# The Retention Effects of Unvested Equity: Evidence from Accelerated Option Vesting

The Retention Effects of Unvested Equity: Evidence from Accelerated Option Vesting Abstract We document that firms can effectively retain executives by granting deferred equity pay. We show this by analyzing a unique regulatory change (FAS 123-R) that prompted 723 firms to suddenly eliminate stock option vesting periods. This allowed CEOs to keep 33% more options when departing the firm, and we find that voluntary CEO departure rates subsequently rose from 5% to 21%. Our identification strategy exploits FAS 123-R’s almost-random timing, which was staggered by firms’ fiscal year-ends. Firms that experienced departures suffered negative stock price reactions, and responded by increasing compensation for remaining and newly hired executives. Received June 6, 2016; editorial decision October 10, 2017 by Editor Andrew Karolyi. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online. Demand for general human capital is rising across the economy, which makes it important to understand how firms can retain highly talented managers. One key retention mechanism that contract theory proposes is to defer parts of managers’ compensation into the future, by granting equity that does not vest for several years (Edmans et al. 2012). Managers who voluntarily depart their firms typically forfeit unvested equity, which raises their cost of pursuing an outside option. Boards often grant managers large amounts of time-vesting equity based on this rationale (Ittner, Lambert, and Larcker 2003). Nevertheless, whether unvested equity actually conveys retention incentives is unclear, for several reasons. First, firms may grant unvested equity primarily to provide incentives against myopic behavior, rather than to retain talent (Gopalan et al. 2014; Edmans, Fang, and Lewellen 2017). Second, poaching firms sometimes provide upfront payments that partially compensate managers for forfeiting unvested equity (Xu and Yang 2016).1 Third, models of managerial labor markets highlight that firms’ compensation policies can affect the type of managers that self-select to work for them (Lazear 2005). This endogenous sorting makes it difficult to understand whether retention is driven by firms’ vesting policies or managers’ attributes.2 As a result of these factors, causal identification is challenging, and this may explain why existing empirical work has been unable to link unvested equity to executive turnover (Fee and Hadlock 2003). This paper presents novel evidence on the retention incentives of deferred compensation. We study how executive turnover changes following the sudden elimination of stock option vesting restrictions by means of a major regulatory change in the United States, and document three primary findings. First, voluntary CEO turnover rises significantly when the amount of options forfeited upon leaving decreases. This effect is stronger when the previously unvested options are more valuable. Second, these departures precipitate declines in firm value. Third, firms respond to turnover by raising the pay of remaining executives and newly hired CEOs, implying that departures allow firms to update their beliefs about executives’ outside options. Our findings provide insights into the dynamics of managerial labor markets, and complement the literature on the determinants of forced turnover (Huson, Parrino, and Starks 2001; Eisfeldt and Kuhnen 2013; Jenter and Kanaan 2015). We establish these results by exploiting a unique feature of the accounting regulation FAS 123-R, which required firms for the first time to expense stock options in their financial statements. FAS 123-R imposed retroactive accounting charges on unvested options that firms had granted years before the standard’s adoption in December 2004. Corporate leaders vehemently opposed the new accounting expenses, which they feared would lead to a sudden drop in earnings. Motivated by such concerns, 723 firms exploited a regulatory exemption: They accelerated executives’ previously granted, unvested options to vest immediately, thereby avoiding a 23% dropoff in net income (Choudhary, Rajgopal, and Venkatachalam 2009). At the same time, however, option acceleration shortened the time until a CEO’s options vested by 19 months on average, and increased the value of their vested option holdings by 33%. This allowed departing CEOs to keep an additional $${\}$$0.8m worth of options, an amount equal to their annual equity pay. Our hypothesis is that this sudden, large drop in departure costs led to an increase in executive turnover. A challenge to testing this hypothesis is that firms’ decisions to accelerate option vesting are endogenous. First, some unobservable variables likely affected both option acceleration and turnover. Second, estimates could be affected by reverse causality, if some firms accelerated options to provide a “golden handshake” to outgoing executives (Yermack 2006). Such endogeneity would bias estimates obtained from comparing accelerating and non-accelerating firms. We overcome this challenge by using plausibly exogenous variation in option acceleration caused by FAS 123-R’s staggered compliance dates. Specifically, firms could avoid accounting expenses by accelerating options during the first fiscal year that ended after June 15, 2005. Thus, the acceleration deadline for firms with fiscal years ending between June and December 2005 (“late fiscal-year-end firms”) was already in calendar year 2005, whereas the deadline for firms with fiscal years ending between January and May 2006 (“early fiscal-year-end firms”) was only in calendar year 2006.3 Our 2SLS identification strategy exploits this staggered compliance schedule by instrumenting for option acceleration using an indicator for whether firms had an early or late fiscal year-end. The first-stage tests whether firms accelerated more options during the fiscal year just prior to FAS 123-R compliance. The second stage then tests whether instrumented option acceleration led to higher CEO turnover during the next fiscal year.4 The fiscal years of control firms partially overlap in calendar time with the fiscal years of treated firms, allowing us to control for some time-varying, macro-level determinants of turnover. Further, because each firm is treated in only one of the two sample years, the model accounts for time-invariant firm heterogeneity. (We find similar results when using monthly variation in FAS 123-R compliance dates.) Our analysis starts by validating our fiscal year-end instrument. We show that firms were 2.5 times more likely to accelerate option vesting in their fiscal year just prior to compliance with FAS 123-R, and usually accelerated options in the final month before the regulation took effect. Firms’ fiscal year-ends also likely satisfy the exclusion restriction for an instrumental variable, as they were set years in advance of FAS 123-R and thus should be uncorrelated with any contemporaneous changes that affect turnover. We further confirm that early and late fiscal-year-end firms had identical turnover rates, firm characteristics, and CEO pay before FAS 123-R took effect. Additionally, accelerating firms’ unvested options were mostly in the money or just slightly out of the money at the time of acceleration. Hence CEOs’ potential future payoffs from retaining these options were high, and they may have found it costly to depart their firms and forfeit the options prior to acceleration. We proceed to examine how option acceleration affected CEO turnover. Prior to FAS 123-R, turnover rates were similar across firms that accelerated in 2005 or in 2006. Turnover then rose sharply after the regulation took effect, at first only for the firms that accelerated in 2005, and one year later for firms that accelerated in 2006. Turnover rates for both sets of firms then quickly converged back to pre-FAS 123-R levels. Our 2SLS regressions confirm that these sequential jumps in turnover were due to the elimination of vesting restrictions, and not unobservable variables that may have affected acceleration decisions. A one-standard-deviation increase in the fraction of options accelerated led to a rise in the voluntary CEO turnover rate from 5% to 21.2%. Turnover rose more among CEOs who would have waited longer for options to vest in the absence of acceleration, whose unvested options were more in the money, and whose vested option holdings increased by a larger amount. We also find that turnover among a broader set of top executives rose from 8.8% to 21.3%. These estimates reflect the local average treatment effect (LATE) of option acceleration on turnover, estimated within the subset of firms that chose to accelerate due to FAS 123-R. Hence, our results say little about the effect that option acceleration would have had at firms that chose not to accelerate. The external validity of our 2SLS estimates depends on how similar accelerating firms are to non-accelerators. We find that accelerating firms performed relatively worse prior to FAS 123-R (though median stock returns and ROA were still positive). This may reflect that their CEOs’ ability was more marginal than that of non-accelerating firms’ CEOs. Accelerating firms’ boards therefore may have found turnover to be less costly or presumed that CEOs would receive few attractive outside offers and instead focused on the acceleration benefit of preserving accounting earnings. As such, our estimates are most informative about the retention incentives that unvested options convey to CEOs of firms with below-average performance. The effect could be smaller for CEOs working at the most successful firms. Because departures following option acceleration were relatively sudden, they may have reduced value by disrupting firms. We find that accelerating firms’ abnormal stock returns were $$-$$1.5% in a 3-day window around voluntary CEO departure announcements, erasing $${\}$$29m in value on average. In contrast, non-accelerating firms’ stocks were unaffected by voluntary departures, which were likely planned further in advance. This indicates that markets perceived acceleration-induced CEO departures to be costly. The documented negative returns at accelerating firms are only slightly lower in size than those estimated for other sudden departures, such as those following sudden CEO deaths (Johnson et al. 1985; Jenter, Matveyev, and Roth 2017). Consistent with these studies, the value losses we document could partly be due to search and transition costs. Indeed, accelerating firms that experienced a departure were 58% more likely to resort to appointing an interim CEO than non-accelerating firms, and spent 106 days longer searching for a permanent replacement. We show that departures may have allowed firms to learn about executives’ outside options and the required level of retention incentives. Firms that experienced turnover following acceleration were more likely to discuss retention issues in their proxy filings following the departures. Moreover, such firms subsequently raised non-departing executives’ pay by 11% on average, and newly hired CEOs’ pay by 32%, relative to accelerating firms that experienced no turnover. We also find evidence of information spillovers to accelerating firms’ peers, which increased their own executives’ unvested equity holdings after observing