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Review of Accounting Studies

22-01-2024

Earnings per share targets and CEO incentives

Authors: Christopher Armstrong, Jacky Chau, Christopher D. Ittner, Jason J. Xiao

Published in: Review of Accounting Studies

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Abstract

We examine differences in CEOs’ achievement of earnings per share (EPS) targets related to (1) analysts’ forecasts and (2) internal cash bonus payouts. Our focus on firms with different benchmarks for the same performance metric enables us to assess the relative importance of the incentives that each EPS target provides based on its revealed achievement. Most CEOs meet analysts’ final consensus EPS forecasts but are unlikely to meet bonus EPS targets that exceed forecasted EPS. Nearly all CEOs receive some EPS-based cash bonus, even when missing the forecast. Moreover, CEOs with bonus targets that are easier to achieve than the consensus forecast tend to receive more annual pay, suggesting that boards often set more achievable EPS targets to provide extra compensation to CEOs while maintaining the appearance of pay-for-performance. Our results highlight the importance of considering both types of EPS targets simultaneously when assessing their respective incentive properties.

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Appendix
Available only for authorised users
Footnotes
1
We refer to the collective set of three bonus incentive zone EPS targets as the firm’s “bonus objectives.”
 
2
We refer to analysts’ initial (final) consensus forecast for a firm’s fiscal year as their first (final) forecast. In general, we use first forecasts when measuring how goals are set and final forecasts when measuring whether managers achieve their objectives, as the final forecasts better reflect the expectations CEOs strive to meet. Results are robust to using final forecasts throughout the entire analysis.
 
3
For analysts, see Kim and Schroeder (1990) and Packard (2017). For boards, see Resch (2013), Burchman and Emanuel (2015), Ramagnano and Wolfson (2016), and Kwon et al. (2018).
 
4
See Burgstahler and Dichev (1997), Bartov et al. (2002), Kasznik and McNichols (2002), Skinner and Sloan (2002), and Graham et al. (2005).
 
5
See Bens et al. (2003), Cheng and Warfield (2005), McVay et al. (2006), and Bhojraj et al. (2009).
 
6
See Healy (1985), Gaver et al. (1995), Holthausen et al. (1995), Kim and Yang (2014), Bennett et al. (2017), Young and Yang (2011), Cheng et al. (2015), Kim and Ng (2018), Kim and Yang (2014), Bennett et al. (2017), and Huang et al. (2014).
 
7
During the period covered by our sample, Internal Revenue Code Section 162(m) limited the amount of deductible compensation that a company could pay to its CEO and four other highest-paid executives to $1 million annually, unless the pay was deemed to be performance-based.
 
8
Incentive Lab collects annual data for the 750 largest U.S. firms (based on market capitalization) starting in 1999. Because the composition of the 750 largest firms changes from year to year, Incentive Lab retains all firms that enter the database in any year. Data are then backfilled and forward filled for all the firms, beginning with 1999.
 
9
To enhance comparability with analysts’ annual EPS forecasts, we only include annual cash incentive plans with EPS targets. We exclude targets based on other earnings numbers, such as net income, EBIT, EBITDA, operating income, and gross profit, subsidiary-level goals, and EPS targets measured over horizons other than one year.
 
10
When referencing EPS outcomes, we use the terms “actual” and “realized” interchangeably.
 
11
A review of these small discrepancies indicates that differences of one cent or less are largely due to rounding differences between the EPS figures in the proxy statement and I/B/E/S (e.g., differences in the number of digits or EPS computations being rounded versus truncated). Excluding the 118 observations with these small differences does not affect our results regarding the relative difficulty of analysts’ forecasts and EPS goal achievement.
 
12
All untabulated analyses are available upon request.
 
13
Our results are robust to excluding from our sample any observations for which the analysts’ consensus forecast exactly equals a bonus objective.
 
14
See Payne and Robb (2000), Cheng and Warfield (2005), Jiang et al. (2010), and Huang et al. (2017).
 
15
Inferences do not change when using the individual implicit claims measures instead.
 
16
See, e.g., Matsumoto (2002), Yu (2008), Doyle et al. (2013), and Indjejikian et al. (2014).
 
17
We measure predictor variables related to the executives’ incentives in the same year as the relative target difficulty and target achievement variables since all of the incentive plan characteristics are determined in the same year. All other predictor variables relate to the prior year to capture the information that would be available to boards and analysts at the time they set their EPS bonus objectives and EPS forecasts, respectively.
 
18
We employ linear probability models because their coefficients are generally easier to interpret than those from non-linear models (e.g., Logit or Probit). To ensure that our inferences from these tests are not an artefact of estimating linear probability models, we also estimate Logit models in untabulated analyses and find similar statistical inferences.
 
