Clawback provision adoption and
the use of non-GAAP earnings measure
in compensation contract
Name: Jeongri Kim
Student number: 11846003
Thesis supervisor: Prof. Kroos, Peter Date: June 24, 2018
Word count: 12,154
MSc Accountancy & Control, specialization Control
Statement of Originality
This document is written by student [Jeongri Kim] who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Abstract
The primary purpose of this study is to investigate how clawback provisions adoption influences the use of non-GAAP earnings performance measures in executive compensation contract. The empirical results show that clawback adopting firms are more likely to change performance measures for short-term incentive compensation, relative to non-adopters. Also, non-adopting firms seem to use non-GAAP performance measures in more constant basis. I investigate whether adopting firms use the non-GAAP earnings performance measures more after adopting clawbacks in order to inflate opportunistically motivated managers’ compensation. However, I don’t find significant relation between clawback adoption and the more use of non-GAAP earnings performance measures in executive compensation contract. The results, nevertheless, show some evidence that adopting firms change more frequently performance measures in executive compensation contract.
Keywords: clawback provision, executive compensation, non-GAAP earnings metrics, performance measure
Contents
1 Introduction ... 6
1.1 Background ... 6
1.2 Research Question ... 7
1.3 Relevance of the question ... 8
1.4 Structure of the thesis ... 9
2 Literature review ... 10
2.1 Agency theory and Regulation ... 10
2.2 Adoption of clawback provisions ... 12
2.3 The use of Non-GAAP earnings measure ... 15
2.4 Hypothesis development ... 19
3 Data collection and Sample selection ... 21
3.1 Agency theory and Regulation ... 21
4 Research Design ... 25 4.1 Empirical models ... 25 4.2 Control variables ... 27 5 Empirical results ... 29 5.1 Descriptive statistics ... 29 5.2 Main analysis ... 31 6 Conclusion ... 36 References ... 38 Appendices ... 43
1 Introduction
1.1 Background
Since the introduction of the separation of ownership and control, managers’ self-serving behavior and the effect of opportunism on accounting choices have been an important topic debated by researchers and regulators (Healy 1985; Gaver et al. 1995; Roychowdhury 2006; Abernethy et al. 2017). In modern corporate environment, most of firms implement performance-based compensation to encourage managers’ productive effort that will increase value to the firm. However, at the same time, the financial incentives can motivate managers’ opportunistic actions as well (Guidry et al. 1998). Managers may behave to increase the proceeds of their incentive compensation instead, rather than making the best decisions for shareholders. It is one of the classic agency problems, and likely to lead to managers’ engagement in earnings manipulation and intentional misreporting. The agency costs associated with earnings manipulation negatively affect financial reporting reliability, and cost shareholders to pay for such inappropriately excess compensation and to recover damaged reputation in case that restatement is required. Thus, after several accounting scandals, SOX of 2002 was initiated to curb opportunistic earnings manipulation and decrease managers’ misreporting incentives. Clawback provisions, amongst others, specifically aimed at reducing the risk of misreporting. Subsequently, after experiencing some drawbacks, the Dodd-Frank act was introduced to mandate all listed firms to implemet clawbacks and to make firms directly take actions for the execution of such provisions.
This paper examines the effect of adopting clawback policies on the use of adjusted performance metrics (i.e., non-GAAP earnings) in compensation contract. Clawback provisions are initiated in an attempt to recover executives incentive compensation based on misstated financial reports. The recoupment provisions are supposed to diminish managers’ incentive for income-increasing earnings management by increasing the cost of misreporting. Due to the increased cost, the expected benefits of misreporting will decrease, thereby reducing likelihood of earnings manipulation. However, while the instruments for earnings manipulation are constrained after clawbacks adoption, managers’ self-serving motivation inherent in incentive compensation does not necessarily change. So, managers have reacted to regulatory influences by finding alternative ways to gain monetary benefits from inflated compensation tied to reported performance. Consistent with long-held concerns about managers’ opportunistic motives, for example, researchers document evidence that after
adoption of clawbacks, managers are more likely to use alternative ways of earnings management to draw more favorable picture of earnings and inflate their own compensation tied to those numbers.
In sum, since agency problems associated with incentive compensation still remain, different ways to push high compensation manifest as unintended consequences of a clawback provision adoption. As stated above, one way of blowing up compensation is substitution between earnings management techniques. That is, managers at clawback adopting firms may substitute one earnings management such as accounting accruals manipulation for real transaction management that is viewed less risky and less likely to be seen improper by regulators (Chan et al. 2015). Alternately, choosing other performance measures (i.e., non-GAAP earnings metrics) for their compensation contract may be preferred by managers. Because of the removal of some line items (e.g, income-decreasing expense items), non-GAAP earnings is typically higher than non-GAAP earnings, and therefore can lead to greater compensation relative to payout tied to GAAP earnings.
1.2 Research Question
Under the assumption that the introduction of clawback policies does not affect the self-serving behavior of individual managers, the introduction of clawback policies affect the cost of misreporting and can make managers search for alternative ways of inflating their compensation. Prior research documented that by switching earnings management method from accrual-based to real activities management, managers could maintain ability to adjust reported performance on which their incentives are based (Doyle et al. 2013). But, instead of directly increasing reported performance by manipulating earnings, they can switch performance evaluation measures from GAAP earnings to non-GAAP earnings measures. That is, managers are more likely to use non-GAAP performance metrics in compensation contract since GAAP earnings generally tend to be higher than GAAP earnings. As non-GAAP earnings are frequently used when managers try to improve reported performance or camouflage GAAP loss, managers are likely to take advantage of discretionary characteristics of non-GAAP earnings measures to inflate their compensation. This paper, therefore, examines the effects of clawback provisions adoption on the use of non-GAAP performance metrics in compensation contract and answers the following research question:
RQ: Is the introduction of clawback provisions associated with the increased use of non-GAAP performance measures in incentive compensation contracts?
1.3 Relevance of the question
This paper makes several contributions to the existing literature. First, this study contributes to the literature that links incentive compensation to the choice of performance measures when applicable law or regulations are in place. Despite the growing attention to executive pay and non-GAAP earnings disclosure, little evidence exists on the association between the change in compensation contracting and the use of non-GAAP earnings metrics after voluntary adoption of clawback provisions. Prior studies examine the relation between clawback provisions and executive compensation and/or governance structure (Earle 2010; de Haan et al. 2013; Iskandar-Datta and Jia 2013; Chen et al. 2015; Kroos et al. 2017; Natarajan and Zheng 2017) or study the association between compensation contract and earnings management and/or non-GAAP earnings metrics in isolation (Amstrong et al. 2012; Bansal et al. 2013; Isidro and Marques 2013; Chen et al. 2015; Guest et al. 2018). However, none of these studies directly examines how adopting clawback provisions impact the design of executive compensation contracts, and subsequently the potentially opportunistic use of non-GAAP metrics in those compensation contracts.