option acceleration. We hand-collect data to document that executives who departed accelerating firms subsequently pursued a variety of outside opportunities. Among departing CEOs, 44% took new executive positions at other firms, 21% joined boards as non-executive directors (with 8% joining as chairmen), and 17% entered consulting or investment management. Departing CEOs were on average 56 years old, and only 11% went into retirement. Among other top executives, 57% took new executive positions, 8% accepted non-executive board positions, and 6% joined consulting firms; their average departure age was 51 years. We conclude with placebo tests showing that our results likely cannot be explained by unobserved performance shocks or other variables that may differ across fiscal year-ends. First, option acceleration is unrelated to executive turnover in fiscal years prior to FAS 123-R. Second, acceleration did not affect the turnover of outside directors, who were largely unaffected by FAS 123-R because they held few unvested options (Yermack 2004). Thus, an omitted variable can confound our results only if it causes turnover among executives but not directors, and further affects late fiscal-year-end firms only in 2005 and early fiscal-year-end firms only in 2006. Finally, we show that our results are not explained by firms reporting lower net income or experiencing analyst downgrades after FAS 123-R took effect. Our paper contributes to the understanding of managerial labor markets by quantifying the effect of deferred compensation on turnover. We relate to the literature that studies determinants of forced CEO turnover, such as governance (Weisbach 1988; Denis, Denis, and Sarin 1997; Huson, Parrino, and Starks 2001; Denis and Serrano 1996), industry shocks (Jenter and Kanaan 2015; Eisfeldt and Kuhnen 2013; Peters and Wagner 2014; Kaplan and Minton 2012), or earnings management (Hazarika, Karpoff, and Nahata 2012). Our paper is most closely related to Gopalan, Huang, and Maharjan (2016), who examine turnover after annual equity grants vest. Our setting differs as we examine a large, one-time elimination of vesting periods, and study changes to pay and firm value following turnover.5 Our paper also documents new evidence on the pay consequences of CEO departures. Existing work finds that firm size determines executive pay in equilibrium, as the most productive managers sort to the largest firms (Gabaix and Landier 2008; Edmans, Gabaix, and Landier 2009). However, little is known about the dynamics that lead to this equilibrium. Our result that firms increase pay following voluntary turnover highlights one mechanism by which pay converges to its market value. Our findings also suggest that deferred pay may be a (designed) friction to managerial sorting. More broadly, we contribute to the literature on how vesting restrictions affect incentives. Cai and Vijh (2007) find that executives pursue mergers to accelerate the vesting of their equity holdings. Other papers show that CEOs with short vesting periods act myopically (Edmans, Fang, and Lewellen 2017; Ladika and Sautner 2018) and that CEOs release more news when equity vests (Edmans et al. 2017). 1. Background on FAS 123-R Prior to FAS 123-R, accounting regulations did not require firms to expense at-the-money options in their financial statements, and almost all firms avoided charges by granting executives such options.6 FAS 123-R’s main reform was to require firms to expense the fair value of all new options awards. (Since 2009, FAS 123-R has been codified as ASC Topic 718.) Additionally, firms had to expense previously granted options that had not yet vested when the regulation took effect. This provision received little attention while FAS 123-R was debated, but it created substantial, unexpected charges for firms with many outstanding unvested options. However, an exemption allowed firms to avoid these expenses by accelerating options to fully vest prior to FAS 123-R’s compliance date, which was each firm’s first full fiscal year that started after June 15, 2005 (I.A. Figure 1). Most often firms accelerated option vesting right in the month before compliance (I.A. Figure 2). Firms that accelerated unvested out-of-the-money options avoided all expenses. Firms that accelerated unvested in-the-money options had to expense the options’ intrinsic values (the difference between the acceleration-date stock price and option strike price), but for many firms this was significantly lower than the fair-value expense required in the absence of acceleration (Balsam, Reitenga, and Yin 2008). Figure 1 View largeDownload slide Hypothesis testing using staggered FAS 123-R compliance dates Panel A shows the treatment and control groups for testing the effect of FAS 123-R compliance on option acceleration (first stage), and panel B shows these groups for testing the effect of option acceleration on CEO turnover (second stage). Figure 1 View largeDownload slide Hypothesis testing using staggered FAS 123-R compliance dates Panel A shows the treatment and control groups for testing the effect of FAS 123-R compliance on option acceleration (first stage), and panel B shows these groups for testing the effect of option acceleration on CEO turnover (second stage). Figure 2 View largeDownload slide Effect of staggered FAS 123-R compliance on option acceleration The sample contains all firm-fiscal year observations ending between January 2005 and December 2006. Bars represent the percentage of firms with a fiscal year ending in a given month that accelerated option vesting during that fiscal year. The figure illustrates, for example, that 19% of firms with fiscal year ending in June 2005 accelerated option vesting during the fiscal year between July 2004 and June 2005. FAS 123-R compliance took effect for each firm in its first fiscal year starting after June 15, 2005. Firms had to accelerate option vesting before this compliance date to avoid expenses. Figure 2 View largeDownload slide Effect of staggered FAS 123-R compliance on option acceleration The sample contains all firm-fiscal year observations ending between January 2005 and December 2006. Bars represent the percentage of firms with a fiscal year ending in a given month that accelerated option vesting during that fiscal year. The figure illustrates, for example, that 19% of firms with fiscal year ending in June 2005 accelerated option vesting during the fiscal year between July 2004 and June 2005. FAS 123-R compliance took effect for each firm in its first fiscal year starting after June 15, 2005. Firms had to accelerate option vesting before this compliance date to avoid expenses. Numerous firms argued that the charges to operating earnings under FAS 123-R would reduce financial statement informativeness and lead to costly missed earnings forecasts. We find that 85% of firms that accelerated options stated in 8-K filings that the primary reason was to reduce expenses (I.A. Figure 3). Below we show that accelerating firms discussed turnover risk in financial disclosures, but only in the years after option acceleration (I.A. Table 7). Figure 3 View largeDownload slide Unvested option moneyness at accelerating firms Panel A plots the Kernel density of Unvested option moneyness, separately for accelerating and non-accelerating firms. Unvested option moneyness is the weighted average of moneyness of unvested options, measured at the end of the fiscal year just prior to FAS 123-R compliance. The variable includes all accelerated options that were scheduled to remain unvested prior to acceleration. In panel B, bars represent the fraction of accelerating or non-accelerating firms with a given percentage of deep out-of-the-money unvested options. Deep out-of-the-money options have a stock-price-to-strike-price ratio below 0.7. The ratio is measured at the end of the fiscal year just prior to FAS 123-R compliance. Figure 3 View largeDownload slide Unvested option moneyness at accelerating firms Panel A plots the Kernel density of Unvested option moneyness, separately for accelerating and non-accelerating firms. Unvested option moneyness is the weighted average of moneyness of unvested options, measured at the end of the fiscal year just prior to FAS 123-R compliance. The variable includes all accelerated options that were scheduled to remain unvested prior to acceleration. In panel B, bars represent the fraction of accelerating or non-accelerating firms with a given percentage of deep out-of-the-money unvested options. Deep out-of-the-money options have a stock-price-to-strike-price ratio below 0.7. The ratio is measured at the end of the fiscal year just prior to FAS 123-R compliance. Table 7 Comparison of accelerating versus non-accelerating firms Accelerating firms (2001-2004) Non-accelerating firms (2001–2004) Difference in means Mean Median SD Obs. Mean Median SD Obs. t-stat CEO turnover 0.05 2,044 0.06 8,595 –2.22** Voluntary CEO turnover 0.04 2,044 0.05 8,595 –1.91* Voluntary CEO turnover (JKPW) 0.05 933 0.08 3,986 –2.44** Executive turnover 0.09 0.00 0.18 1,932 0.09 0.00 0.17 8,076 –0.33 Log assets 5.68 5.64 1.75 2,028 5.92 5.95 2.03 8,467 –2.14** Market/book ratio 2.24 1.60 1.96 1,984 2.10 1.47 2.31 8,230 1.07 Stock return –0.01 0.05 0.58 1,946 0.07 0.13 0.52 8,028 –1.77* Stock volatility 0.22 0.20 0.12 1,866 0.18 0.16 0.10 7,629 4.50*** ROA –0.04 0.03 0.24 1,904 $$-$$0.02 0.05 0.22 8,103 –1.69* Sales growth 0.14 0.08 0.32 2,003 0.13 0.08 0.31 8,311 2.04** CEO age above 61 0.15 1,836 0.17 7,574 –1.15 Frac. executives above 61 0.08 0.00 0.20 1,927 0.10 0.00 0.23 8,032 –2.24** Unvested option duration 21.08 19.81 11.04 1,064 20.24 18.96 11.43 4,220 2.00** Unvested option moneyness 1.34 1.11 0.96 1,181 1.40 1.16 0.99 4,560 –1.18 Vested option value 5,774 1,934 9,461 841 7,084 1,736 11,926 3,770 –1.97* Vested option PPS 113 47 165 841 142 48 214 3,770 –2.47** Total compensation 3,743 2,112 4,130 959 4,129 2,407 4,342 4,328 –1.00 Equity compensation 2,356 1,081 3,171 959 2,339 976 3,249 4,328 0.05 Accelerating firms (2001-2004) Non-accelerating firms (2001–2004) Difference in means Mean Median SD Obs. Mean Median SD Obs. t-stat CEO turnover 0.05 2,044 0.06 8,595 –2.22** Voluntary CEO turnover 0.04 2,044 0.05 8,595 –1.91* Voluntary CEO turnover (JKPW) 0.05 933 0.08 3,986 –2.44** Executive turnover 0.09 0.00 0.18 1,932 0.09 0.00 0.17 8,076 –0.33 Log assets 5.68 5.64 1.75 2,028 5.92 5.95 2.03 8,467 –2.14** Market/book ratio 2.24 1.60 1.96 1,984 2.10 1.47 2.31 8,230 1.07 Stock return –0.01 0.05 0.58 1,946 0.07 0.13 0.52 8,028 –1.77* Stock volatility 0.22 0.20 0.12 1,866 0.18 0.16 0.10 7,629 4.50*** ROA –0.04 0.03 0.24 1,904 $$-$$0.02 0.05 0.22 8,103 –1.69* Sales growth 0.14 0.08 0.32 2,003 0.13 0.08 0.31 8,311 2.04** CEO age above 61 0.15 1,836 0.17 7,574 –1.15 Frac. executives above 61 0.08 0.00 0.20 1,927 0.10 0.00 0.23 8,032 –2.24** Unvested option duration 21.08 19.81 11.04 1,064 20.24 18.96 11.43 4,220 2.00** Unvested option moneyness 1.34 1.11 0.96 1,181 1.40 1.16 0.99 4,560 –1.18 Vested option value 5,774 1,934 9,461 841 7,084 1,736 11,926 3,770 –1.97* Vested option PPS 113 47 165 841 142 48 214 3,770 –2.47** Total compensation 3,743 2,112 4,130 959 4,129 2,407 4,342 4,328 –1.00 Equity compensation 2,356 1,081 3,171 959 2,339 976 3,249 4,328 0.05 Statistics are reported for firm-fiscal year observations ending between January 2001 and December 2004, and all variables are measured at the firm-fiscal-year level. The table compares accelerating and non-accelerating firms. Statistics are reported for only those accelerating firms that accelerated options in the fiscal year before FAS 123-R took effect. t-statistics are based on standard errors that are clustered by fiscal year and Fama-French 48 industry. