street earnings come from. This timing, however, might be too late, because analyst tracking services use the “majority rule” and by the time of the earnings announcement, all analysts have already made their forecasts. Assuming forecast tracking services consistently follow the majority rule, the announced pro forma earnings would be too late to influence what components should be excluded from street earnings.

  9. According to the definition in the Compustat manual, we treat Compustat’s operating earnings as a reasonable “recurring earnings” measure and refer to it as “Compustat’s version of core earnings” throughout the paper. We are aware of another variable specifically labeled “core earnings” in Compustat after 2002, but do not use it because it does not exclude important nonrecurring items such as restructuring charges.

  10. Gu and Chen (2004) note that analysts’ exclusions are persistent, suggesting that analysts have excluded items that should have been included (e.g., recurring expenses).

  11. Compustat also records a data item for special items in aggregate dollar amount. Bradshaw and Sloan (2002) use this variable in their analyses. We do not use this alternative measure because it is a pre-tax measure and it is not reported on a diluted EPS basis. This measurement difference is relevant to comparisons of coefficients between the two studies.

  12. Chuck et al. (2009) and Lansford et al. (2010, appendix C) document the incompleteness of the CIG database even after Reg. FD. This problem is unlikely to have a material impact on our measurement of GUIDE because guiding firms provide an average (median) number of 3.6 (4) forecasts during the fiscal year. It is unlikely that the CIG omits all these forecasts for a firm year.

  13. Similar to Baik et al. (2009), our sample includes a small percentage of negative E/P ratio firms. When firms have respectable stock prices despite reporting losses, they are more glamorous than those that have the same stock prices but report accounting profits and should be included in the test. On the other hand, including loss firms creates two problems. First, some loss firms are depressed instead of being glamorous. Second, among loss firms, the more glamorous firms have less negative E/P ratios. Therefore, we expect the coefficient on E/P to be positive for the subsample of loss firms, even though it is negative for the full sample. In a robustness test, instead of using E/P, we use a variable that takes the value of positive E/P ratios and is coded as 0 if the ratio is negative and a second variable that takes the value of negative E/P ratios and is coded as 0 if the ratio is positive. Our results remain unchanged with this specification. We thank an anonymous reviewer for this insight.

  14. We avoid 2001 because there appears to be a chilling effect right after the implementation of Reg. FD. For example, Wang (2007) finds that half of the firms that previously provided guidance privately decided not to provide any disclosure after Reg. FD and that the information environment of these firms deteriorated subsequently.

  15. We elect to use annual data in our analyses because in recent years, managers’ decisions to provide quarterly earnings guidance have been influenced by the mounting criticism of quarterly earnings guidance around 2006 (Houston et al. 2010). According to the NIRI annual surveys, the percentage of its member firms providing quarterly earnings guidance was 61% at the beginning of 2005, but dropped to 52% at about the same time in 2006, 14% in 2007, and 30% in 2008 (National Investors Relations Institute (NIRI) 2006, 2007, 2008). Moreover, more accounting adjustments are made in the fourth fiscal quarter than in any other quarters, resulting in seasonality in the reporting of special items (Bradshaw and Sloan 2002). However, our inferences using quarterly data are largely similar to those using annual data.

  16. GUIDE is negatively correlated with VSPECIAL, consistent with Waymire’s (1985) evidence that managers are less likely to issue guidance as the uncertainty of their operations increases.

  17. Some firms issue multiple forecasts for a fiscal year. In a robustness test, we replace GUIDE with a guidance frequency count for the year. This new variable or alternatively its log transformation is positively associated with incremental exclusions.

  18. In some instances, analysts actually exclude less than the total amount Compustat classifies in the special items category, resulting in negative values for INCREMENT. We repeat our Table 3 analyses after excluding these observations and find that the tenor of our results is unchanged. Similar to the Table 2 results, we find that earnings guidance is significantly positively associated with incremental exclusions only for the firms that did not report special items in the prior year. We conclude that, in general, analysts are more likely to make positive incremental exclusions and less likely to make negative incremental exclusions when managers guide. Although we do not analyze when (or why) analysts sometimes exclude less than the total amount in Compustat’s special items variable, our results are unaffected by these instances. However, understanding the instances why analysts make income-decreasing exclusions is an interesting question that we leave for future research.

  19. In an untabulated robustness test, we add firm fixed effects to control for time-invariant factors not included in Eq. 2. The coefficient on GUIDE is still significantly positive.

  20. It might be surprising that in Panel B of Table 4 even for the firms coded as “Non-Special Item Firms”, 16 exclusions are special items. This apparent discrepancy arises because our firm categorizations in the columns are based on special items classified by Compustat, whereas the coded special items in the rows are based on categories defined by Black and Christensen (2009). Even though managers may treat an item as a “special item,” Compustat does not necessarily agree with managers’ claims (Frankel 2009).

  21. The inferences are based on AP Financial Wire Oct. 25, 2007 for Cadence, Business Wire Feb. 2, 2006 for i2, Business Wire Jan. 31, 2007 for Allergan, and AP Financial Wire May 7, 2007 for TNS. For example, in the case of i2, the press release states unambiguously “Analysts polled by Thomson Financial expected the company to earn, on average, 30 cents per share on $70.9 million in revenue. Analysts estimates were for operating revenue versus total revenue” (AP Financial Wire, “i2 shares surge on 4Q profit,” February 2, 2006).

  22. The results in Table 5 are based on 3,990 observations due to data requirements to construct the control variables.

  23. Managers may argue that they encourage analysts to make exclusions when the recurring expenses are not predictive of future performance rather than for opportunistic reasons. Our test controls for this explanation and still finds a positive association between earnings guidance and recurring expense exclusions.