Among prior studies related to this paper, Black et al. (2018c) would be most closely related. They find that the internal use of non-GAAP performance metrics in compensation contracting is positively associated with the external reporting of non-GAAP earnings to shareholders. They suggest that it is likely to improve reporting quality and earnings credibility to investors and lead to less aggressive non-GAAP reporting when non-GAAP metrics are used for both purposes. However, they do not further examine the influence of managers’ opportunism on the use of non-GAAP numbers when other earnings management techniques are risky. This study is focused on how clawback provisions adoption affects the use of non-GAAP earnings in performance evaluation as alternatives to inflate mangers’ compensation.
This study also features a societal contribution. That is, when developing regulation, regulations have to trade-off the costs imposed on firms due to increased bureaucracy for the benefits of regulation, as well as the unintended consequences of regulation. The results of this study speak to this as it should help regulators predict the unintended consequences of
impending mandatory clawback adoption, and, in particular, develop a better understanding about how managers’ potential self-serving motivation may impact the use of non-GAAP earnings measures in compensation contract.
1.4 Structure of the thesis
The remainder of this paper is organized as follows. The second section reviews the literature and develops the hypothesis. The third section discusses the sample, and the fourth section describes empirical models and variable measurement. The fifth section discusses the descriptive statistics and the findings of this study. The sixth section concludes and provides limitations.
2 Literature review
2.1 Agency theory and Regulation
Separation of ownership and management and agency costs
In the modern corporate environment, the separation of ownership and management has led to the rise of many large publicly held firms known for their products by large shares of consumers. The benefits of the separation of ownership and control are that shareholders can diversify risks and benefit from professional management. At the same time, however, agency problems inherent in the separation structure may arise (Jensen and Meckling 1976; Lambert 2001; Wells 2010). One of the most common problems is misalignment of interests between shareholders and managers, which might induce manager’s opportunistic behavior to seek short-term benefits rather than to improve long-term firm value. This problem is amplified when there is information asymmetry. This refers to situations where managers have an informational advantage relative to corporate outsiders such as shareholders or debtholders. Given that managers have more critical information than diffused shareholders, they thus could utilize this information to make self-centered decisions.
In order to alleviate the problems described above, firms generally incentivize managers by designing incentive compensation contracts where they contract on available (financial) performance measures. On the one hand generous pay packages motivate managers’ productive efforts, but on the other hand self-interested managers may now be incentivized to engage in firm value-decreasing behaviors such as accounting manipulation or misreporting in an attempt to increase their incentive compensation (Abernethy et al. 2017; Bergstresser and Philippon 2006; Dechow and Skinner 2000; Healy 1985; Platt and McCarthy 1985). The latter may lead to more serious consequences since not only is high compensation provided at shareholders’ expense (Gavin 2003), but also these behaviors could deteriorate long-term health of company in the event of, for example, restatement. As a result of potential detriments, the level and design of compensation packages have come under close scrutiny by regulators and public (Fried and Shilon 2011; Murphy 2012). In addition, the question of how to best measure and report performance for both internal contracting and external reporting has long been discussed (Lambert 2001).
In order to mitigate the potential risks associated with agency costs and compensation contract, after several accounting manipulation and financial reporting scandals, Sarbanes-Oxley Act (SOX) was enacted in 2002 as part of regulatory solutions. SOX included a variety of new rules to increase disclosure requirements and to heighten civil and criminal penalties for misreporting. For example, SOX also included provisions on mandated disclosure of a set of internal control procedures, all material off-balance sheet items, adequacy of the company’s internal control on financial reporting (ICFR), and whistleblower-protection, among others. For provisions closely related this paper, in particular, Section 304 of SOX (i.e., a clawback provision) enabled the Securities Exchange Commission (SEC) to recover all the incentive pay awarded to the CEO and the CFO in the event of a required accounting restatement as a result of misconduct. It aimed to ex ante reduce managers’ likelihood of engaging in accounting manipulation or intentional misreporting, and ex post penalize them by recoupment of excess pay if they get caught.
Another regulatory influence relevant to this study is Section 401(b) of SOX. The US congress included this specific provision on non-GAAP performance metrics in SOX to place limitations on fairly less regulated non-GAAP reporting. Following the congressional directive, the SEC implemented Regulation G in March of 2003 to tightly regulate non-GAAP disclosure and put relatively more emphasis on GAAP performance metrics. In response to this new regulation, firms changed their reporting practice, which led to a decline in the proportion of firms’ non-GAAP reporting (Entwistle et al. 2006b), frequency and magnitude of exclusions (Marques 2006; Heflin and Hsu 2008), an improvement in the quality of exclusions (Entwistle et al. 2006b; Kolev et al. 2008), and an increase in users’ perception of non-GAAP metrics credibility (Marques 2006; Black et al. 2012). However, although there was temporary decrease in the frequency of firms’ non-GAAP reporting right after Regulation G, the use of non-GAAP earnings has proliferated again and are increasingly reported in firms’ earnings announcements.
Subsequent to the financial crisis in 2008-2009, regulatory changes were initiated with regard to both clawback and regulation on non-GAAP disclosure. Specifically, Dodd-Frank Act of 2010 added a new provision that mandates every publicly traded firm to put in place a clawback policy. As for non-GAAP reporting, the SEC issued Compliance and Disclosure Interpretations (C&DIs) on non-GAAP earnings in January of 2010 to provide more specified guidance about how regulation applies to reporting practice, thereby mitigating the risk of managers’ opportunistic use.
2.2 Adoption of clawback provisions
History of clawbacks
Section 304 of the Sarbanes-Oxley Act of 2002 (SOX) included requirements for CEOs and CFOs of public firms to reimburse (1) any bonus of other incentive-based compensation received from the employer and (2) any profits realized from the sale of securities of the issuer when the firms’ financial reports are required to be restated because of a triggering event. Because of ambiguities in this law and the limited capacity of the SEC relative to the demanding procedure of the clawback of those excessive gains, however, clawbacks have rarely been enforced. To overcome this pitfall, Section 954 of the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010 mandates all listed companies include clawback provisions in executive compensation contracts. DFA differs from SOX in several terms. For example, DFA extends a period of time prior to a clawback’s triggering event to the 3-year period whereas the “look-back” period under SOX is just 12-month period. This extended look-back period increases further managers’ misreporting costs by enabling firms to recapture erroneously awarded performance-based compensation even several years after managers’ undesirable conducts (Babenko et al. 2017). Moreover, DFA does not limit the restatement to the case related to fraud, and shift the enforcement responsibility for compensation recovery policies from the SEC to the individual firms. To date, the SEC has yet to provide guidance for the implementation of mandated clawback provisions, the growing number of companies have voluntarily adopted clawback provisions in the interim, with differences in covered NEOs and recoupment triggers, ranging from financial restatement, materially inaccurate financial statements, material noncompliance under the securities laws to ethical misconducts, poor management, and excessive risk-taking.