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. Some variables are available only for ExecuComp firms. The variable appendix provides the variable definitions. Table 7 Comparison of accelerating versus non-accelerating firms Accelerating firms (2001-2004) Non-accelerating firms (2001–2004) Difference in means Mean Median SD Obs. Mean Median SD Obs. t-stat CEO turnover 0.05 2,044 0.06 8,595 –2.22** Voluntary CEO turnover 0.04 2,044 0.05 8,595 –1.91* Voluntary CEO turnover (JKPW) 0.05 933 0.08 3,986 –2.44** Executive turnover 0.09 0.00 0.18 1,932 0.09 0.00 0.17 8,076 –0.33 Log assets 5.68 5.64 1.75 2,028 5.92 5.95 2.03 8,467 –2.14** Market/book ratio 2.24 1.60 1.96 1,984 2.10 1.47 2.31 8,230 1.07 Stock return –0.01 0.05 0.58 1,946 0.07 0.13 0.52 8,028 –1.77* Stock volatility 0.22 0.20 0.12 1,866 0.18 0.16 0.10 7,629 4.50*** ROA –0.04 0.03 0.24 1,904 $$-$$0.02 0.05 0.22 8,103 –1.69* Sales growth 0.14 0.08 0.32 2,003 0.13 0.08 0.31 8,311 2.04** CEO age above 61 0.15 1,836 0.17 7,574 –1.15 Frac. executives above 61 0.08 0.00 0.20 1,927 0.10 0.00 0.23 8,032 –2.24** Unvested option duration 21.08 19.81 11.04 1,064 20.24 18.96 11.43 4,220 2.00** Unvested option moneyness 1.34 1.11 0.96 1,181 1.40 1.16 0.99 4,560 –1.18 Vested option value 5,774 1,934 9,461 841 7,084 1,736 11,926 3,770 –1.97* Vested option PPS 113 47 165 841 142 48 214 3,770 –2.47** Total compensation 3,743 2,112 4,130 959 4,129 2,407 4,342 4,328 –1.00 Equity compensation 2,356 1,081 3,171 959 2,339 976 3,249 4,328 0.05 Accelerating firms (2001-2004) Non-accelerating firms (2001–2004) Difference in means Mean Median SD Obs. Mean Median SD Obs. t-stat CEO turnover 0.05 2,044 0.06 8,595 –2.22** Voluntary CEO turnover 0.04 2,044 0.05 8,595 –1.91* Voluntary CEO turnover (JKPW) 0.05 933 0.08 3,986 –2.44** Executive turnover 0.09 0.00 0.18 1,932 0.09 0.00 0.17 8,076 –0.33 Log assets 5.68 5.64 1.75 2,028 5.92 5.95 2.03 8,467 –2.14** Market/book ratio 2.24 1.60 1.96 1,984 2.10 1.47 2.31 8,230 1.07 Stock return –0.01 0.05 0.58 1,946 0.07 0.13 0.52 8,028 –1.77* Stock volatility 0.22 0.20 0.12 1,866 0.18 0.16 0.10 7,629 4.50*** ROA –0.04 0.03 0.24 1,904 $$-$$0.02 0.05 0.22 8,103 –1.69* Sales growth 0.14 0.08 0.32 2,003 0.13 0.08 0.31 8,311 2.04** CEO age above 61 0.15 1,836 0.17 7,574 –1.15 Frac. executives above 61 0.08 0.00 0.20 1,927 0.10 0.00 0.23 8,032 –2.24** Unvested option duration 21.08 19.81 11.04 1,064 20.24 18.96 11.43 4,220 2.00** Unvested option moneyness 1.34 1.11 0.96 1,181 1.40 1.16 0.99 4,560 –1.18 Vested option value 5,774 1,934 9,461 841 7,084 1,736 11,926 3,770 –1.97* Vested option PPS 113 47 165 841 142 48 214 3,770 –2.47** Total compensation 3,743 2,112 4,130 959 4,129 2,407 4,342 4,328 –1.00 Equity compensation 2,356 1,081 3,171 959 2,339 976 3,249 4,328 0.05 Statistics are reported for firm-fiscal year observations ending between January 2001 and December 2004, and all variables are measured at the firm-fiscal-year level. The table compares accelerating and non-accelerating firms. Statistics are reported for only those accelerating firms that accelerated options in the fiscal year before FAS 123-R took effect. t-statistics are based on standard errors that are clustered by fiscal year and Fama-French 48 industry. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. Some variables are available only for ExecuComp firms. The variable appendix provides the variable definitions. FAS 123-R culminated a long, heated debate about the accounting treatment of stock options. Previous proposals to institute fair-value expensing drew substantial criticism from firms and investors, and were abandoned or watered down. Yet the corporate scandals of the early 2000s created momentum for option expensing, and opposition to FAS 123-R was relatively muted between its initial proposal in March 2004 and final adoption in December 2004. Nevertheless, firms were unable to anticipate the impact of FAS 123-R for two reasons. First, the regulation’s final compliance schedule was unexpectedly changed just two months before the regulation took effect. FAS 123-R originally required all firms to begin expensing options on June 15, 2005 (independent of their fiscal years). However, without prior notice, on April 14, 2005, the SEC delayed compliance to the first fiscal year starting after June 15, 2005. The change occurred because regulators were overburdened, and because accountants pointed out the difficulty of firms changing accounting standards in the middle of a fiscal year (McConnell et al. 2005). Second, firms initially did not know whether option acceleration would trigger accounting charges. On October 6, 2004, the Financial Accounting Standard Board (FASB) decided in a narrow 4-3 vote to permit acceleration. Almost no firm accelerated option vesting prior to the vote, due to uncertainty over its outcome (Choudhary, Rajgopal, and Venkatachalam 2009). 2. Sample, Identification Strategy, and Empirical Measures 2.1 Sample Our sampling procedure starts with all 4,991 firms that are in either the ExecuComp (mostly S&P 1500 firms) or BoardEx databases. We exclude 403 firms that voluntarily expensed stock options at fair value before FAS 123-R was proposed, because these firms could not benefit from option acceleration and also may have differed from other firms along dimensions that affect turnover (Aboody, Barth, and Kasznik 2004). We also exclude 70 firms that changed their fiscal year between 2004 and 2006, perhaps to delay compliance with FAS 123-R, and 33 firms with assets below $${\}$$5m. Our final sample contains 4,485 firms, of which 1,704 are in ExecuComp and 2,781 are only in BoardEx. 2.2 Identification strategy 2.2.1 2SLS model Executives typically forfeit unvested options when voluntarily departing the firm. This creates a departure cost whenever an executive anticipates that she could earn positive payoffs by staying at the firm and exercising the options in the future, after they vest. We therefore predict that the likelihood of voluntary turnover is higher when more of an executive’s options have vested. A reasonable setting for testing this hypothesis is option acceleration in anticipation of FAS 123-R, because the elimination of vesting periods led to a sudden drop in executives’ departure costs. However, causality cannot be inferred by simply comparing executive turnover at accelerating and non-accelerating firms, because unobservable variables may have influenced both the acceleration decision and turnover. To overcome this challenge, we exploit that FAS 123-R’s compliance dates were staggered quasi-randomly across time by firms’ fiscal year-ends. We estimate the following 2SLS model for firm $$f$$ and fiscal year $$t$$: \begin{align} {\textit{Option acceleration}}_{f,t} &= \pi_1 {\textit{FAS 123-R takes effect}}_{f,t} + \pi_2 X_{f,t} + \lambda_i + \mu_t + u_{f,t} \end{align} (First Stage) \begin{align} {\textit{Executive turnover}}_{f,t+1} &= \gamma_1 \widehat{{\textit{Option acceleration}}}_{f,t} + \gamma_2 X_{f,t} + \lambda_i + \mu_t + \nu_{f,t} \end{align} (Second Stage) In this model, FAS 123-R takes effect$$_{f,t}$$ is our instrument for option acceleration, $$X_{f,t}$$ is a vector of firm characteristics, and $$\lambda_i$$ and $$\mu_t$$ are industry and year fixed effects. (We describe all variables in detail below.) Each regression contains two observations per firm: One for the fiscal year ending between January and December 2005, and one for the fiscal year ending between January and December 2006. All variables are measured at the firm-fiscal year level. The year fixed effect equals 1 for firm-fiscal year observations ending in calendar year 2005, and 0 for observations ending in calendar year 2006. Option acceleration$$_{f,t}$$ measures either whether a firm accelerated option vesting during a fiscal year, or what fraction of options it accelerated. FAS 123-R takes effect$$_{f,t}$$ equals 1 for firm-fiscal year observations ending between June 2005 and May 2006, and 0 for all other firm-fiscal year observations. (I.A. Table 3 exploits month-by-month variation in FAS 123-R compliance.) Table 3 Staggered FAS 123-R compliance, option acceleration, and CEO turnover A. First-stage regressions B. Reduced-form regressions Dependent variable Frac. options accelerated Accelerate CEO turnover Voluntary CEO turnover Voluntary CEO turnover (JKPW) Executive turnover Model OLS OLS Sample All firms All firms All firms All firms ExecuComp firms All firms Window of analysis 2005–2006 2005–2006 (1) (2) (3) (4) (5) (6) FAS 123-R takes effect 0.040*** 0.145*** 0.068*** 0.052*** 0.080*** 0.041*** (8.15) (11.13) (5.30) (4.25) (4.24) (4.73) Log assets –0.000 –0.001 0.024*** 0.014*** 0.008 0.027*** (–0.30) (–0.37) (7.40) (4.94) (1.37) (13.62) Market/book ratio –0.001* –0.002* 0.005*** 0.003*** 0.001 0.004*** (–1.91) (–1.88) (3.43) (3.68) (1.42) (5.12) Stock return –0.043*** –0.110*** –0.012 0.019 –0.002 –0.028*** (–7.03) (–8.94) (–0.87) (1.54) (–0.08) (–3.08) Stock volatility 0.066* 0.087 0.089 –0.006 0.186 0.092* (1.92) (1.41) (1.20) (–0.10) (1.15) (1.81) ROA 0.009 0.071*** –0.107*** –0.032 –0.269*** –0.005 (0.73) (2.82) (–3.49) (–1.25) (–3.16) (–0.21) Sales growth 0.001 –0.023 –0.042** –0.009 –0.035 –0.031*** (0.19) (–1.58) (–2.33) (–0.54) (–0.87) (–2.68) CEO age under 61 –0.005 –0.016 0.002 0.010 0.069*** (–1.38) (–1.64) (0.19) (0.97) (3.82) Non-compete clauses 0.000 –0.001 –0.005** –0.005*** –0.008*** –0.003* (0.18) (–0.53) (–1.97) (–2.63) (–2.68) (–1.88) Distance to peers –0.000 0.000 –0.000 –0.000 –0.000 0.000 (–0.44) (0.07) (–0.52) (–0.60) (–1.24) (0.26) Frac. executives above 61 –0.040*** (–3.13) Year fixed effects Yes Yes Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Yes Yes Observations 4,660 4,892 4,892 4,892 2,399 4,942 Adjusted $$R^2$$ 0.082 0.132 0.025 0.014 0.022 0.058 F-Stat (FAS 123-R takes effect) 75.09 123.99 A. First-stage regressions B. Reduced-form regressions Dependent variable Frac. options accelerated Accelerate CEO turnover Voluntary CEO turnover Voluntary CEO turnover (JKPW) Executive turnover Model OLS OLS Sample All firms All firms All firms All firms ExecuComp firms All firms Window of analysis 2005–2006 2005–2006 (1) (2) (3) (4) (5) (6) FAS 123-R takes effect 0.040*** 0.145*** 0.068*** 0.052*** 0.080*** 0.041*** (8.15) (11.13) (5.30) (4.25) (4.24) (4.73) Log assets –0.000 –0.001 0.024*** 0.014*** 0.008 0.027*** (–0.30) (–0.37) (7.40) (4.94) (1.37) (13.62) Market/book ratio –0.001* –0.002* 0.005*** 0.003*** 0.001 0.004*** (–1.91) (–1.88) (3.43) (3.68) (1.42) (5.12) Stock return –0.043*** –0.110*** –0.012 0.019 –0.002 –0.028*** (–7.03) (–8.94) (–0.87) (1.54) (–0.08) (–3.08) Stock volatility 0.066* 0.087 0.089 –0.006 0.186 0.092* (1.92) (1.41) (1.20) (–0.10) (1.15) (1.81) ROA 0.009 0.071*** –0.107*** –0.032 –0.269*** –0.005 (0.73) (2.82) (–3.49) (–1.25) (–3.16) (–0.21) Sales growth 0.001 –0.023 –0.042** –0.009 –0.035 –0.031*** (0.19) (–1.58) (–2.33) (–0.54) (–0.87) (–2.68) CEO age under 61 –0.005 –0.016 0.002 0.010 0.069*** (–1.38) (–1.64) (0.19) (0.97) (3.82) Non-compete clauses 0.000 –0.001 –0.005** –0.005*** –0.008*** –0.003* (0.18) (–0.53) (–1.97) (–2.63) (–2.68) (–1.88) Distance to peers –0.000 0.000 –0.000 –0.000 –0.000 0.000 (–0.44) (0.07) (–0.52) (–0.60) (–1.24) (0.26) Frac. executives above 61 –0.040*** (–3.13) Year fixed effects Yes Yes Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Yes Yes Observations 4,660 4,892 4,892 4,892 2,399 4,942 Adjusted $$R^2$$ 0.082 0.132 0.025 0.014 0.022 0.058 F-Stat (FAS 123-R takes effect) 75.09 123.99 The regressions contain all firm-fiscal year observations ending between January 2005 and December 2006, and all variables are measured at the firm-fiscal year level. Frac. options accelerated is the number of options accelerated during the fiscal year, divided by the number of options outstanding at the beginning of the fiscal year. Accelerate equals 1 if a firm accelerated option vesting during the fiscal year, and 0 in all other fiscal years. CEO turnover equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. Voluntary CEO turnover equals 1 if a firm experiences a voluntary CEO departure during the next fiscal year, and 0 in all other fiscal years. Voluntary CEO turnover (JKPW) equals 1 if a firm experiences a voluntary CEO departure during the next fiscal year that is identified using the JKPW database, and 0 in all other fiscal years. Executive turnover is the number of executives departing during the next fiscal year divided by the total number of top executives. Our instrument FAS 123-R takes effect equals 1 for firm-fiscal year observations ending between June 2005 and May 2006, and 0 for all other firm-fiscal year observations. