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Review of Accounting Studies
Published in:

09-11-2022

The risk-relevance of non-GAAP earnings

Authors: Frank Heflin, Kalin S. Kolev, Benjamin Whipple

Published in: Review of Accounting Studies | Issue 1/2024

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Abstract

We study the risk-relevance of non-GAAP earnings. Risk is an important earnings attribute in valuation models, and the FASB’s conceptual framework identifies providing information about risk as a primary objective for earnings. Although prior research addresses the value-relevance of non-GAAP earnings, researchers have paid little attention to their risk-relevance. We find that non-GAAP adjustments yield an earnings number that isolates the more risk-relevant components of earnings. Excluded earnings components, however, contain some, albeit less, information about risk. Thus, although non-GAAP earnings can help investors prioritize the more versus less risk-relevant components of earnings, non-GAAP earnings are potentially most informative about risk when used together with GAAP earnings.
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Appendix
Available only for authorised users
Footnotes
1
Specifically, the conceptual framework states that “investors’, lenders’, and other creditors’ expectations about returns depend on their assessment of the amount, timing, and uncertainty of (the prospects for) future net cash inflows to the entity” (SFAC No. 8, FASB 2010).
 
2
Evidence from prior research on earnings and risk includes: (1) volatility in GAAP earnings is associated with both contemporaneous and future equity returns (Beaver et al. 1970; Eskew 1979), (2) full fair value income is more risk-relevant than GAAP net income (Hodder et al. 2006), and (3) fair-value pension measures impair the risk-relevance of GAAP earnings (Hann et al. 2007). Research on risk also extends to the balance sheet (Blankespoor et al. 2013).
 
3
As we discuss in Sections 3 and 5, we identify non-GAAP earnings using analysts’ metrics in I/B/E/S for several reasons. An alternative method is to identify non-GAAP earnings using managers’ metrics. In additional analyses, we use managers’ non-GAAP earnings and find inferences similar to our primary risk-relevance results.
 
4
This research design follows a long line of research on information about risk in earnings (e.g., Barth et al. 1995; Beaver et al. 1970; Hann et al. 2007; Hodder et al. 2006). We discuss the intuition of this design in Section 3.
 
5
The non-GAAP literature commonly partitions total exclusions into special item (e.g., restructurings, impairments) and other item exclusions (e.g., amortization of intangibles, stock compensation expense) by comparing non-GAAP earnings, operating earnings, and GAAP earnings. Similar to our calculation of total exclusion volatility, we calculate (1) special item exclusion volatility as the difference between GAAP earnings volatility and operating earnings volatility, and (2) other item exclusion volatility as the difference between operating earnings volatility and non-GAAP earnings volatility.
 
6
We note that, even if an earnings construct only contains information about risk (as opposed to conveying new information about risk), non-GAAP earnings are still risk-relevant in the sense that the earnings number captures information that is useful in assessing risk. That is, risk-relevance is a parallel to value-relevance (see Barth et al. (2001) for a comprehensive discussion of value-relevance). In addition, the FASB emphasizes that the desired characteristics of financial reports include both predictive and confirmatory value (SFAC 8). Thus, even if an earnings construct solely captures information about firm risk (as opposed to directly informing on risk), it is still risk-relevant.
 
7
Conceptually, signals about the mean of expected cash flows are distinct from signals about the riskiness of those cash flows and vice versa. Nevertheless, we examine whether our measures of risk-relevance are distinct from measures of earnings persistence.
 
8
Some studies use terms other than “risk-relevance,” such as “informative” about risk, “better captures information” about risk, or simply “better explains” risk (e.g., Blankespoor et al. 2013).
 
9
Early research also provides evidence that accounting earnings are credit-risk-relevant. For example, evidence in Horrigan (1966), West (1970), and Kaplan and Urwitz (1979) suggests that profit margin and earnings variability contribute to explaining corporate bond ratings.
 
10
We view the value- and risk-relevance literatures as complementary rather than overlapping. In particular, signals about the mean of expected cash flows do not necessarily inform on their dispersion, and vice versa.
 