Financial reporting quality and clawbacks
The uncertainty regarding composition of clawback provisions and resulting implications of voluntary adoption have motivated researchers to examine the real effects of clawback adoption. One set of studies reports the findings that support an improvement in financial reporting quality, corporate governance, and other firm outcomes following clawback adoption. These findings are generally consistent with the publicized intent of clawback provisions under SOX. For example, deHaan et al. (2013) find evidence of decrease in meet-or-beat behavior and unexplained audit fees for clawback adopting firms and suggest that
actual financial reporting quality increases following clawback adoption. Because an effective clawback provision increases managers’ cost of being caught by enabling firms to recover ill-awarded performance-based compensation even after managers leave the firm, this provision triggered by predefined events can decrease executives’ incentives to intentionally manipulate financial statements and encourage efforts to avoid unintentional errors. Thus, clawback adoption leads to the improvement in financial reporting quality. Similarly, researchers also document an improvement in perceived financial reporting quality after clawback adoption. They observe a significant increase in earnings response coefficients and a decrease in analyst forecast dispersion, relative to propensity-matched control firms. In a similar vein, Chan et al. (2012) find increase in firms’ earnings response coefficients and lower audit fees and audit lag and, hence, suggest that not only investors but also auditors welcome such provisions as associated with improved financial reporting quality. More specifically, based on previous research reporting the association between poor firm governance and material internal control weakness, these authors expect and find evidence that managers at adopting firms will have more of an incentive to enhance the internal control of the firms, and in turn auditors will perceive adopting firms as having lower material internal control risk. Additionally, consistent with these findings, Chen et al. (2015) document significant decrease in restatement frequency and abnormal accruals after adopting clawbacks. These authors, however, employ several new empirical methods (e.g., fixed-effect regression) to address concerns about potential endogeneity issues, rather than using difference-in-difference design and a propensity-matching method that other studies on clawback usually employ to reduce the similar concerns about omitted time-variant variables or market-wide influences. Regarding accounting restatement, all of the studies above find the declines in the post-adoption period. However, as several researchers (Chan et al. 2015; deHaan et al. 2013; Denis 2012) noted, a reduction in accounting restatement subsequent to clawback adoption should be interpreted with caution. If managers are reluctant to disclose amended financial statement in an attempt to avoid triggering clawbacks or auditors reduce effort to detect such irregularities, a decrease in the occurrence of financial misstatement after clawbacks adoption would not necessarily be the effect of clawback provisions.
Unintended consequences of clawbacks
Although much research supports the positive association between clawback initiation and enhanced corporate governance and resulting a increase in financial reporting quality, some
researchers question as to whether such provisions might lead to consequences that are not planned. Because it’s often the case with narrow and well-intended regulations, there may be negative consequences associated with clawbacks adoption. Researchers find that firms may switch earnings management from one method to others such as real methods following regulations. As prior accounting literature shows, accrual manipulation (Burgstahler and Eames 2006; Dechow et al. 2003) and real activities manipulation (Roychowdhury 2006; Gunny 2010) are two most commonly used tools to exceed analyst forecast. Therefore, those two methods can substitute each other depending on the firm-specific situation. Earlier in 2008, for example, Cohen et al. suggest that real transactions management is possibly less likely to be detected and may induce switching in earnings management technique after the passage of SOX. Pointing out that real transactions management is likely to be more costly to shareholders as this management represents a deviation from optimal business practices, the authors raise the concerns over real benefits of the new regulation. Chan et al. (2015) also explore the possibility of substitution between earnings management techniques and find similar evidence. Cohen et al. (2008) examine the effects just after the passage of SOX, whereas Chan et al. (2015) examine specifically the effect of clawback provisions. They suggest that clawbacks discourage managers from using accrual-based earnings management, and, instead, lead to an increase in real transactions management (e.g., reduction in expenditure, such as R&D spending, discretionary operating expenses). That is, while high accounting accruals are more likely to attract increased attention from the SEC and auditors because high accruals are often related to financial restatement (Dechow et al. 2010), real transactions management is viewed less risky and less contentious relative to accruals management. That is because this management is less likely to be considered inappropriate by regulators and auditors. The authors further find that adopting firms, relative to non-adopters, with higher growth opportunities or higher transient institutional ownership and managers under greater pressure to meet short-term earnings goals are more likely to engage in real transactions management.
Similarly, Doyle et al. (2013) and Black et al. (2017) broaden this substitution tendancy of firms to the association with the use of non-GAAP earnings disclosure. They report that firms are more likely to take advantage of discretionary characteristics of non-GAAP earnings disclosure when accrual or real earnings management is risky. This latter substitution may suggest the possible association between the use of non-GAAP earnings measures and increased risk of earnings management under GAAP after clawback adoption.
Unintended consequence following clawback adoption is also witnessed in the level and structure of compensation contract. Several studies document higher total compensation level after implementation of clawback policies (deHaan et al. 2013; Chen et al. 2015; Babenko et al. 2017), suggesting that clawback-adopters may need to compensate managers for their increased risk to maintain the overall attractiveness of their pay packages. While deHaan et al. (2013) and Kroos et al. (2017)1 find increase in base salary, Chen et al. (2015) and Babenko et al. (2017) report increase in performance-based compensation. Iskandar-Datta and Jia (2013), however, find no evidence of higher CEO compensation or change in design of compensation following adoption. This increased level of compensation may imply a trade-off between reduced risk of opportunistic behaviors and increased needs for incentivising productive effort.
In sum, the adoption of clawback provisions appears to effectively mitigate the risk of financial misreporting either with or without managers’ intention, thereby increasing investors’ confidence in financial information. In response to these expectations, many firms have voluntarily adopted clawbacks. According to Equilar, a consulting firm providing board intelligence solutions, roughly 92% of S&P 500 companies disclosed a clawback policy in 20162. However, as shown in the unintended consequences of clawbacks and uncertain causal linkage between clawback adoption and the frequency of restatement, whether clawback adoption does actually reduce managers’opportunism motivation and earnings manipulation is still an open question.