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. The year fixed effect equals 1 for firm-fiscal year observations ending in calendar year 2005, and 0 for firm-fiscal year observations ending in calendar year 2006. Industry fixed effects are based on the Fama-French 48 industry classification. F-Stat is the Kleibergen and Paap (2006) F-Statistic of our instrument FAS 123-R takes effect. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. Table 3 Staggered FAS 123-R compliance, option acceleration, and CEO turnover A. First-stage regressions B. Reduced-form regressions Dependent variable Frac. options accelerated Accelerate CEO turnover Voluntary CEO turnover Voluntary CEO turnover (JKPW) Executive turnover Model OLS OLS Sample All firms All firms All firms All firms ExecuComp firms All firms Window of analysis 2005–2006 2005–2006 (1) (2) (3) (4) (5) (6) FAS 123-R takes effect 0.040*** 0.145*** 0.068*** 0.052*** 0.080*** 0.041*** (8.15) (11.13) (5.30) (4.25) (4.24) (4.73) Log assets –0.000 –0.001 0.024*** 0.014*** 0.008 0.027*** (–0.30) (–0.37) (7.40) (4.94) (1.37) (13.62) Market/book ratio –0.001* –0.002* 0.005*** 0.003*** 0.001 0.004*** (–1.91) (–1.88) (3.43) (3.68) (1.42) (5.12) Stock return –0.043*** –0.110*** –0.012 0.019 –0.002 –0.028*** (–7.03) (–8.94) (–0.87) (1.54) (–0.08) (–3.08) Stock volatility 0.066* 0.087 0.089 –0.006 0.186 0.092* (1.92) (1.41) (1.20) (–0.10) (1.15) (1.81) ROA 0.009 0.071*** –0.107*** –0.032 –0.269*** –0.005 (0.73) (2.82) (–3.49) (–1.25) (–3.16) (–0.21) Sales growth 0.001 –0.023 –0.042** –0.009 –0.035 –0.031*** (0.19) (–1.58) (–2.33) (–0.54) (–0.87) (–2.68) CEO age under 61 –0.005 –0.016 0.002 0.010 0.069*** (–1.38) (–1.64) (0.19) (0.97) (3.82) Non-compete clauses 0.000 –0.001 –0.005** –0.005*** –0.008*** –0.003* (0.18) (–0.53) (–1.97) (–2.63) (–2.68) (–1.88) Distance to peers –0.000 0.000 –0.000 –0.000 –0.000 0.000 (–0.44) (0.07) (–0.52) (–0.60) (–1.24) (0.26) Frac. executives above 61 –0.040*** (–3.13) Year fixed effects Yes Yes Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Yes Yes Observations 4,660 4,892 4,892 4,892 2,399 4,942 Adjusted $$R^2$$ 0.082 0.132 0.025 0.014 0.022 0.058 F-Stat (FAS 123-R takes effect) 75.09 123.99 A. First-stage regressions B. Reduced-form regressions Dependent variable Frac. options accelerated Accelerate CEO turnover Voluntary CEO turnover Voluntary CEO turnover (JKPW) Executive turnover Model OLS OLS Sample All firms All firms All firms All firms ExecuComp firms All firms Window of analysis 2005–2006 2005–2006 (1) (2) (3) (4) (5) (6) FAS 123-R takes effect 0.040*** 0.145*** 0.068*** 0.052*** 0.080*** 0.041*** (8.15) (11.13) (5.30) (4.25) (4.24) (4.73) Log assets –0.000 –0.001 0.024*** 0.014*** 0.008 0.027*** (–0.30) (–0.37) (7.40) (4.94) (1.37) (13.62) Market/book ratio –0.001* –0.002* 0.005*** 0.003*** 0.001 0.004*** (–1.91) (–1.88) (3.43) (3.68) (1.42) (5.12) Stock return –0.043*** –0.110*** –0.012 0.019 –0.002 –0.028*** (–7.03) (–8.94) (–0.87) (1.54) (–0.08) (–3.08) Stock volatility 0.066* 0.087 0.089 –0.006 0.186 0.092* (1.92) (1.41) (1.20) (–0.10) (1.15) (1.81) ROA 0.009 0.071*** –0.107*** –0.032 –0.269*** –0.005 (0.73) (2.82) (–3.49) (–1.25) (–3.16) (–0.21) Sales growth 0.001 –0.023 –0.042** –0.009 –0.035 –0.031*** (0.19) (–1.58) (–2.33) (–0.54) (–0.87) (–2.68) CEO age under 61 –0.005 –0.016 0.002 0.010 0.069*** (–1.38) (–1.64) (0.19) (0.97) (3.82) Non-compete clauses 0.000 –0.001 –0.005** –0.005*** –0.008*** –0.003* (0.18) (–0.53) (–1.97) (–2.63) (–2.68) (–1.88) Distance to peers –0.000 0.000 –0.000 –0.000 –0.000 0.000 (–0.44) (0.07) (–0.52) (–0.60) (–1.24) (0.26) Frac. executives above 61 –0.040*** (–3.13) Year fixed effects Yes Yes Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Yes Yes Observations 4,660 4,892 4,892 4,892 2,399 4,942 Adjusted $$R^2$$ 0.082 0.132 0.025 0.014 0.022 0.058 F-Stat (FAS 123-R takes effect) 75.09 123.99 The regressions contain all firm-fiscal year observations ending between January 2005 and December 2006, and all variables are measured at the firm-fiscal year level. Frac. options accelerated is the number of options accelerated during the fiscal year, divided by the number of options outstanding at the beginning of the fiscal year. Accelerate equals 1 if a firm accelerated option vesting during the fiscal year, and 0 in all other fiscal years. CEO turnover equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. Voluntary CEO turnover equals 1 if a firm experiences a voluntary CEO departure during the next fiscal year, and 0 in all other fiscal years. Voluntary CEO turnover (JKPW) equals 1 if a firm experiences a voluntary CEO departure during the next fiscal year that is identified using the JKPW database, and 0 in all other fiscal years. Executive turnover is the number of executives departing during the next fiscal year divided by the total number of top executives. Our instrument FAS 123-R takes effect equals 1 for firm-fiscal year observations ending between June 2005 and May 2006, and 0 for all other firm-fiscal year observations. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. The year fixed effect equals 1 for firm-fiscal year observations ending in calendar year 2005, and 0 for firm-fiscal year observations ending in calendar year 2006. Industry fixed effects are based on the Fama-French 48 industry classification. F-Stat is the Kleibergen and Paap (2006) F-Statistic of our instrument FAS 123-R takes effect. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. The first stage compares each firm’s acceleration decision (or amount of options accelerated) in the fiscal year just prior to FAS 123-R compliance to adjacent, control-period fiscal years. For late fiscal-year-end firms complying with FAS 123-R in calendar year 2005, the control group is firms with fiscal years ending between January and May 2005 that had not yet complied. For early fiscal-year-end firms complying in 2006, the control group is firms with fiscal years ending between June and December 2006 that had already complied. A positive value of $$\pi_1$$ would indicate that firms were more likely to accelerate option vesting (or to accelerate more options) during the fiscal year just prior to FAS 123-R compliance. We expect this because firms could only avoid expensing unvested options by eliminating vesting provisions prior to their compliance dates. Our instrument likely satisfies the exclusion restriction because firms did not anticipate that FASB would set FAS 123-R’s compliance schedule based on fiscal year-ends. The second stage regresses CEO or executive turnover during the next fiscal year on the fitted value of option acceleration from the first stage. A positive value of $$\gamma_1$$ would indicate that firms that accelerated vesting due to upcoming FAS 123-R compliance experienced higher turnover during the following fiscal year. We examine turnover over the next fiscal year because executives likely required a few months to identify preferable outside opportunities, yet our results are robust to using shorter horizons (see I.A. Table 4). Standard errors in the second stage are adjusted for the use of estimated regressors from the first stage, and the sample is identical to that of the first stage. Table 4 Effect of option acceleration on vested option holdings Dependent variable Log vested option value $$\Delta$$Log vested option value Log vested option PPS $$\Delta$$Log vested option PPS Log vested option value Log vested option PPS Model Sample OLS ExecuComp firms Window of analysis 2003–2007 2005–2006 2003–2007 2005–2006 2003–2007 2003–2007 (1) (2) (3) (4) (5) (6) Accelerate 0.290** 0.340** 0.219*** 0.247*** 0.135 0.115 (2.19) (2.02) (2.82) (2.86) (1.02) (1.43) Accelerate$$\times$$CEO turnover 0.779* 0.514** (1.91) (2.27) CEO turnover –0.611*** –0.325*** (–5.36) (–4.92) Log assets 1.035*** 0.084** 0.661*** 0.048** 1.031*** 0.659*** (5.63) (2.00) (6.11) (2.08) (5.74) (6.22) Market/book ratio 0.062** –0.016** 0.037** –0.009** 0.064** 0.038** (2.13) (–1.97) (2.12) (–2.08) (2.32) (2.29) Stock return 0.818*** 1.827*** 0.526*** 1.166*** 0.786*** 0.509*** (8.38) (7.08) (9.49) (8.58) (8.09) (9.16) Stock volatility –0.642 3.410*** –2.054** 1.709*** –0.709 –2.085*** (–0.43) (2.82) (–2.50) (2.96) (–0.48) (–2.58) ROA 1.689*** –1.735** 1.062*** –0.961*** 1.667*** 1.058*** (3.26) (–2.45) (3.73) (–2.76) (3.26) (3.76) Sales growth 0.253 0.101 0.138 0.102 0.260 0.141 (1.30) (0.32) (1.23) (0.65) (1.39) (1.31) CEO age above 61 0.815*** –0.204* 0.586*** –0.140** 0.858*** 0.609*** (5.02) (–1.69) (6.12) (–2.08) (5.26) (6.33) Year fixed effects Yes Yes Yes Yes Yes Yes Industry fixed effects No Yes No Yes No No Firm fixed effects Yes No Yes No Yes Yes Observations 7,025 2,220 7,025 2,220 7,025 7,025 Adjusted $$R^2$$ 0.052 0.049 0.060 0.070 0.060 0.067 Dependent variable Log vested option value $$\Delta$$Log vested option value Log vested option PPS $$\Delta$$Log vested option PPS Log vested option value Log vested option PPS Model Sample OLS ExecuComp firms Window of analysis 2003–2007 2005–2006 2003–2007 2005–2006 2003–2007 2003–2007 (1) (2) (3) (4) (5) (6) Accelerate 0.290** 0.340** 0.219*** 0.247*** 0.135 0.115 (2.19) (2.02) (2.82) (2.86) (1.02) (1.43) Accelerate$$\times$$CEO turnover 0.779* 0.514** (1.91) (2.27) CEO turnover –0.611*** –0.325*** (–5.36) (–4.92) Log assets 1.035*** 0.084** 0.661*** 0.048** 1.031*** 0.659*** (5.63) (2.00) (6.11) (2.08) (5.74) (6.22) Market/book ratio 0.062** –0.016** 0.037** –0.009** 0.064** 0.038** (2.13) (–1.97) (2.12) (–2.08) (2.32) (2.29) Stock return 0.818*** 1.827*** 0.526*** 1.166*** 0.786*** 0.509*** (8.38) (7.08) (9.49) (8.58) (8.09) (9.16) Stock volatility –0.642 3.410*** –2.054** 1.709*** –0.709 –2.085*** (–0.43) (2.82) (–2.50) (2.96) (–0.48) (–2.58) ROA 1.689*** –1.735** 1.062*** –0.961*** 1.667*** 1.058*** (3.26) (–2.45) (3.73) (–2.76) (3.26) (3.76) Sales growth 0.253 0.101 0.138 0.102 0.260 0.141 (1.30) (0.32) (1.23) (0.65) (1.39) (1.31) CEO age above 61 0.815*** –0.204* 0.586*** –0.140** 0.858*** 0.609*** (5.02) (–1.69) (6.12) (–2.08) (5.26) (6.33) Year fixed effects Yes Yes Yes Yes Yes Yes Industry fixed effects No Yes No Yes No No Firm fixed effects Yes No Yes No Yes Yes Observations 7,025 2,220 7,025 2,220 7,025 7,025 Adjusted $$R^2$$ 0.052 0.049 0.060 0.070 0.060 0.067 The regressions contain firm-fiscal year observations for ExecuComp firms that end between January 2003 and December 2007 (January 2005 and December 2007 in Columns 2 and 4). All variables are measured at the firm-fiscal-year level. Log vested option value is the natural logarithm of the Black-Scholes value of a CEO’s vested stock options at the end of the fiscal year. Log vested option PPS is the natural logarithm of the change in the dollar value of a CEO’s vested option holdings for a 1% change in the firm’s stock price. To single out the impact of option acceleration from other common changes to vested option holdings, we add back the value/PPS of options that are exercised during the fiscal year, and subtract the value/PPS of options that were scheduled to vest during the fiscal year. Accelerate equals 1 if a firm accelerated option vesting during the fiscal year, and 0 in all other fiscal years. CEO turnover equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. Year fixed effects equal 1 for firm-fiscal year observations that end in the same calendar year. Industry fixed effects are based on the Fama-French 48 industry classification. