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The use of adjusted earnings in performance evaluation

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Abstract

We document widespread adoption of adjustments to earnings for performance evaluation; 84% of our sample of S&P 1500 firms use adjusted earnings for bonus compensation. We find that the transactions removed from adjusted earnings vary widely and include both transitory and nontransitory items. We examine the determinants of using adjusted earnings and find some evidence that boards are more likely to contract using adjusted earnings when firms have high levels of intangible assets, more volatile earnings, CEOs with shorter tenures, CEOs who also act as board chairperson, or larger compensation committees or are reporting losses. We find that firms with an independent chairperson or lead director are less likely to contract using adjusted earnings. We examine the compensation consequences of the use of adjusted earnings and find that CEOs compensated on adjusted earnings are less likely to miss minimum bonus thresholds, are less likely to meet maximum bonus thresholds, and have higher overall bonus compensation, controlling for firm performance. Taken together, our analyses suggest that both managerial power and efficient contracting concerns explain the use of adjusted earnings in CEO compensation contracts.

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Notes

  1. For example, in The Wall Street Journal, Rapoport (2014) states that “U.S. companies increasingly are using unconventional earnings measures in determining bonuses, making it easier for them to appear more profitable when they reward executives with big paydays”; Hoffman (2015) states that activist investors “point to nonstandard financial metrics they say reward executives even when business falters”; and Lahart (2016) states that “[e]arnings before the bad stuff can do good things for executive pay.” In addition, the proxy advisory firm Institutional Shareholder Services (ISS) requested feedback on the use of adjusted performance metrics for compensation, suggesting ISS may update voting guidelines to consider firms’ performance measure design (Institutional Shareholder Services 2015, 2017).

  2. Sensitivity, or responsiveness, measures the extent to which the expected value of a performance measure changes with an agent’s actions, and noise is the variation in the signal of the agent’s effort.

  3. Some companies state this intention in their compensation disclosures. For example, in the 2013 Hartford Financial proxy statement, the CEO’s adjusted earnings performance measure “includes certain year-end adjustments, which are intended to avoid advantaging or disadvantaging management for the effect of items outside its control.”

  4. Regulation G requires a quantitative reconciliation from non-GAAP financial measures to the most comparable GAAP measures in public disclosures, but the SEC’s 2013 “Compliance and disclosure interpretations: Regulation S-K” exempts compensation disclosures from this reconciliation requirement. As we discuss subsequently, adjusted earnings for performance evaluation frequently differ from the non-GAAP earnings disclosed in the earnings announcement.

  5. We explore these characteristics as predictors of the use of adjusted earnings because research already confirms that boards adjust earnings to reduce incentives for myopic behavior (e.g., Dechow et al. 1994), and boards likely rely primarily on equity compensation to align the interests of managers with shareholders.

  6. We do not necessarily expect boards to exclude all transitory components of earnings from earnings for performance evaluation, as boards may determine that some of these transactions reflect managerial decisions.

  7. If the choice not to disclose the measurement of earnings for performance evaluation is an opportunistic one that reflects an intentional lack of transparency, we will be biased against finding results of opportunism in the use of adjusted earnings in our analyses.

  8. For some analyses we also require I/B/E/S data, further reducing our sample size. In analyses not reported here, we confirm that our results hold for this subsample.

  9. An alternative measure of the use of adjusted earnings is the magnitude of the adjustments from earnings. Firms are not required to disclose the values of adjustments in the proxy statements, however. Although many firms provide some disclosure of the subtotal to which they are reconciling, those subtotals, even when they are disclosed as unadjusted subtotals, frequently differ from Compustat subtotals with similar titles. As such, we cannot determine the magnitude of each exclusion.

  10. Per private correspondence with Audit Analytics, they classified measures as “nonstandard” only if companies explicitly stated they used non-GAAP measures for performance evaluation.

  11. The level of detail in these disclosures varies greatly, and firms rarely disclose the values of each adjustment, making it infeasible to collect dollar values of exclusions. Unlike non-GAAP disclosures in earnings announcements, firms are not required to provide a full reconciliation of earnings for performance evaluation to GAAP earnings.

  12. As an example, Biogen 2013 states the performance measures were adjusted to exclude, among other items, costs related to inventory build-up described as “[i]nventory build related to the U.S. commercial launch of TECFIDERA [a new pharmaceutical product].”

  13. Additionally, some firms (i) “reserve the right to exclude” items from earnings for performance evaluation and do not disclose precisely which line items they include or exclude, and (ii) disclose a description of the calculation of earnings in vague terms that do not clearly differentiate between whether the firm did exclude particular items or would exclude particular items had they occurred. For example, Constellation Brands states in its 2013 proxy statement: “The effects of extraordinary items, such as certain unusual or nonrecurring items of gain or loss, the effects of mergers, acquisitions, divestitures, spin-offs or significant transactions, among other items specified in the plan, are excluded in calculating EBIT for this purpose.” We identify 80 observations in which firms provided disclosures where they “reserve the right to exclude” certain transactions. These observations are included in Table 5. The frequencies of exclusions for each transaction do not change substantially when we exclude firm-year observations that “reserve the right to exclude” transactions (not tabulated here).

  14. In our main analyses, we use OLS regression because we include several categorical variables (industry fixed effects), which can lead to biased inferences when using a logit or probit model (Greene 2004). We perform sensitivity tests using logit and probit specifications without the inclusion of fixed effects. The inclusion of industry effects, however, controls for industry-specific adjustments and the use of industry-specific adjusted performance metrics, similar to the prevalence of alternative earnings measures discussed by Francis et al. (2003). Thus we hesitate to rely on associations derived from specifications that do not include industry controls. Nonetheless, we confirm that our results are robust to the use of logit and probit specifications without the inclusion of fixed effects (not tabulated).