2.3 The use of Non-GAAP earnings measure
Non-GAAP performance measures in external earnings disclosure
The number of companies reporting non-GAAP earnings has increased over the last decade (Young 2014; Black et al. 2018a). Although there is not a single, uniform definition for non-GAAP disclosure, generally accepted definition of non-non-GAAP earnings is “company’s reported earnings adjusted to exclude nonrecurring and one-time items”. Because of this absence of clear definition, there are different types of non-GAAP earnings. In academic
1 Their research is focused on CFO compensation.
http://marketing.equilar.com/35-2017-executive-compensation-studies, I/B/E/S earnings, pro forma earnings and non-GAAP (diluted) EPS are commonly used. Besides, other variants such as EBIT, EBITDA are also defined non-GAAP earnings metrics, but they are rarely used for research since those metrics use different bases.
Based on this discretionary exclusion characteristic of non-GAAP earnings, one major stream of prior literature examines what specific items are commonly excluded. Among others, depreciation and amortization and stock-based compensation are frequently excluded items (Bhattacharya et al. 2004; Black et al. 2017). Specifically, Black et al. (2017) find that items related to investments and amortization of intangible assets are most commonly excluded. This finding is slightly different from previous research, and that is probably because they examine a quite recent time period (from 2009 to 2014). Although there are frequently excluded items, calculation of non-GAAP earnings usually varies across firms since managers have considerable freedom to decide items excluded from non-GAAP earnings. As a result, it may result in inconsistency in non-GAAP earnings measures even within the same firm and make proper financial comparison across firms or over a period of time difficult (Black et al. 2017; Halsey and Soybel 2002; Gavin 2003).
Concerns over considerable discretion in definition and the use of non-GAAP metrics motivate researchers to examine the motives of non-GAAP earnings disclosure. However, the evidence regarding managers’ motivation behind non-GAAP reporting is mixed (Entwistle et al. 2006a; Frankel et al. 2011; Shiah-Hou et al. 2016).
One side of conflicting views is informativeness motive. Researchers advocating this motive argue that managers disclose non-GAAP earnings to better inform investors of the firm’s real operating performance. Since GAAP financial information is prepared in accordance with a set of standards, it ensures consistency, reliability, transparency and comparability. Nevertheless, because earnings on GAAP basis reflect every periodic accounting change, some managers complain that the influence of those items are not relevant to firm’s core operating performance and that, therefore, one-time and nonrecurring items should be factored out. Managers, in turn, often disclose non-GAAP earnings as a supplement to GAAP earnings (Bhattacharya et al. 2003; Lougee and Marquardt 2004). Consistent with this view, Harsey and Soybel (2002) report that, by excluding one-time and/or non-operating items, non-GAAP earnings enhance consistency of earnings. Black et al. (2018a) review the extant dataset of detailed non-GAAP disclosure and suggest that non-GAAP earnings are useful for both valuation and compensation contracting.
In addition, Bhattacharya et al. (2003) support this informative reporting motivation by examining the needs for adjusted earnings of other market participants. They show that not
only do managers report non-GAAP earnings, but also other market participants (e.g., investors, analysts) demand and/or supply non-GAAP metrics.
By contrast, proponents of opportunistic motive empathize that managers use non-GAAP earnings disclosure to manage earnings and achieve benchmark. Consistent with agency theory and information asymmetry, managers may utilize private information and the discretion on non-GAAP earnings metrics to inflate their compensation. Moreover, this strategic non-GAAP disclosures might mislead investors and decrease shareholder value. The findings of prior research show evidence that managers are likely to report non-GAAP earnings to present more favorable earnings profile (Bhattacharya et al. 2003; Walker and Louvari 2003; Black and Christensen 2009; Doyle et al. 2013; Isidro and Marques 2013; Black et al. 2017). Specifically, Doyle et al. (2013), for example, compare firms using income-increasing exclusions to control firms reporting just GAAP earnings and report that managers opportunistically adjust non-GAAP earnings in order to meet or beat analyst expectations. They also find evidence of substitution between accrual earnings management and non-GAAP earnings exclusion. Similarly, Bentley et al. (2018) examine the gap between non-GAAP earnings reported by managers and the numbers reported by analysts and suggest that managers may opportunistically exclude more items than analysts do, resulting in the difference between those numbers. They also document that increasing number of firms exclude recurring items, especially when firms want to camouflage GAAP loss. Additionally, Chan et al. (2012) examine how auditors view non-GAAP disclosures and find the association between opportunistic non-GAAP earnings disclosures and higher audit fees and higher auditor resignation.
Non-GAAP performance measures in internal compensation contract
Most commonly used performance measures in executive compensation contract, among financial performance measures, are accounting-based metrics (e.g., EPS, Net Income) and market-based measures (e.g., stock price). Because performance-based compensation is associated with agency costs, the determinants and choices of performance measures in incentive compensation contracting have drawn attention from researchers and public. That is, depending on how to mix and adjust relative weights of such measures, compensation contract may mitigate agency conflicts and effectively incentivize managers productive efforts at the same time. Thus, the use of accurate performance measures is critical for the design of compensation contract. Also, since the level of executive compensation is usually excessively
higher than those of ordinary employees and significantly related to shareholders value, compensation committees are required to report the pay packages of their top executives and the metrics on which they arrive at the final numbers.
With this background, an increasing number of firms expand the use of non-GAAP earnings measures into their internal compensation contracting (Black et al. 2018b,c; Curtis et al. 2017; Grey et al. 2013). Like opposing views on the use of non-GAAP earnings for external performance reporting, there are two contrasting perspectives on the use in compensation contract. Supporters report that the use of adjusted earnings allows efficient contracting by excluding effects of events beyond managers’ control. For example, Bansal et al. (2013) find that managers with higher stock-based compensation to vega are more likely to disclose non-GAAP earnings with higher quality. Curtis et al. (2017) use more firm-oriented approach and examine the association between determinants and consequences of the use of non-GAAP measures and future firm performance. Their results support efficient contracting view. Black et al. (2018) further examine the effects and association of the use of non-GAAP measures for two different purposes. They find the positive association between non-GAAP EPS use in the proxy statement and the use of non-GAAP EPS in the earnings announcement and conclude that overall quality of non-GAAP earnings reporting improves when both the board and the manager use non-GAAP performance metrics.
On the other hand, critics argue that the use of adjusted earnings can encourage powerful managers’ opportunistic behaviors when they camouflage their actual performance in order to artificially increase their compensation payout. In addition, performance measures in compensation contract such as accounting numbers and stock-price are generally decided by following firm’s customary practice (Murphy and Oyer 2001), managers are more likely to affect the compensation practice to skew for their own interest. For example, Pozen and Kothari (2017) take a deeper look at this opportunism motivation by thoroughly examining the 2015 compensation committee reports of well-known companies. They find that large portions of cash bonus and long-term incentive compensation are calculated on a non-GAAP basis in the CEO’s favor. They also report that non-GAAP earnings are usually adjusted in complex and inconsistent ways to inflate performance numbers, and that excluded items, in many cases, tend to be recurring income-decreasing expenses. In line with these findings and increased public concerns over nonstandard measures, Guest et al. (2018) examine CEO pay for the S&P 500 firms and the correlation between firms’ non-GAAP earnings and contemporaneous stock returns. They document that board of directors are influenced
significantly by positive non-GAAP earnings adjustments in approving a higher level of CEO pay that would otherwise not be supported by GAAP earnings or the firm’s stock price.