  24. While the focus of this study is on managers’ influence on the street earnings number issued by forecast tracking services, a growing literature explores the voluntary disclosure of realized pro forma earnings metrics in quarterly earnings press releases (e.g., Bhattacharya et al. 2003; Brown et al. 2010). It is important to note that interim earnings announcements containing manager-disclosed pro forma earnings numbers can also influence analysts’ exclusions in forecasting annual earnings since quarterly earnings exclusions will almost certainly be excluded from the annual number as well. We find that our previous results are robust to controlling for quarterly pro forma earnings disclosures. Moreover, if we replace GUIDE with a new guidance measure that is coded 1 if the firm has both a management forecast and an interim pro forma earnings disclosure that excludes recurring items, this new guidance measure is more highly associated with incremental exclusions.

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Acknowledgments

We thank Ting Chen, Steve Crawford, Marcus Kirk, Lynn Rees, David Reppenhagen, Larry Walther, Richard Sloan (the editor), Mark Bradshaw (the discussant), two anonymous referees, and participants at the 2010 RAST Conference, the Florida State University Accounting Workshop, the 2009 BYU Accounting Research Symposium, and the AAA 2010 Annual Meeting. We also express thanks to Will Ciconte, Candace Jones, Lan Su, Glen Young, Helen Xu, and Ying Zhou for their valuable research assistance. Jenny Tucker thanks the Luciano Prida, Sr. Term Professorship Foundation for financial support.

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Authors and Affiliations

  1. Marriott School of Management, Brigham Young University, Provo, UT, USA

    Theodore E. Christensen

  2. Johnson Graduate School of Management, Cornell University, Ithaca, NY, USA

    Kenneth J. Merkley

  3. Fisher School of Accounting, University of Florida, Gainesville, FL, US

    Jennifer Wu Tucker

  4. College of Management, Georgia Institute of Technology, Atlanta, GA, USA

    Shankar Venkataraman

Authors
  1. Theodore E. Christensen
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  2. Kenneth J. Merkley
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  3. Jennifer Wu Tucker
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  4. Shankar Venkataraman
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Correspondence to Theodore E. Christensen.

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Data availability The data are available from the public sources identified in the text.

Appendix: Managers’ decision to issue earnings guidance

Appendix: Managers’ decision to issue earnings guidance

To control for a potential selection bias in our primary test, we model managers’ earnings guidance decision following Ajinkya et al. (2005). We drop the outside director variable because of data constraints and augment the model with an indicator variable for special items because, as we argue for Hypothesis 1, managers are more likely to guide when they anticipate special items than when they do not. Our probit model is Eq. 5.

$$ \begin{aligned} Prob\left( {GUIDE} \right) =\, & c_{0} + c_{1} SPI + c_{2} SIZE + c_{3} ANALYST + c_{4} IO + c_{5} M/B + c_{6} LOSS \\ & + c_{7} DECLINE + c_{8} VCORE + c_{9} BETA + c_{10} LITIG + e \\ \end{aligned} $$
(5)

GUIDE is an indicator variable for earnings guidance issuance as defined in Sect. 3. SPI is 1 for firms that report non-zero special items for the current year and 0 otherwise. SIZE is the natural logarithm of total assets at the beginning of the year, proxying for the importance of transparency for large firms. ANALYST proxies for the demands of earnings guidance by analysts for valuation and is measured by the number of estimates in the last consensus for the prior-year earnings compiled by First Call before the prior-year earnings announcement. IO proxies for the demand of earnings guidance by institutional investors for monitoring and is measured as the percentage ownership by institutions according to the most recent 13F reports before the current fiscal year begins, obtained from Thomson Financial. We use the market-to-book ratio at the beginning of the fiscal year, M/B, to proxy for managers’ incentive to avoid a torpedo effect at the earnings announcement from lack of early communication (Skinner and Sloan 2002). Prior studies have found that poorly performing firms are reluctant to provide earnings guidance (Miller 2002; Houston et al. 2010). We use two indicator variables as proxies for poor performance: LOSS is coded 1 if the firm experiences losses in the previous year and 0 otherwise. DECLINE is coded 1 if the firm experiences an earnings decline in the previous year (i.e., the GAAP earnings number in the current year is lower than that in the previous year) and 0 otherwise. We model the uncertainty associated with a firm’s operations but do not offer directional predictions because reasonable arguments can be made for either direction. VCORE captures the uncertainty in core earnings that managers face and is measured as the average absolute change in core earnings in the previous 3 years, scaled by the stock price at the beginning of the current year (both earnings and price are adjusted for stock splits). BETA captures general business risk and is estimated in a market model using the daily returns in the previous fiscal year. Finally, we include litigation risk and expect firms with exposure to higher risk to be more likely to issue guidance. LITIG is 1 if the 4-digit SIC code is 2833-2836, 8731-8734, 3570-3577, 7370-7374, 3600-3674, or 5200-5961 and 0 otherwise (Francis et al. 1994).

Table 6 presents the results and the tests of significance. We employ standard errors that are robust to heteroskedasticity and within-firm error correlations. As expected, SPI has a positive coefficient, indicating that firms with special items are more likely to guide than those without special items. The results for the other variables are all consistent with prior research. The model pseudo R2 is reasonable at about 10%.

Table 6 Probit estimation results
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Christensen, T.E., Merkley, K.J., Tucker, J.W. et al. Do managers use earnings guidance to influence street earnings exclusions?. Rev Account Stud 16, 501–527 (2011). https://doi.org/10.1007/s11142-011-9158-3

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