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. Table 4 Effect of option acceleration on vested option holdings Dependent variable Log vested option value $$\Delta$$Log vested option value Log vested option PPS $$\Delta$$Log vested option PPS Log vested option value Log vested option PPS Model Sample OLS ExecuComp firms Window of analysis 2003–2007 2005–2006 2003–2007 2005–2006 2003–2007 2003–2007 (1) (2) (3) (4) (5) (6) Accelerate 0.290** 0.340** 0.219*** 0.247*** 0.135 0.115 (2.19) (2.02) (2.82) (2.86) (1.02) (1.43) Accelerate$$\times$$CEO turnover 0.779* 0.514** (1.91) (2.27) CEO turnover –0.611*** –0.325*** (–5.36) (–4.92) Log assets 1.035*** 0.084** 0.661*** 0.048** 1.031*** 0.659*** (5.63) (2.00) (6.11) (2.08) (5.74) (6.22) Market/book ratio 0.062** –0.016** 0.037** –0.009** 0.064** 0.038** (2.13) (–1.97) (2.12) (–2.08) (2.32) (2.29) Stock return 0.818*** 1.827*** 0.526*** 1.166*** 0.786*** 0.509*** (8.38) (7.08) (9.49) (8.58) (8.09) (9.16) Stock volatility –0.642 3.410*** –2.054** 1.709*** –0.709 –2.085*** (–0.43) (2.82) (–2.50) (2.96) (–0.48) (–2.58) ROA 1.689*** –1.735** 1.062*** –0.961*** 1.667*** 1.058*** (3.26) (–2.45) (3.73) (–2.76) (3.26) (3.76) Sales growth 0.253 0.101 0.138 0.102 0.260 0.141 (1.30) (0.32) (1.23) (0.65) (1.39) (1.31) CEO age above 61 0.815*** –0.204* 0.586*** –0.140** 0.858*** 0.609*** (5.02) (–1.69) (6.12) (–2.08) (5.26) (6.33) Year fixed effects Yes Yes Yes Yes Yes Yes Industry fixed effects No Yes No Yes No No Firm fixed effects Yes No Yes No Yes Yes Observations 7,025 2,220 7,025 2,220 7,025 7,025 Adjusted $$R^2$$ 0.052 0.049 0.060 0.070 0.060 0.067 Dependent variable Log vested option value $$\Delta$$Log vested option value Log vested option PPS $$\Delta$$Log vested option PPS Log vested option value Log vested option PPS Model Sample OLS ExecuComp firms Window of analysis 2003–2007 2005–2006 2003–2007 2005–2006 2003–2007 2003–2007 (1) (2) (3) (4) (5) (6) Accelerate 0.290** 0.340** 0.219*** 0.247*** 0.135 0.115 (2.19) (2.02) (2.82) (2.86) (1.02) (1.43) Accelerate$$\times$$CEO turnover 0.779* 0.514** (1.91) (2.27) CEO turnover –0.611*** –0.325*** (–5.36) (–4.92) Log assets 1.035*** 0.084** 0.661*** 0.048** 1.031*** 0.659*** (5.63) (2.00) (6.11) (2.08) (5.74) (6.22) Market/book ratio 0.062** –0.016** 0.037** –0.009** 0.064** 0.038** (2.13) (–1.97) (2.12) (–2.08) (2.32) (2.29) Stock return 0.818*** 1.827*** 0.526*** 1.166*** 0.786*** 0.509*** (8.38) (7.08) (9.49) (8.58) (8.09) (9.16) Stock volatility –0.642 3.410*** –2.054** 1.709*** –0.709 –2.085*** (–0.43) (2.82) (–2.50) (2.96) (–0.48) (–2.58) ROA 1.689*** –1.735** 1.062*** –0.961*** 1.667*** 1.058*** (3.26) (–2.45) (3.73) (–2.76) (3.26) (3.76) Sales growth 0.253 0.101 0.138 0.102 0.260 0.141 (1.30) (0.32) (1.23) (0.65) (1.39) (1.31) CEO age above 61 0.815*** –0.204* 0.586*** –0.140** 0.858*** 0.609*** (5.02) (–1.69) (6.12) (–2.08) (5.26) (6.33) Year fixed effects Yes Yes Yes Yes Yes Yes Industry fixed effects No Yes No Yes No No Firm fixed effects Yes No Yes No Yes Yes Observations 7,025 2,220 7,025 2,220 7,025 7,025 Adjusted $$R^2$$ 0.052 0.049 0.060 0.070 0.060 0.067 The regressions contain firm-fiscal year observations for ExecuComp firms that end between January 2003 and December 2007 (January 2005 and December 2007 in Columns 2 and 4). All variables are measured at the firm-fiscal-year level. Log vested option value is the natural logarithm of the Black-Scholes value of a CEO’s vested stock options at the end of the fiscal year. Log vested option PPS is the natural logarithm of the change in the dollar value of a CEO’s vested option holdings for a 1% change in the firm’s stock price. To single out the impact of option acceleration from other common changes to vested option holdings, we add back the value/PPS of options that are exercised during the fiscal year, and subtract the value/PPS of options that were scheduled to vest during the fiscal year. Accelerate equals 1 if a firm accelerated option vesting during the fiscal year, and 0 in all other fiscal years. CEO turnover equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. Year fixed effects equal 1 for firm-fiscal year observations that end in the same calendar year. Industry fixed effects are based on the Fama-French 48 industry classification. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. Our model compares turnover rates among late fiscal-year-end firms following FAS 123-R compliance in calendar year 2005 to those of early fiscal-year-end firms that had not yet complied. It also compares turnover rates among early fiscal-year-end firms following compliance in calendar year 2006 to those of late fiscal-year-end firms that had already complied. Figure 1 illustrates this research design, showing that treatment and control groups consist of adjacent fiscal years, and switch over time based on the staggered FAS 123-R compliance schedule. One benefit of this design is that results cannot be explained by time-invariant differences between early and late fiscal-year-end firms. Our identification strategy also aims to control for some macroeconomic shocks that affect all firms at once. I.A. Figure 1 shows that for the specific case of May and June fiscal-year-end firms, the treatment and control periods almost completely overlap in calendar time. A contemporaneous shock would not explain turnover differences between these firms. However, our ability to account for such shocks is more limited than in this example, as it depends on the size of the gap (in calendar time) between firms’ fiscal year-ends. The vast majority of firms have a fiscal year ending in December, and these firms’ treatment periods overlap with control firms by five months or less.7 Our identification strategy thus only partially controls for shocks that coincide with FAS 123-R. Notably, our results are robust to excluding December fiscal-year-end firms. Moreover, we find no evidence that CEO departures are clustered in calendar time (see Figure 5), as one would expect if turnover is driven by a shock at a single point in time. Figure 5 View largeDownload slide Calendar-time variation in option acceleration and CEO turnover The sample contains 68 voluntary CEO departures following option acceleration. Each point plots the date at which options were accelerated and the announcement date of the CEO departure. Data on CEO departure dates are from Capital IQ. Figure 5 View largeDownload slide Calendar-time variation in option acceleration and CEO turnover The sample contains 68 voluntary CEO departures following option acceleration. Each point plots the date at which options were accelerated and the announcement date of the CEO departure. Data on CEO departure dates are from Capital IQ. 2.2.2 Validity of 2SLS assumptions Our instrument must satisfy two key assumptions to identify the causal effect of acceleration: Relevance condition: $$\pi_1 \ne 0$$. Our option acceleration measures are correlated with FAS 123-R takes effect$$_{f,t}$$ after controlling for other firm characteristics $$X_{f,t}$$. Exclusion restriction: $$Cov({\textit{FAS 123-R takes effect}}_{f,t}, \nu_{f,t}) = 0$$. Differences in FAS 123-R compliance dates across firms only affect turnover through their effect on option acceleration. Section 3 shows that firms were far more likely to accelerate options during the fiscal year immediately preceding FAS 123-R compliance, confirming the relevance condition. The exclusion restriction is satisfied if the determinants of turnover do not differ across early and late fiscal-year-end firms. We cannot test this condition for unobservable determinants, but Table 1 provides evidence for key observable variables. The table shows that differences in turnover rates are small and statistically insignificant prior to FAS 123-R. Stock and accounting performance and other firm characteristics are also statistically indistinguishable across fiscal year-ends. Additionally, executives of early and late fiscal-year-end firms had similar option holdings and annual pay packages. This indicates that our instrument likely satisfies the exclusion restriction. Table 1 Comparison of early versus late fiscal-year-end firms Early fiscal-year-end firms (2001–2004) Late fiscal-year-end firms (2001–2004) Difference in means Mean Median SD Obs. Mean Median SD Obs. t-stat CEO turnover 0.07 1,408 0.06 9,431 0.74 Voluntary CEO turnover 0.05 1,408 0.05 9,431 0.34 Voluntary CEO turnover (JKPW) 0.08 737 0.07 4,284 0.66 Executive turnover 0.10 0.00 0.18 1,316 0.09 0.00 0.17 8,881 1.15 Log assets 5.66 5.70 1.81 1,397 5.90 5.90 2.01 9,296 $$-$$0.95 Market/book ratio 2.17 1.51 2.97 1,376 2.12 1.50 2.10 9,036 0.28 Stock return 0.02 0.09 0.60 1,367 0.05 0.12 0.53 8,804 $$-$$0.16 Stock volatility 0.20 0.17 0.11 1,313 0.19 0.16 0.11 8,374 1.10 ROA 0.01 0.06 0.21 1,347 $$-$$0.03 0.04 0.23 8,855 1.48 Sales growth 0.09 0.07 0.28 1,391 0.13 0.08 0.32 9,121 $$-$$1.14 CEO age above 61 0.18 1,203 0.16 8,386 1.02 Frac. executives above 61 0.10 0.00 0.22 1,306 0.09 0.00 0.22 8,840 0.26 Unvested option duration 20.89 19.74 10.47 664 20.35 19.07 11.45 4,735 0.89 Unvested option moneyness 1.33 1.13 0.93 728 1.39 1.16 0.98 5,133 $$-$$0.36 Vested option value 5,406 1,554 7,831 700 5,542 1,824 7,593 4,009 0.14 Vested option PPS 106 37 141 700 115 50 141 4,009 $$-$$0.53 Total compensation 3,411 2,133 3,162 805 3,701 2,368 3,300 4,602 $$-$$1.24 Equity compensation 1,976 819 2,412 805 2,041 1,011 2,402 4,602 $$-$$0.35 Early fiscal-year-end firms (2001–2004) Late fiscal-year-end firms (2001–2004) Difference in means Mean Median SD Obs. Mean Median SD Obs. t-stat CEO turnover 0.07 1,408 0.06 9,431 0.74 Voluntary CEO turnover 0.05 1,408 0.05 9,431 0.34 Voluntary CEO turnover (JKPW) 0.08 737 0.07 4,284 0.66 Executive turnover 0.10 0.00 0.18 1,316 0.09 0.00 0.17 8,881 1.15 Log assets 5.66 5.70 1.81 1,397 5.90 5.90 2.01 9,296 $$-$$0.95 Market/book ratio 2.17 1.51 2.97 1,376 2.12 1.50 2.10 9,036 0.28 Stock return 0.02 0.09 0.60 1,367 0.05 0.12 0.53 8,804 $$-$$0.16 Stock volatility 0.20 0.17 0.11 1,313 0.19 0.16 0.11 8,374 1.10 ROA 0.01 0.06 0.21 1,347 $$-$$0.03 0.04 0.23 8,855 1.48 Sales growth 0.09 0.07 0.28 1,391 0.13 0.08 0.32 9,121 $$-$$1.14 CEO age above 61 0.18 1,203 0.16 8,386 1.02 Frac. executives above 61 0.10 0.00 0.22 1,306 0.09 0.00 0.22 8,840 0.26 Unvested option duration 20.89 19.74 10.47 664 20.35 19.07 11.45 4,735 0.89 Unvested option moneyness 1.33 1.13 0.93 728 1.39 1.16 0.98 5,133 $$-$$0.36 Vested option value 5,406 1,554 7,831 700 5,542 1,824 7,593 4,009 0.14 Vested option PPS 106 37 141 700 115 50 141 4,009 $$-$$0.53 Total compensation 3,411 2,133 3,162 805 3,701 2,368 3,300 4,602 $$-$$1.24 Equity compensation 1,976 819 2,412 805 2,041 1,011 2,402 4,602 $$-$$0.35 Statistics are reported for all firm-fiscal year observations ending between January 2001 and December 2004, and all variables are measured at the firm-fiscal-year level. The table compares early fiscal-year-end firms (fiscal year ending in January through May) and late fiscal-year-end firms (fiscal year ending in June through December). t-statistics, shown in parentheses, are based on standard errors that are clustered by fiscal year and Fama-French 48 industry. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. Some variables are available only for ExecuComp firms. The variable appendix provides the variable definitions. Table 1 Comparison of early versus late fiscal-year-end firms Early fiscal-year-end firms (2001–2004) Late fiscal-year-end firms (2001–2004) Difference in means Mean Median SD Obs. Mean Median SD Obs. t-stat CEO turnover 0.07 1,408 0.06 9,431 0.74 Voluntary CEO turnover 0.05 1,408 0.05 9,431 0.34 Voluntary CEO turnover (JKPW) 0.08 737 0.07 4,284 0.66 Executive turnover 0.10 0.00 0.18 1,316 0.09 0.00 0.17 8,881 1.15 Log assets 5.66 5.70 1.81 1,397 5.90 5.90 2.01 9,296 $$-$$0.95 Market/book ratio 2.17 1.51 2.97 1,376 2.12 1.50 2.10 9,036 0.28 Stock return 0.02 0.09 0.60 1,367 0.05 0.12 0.53 8,804 $$-$$0.16 Stock volatility 0.20 0.17 0.11 1,313 0.19 0.16 0.11 8,374 1.10 ROA 0.01 0.06 0.21 1,347 $$-$$0.03 0.04 0.23 8,855 1.48 Sales growth 0.09 0.07 0.28 1,391 0.13 0.08 0.32 9,121 $$-$$1.14 CEO age above 61 0.18 1,203 0.16 8,386 1.02 Frac. executives above 61 0.10 0.00 0.22 1,306 0.09 0.00 0.22 8,840 0.26 Unvested option duration 20.89 19.74 10.47 664 20.35 19.07 11.45 4,735 0.89 Unvested option moneyness 1.33 1.13 0.93 728 1.39 1.16 0.98 5,133 $$-$$0.36 Vested option value 5,406 1,554 7,831 700 5,542 1,824 7,593 4,009 0.14 Vested option PPS 106 37 141 700 115 50 141 4,009 $$-$$0.53 Total compensation 3,411 2,133 3,162 805 3,701 2,368 3,300 4,602 $$-$$1.24 Equity compensation 1,976 819 2,412 805 2,041 1,011 2,402 4,602 $$-$$0.35 Early fiscal-year-end firms (2001–2004) Late fiscal-year-end firms (2001–2004) Difference in means Mean Median SD Obs. Mean Median SD Obs. t-stat CEO turnover 0.07 1,408 0.06 9,431 0.74 Voluntary CEO turnover 0.05 1,408 0.05 9,431 0.34 Voluntary CEO turnover (JKPW) 0.08 737 0.07 4,284 0.66 Executive turnover 0.10 0.00 0.18 1,316 0.09 0.00 0.17 8,881 1.15 Log assets 5.66 5.70 1.81 1,397 5.90 5.90 2.01 9,296 $$-$$0.95 Market/book ratio 2.17 1.51 2.97 1,376 2.12 1.50 2.10 9,036 0.28 Stock return 0.02 0.09 0.60 1,367 0.05 0.12 0.53 8,804 $$-$$0.16 Stock volatility 0.20 0.17 0.11 1,313 0.19 0.16 0.11 8,374 1.10 ROA 0.01 0.06 0.21 1,347 $$-$$0.03 0.04 0.23 8,855 1.48 Sales growth 0.09 0.07 0.28 1,391 0.13 0.08 0.32 9,121 $$-$$1.14 CEO age above 61 0.18 1,203 0.16 8,386 1.02 Frac. executives above 61 0.10 0.00 0.22 1,306 0.09 0.00 0.22 8,840 0.26 Unvested option duration 20.89 19.74 10.47 664 20.35 19.07 11.45 4,735 0.89 Unvested option moneyness 1.33 1.13 0.93 728 1.39 1.16 0.98 5,133 $$-$$0.36 Vested option value 5,406 1,554 7,831 700 5,542 1,824 7,593 4,009 0.14 Vested option PPS 106 37 141 700 115 50 141 4,009 $$-$$0.53 Total compensation 3,411 2,133 3,162 805 3,701 2,368 3,300 4,602 $$-$$1.24 Equity compensation 1,976 819 2,412 805 2,041 1,011 2,402 4,602 $$-$$0.35 Statistics are reported for all firm-fiscal year observations ending between January 2001 and December 2004, and all variables are measured at the firm-fiscal-year level. The table compares early fiscal-year-end firms (fiscal year ending in January through May) and late fiscal-year-end firms (fiscal year ending in June through December). t-statistics, shown in parentheses, are based on standard errors that are clustered by fiscal year and Fama-French 48 industry. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. Some variables are available only for ExecuComp firms. The variable appendix provides the variable definitions. Relatedly, the exclusion restriction could be violated if FAS 123-R compliance was delayed for firms that benefitted most from avoiding option expenses. This could be the case if early fiscal-year-end firms lobbied FASB to delay their compliance dates until 2006. I.A. Table 1 shows that most comments submitted to FASB prior to FAS 123-R’s approval opposed the regulation, and negative feedback was more prevalent among accelerating firms. However, we find no evidence that this opposition was related to firms’ fiscal year-ends. 2.3 Empirical measures 2.3.1 Turnover We track the employment status of 5,167 CEOs and 15,263 executives of our sample firms using data from ExecuComp and BoardEx. CEO turnover$$_{f,t+1}$$ equals 1 when a firm experiences a CEO departure during the next fiscal year ($$t+1$$), and 0 in all other fiscal years. For this and all other turnover variables, we follow Eisfeldt and Kuhnen (2013) by recording a departure event when the executive is at the firm at the end of the current fiscal year, but not at the end of the next fiscal year. We use two variables to isolate voluntary departures. Our first variable, Voluntary CEO turnover (JKPW)$$_{f,t+1}$$, uses information on forced CEO departures at ExecuComp firms from a database constructed by Jenter and Kanaan (2015) and Peters and Wagner (2014) (henceforth JKPW). This variable equals 1 when an ExecuComp firm experiences a CEO departure during the next fiscal year that is not listed as forced in the JKPW database, and 0 in all other fiscal years. This variable is defined for ExecuComp firms only. Our second variable, Voluntary CEO turnover$$_{f,t+1}$$, is created for all firms. For ExecuComp firms it equals Voluntary CEO turnover (JKPW)$$_{f,t+1}$$. To extrapolate the variable to BoardEx firms, we first regress CEO firings from the JKPW database of ExecuComp firms on determinants of forced turnover. We then use the coefficients from this predictive model to calculate fitted values for each CEO departure among BoardEx firms, and classify a departure as voluntary unless its fitted value is in the top quintile of the distribution (see the variable appendix for details). Voluntary CEO turnover$$_{f,t+1}$$ equals 1 for BoardEx firms that experience such a (predicted) voluntary departure during the next fiscal year, and 0 in all other fiscal years. This is an imperfect measure, but to our knowledge no database classifies departures of non-ExecuComp CEOs. We also study whether acceleration affects turnover among a broader set of executives. These supplemental tests use Executive turnover$$_{f,t+1}$$, which equals the number of top executives departing over the next fiscal year ($$t+1$$), divided by the number of top executives at the end of fiscal year $$t$$. Top executives are all individuals listed in ExecuComp, and all senior managers listed in BoardEx. Table 2 presents summary statistics for firm-fiscal year observations ending between January 2005 and December 2006. CEO departures occur in 11% of firm-fiscal years. Voluntary CEO turnover occurs in 9% of firm-fiscal years across the entire sample, but is higher at 12% among ExecuComp firms. This difference is consistent with prior evidence that smaller firms have lower forced and voluntary CEO turnover (Huson, Parrino, and Starks 2001). On average, 13% of top executives depart in a fiscal year. Overall, our turnover rates are similar to those documented by previous work (Eisfeldt and Kuhnen 2013; Jenter and Kanaan 2015). Table 2 Summary statistics A. All firms Variable Mean Median SD Obs. CEO turnover 0.11 8,612 Voluntary CEO turnover 0.09 8,612 Voluntary CEO turnover (JKPW) 0.12 3,128 Executive turnover 0.13 0.00 0.24 7,849 Frac. options accelerated 0.03 0.00 0.12 7,582 Accelerate 0.08 8,612 Log assets 6.03 6.09 1.98 8,394 Market/book ratio 2.18 1.56 2.99 8,088 Stock return 0.03 0.06 0.40 7,931 Stock volatility 0.13 0.11 0.08 6,860 ROA –0.01 0.05 0.22 7,298 Sales growth 0.20 0.13 0.31 8,155 CEO age above 61 0.19 7,609 Frac. executives above 61 0.12 0.00 0.25 8,063 Non-compete clauses 3.80 4.00 2.30 8,488 Distance to peers 1,299 1,207 489 7,700 B. Accelerating firms Frac. options accelerated 0.34 0.25 0.29 647 Unvested option duration 18.75 17.44 10.88 490 Unvested option moneyness 1.15 0.97 0.90 505 Vested option value 8,181 2,289 16,831 262 Vested option PPS 185 71 374 262 Total compensation 3,393 1,967 4,469 318 Equity compensation 1,955 837 3,477 318 A. All firms Variable Mean Median SD Obs. CEO turnover 0.11 8,612 Voluntary CEO turnover 0.09 8,612 Voluntary CEO turnover (JKPW) 0.12 3,128 Executive turnover 0.13 0.00 0.24 7,849 Frac. options accelerated 0.03 0.00 0.12 7,582 Accelerate 0.08 8,612 Log assets 6.03 6.09 1.98 8,394 Market/book ratio 2.18 1.56 2.99 8,088 Stock return 0.03 0.06 0.40 7,931 Stock volatility 0.13 0.11 0.08 6,860 ROA –0.01 0.05 0.22 7,298 Sales growth 0.20 0.13 0.31 8,155 CEO age above 61 0.19 7,609 Frac. executives above 61 0.12 0.00 0.25 8,063 Non-compete clauses 3.80 4.00 2.30 8,488 Distance to peers 1,299 1,207 489 7,700 B. Accelerating firms Frac. options accelerated 0.34 0.25 0.29 647 Unvested option duration 18.75 17.44 10.88 490 Unvested option moneyness 1.15 0.97 0.90 505 Vested option value 8,181 2,289 16,831 262 Vested option PPS 185 71 374 262 Total compensation 3,393 1,967 4,469 318 Equity compensation 1,955 837 3,477 318 Statistics are reported for firm-fiscal year observations ending between January 2005 and December 2006, and all variables are measured at the firm-fiscal-year level. Panel A presents summary statistics for all sample firms, and panel B for accelerating firms only. Our sample contains 723 unique firms that accelerated option vesting. These firms generated 652 (75) option accelerations events during the fiscal years ending between January 2005 and December 2005 (January 2006 and December 2006); four firms accelerated options in two separate fiscal years. Some variables are available only for ExecuComp firms. The variable appendix provides the variable definitions. Table 2 Summary statistics A. All firms Variable Mean Median SD Obs. CEO turnover 0.11 8,612 Voluntary CEO turnover 0.09 8,612 Voluntary CEO turnover (JKPW) 0.12 3,128 Executive turnover 0.13 0.00 0.24 7,849 Frac. options accelerated 0.03 0.00 0.12 7,582 Accelerate 0.08 8,612 Log assets 6.03 6.09 1.98 8,394 Market/book ratio 2.18 1.56 2.99 8,088 Stock return 0.03 0.06 0.40 7,931 Stock volatility 0.13 0.11 0.08 6,860 ROA –0.01 0.05 0.22 7,298 Sales growth 