2.4 Hypothesis development
The findings of the extant research show that the adoption of clawback provisions are generally associated with higher financial reporting quality by reducing managers’ incentive for earnings management, and thus improving informativeness of accounting statements. For instance, managers are more likely to prepare financial reporting in accordance with GAAP to avoid triggering events. If managers manage reported earnings beyond GAAP to inflate firm performance and their bonuses tied to it, regulators or auditors may intensify scrutiny over accounting statements. As a result, it would increase the likelihood of misstatement and, thus, the gains from opportunistic behavior may be much lower than the costs they have to pay if got caught. As such, clawbacks can curtail, at least in part, managerial opportunism associated with incentive compensation.
Clawback provisions, however, might not address all the possible problems inherent in incentive compensation. First, managers’ self-serving incentives can remain even if there were regulations in place. As Shiah-Hou and Teng (2016) show that some managers may exclude recurring components to reach at strategic non-GAAP earnings even after the SEC intervention, managers may continue to manage earnings to inflate their compensation in the post-clawback period. Furthermore, increased level of compensation at some clawback adopting firms may indicate that financial compensation is still a strong and critical incentive for managers after clawback adoption. Second, managers are more likely to continue engaging in opportunistic behavior, particularly when there are alternative tools that are useful, but less subject to regulations. For example, substitution between earnings management techniques after adopting clawback provisions (Chan et al. 2015) can be one illustration. Consistent with this behavior, Kolev et al. (2008) find similar substitution in the non-GAAP regulation case. They report that, although intensified scrutiny over non-GAAP disclosure discourages at least some opportunistic motivation, managers may adapt to the new regulation (i.e., Regulation G) by shifting more recurring items into special items. Evidence that managers are more likely to report non-GAAP earnings when GAAP earnings do not meet or beat earnings targets, also, supports the idea of using alternatives to achieve desired financial reporting targets and increase their compensation.
As unintended consequence after the implementation of clawback provisions, managers may switch from accruals-based earnings management to real transactions management. Besides that, they increase the use of non-GAAP earnings instead. Because the increased cost of using accrual-based management, which is subject to clawback provisions, and constrain the available tools managers can use to manage earnings, the need to use alternatives, which are relatively less subject to clawbacks, increases. Therefore, as long as it is assumed that managers’ opportunistic motivation is maintained and that available alternatives exist, it is intuitive that managers – to the degree that they are able to influence the choice of performance measures in their incentive contracts – may also substitute performance measures in their compensation with other non-GAAP measures that serve their purpose of inflating their compensation. As an illustration of how managers may be able to influence the performance measures in their incentive contracts, Morse et al. (2011) show how CEOs are able to ex-post shift the weight towards the better performing performance measures. With respect to the choice between GAAP and non-GAAP earnings, since non-GAAP earnings are typically higher than GAAP earnings, managers may benefit more by using non-GAAP measures in compensation contract tied to accounting performance. On the basis of the aforementioned, the hypothesis is formulated as follows:
H1: The adoption of clawback provisions has positive association with the increased use of non-GAAP earnings measures in executive compensation contracts.
3 Data collection and Sample selection
3.1 Agency theory and Regulation
I manually collect the data of the clowaback provisions adoption and the use of non-GAAP performance measures from firms’ annual proxy filings in the SEC’s EDGAR database from 2007 through 2013. The detailed process of collecting data is illustrated below. This noble set of hand-collected empirical data gives me enrich understanding of firms’ general executive compensation contracting and implementation of such provisions as clawbacks.
Clawback adoption data
I start with an initial set of publicly traded firms that belongs to the S&P 1500 from 2009 to 2011. Since a limited number of firms voluntarily adopted clawback provisions prior 2008 and 52 % of S&P 1500 firms adopted clawbacks in 2011, this sample period allows us to observe a significant change in trend of firms’ voluntary clawback adoption. Financial firms (SIC code 6000-6999) are excluded from the initial sample because many of these firms in the US are participants of TARP (Troubled Asset Relief Program) during the financial crisis and thus are subject to mandatory clawback provision. Because such firms could be under additional provisions and limitations, including those firms in the sample may influence the results. Among the remaining firms, I randomly select a firm and search the text of each proxy statement (SEC form DEF 14A) from January 1, 2007 through December 31, 2013 for words indicating that the firm has a clawback provision for the first time. By repeating this process, I collect 50 firms for each year from 2009 to 2011, which leads to a set of 150 new clawback adopting firms during that period. The search process is based on keywords and also all particularly or partially relevant textual variances of these keywords such as “clawback,” “claw,” “recoup(ment),” “recover(y),” “recapture,” “reimburse(ment),” “forfeit(ure).” Based on the initial set of keywords identified, I further read firm’s disclosures to ascertain the nature of a clawback provision and select only such provision that is relevant to this study. After carefully reading contents related keywords, I exclude provisions that are not triggered by financial restatement (e.g., recoupment rules just pertaining to noncompete violations, poor performance, or termination of contract), but include both “robust (i.e., triggering events are not limited to misconduct)” and “misconduct (i.e., only restatement related to fraud or other illegal behavior)” provisions. I also exclude provisions that simply replicate requirement in
Section 304 of SOX, as well as provisions that cover other NEOs except CEO. When each of remaining provisions meets such criteria, I gather data on the date that the provision was first disclosed, and the adoption year and month (if available). Finally, to ensure the accuracy of hand-collected data, I randomly check a subset of full sample.
Selecting and matching control firms
Since this paper examines the effects of voluntary adoption of clawback provisions on the choice of performance measures in compensation contract, this could raise endogeneity concerns. That is, as other studies that examine a discretionary adoption of new governance mechanism, there is a concern that the results may be affected by unobserved factors that are correlated with both clawback adoption and outcome variables of interest. Therefore, the empirical model should be able to reduce the effects of omitted variables associated with clawback adoption that might be associated with dependent variable (i.e., change in the use of non-GAAP performance measures in compensation contract). To address this issue, this study uses a difference-in-differences (DID) methodology for analyzing changes in the use of non-GAAP performance measures before and after clawback adoption.