  15. Our inferences are unchanged when we measure tenure as the length of the CEO’s employment at the firm, rather than the length of her employment as CEO (not tabulated).

  16. CEO tenure has also been used as a proxy for CEO entrenchment (e.g., Berger et al. 1997). If longer tenures are consistent with both entrenchment and responsibility for past decisions that result in contemporaneous charges (like goodwill impairments), then the offsetting effects of entrenchment and control may prevent us from finding a significant association between tenure and the use of adjusted earnings.

  17. An additional set of predictors we could include in this model would control for the ex ante probability of transitory items that could be excluded from earnings. As a robustness check, we exclude all firms that do not report special items on Compustat and find similar but weaker results (not tabulated). Future research could consider models of expected special items, such as that of Cain et al. (2019).

  18. Our inferences are consistent when we measure these variables at the board level (not tabulated).

  19. Our inferences are also unchanged if we include alternative measures of the strength of board monitoring, including the mean tenure of the compensation committee members, as concerns have been raised about the ability of long-tenured directors to monitor management (Huang 2013; Francis and Lublin 2016; Livnat et al. 2016), the CEO pay slice—the proportion of total compensation paid to the five most highly paid executives that is paid to the CEO (e.g., Bebchuk et al. 2011)— and the presence of institutional investors, who function as outside monitors (e.g., Hartzell and Starks 2003; Abernethy et al. 2015). We do not include these variables in our presented analyses for parsimony (not tabulated).

  20. These measures control for the noise in earnings perceived by market participants. Although alignment between CEOs and shareholders is an important contracting goal, we expect boards to use equity compensation to align the interests of managers with shareholders, rather than to adjust cash compensation performance measures.

  21. Boards can either define adjusted performance measures ex ante or allow ex post adjustments to performance measures. Regardless of the timing, if the use of adjusted performance measures does not allow for rent extraction, boards will adjust both the value of the performance measure and the performance target. In this case, we do not expect to find evidence of an association between the use of adjusted earnings and the probability of reaching earnings thresholds.

  22. Our design differs from that of Kim and Yang (2014). We use earnings for performance evaluation as reported by firms in their proxy statements, whereas Kim and Yang assume that earnings for performance evaluation is the same as I/B/E/S actual earnings. Also, unlike Kim and Yang, we collect target values from proxy statements to compare to earnings for performance evaluation to capture whether CEOs met or exceeded bonus target values, rather than use a bonus/no bonus indicator. We use this methodology because some CEOs receive discretionary bonuses not tied to performance targets, and many CEOs receive cash bonuses based on measures other than earnings.

  23. Although analysts are not entirely free of bias (e.g., Hong and Kubik 2003) or CEO influence, the CEO is less likely to be able to directly negotiate with analysts than with the board of directors about which transactions to exclude from earnings. Nonetheless, we confirm that our inferences are unchanged if we include indicator variables for current year seasoned equity offerings or mergers and acquisitions that could allow for analysts with brokerage affiliations to introduce bias into their earnings forecasts (not tabulated).

  24. In some cases, analysts may choose to remove items that are recurring but not informative to investors. If the only item an analyst excludes is a recurring item and the board makes no exclusions, we would classify this observation as NonIBES, even if the board did not allow an opportunistic exclusion. This biases against finding results of opportunism using the NonIBES variable. If the analyst excludes recurring items in addition to nonrecurring items, our classification will be unaffected.

  25. We expect that analysts exclude transitory items, regardless of whether they are under the CEO’s control. If the patterns we observe are driven by cases where both the board and analysts exclude all transitory items, even though some of those transitory items were under the control of the CEO and should have been considered when setting compensation, the coefficient on Adjusted may remain positive and significant in our tests that include the interaction between NonIBES and Adjusted.

  26. Our results are consistent if we control for firm size using market value (not tabulated), as do, for example, Edmans et al. (2008).

  27. We confirm that Compustat did not report restated earnings for any firm-years in our sample; none were included in the Compustat “pre amends” or “pre amendss” tables.

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Acknowledgements

We thank two anonymous reviewers, Patty Dechow, Judy Beckman, Terrence Blackburne, Mary Ellen Carter, Agnes Cheng, Peter Demerjian, Shane Dikolli, Omri Even-Tov, Bjorn Jorgensen, Dawn Matsumoto, Sarah McVay, Jim Ohlson, Phil Quinn; workshop participants at Baylor University, Duke University, Hong Kong Polytechnic University, the University of California—Berkeley, Duke University, San Diego State University, the University of Rhode Island, and Washington University in St. Louis; and participants at the 2015 Conference on the Convergence of Financial and Managerial Accounting and the 2017 UBCOW conference for helpful comments. Asher Curtis thanks the Lane A. Daley Fellowship and Herbert O. Whitten Endowment for financial support. We thank Ana Albuquerque, Mary Ellen Carter, and Luann Lynch for the use of their CEO founder data.

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  1. University of Washington, Seattle, WA, USA

    Asher Curtis

  2. San Diego State University, San Diego, CA, USA

    Valerie Li

  3. University of Illinois at Chicago, Chicago, IL, USA

    Paige H. Patrick

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Curtis, A., Li, V. & Patrick, P.H. The use of adjusted earnings in performance evaluation. Rev Account Stud 26, 1290–1322 (2021). https://doi.org/10.1007/s11142-021-09580-1

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