19
In Table 4, we denote statistical significance using symbols but suppress the respective t- and z-statistics for brevity. While we focus on observations with similar EPS computations to better control for congruence in boards’ goal-setting and analysts’ forecast-setting purposes, inferences change little when using the full sample of observations (n = 1,861) for our analyses instead.
 
20
Degeorge et al. (1999) note that EPS is measured (and reported and forecast) rounded to the closest penny and that normalized EPS can give rise to spurious patterns in the distribution. As we use EPS data from two separate sources (analysts and bonus plans), we set the cutoff at two cents to avoid instances of misclassification due to rounding choices by data providers. To ensure that our results are not entirely attributable to this choice, we also estimate sensitivity analyses using the one-cent definition and find that inferences are unchanged.
 
21
One explanation for firms just meeting the final consensus forecast is to avoid subsequent forecast ratcheting when firms substantially exceed their EPS forecasts. In untabulated tests, we examine whether analysts’ forecasts exhibit ratcheting. Forecast changes significantly relate to EPS growth and stock returns in the prior year as well as negative deviations from the prior year’s forecast. This evidence indicates that analysts consider past performance when setting EPS targets, thereby providing incentives for CEOs to avoid substantial EPS growth that could lead to large upward revisions in analysts’ forecasts in the following year.
 
22
Although firms are significantly more likely to just meet a bonus objective than to just miss it in some comparisons, untabulated analyses indicate that these observations typically reflect cases where the consensus forecast and bonus objectives are very similar. For example, all firm-years but one in which the consensus forecast is the most difficult goal and the firm just meets the bonus maximum have maximums within two cents of the final forecast. Similarly, in firm-years with consensus forecasts between the bonus target and maximum, the bonus target is within two cents of the forecast in 15 of the 19 cases in which the firm just meets the bonus target.
 
23
Supplemental analyses are highly consistent with this notion, with 62% of incentive zone firm-years meeting the final consensus forecast but not the bonus maximum. Among the 160 firm-years in which the bonus maximum is achieved, it exceeds the forecast in only 31 cases and equals the forecast in nine cases. In every other case, the forecast exceeds the maximum bonus target.
 
24
As an alternative to using the relative target difficulty indicators, we estimate the achievement models using differences between the forecast and the respective bonus objective (with one variable for positive differences and one for negative differences to allow for differential relations depending on the sign). For all three bonus objectives, realized EPS exceeds (falls below) the bonus objective by a greater margin the higher (lower) the forecast is relative to the bonus objective.
 
25
In untabulated analyses using the incentive zone subsample, the bonus threshold is met over 95% of the time when bonus EPS is higher, significantly greater than the 89.93% achievement rate at firms with similar EPS computations. In contrast, the bonus threshold is achieved in 80.49% of firm-years when bonus EPS is lower, significantly lower than the achievement rates in the other two samples. The bonus maximum exhibits statistically similar 24.12% and 22.70% achievement rates (as well as mean and median differences between actuals and maximums) in these two EPS samples and lower achievement when the bonus EPS computation is lower than that of analyst EPS (16.21%).
 
26
We re-estimate the models in Panel A Table 5 after supplementing Realized EPS – GAAP EPS with a variable measuring the difference between actual bonus EPS and actual I/B/E/S EPS. Larger values of this variable imply that the board makes more income-increasing EPS adjustments than analysts. We again do not find an association between relative target difficulty and forecast achievement in the Higher Bonus EPS sample. However, in the Lower Bonus EPS sample, the likelihood (but not extent) of meeting the ending consensus forecast is higher when the first forecast exceeds or equals the bonus target, relative to when the forecast is lower. The coefficients on the target difficulty indicators in the bonus achievement models generally increase in magnitude as the analysts’ forecast becomes relatively more difficult, again consistent with CEOs meeting their bonus objectives on the way to achieving the consensus forecast.
 
27
Bonus objectives may also be moving targets when boards have the discretion to make ex-post changes to the EPS computations used to determine bonus awards. If these changes yield realized bonus EPS that differs from final forecast EPS, we exclude the observation from our primary sample, even if the first EPS computations for both purposes are similar.
 
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Metadata
Title
Earnings per share targets and CEO incentives
Authors
Christopher Armstrong
Jacky Chau
Christopher D. Ittner
Jason J. Xiao
Publication date
22-01-2024
Publisher
Springer US
Published in
Review of Accounting Studies
Print ISSN: 1380-6653
Electronic ISSN: 1573-7136
DOI
https://doi.org/10.1007/s11142-023-09815-3