To employ a difference-in differences design method, I select the control firms using fundamental logics of a propensity-matching method. Propensity-matching method helps me to control for observable variables that determine clawback adoption and hence reduce concerns about selecting dissimilar control firms (deHaan et el. 2013; Kroos et al. 2017; Roberts and Whited 2012). However, since running a logistic regression to predict the propensity score is not possible due to the lack of clawback adoption information for every firm in the initial set of sample, I also use manual collecting method for propensity matching. To ensure reasonable assurance that treatment and control firms are balanced after manual-matching process, I use firm size and industry as the key variables to select matched control firms that had the similar trends in dependent variables prior to clawback provision adoption. In particular, prior research identifies firm size as one of the most critical determinants of clawback adoption. Following this finding, for each of treatment firms identified by keyword searching, I narrow down firms in Russell 3000 to a subset of firms that have total asset in a range between 70% and 130% of total asset of the treatment firm (i.e., clawback adopting firm). I also filter this group of control firm candidates by industry to exclude firms performing in a different business environment. Firms that have the same first two-digit SIC
code remain in the filtered set. For these remaining firms, I check the firms’ proxy statements to include only firms that never had clawbacks in place 2 years before and after the year when a treatment firm adopted clawback provisions. Lastly, among the remaining firms that have never adopted clawback provisions in 5 consecutive years, I choose one firm in closest to the treatment firm in terms of firm size. I match control firms to each of treatment firms without replacement. The total number of matched pair is 116 and 1158 firm-year observations.
Non-GAAP performance measures data
In order to collect the data on the use of non-GAAP performance measures in executive compensation contracts, I also manually collect details of the data from firms’ annual proxy filings (DEF 14A). I hand-collect the data on CEO compensation contract of selected clawback adopting firms and control firms matched to the treatment firms by using keyword searching. The search process is basically the same as the process for collecting clawback adoption information. I, firstly, search for keywords such as “non-GAAP,” “Pro forma,” adjusted,” ”exclude,” and variations3 of such words in executive compensation section in firms’ proxy filings. Then I read the contents that are relevant to incentives to make sure whether the measures of performance is for CEO and for short-term based incentives. This paper specifically examines the effect of clawback adoption on, among other NEOs, CEO compensation contract. Because I randomly select clawback adopting firms, which means that I cannot control for clawback policy coverage in data collecting process, focusing on the most common clawback provisions increases the number of observation available for analysis. Also, like most prior studies on executive compensation contract, I focus on short-term CEO incentive contract for empirical analysis. Because long-term incentive plans are usually the same for a long-term period(e.g., 3 year-long equity award plan), relative to short-term bonus incentive, it may be difficult to observe directly related changes in executive compensation between before and after the adoption of clawback provisions. In contrast, performance goals and measures for the short-term bonus incentives are generally determined by the compensation committee on a yearly basis. Thus, I focus on short-term incentive compensation for this study.
When the performance measures in the proxy statements are to determine short-term CEO incentives, I read the contents and compensation summary tables to identify non-GAAP
performance measures that are proper for this study. From the reading of compensation contracts, I identify two types of adjusted numbers as non-GAAP earnings metrics from the firms’ proxy filings. The first type of non-GAAP measures is adjusted numbers that are explicitly named adjusted EPS/Net Income/earnings”. The second type of non-GAAP measures is adjusted numbers that are not directly named adjusted” numbers, instead accompanied by additional explanations or notes. As there are not uniform definitions of non-GAAP metrics, it is important to clarify the non-non-GAAP measures that are used for empirical tests in this paper. Based on adjusted numbers identified in the proxy filings, I define non-GAAP earnings performance measures as the extent to which unusual, one-time expenses and/or gains are excluded. The common non-GAAP performance measures are categorized into three types : (i) “adjusted/core“ Net Income, Earnings, Pre-Tax Income, Operating Net Income, Net Profit After Tax, EBIT(DA), EBT, Pre-Tax-bonus Income, Revenue, (ii) “adjusted /Core/ Base business/ Currency-neutral/ Pro forma“ EPS, (iii) ROIC (Return on Invested Capital), adjusted ROE, FFO (Funds from Operations), FCF (Free Cash Flow), Net Debt.
From the initial 1,158 firm-year observations with 236 propensity matched pairs, but 630 observations were excluded as there are missing data on Audit Analytics, ISS, and Execucomp. The final sample is composed of 528 firm-year observations of the 67 pairs of firms.
For other data needed for the empirical analysis, I obtain data from WRDS database: data on firm financial characteristics from Compustat, Executive compensation form ExecuComp, board structure and audit from Audit Analytics, Stock returns form CRSP.
4 Research Design
In this chapter, I describe the empirical models used to test my hypothesis, and illustrate the main variables of interest. I also include how I measure control variables in the models.
4.1 Empirical models
Two different models are used to examine the effects of firm-initiated clawback adoption on the use of non-GAAP earnings performance measures in CEOs compensation contracts. The first model looks at the effects of clawback adoption within the company.
The regression equation for the first model is formulated as follows:
NONGAAPi,t = α0 + α1ADOPTi + ΣαkCONTROLSi,t + εi,t (1),
where NONGAAPi,t is binary variable equal to one if non-GAAP earnings measures
are used in performance evaluation for executive compensation at company i in year t, zero
otherwise. ADPTi is defined as an indicator variable equal to one if the firm has clawback
provision in place in year t, zero otherwise. The coefficient α1 represents the difference in the
use of non-GAAP performance measures for firms that have adopted a clawback vis- à-vis firms that have not. Based on my hypothesis, I expect α1 > 0.
In the second model, this paper takes a common approach to address self-selection concerns and use a difference-in-differences (DID) methodology. As noted above, given that firm have discretion whether or not to adopt clawback policies, adopting firms may differ from non-adopters in many characteristics in addition to decision on voluntary clawback adoption. The DID methodology allows me to distinguish the effects of a clawback adoption from the effects of market-wide or unobserved time-invariant factors that may drive changes in the outcome variables (i.e., change in performance measures for executive compensation contract). In addition, propensity-matching methodology helps to compose a control firms that have similar characteristics except for the fact that the control group did not have clawback provisions in place during the sample period.