11
Using I/B/E/S to identify non-GAAP reporting results in our missing managers’ more aggressive non-GAAP adjustments (Bentley et al. 2018). Therefore, as an additional analysis, we examine the robustness of our inferences using a subsample of observations with available Bentley et al. (2018) data; we discuss the results in Section 5.5.
 
12
Prior to calculating the standard deviations, we convert the earnings per share variables to an asset-deflated basis using assets per share as a deflator, consistent with prior research (e.g., Kolev et al. 2008).
 
13
Although common in the literature, the time-series requirements for the variable construction, along with the minimum stock price requirement of $5 in each of these quarters (see Section 3.1), potentially imposes a survivorship requirement and shifts our sample away from the poorest performing firms.
 
14
The windows that were used to compute earnings volatility in prior risk-relevance research vary. For example, Hodder et al. (2006) use a five-year window to compute volatility of annual earnings. Chen et al. (2008) use six quarters, while Dou et al. (2014) use 20 quarters, to compute volatility in quarterly earnings.
 
15
Operating earnings is an earnings measure calculated by Compustat to capture firms’ earnings before special items.
 
16
As noted in the introduction, we also examine the relation between non-GAAP earnings and future equity risk in an attempt to shed light on whether non-GAAP earnings convey new information about risk or primarily reflect existing information about risk that investors obtain elsewhere. We discuss this distinction in more detail when motivating the research design for our future risk analysis.
 
17
Our decomposition of the standard deviation of earnings into the standard deviations of various components parallels the approach in Hodder et al. (2006) and Barth et al. (1995).
 
18
Baginski and Wahlen (2003) also address the notion of risk-relevance, but in a pricing context, as do Hodder et al. (2006) in subsequent analyses. The pricing analyses in Baginski and Wahlen (2003) and Hodder et al. (2006) also do not require that accounting risk measures convey new information about risk. We conduct pricing analyses in Section 5.1.
 
19
We winsorize variables based on standard deviations at the 0 and 98th percentiles.
 
20
We recognize that the time-series nature (e.g., 12-quarter window to calculate volatility) of our analyses leads to overlapping data in the construction of both independent and dependent variables for a particular firm. This is one reason why we cluster standard errors by firm. In additional untabulated analyses, we re-estimate the regressions underlying Tables 2 and 3 on a subsample with no overlap (the fourth quarter of every third year in the data) and continue to find that non-GAAP earnings generally identify the more risk-relevant earnings components but that GAAP earnings contain incremental information about risk beyond the information in non-GAAP earnings.
 
21
For the future risk analyses, we continue to measure total risk (ReturnSTD) as the standard deviation of a firm’s monthly returns. We change the calculation of systematic risk (Beta) to accommodate the shorter one-year measurement window for future risk. Specifically, we measure Beta using daily firm and market returns, as opposed to the monthly returns we use in our primary analyses.
 
22
Baginski and Wahlen (2003) also address whether accounting risk measures are related to prices, albeit in a different context and using a different design. Specifically, they develop a measure of the effect of risk on price by estimating an abnormal earnings price based on risk-free rates of return and comparing that to actual share price. Their evidence suggests the pricing of abnormal earnings is useful in assessing variation in risk.
 
23
Negative values for abnormal earnings are inconsistent with a pricing equation such as Equation (2) because abnormal earnings cannot be negative in perpetuity. Accordingly, we drop observations with negative values of abnormal earnings when we estimate Equation (2). In untabulated analyses, we estimate Equation (2) including observations with negative abnormal earnings and find that our inferences hold.
 
24
To underscore the point, we note that 69.6% of our observations have missing data for at least one quarter in the respective 12-quarter window, which would result in their elimination from the main analysis.
 
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Metadata
Title
The risk-relevance of non-GAAP earnings
Authors
Frank Heflin
Kalin S. Kolev
Benjamin Whipple
Publication date
09-11-2022
Publisher
Springer US
Published in
Review of Accounting Studies / Issue 1/2024
Print ISSN: 1380-6653
Electronic ISSN: 1573-7136
DOI
https://doi.org/10.1007/s11142-022-09725-w

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