0.20 0.13 0.31 8,155 CEO age above 61 0.19 7,609 Frac. executives above 61 0.12 0.00 0.25 8,063 Non-compete clauses 3.80 4.00 2.30 8,488 Distance to peers 1,299 1,207 489 7,700 B. Accelerating firms Frac. options accelerated 0.34 0.25 0.29 647 Unvested option duration 18.75 17.44 10.88 490 Unvested option moneyness 1.15 0.97 0.90 505 Vested option value 8,181 2,289 16,831 262 Vested option PPS 185 71 374 262 Total compensation 3,393 1,967 4,469 318 Equity compensation 1,955 837 3,477 318 A. All firms Variable Mean Median SD Obs. CEO turnover 0.11 8,612 Voluntary CEO turnover 0.09 8,612 Voluntary CEO turnover (JKPW) 0.12 3,128 Executive turnover 0.13 0.00 0.24 7,849 Frac. options accelerated 0.03 0.00 0.12 7,582 Accelerate 0.08 8,612 Log assets 6.03 6.09 1.98 8,394 Market/book ratio 2.18 1.56 2.99 8,088 Stock return 0.03 0.06 0.40 7,931 Stock volatility 0.13 0.11 0.08 6,860 ROA –0.01 0.05 0.22 7,298 Sales growth 0.20 0.13 0.31 8,155 CEO age above 61 0.19 7,609 Frac. executives above 61 0.12 0.00 0.25 8,063 Non-compete clauses 3.80 4.00 2.30 8,488 Distance to peers 1,299 1,207 489 7,700 B. Accelerating firms Frac. options accelerated 0.34 0.25 0.29 647 Unvested option duration 18.75 17.44 10.88 490 Unvested option moneyness 1.15 0.97 0.90 505 Vested option value 8,181 2,289 16,831 262 Vested option PPS 185 71 374 262 Total compensation 3,393 1,967 4,469 318 Equity compensation 1,955 837 3,477 318 Statistics are reported for firm-fiscal year observations ending between January 2005 and December 2006, and all variables are measured at the firm-fiscal-year level. Panel A presents summary statistics for all sample firms, and panel B for accelerating firms only. Our sample contains 723 unique firms that accelerated option vesting. These firms generated 652 (75) option accelerations events during the fiscal years ending between January 2005 and December 2005 (January 2006 and December 2006); four firms accelerated options in two separate fiscal years. Some variables are available only for ExecuComp firms. The variable appendix provides the variable definitions. 2.3.2 Option acceleration Our option acceleration data are from the R. G. Associates Option Accelerated Vester Database. The data include the firms that accelerated option vesting, the acceleration dates, and the number of options accelerated. The investment advisory firm R. G. Associates compiled these data by searching through firms’ financial forms and press releases for phrases related to option acceleration or option vesting provisions. A limitation of the data is that firms were only required to disclose aggregate figures, and they did not report information separately by executives. The database covers late 2004 to February 2006, and we extend it through December 2006 using the same textual analysis procedure. R. G. Associates originally used the database for newsletters to clients, and it has also been used by Balsam, Reitenga, and Yin (2008) and Choudhary, Rajgopal, and Venkatachalam (2009). We construct two measures of option acceleration. First, Frac. options accelerated is the number of options accelerated during the fiscal year divided by the number of (unvested and vested) options outstanding at the beginning of the fiscal year. The variable equals 0 for all firm-fiscal year observations in which no options were accelerated. Second, Accelerate equals 1 when a firm accelerated options during the fiscal year, and 0 in all other fiscal years. Table 2 shows that option acceleration occurred in 8% of firm-fiscal years. Overall, 723 firms accelerated option vesting during our sample period: 652 during fiscal years ending between January and December 2005 and 75 during fiscal years ending between January and December 2006 (there are 727 total acceleration events because four firms accelerated options in two separate years). Of these firms, 286 are in ExecuComp and 437 are in BoardEx. Table 2 also shows that the unconditional mean of Frac. options accelerated is small, but conditional on acceleration 34% of all outstanding options were affected (see panel B). 2.3.3 Unvested option holdings Some of our tests examine whether turnover was higher among CEOs whose departure costs decreased more due to option acceleration. We construct two variables that represent the impact of option acceleration. First, we measure the extent to which a CEO’s unvested options were in the money, as this affected the potential payoff from option acceleration. We collect data from Thomson Insiders on the vesting schedules of all options granted since January 2000. We then construct unvested option holdings in the fiscal year of acceleration as the set of grants that (absent acceleration) were not scheduled to vest by the end of the fiscal year. We measure each grant’s moneyness as the firm’s stock price at the end of the fiscal year divided by the strike price. We obtain similar values when measuring the stock price on the acceleration date (as most firms accelerated options in the last month of the fiscal year, see I.A. Figure 2). Unvested option moneyness is the weighted average of the moneyness of all unvested option grants. We use the number of options in each grant as weights, because this is less likely to understate the amount of deep-out-of-the-money options than value-weighting. Second, we measure how long CEOs would have waited for their options to vest in the absence of acceleration. We define the duration of each unvested option grant in the fiscal year of acceleration as the number of months between the end of the fiscal year and the scheduled vesting date. Unvested option duration is the number-weighted average of the duration of all unvested option grants. This variable can be interpreted as the average number of months until options vest. Table 2 shows that the mean of Unvested option moneyness was 1.15, and that of Unvested option duration was 18.8. The latter statistic equals approximately one-third of the median CEOs’ tenure of five years. Section 3.3 provides further evidence on the moneyness of accelerating and non-accelerating firms’ options. 2.3.4 Firm, executive, and labor market controls Our empirical models include firm, executive, and labor market characteristics that prior work has identified as determinants of option acceleration and executive turnover. We control for Log assets and Market/book ratio because large or high-growth firms grant executives more options, and hence may benefit more from acceleration. We control for firm performance using Stock return and ROA. We further control for Stock volatility and Sales growth. We account for retirement-induced turnover using CEO age above 61, which equals 1 for firms with a CEO aged 61 or older. In regressions that study top executive turnover, we replace this variable with Frac. executives above 61. We control for executives’ labor market opportunities using state-level enforcement of non-compete laws (Non-compete clauses) and geographic proximity to other firms in the same industry (Distance to peers). Table 2 reports summary statistics for these variables. I.A. Table 2 shows that 72% of sample firms have a December fiscal year-end, but more than 1,000 firms have fiscal years ending in other months, including 499 early fiscal-year-end firms. Below we show that our results are robust to excluding firms with December fiscal years. The table also shows that the distribution of fiscal-year ends is similar across accelerating and non-accelerating firms. For example, 12.7% of accelerating firms have an early fiscal-year end, compared to 10.8% of non-accelerating firms. 3. Option Acceleration and Executive Turnover around FAS 123-R Compliance 3.1 Acceleration around FAS 123-R Figure 2 depicts the relationship between staggered FAS 123-R compliance dates and option acceleration. We sort firm-fiscal year observations by the month in which the fiscal year ends, from January 2005 through December 2006. Bars represent the percentage of firms with a fiscal year ending in a given month that accelerated option vesting during that fiscal year. The acceleration rate was 5.7% among firms with a fiscal year ending between January and May 2005, but rose to 19.2% for firms with a fiscal year ending in June 2005. This sharp increase is likely due to FAS 123-R, as these firms were the first to comply with the regulation. Acceleration rates remained high (16.4% on average) for firms with fiscal years ending later in 2005. Firms with a fiscal year ending between January and May 2006 were also much more likely to accelerate options than a year earlier, when compliance with FAS 123-R was not imminent. However, their acceleration rate of 14.3% was slightly lower than that of firms with a fiscal year ending between June and December 2005. Acceleration rates then dropped to 0.2% for firms with later fiscal years that had already complied with FAS 123-R. Table 3, panel A, similarly compares acceleration rates across staggered FAS 123-R compliance dates in a regression framework. The two columns present our first-stage regressions of Frac. options accelerated and Accelerate on the instrument FAS 123-R takes effect. Both regressions show that our instrument has a large positive effect on option acceleration. Column 2 shows that the acceleration rate was 14.5% higher in firm-fiscal years that immediately preceded FAS 123-R compliance than firm-fiscal years that did not precede compliance or took place afterward. This is 2.5 times higher than the 5.7% acceleration rate for fiscal years ending between January and May 2005. Our instrument’s statistical significance is high ($$t$$-statistics above 8), and the F-statistics are far above the commonly used threshold of 10 (Staiger and Stock 1997; Stock, Wright, and Yogo 2002). These findings confirm that our instrument satisfies the relevance condition. 3.2 FAS 123-R compliance and turnover: Reduced-form regressions Table 3, panel B, reports reduced-form models that regress turnover directly on our instrument. Column 3 examines the effect of FAS 123-R compliance on CEO turnover, Columns 4 and 5 on the two measures of voluntary CEO turnover, and Column 6 on executive turnover. Reduced-form regressions are useful for gauging whether 2SLS results are consistent with an instrument’s expected causal effect. A reduced-form coefficient of 0 on FAS 123-R takes effect would indicate that 2SLS estimates are driven mostly by omitted variables or regression misspecification (Angrist and Pischke 2009). However, we obtain positive and highly significant coefficients on FAS 123-R takes effect in all four regressions. In economic terms, Column 3 indicates that the CEO turnover rate was 6.8% higher in the fiscal year after firms complied with FAS 123-R; these fiscal years began shortly after many firms accelerated unvested options to avoid accounting expenses. This is initial evidence that FAS 123-R affected turnover through its effect on option acceleration, and we explore this channel using 2SLS tests in Section 4. 