The regression equation for the second model is as follows:
NONGAAPi,t = α0 + α1CLAWi + α2AFTERi,t + α3CLAWi*AFTERi,t + ΣαkCONTROLSi,t +
Where CLAWi is an indicator variable equal to one if the firm i adopts a clawback
provision at one point during my sample period, zero otherwise, and AFTERi,t is an binary
variable equal to one for firm-years in which clawback adopting firms and control firms have clawback provisions in place, zero otherwise (Even though a control firm has never adopted a clawback, each control firm is assigned a pseudo adoption year which is the same year when the matched treatment firm implemented a clawback provision). The CLAW variable indicates constant differences between treatment firms and control firms, while the AFTER variable controls for characteristics common to both the treatment and the control firms. CLAW*AFTER indicates the difference-in differences estimator of the effect of clawback adoption on the change in the performance measures of compensation contract, especially from GAAP measures to non-GAAP measures. The sum of coefficients α1 + α2 + α3 denotes
the effect on the change in the use of non-GAAP performance measures in executive compensation for adopting firms after the treatment. The coefficient α1 reflects the association
with the adopters before the treatment, while α2 shows the effect on the change in non-GAAP
measures for control group after the treatment. Thus, coefficient of interest is α3, which
represents the change in the use of non-GAAP performance measures in compensation contract for adopters after adopting clawback provisions, relative to the change for non-adopters. In this paper, the expected coefficient α3 ispositive. Compared to equation (1),
which is used to test the effect of clawback adoption within adopters or within the adopting firms, equation (2) focuses on the difference between the effect on adopting firms and the effect on nonadopters. Outcome variable NONGAAP is an indicator variable equal to one if any kind of non-GAAP measure is used in evaluating performance for executive bonus incentive in the firm-year, zero otherwise. This variable captures the effects of treatment on determining incentive compensation for CEO. All variables used in the models are defined in Appendix C.
Another empirical model test the year-to-year change in performance measures for executive compensation. The descriptive statistics of performance measures show that firms change performance measures for short-term incentive on annual basis. The next equation examines the association between clawback adoption and the change in annual performance measures.
CHANGEi,t = α0 + α1CLAWi + ΣαkCONTROLSi,t + εi,t (3),
Where CHANGE is an outcome variable equal to one if the firm changes the performance measure in prior year to other measure in the firm-year t, and CLAWi is an
indicator variable equal to one if the firm i adopts a clawback provision at one point during my
sample period, zero otherwise. The coefficient α1 represents the difference in the change of
performance measures between clawback adopters and non-adopters. Based on my hypothesis, I expect that clawback adopting firms are more likely to change performance measures, and thus predict α1 > 0.
4.2 Control variables
For the empirical models, I include control variables following prior studies on executive compensation contract and clawback provisions. The control variables in the models are generally categorized into 4 types. Variables in the first type of variables are perceived to impact executive compensation. I include firm size, growth opportunities (Chan et al. 2015; dehaan 2013; Kroos et al.2017) to control for other factors. Firm size is measured by the natural log of the book value of total assets (FIRM_SIZE). Growth opportunities (GROWTH) are measured by the market to book value of equity. In the second type of variables firm age, return on asset, earnings volatility and leverage are included. These variables represent firm complexity and financial condition, and have frequently been included in the models of prior research in order to control for the influence of such a firm’s financial condition on executive compensation. Firm_Age is measured as the number of years a firm exists in the COMPUSTAT database, LEVERAGE is measured as the current plus long-term debt divided by current book value of total assets. Also, the return on asset and the standard deviation of the past three years’ return on assets are included as ROA and SD_ROA, respectively. In addition, accounting restatement in the prior year is included as PRIOR_REST. The other type of control variables is related to CEO characteristics. The number of years the current CEO has been in that position is included as CEO_TENURE to control for CEO power on decision regarding compensation contract. The last category represents the characteristics of a firm’s board. I include control variables about the board since the compensation committees are officially in charge of decisions about executive compensation and the board members approve the compensation contract. I measure board size as the number of board members
(BOARD_SIZE). To control for influence of board independency, I measure the fraction of outside directors on the board as IND_BOARD. In addition, the average number of other boards on which outside directors serve (BUSY_DIR) and the separation of the duties of CEO and chairman through an binary variable equal to one if the firm’s CEO serves as the chairman on the board, zero otherwise (CEO_CHAIR).
5 Empirical results
5.1 Descriptive statistics
The first part of this chapter provides a detailed descriptive analysis of the two main topics of this paper. I present descriptive statistics of hand-collected data on clawback provisions and the use of non-GAAP measures in executive compensation in firms’ proxy filings.
Clawback provisions
Table 1 summarizes the number of observations in the full sample and the number of clawback adopters in the sample for the propensity matching model. Panel B of Table 1 shows the number of clawback adopters by two-digit SIC code. As shown below, adopting firms from across industry are included in the sample, but almost 24 % of adopting firms are computer equipment and service providers. It may reflect the fact that majority of firms in that industry are relatively large in terms of firm size, and thus might had have strong corporate governance, which is identified one of the major determinants of clawback adoption.
Table 1 Descriptive statistics
Panel A: Number of observations
Year Number of observation Number of New Adopters in the final sample, Claw=1 Claw=0 2007 17 13 2008 40 30 2009 63 41 20 2010 64 44 25 2011 61 45 22 2012 46 31 2013 20 13
Panel B: Number of Percentage of Clawback Adopters by Two-Digit SIC Code
Clawback Adopters in the sample
Industry (SIC) Distribution Frequency %
oil and gas (13) 2 3.0%
Building construction (15) 1 1.5%
food products (20) 6 9.0%
Apparel & Fabric (23) 2 3.0%
paper & furniture products (25-27) 3 4.5%
chemical products (28) 3 4.5%
manufacturing ( 39) 1 1.5%
computer equipment and services (35,73) 16 23.9%
electronic equipment (36) 4 6.0%
Transportation (37,45) 2 3.0%
scientific instruments (38) 8 11.9%
Electric, gas, and sanitary services (49) 6 9.0%
Durable goods (50) 5 7.5%
retail (53,56) 2 3.0%
Eating and drinking establishments (58) 1 1.5%
Health (80) 2 3.0%
Educational services (82) 2 3.0%
Engineering, Accounting, research related
services (87) 1 1.5%
Total 67 100%
** Financial Firms (6000 – 6999) are excluded because they are TARP participants and subject to mandatory adoption requirement.
Panel C: Descriptive statistics of 118 pairs of Clawback adopters and Non-Adopters matched by manual comparison
Panel D: Summary statistics (Full sample and by clawback adoption)
Full Sample CLAW=0 CLAW=1
Variable N Mean Std. Dev. N Mean Std. Dev. N Mean Std. Dev. FIRM_SIZE 528 7.81 1.38 217 7.89 1.41 311 7.76 1.36 GROWTH 528 2.87 5.05 217 2.44 2.02 311 3.17 6.35 FIRM_AGE 528 31.79 17.99 217 30.40 16.28 311 32.75 19.06 ROA 528 0.07 0.09 217 0.06 0.09 311 0.07 0.10 SD_ROA 528 0.05 0.06 217 0.05 0.06 311 0.04 0.06 LEVERAGE 528 0.19 0.20 217 0.15 0.16 311 0.22 0.21 PRIOR_REST 528 0.09 0.29 217 0.11 0.31 311 0.08 0.28 CEO_TENURE 528 7.00 6.67 217 8.37 8.27 311 6.05 5.07 BOARD_SIZE 528 9.26 1.97 217 9.29 2.22 311 9.24 1.78 IND_BOARD 528 0.78 0.11 217 0.74 0.12 311 0.81 0.09 CEO_CHAIR 528 0.44 0.50 217 0.38 0.49 311 0.47 0.50 BUSY_DIR 528 0.85 0.44 217 0.82 0.46 311 0.86 0.41 NONGAAP 528 0.75 0.43 217 0.79 0.41 311 0.73 0.44 CHANGE 418 0.22 0.42 172 0.13 0.33 246 0.29 0.45
Table 1, Panel B shows the summary statistics of the main sample. Variables are defined in the Appendix.
5.2 Main analysis
Table 2 reports the logistic regression estimates for the hypothesis tests. Panel A of Table 2 shows the findings for the first model with the full sample, which tests the effects of firm-initiated clawback adoption within the firm. Panel 2 provides the results for the DID model (equation 2) in combination with propensity matching methodology. The results are based on logistic regressions. In order to control for industry and year fixed-effects and address the concerns over unobservable omitted variables, I employ the DID design instead of using other model such as fixed-effect analysis. With regard to control variables, as described
above, I use the fundamental financial characteristics of firms, corporate governance features, and CEO specific characteristics.
In general, the results of regression analysis do not support the hypothesis. For panel A, the coefficient on ADOPT that represents the difference in the relation between the presence of clawback provisions in CEO compensation contract and the use of non-GAAP earnings performance measures between clawback adopting firms and non adopting firms. Therefor, this implies that the independent variable of interest in the equation (1) does not have a significant relation with the more use of non-GAAP performance measures in compensation. While I do not find the association between clawback provisions and the use of non-GAAP earnings performance measures, I find evidence, from the control variables, that the firm uses the non-GAAP performance measures in CEO compensation when the firm is larger, and when the board has more independent directors. In addition, the board size has negative association with the more use of non-GAAP performance measures. The latter relation is consistent with the findings of prior research and the hypothesis in this paper that non-GAAP numbers are less likely to be used when the board is larger and the CEO power is limited.
The DID model (with only matched treatment and control firms based on the estimated propensity) with propensity matched sample firms shows similar, but slightly different results. In general, the regression estimates do not show significant relation between the use of non-GAAP performance measures and clawback adoption when controlling for the effects of unobservable variables. As shown in Panel B of Table 2, firm size and independent board have positive relation with the use non-GAAP performance measures. Also, the coefficients imply negative association between board size and the use of non-GAAP performance measures.
The results of the third model report that clawback adopters change the performance measures in CEO compensation more, relative to non-adopting firms (Panel C).The coefficient on CLAW is positive and significant (p<0.01). Even though the DID model in equation (2) dose not support the hypothesis in this paper, this association imply that adopting firms may need to compensate CEOs for the increased risk after adopting clawback provisions by changing directly compensation amount or the performance measures for evaluation.
Table 2
The use of performance measures in CEO compensation contract and clawback adoptionPanel A: Full sample model
NONGAAPi,t = α0 + α1ADOPTi + ΣαkCONTROLSi,t + εi,t
NON GAAP Variable Predicted Sign Coefficient P-value Intercept α0 -5.624 0.000*** ADOPT α1 + 0.303 0.223 FIRM_SIZE 0.817 0.000*** GROWTH 0.115 0.023* FIRM_AGE -0.011 0.18 ROA -1.762 0.268 SD_ROA 6.089 0.012* LEVERAGE -0.359 0.655 PRIOR_REST 0.585 0.166 CEO_TENURE -0.024 0.16 BOARD_SIZE -0.255 0.001*** IND_BOARD 3.823 0.001*** CEO_CHAIR -0.193 0.446 BUSY_DIR -0.001 0.996 Pseudo R2 0.15 N 528
NONGAAP is a binary variable equal to one for firms with NONGAAP earnings performance measures in executive compensation in firm-year observation, zero otherwise. All other variables are described in Appendix 3. Panel A contains logistic regression results. ***Indicates significance at 1 percent, **at 5 percent, *at 10 percent, based on two-tailed tests.
Panel B: DID model (Propensity-matched sample)
NONGAAPi,t = α0 + α1CLAWi + α2AFTERi,t + α3CLAWi*AFTERi,t + ΣαkCONTROLSi,t + εi,t
NON GAAP Variable Predicted Sign Coefficient P-value Intercept α0 -5.129 0.002*** CLAW α1 -1.441 0.002** AFTER α2 0.306 0.507 CLAW*AFTER α3 + 1.142 0.056 FIRM_SIZE 0.886 0.000*** GROWTH 0.177 0.003** FIRM_AGE -0.022 0.034* ROA -3.494 0.135 SD_ROA 3.572 0.332 LEVERAGE -0.428 0.698 PRIOR_REST 0.649 0.214 CEO_TENURE -0.055 0.011* BOARD_SIZE -0.242 0.006** IND_BOARD 3.247 0.033* CEO_CHAIR 0.026 0.938 BUSY_DIR 0.723 0.071 Pseudo R2 0.23 N 400
This table examines the effect of clawback adoption on the use of non-GAAP earnings measures using DID design model, and Panel B shows logistic regression results. NONGAAP is a binary variable equal to one for firms with NONGAAP earnings performance measures in executive compensation in firm-year observation, zero otherwise. Industry and year fixed effects are included. All other variables are described in Appendix 3. ***Indicates significance at 1 percent, **at 5 percent, *at 10 percent, based on two-tailed tests.
Panel C
:
The year-to-year change in performance measures for CEO compensation contract and clawback adoptionCHANGEi,t = α0 + α1CLAWi + ΣαkCONTROLSi,t + εi,t
CHANGE Variable Predicted Sign Coefficient P-value Intercept α0 -4.688 0.001** CLAW α1 + 1.037 0.000*** FIRM_SIZE 0.207 0.132 GROWTH -0.033 0.428 FIRM_AGE 0.001 0.909 ROA -2.270 0.163 SD_ROA -1.204 0.634 LEVERAGE -1.386 0.103 PRIOR_REST 0.011 0.979 CEO_TENURE 0.001 0.973 BOARD_SIZE -0.103 0.255 IND_BOARD 3.122 0.031* CEO_CHAIR -0.165 0.562 BUSY_DIR 0.200 0.546 Pseudo R2 0.07 N 418
Panel C shows logistic regression results. CHANGE is a binary variable equal to one for firms with changes in performance measures for executive annual incentive compensation in firm-year observation, zero otherwise. All other variables are described in Appendix 3. ***Indicates significance at 1 percent, **at 5 percent, *at 10 percent, based on two-tailed tests.