3.3 Acceleration and vested option holdings The results in Table 3, panel A, do not necessarily prove that option acceleration led to an economically meaningful decrease in top executives’ departure costs. Firms may have accelerated only a small fraction of executives’ options, or accelerated only deep out-of-the-money options with little economic value. In this case, option acceleration may not have materially affected executives’ retention incentives. To account for this possibility, in Figure 3, panel A, we compare the distribution of Unvested option moneyness among accelerating and non-accelerating firms. We measure moneyness at the end of the fiscal year just prior to FAS 123-R compliance to ensure comparability between the two sets of firms, but the distribution for accelerating firms is almost identical when moneyness is measured on the acceleration date. The figure shows that the weighted-average moneyness of unvested options was higher at non-accelerating firms, but was also above 1 for almost half of accelerating firms. This indicates that many CEOs of accelerating firms potentially benefitted from option acceleration. Options that are at or just out of the money can still convey retention incentives to executives, as they may generate positive payoffs in the future. In contrast, executives may perceive that deep-out-of-the-money options have little future value, and forfeiting them may have little impact on the cost of departing the firm. Figure 3, panel B, plots the extent to which unvested options were deep out-of-the-money just prior to FAS 123-R compliance. We define deep-out-of-money options as those with a stock-to-exercise-price ratio below 0.7; the stock price would need to rise 40% for these options to become in the money, and only 25% of accelerating firms achieved such an annual return prior to FAS 123-R. The figure shows that at 24% of accelerating firms all unvested options were in the money, and at another 48% of accelerating firms less than one quarter of unvested options were deep out of the money. At only 18% of accelerating firms more than half of unvested options were deep out of the money. Next, to directly estimate the decrease in departure costs, we measure how much CEOs’ vested options holdings rose due to option acceleration. We construct two variables to measure these holdings. Log vested option value is the natural logarithm of the Black-Scholes value of vested options, measured at the end of the fiscal year prior to FAS 123-R compliance. Log vested option PPS is the options’ pay-for-performance sensitivity (PPS), which is the increase in the holdings’ value when the stock price rises 1% (Hall and Liebman 1998). We construct these variables for CEOs of firms in ExecuComp, which contains detailed data on vested option holdings. To single out the effect of option acceleration from other common changes to vested option holdings, we add back the value or PPS of option exercises during the fiscal year and subtract the value of options that vested under their regular schedule (see the variable appendix for details). A large increase in both vested option variables would indicate that accelerated options were valuable, and that CEOs’ departure costs decreased substantially. Table 4 presents regressions of both variables on Accelerate, the dummy for whether a firm accelerated options during the fiscal year. We either use firm-fixed effect regressions to capture changes in vested option holdings within the same firm over time, or directly estimate fiscal year-on-fiscal year changes in our variables. We use a wider estimation window in the firm-fixed effect models to more accurately identify within-firm averages. The results show that acceleration led to a large rise in holdings. The median accelerating firm’s CEO held vested options worth $${\}$$2.4m (Log vested option value of 7.79) in the fiscal year prior to acceleration. Column 1 implies that these holdings rose by 33% to (exp(7.79 + 0.29)=) $${\}$$3.2m due to option acceleration. This allowed CEOs to keep an extra $${\}$$0.8m worth of options when departing, an amount equivalent to the median CEO’s annual equity pay (see Table 2, panel B). Column 2 shows similar results using the change in vested option values, and Columns 3 and 4 show that acceleration also increased the options’ PPS. The tests in Columns 5 and 6 compare how much vested options increased at accelerating firms that experienced a subsequent CEO departure versus accelerating firms that experienced no turnover. To do this, we interact Accelerate with CEO turnover, the dummy variable that equals 1 for firms that experienced a CEO departure during the next fiscal year. The positive interaction term coefficient in both columns indicates that the impact of option acceleration on vested option holdings was bigger at firms that subsequently experienced CEO turnover. The estimates in Column 5 imply that vested option holdings rose substantially, from $${\}$$2.4m to $${\}$$3.3m, at accelerating firms that experienced turnover, but only little at accelerating firms that experienced no turnover (from $${\}$$2.4m to $${\}$$2.8m). The coefficient on CEO turnover indicates that, generally, when CEOs have fewer vested options, they are more likely to depart. 4. Turnover and Valuation Consequences of Option Acceleration 4.1 Acceleration and turnover: Graphical evidence We proceed to test whether option acceleration led to an increase in executive turnover. Figure 4 plots firm-fiscal years ending between January 2001 and December 2010. Bars represent the percentage of firms that experienced a CEO departure in the following fiscal year. Percentages are shown separately for firms that accelerated option vesting during the fiscal year ending between June and December 2005, and for firms that accelerated during the fiscal year ending between January and May 2006. We look at these two sets of firms as they both accelerated option vesting in the fiscal year prior to FAS 123-R compliance. Non-accelerating firms are excluded from the figure. Figure 4 View largeDownload slide Effect of option acceleration on CEO turnover The sample contains firm-fiscal year observations ending between January 2001 and December 2010. Bars represent the percentage of firms with a fiscal year ending in a given calendar year that experienced a CEO departure during the next fiscal year. Percentages are separately shown for firms that accelerated option vesting in a fiscal year ending between June and December 2005 and firms that accelerated option vesting in a fiscal year ending between January and May 2006. Figure 4 View largeDownload slide Effect of option acceleration on CEO turnover The sample contains firm-fiscal year observations ending between January 2001 and December 2010. Bars represent the percentage of firms with a fiscal year ending in a given calendar year that experienced a CEO departure during the next fiscal year. Percentages are separately shown for firms that accelerated option vesting in a fiscal year ending between June and December 2005 and firms that accelerated option vesting in a fiscal year ending between January and May 2006. The figure shows that for both sets of accelerating firms, turnover rates were similar following the fiscal years that ended in calendar years 2001 through 2004, and ranged from 3.9% to 7.5%. CEO departures then jumped suddenly to 16%, but only among firms that accelerated option vesting during the fiscal years that ended between June and December 2005. In the following year, CEO turnover rose sharply only for firms that accelerated during the fiscal years that ended between January and May 2006. For both sets of firms, turnover remained slightly elevated in the second fiscal year after option acceleration, before decreasing again. By 2008, turnover rates were again the same for both groups. (I.A. Table 6 formally shows that turnover rates converged in the years after option acceleration.) Overall, the figure shows that firms experienced a one-time spike in CEO turnover precisely in the fiscal year after options were accelerated. Table 6 CEO turnover and option characteristics Dependent variable CEO turnover CEO turnover Model Sample OLS Accelerating firms OLS All firms Window of analysis 2005–2006 2005–2006 (1) (2) (3) (4) Unvested option duration 0.006*** –0.000 (2.91) (–0.03) Unvested option moneyness 0.051* 0.008 (1.93) (1.31) Unvested option duration$$\times$$Accelerate 0.006*** (2.59) Unvested option moneyness$$\times$$Accelerate 0.017 (0.64) Accelerate –0.052 0.035 (–1.18) (0.93) Log assets 0.032** 0.030** 0.021*** 0.018*** (2.25) (2.06) (5.23) (4.75) Market/book ratio –0.029 –0.019 0.006*** 0.006*** (–1.46) (–0.89) (6.79) (4.98) Stock return 0.019 –0.062 –0.012 –0.014 (0.26) (–0.88) (–0.75) (–0.84) Stock volatility 0.108 –0.115 0.084 0.037 (0.31) (–0.34) (0.85) (0.38) ROA –0.437*** –0.354** –0.079** –0.069* (–2.75) (–1.99) (–2.09) (–1.82) Sales growth –0.098 –0.102 –0.047** –0.042** (–1.09) (–1.12) (–2.35) (–2.11) CEO age above 61 0.082 0.081 0.022 0.016 (1.29) (1.31) (1.56) (1.14) Year fixed effects Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Observations 388 397 3,745 3,810 Adjusted $$R^2$$ 0.038 0.019 0.021 0.016 Dependent variable CEO turnover CEO turnover Model Sample OLS Accelerating firms OLS All firms Window of analysis 2005–2006 2005–2006 (1) (2) (3) (4) Unvested option duration 0.006*** –0.000 (2.91) (–0.03) Unvested option moneyness 0.051* 0.008 (1.93) (1.31) Unvested option duration$$\times$$Accelerate 0.006*** (2.59) Unvested option moneyness$$\times$$Accelerate 0.017 (0.64) Accelerate –0.052 0.035 (–1.18) (0.93) Log assets 0.032** 0.030** 0.021*** 0.018*** (2.25) (2.06) (5.23) (4.75) Market/book ratio –0.029 –0.019 0.006*** 0.006*** (–1.46) (–0.89) (6.79) (4.98) Stock return 0.019 –0.062 –0.012 –0.014 (0.26) (–0.88) (–0.75) (–0.84) Stock volatility 0.108 –0.115 0.084 0.037 (0.31) (–0.34) (0.85) (0.38) ROA –0.437*** –0.354** –0.079** –0.069* (–2.75) (–1.99) (–2.09) (–1.82) Sales growth –0.098 –0.102 –0.047** –0.042** (–1.09) (–1.12) (–2.35) (–2.11) CEO age above 61 0.082 0.081 0.022 0.016 (1.29) (1.31) (1.56) (1.14) Year fixed effects Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Observations 388 397 3,745 3,810 Adjusted $$R^2$$ 0.038 0.019 0.021 0.016 The regressions contain all firm-fiscal year observations ending between January 2005 and December 2006, and all variables are measured at the firm-fiscal-year level. CEO turnover equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. Unvested option duration is the weighted average number of months until unvested option grants vest. Unvested option moneyness is the weighted average of the moneyness of all unvested option grants. Accelerate equals 1 if a firm accelerated option vesting during the fiscal year, and 0 in all other fiscal years. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. The year fixed effect equals 1 for firm-fiscal year observations ending in calendar year 2005, and 0 for firm-fiscal year observations ending in calendar year 2006. Industry fixed effects are based on the Fama-French 48 industry classification. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. Table 6 CEO turnover and option characteristics Dependent variable CEO turnover CEO turnover Model Sample OLS Accelerating firms OLS All firms Window of analysis 2005–2006 2005–2006 (1) (2) (3) (4) Unvested option duration 0.006*** –0.000 (2.91) (–0.03) Unvested option moneyness 0.051* 0.008 (1.93) (1.31) Unvested option duration$$\times$$Accelerate 0.006*** (2.59) Unvested option moneyness$$\times$$Accelerate 0.017 (0.64) Accelerate –0.052 0.035 (–1.18) (0.93) Log assets 0.032** 0.030** 0.021*** 0.018*** (2.25) (2.06) (5.23) (4.75) Market/book ratio –0.029 –0.019 0.006*** 0.006*** (–1.46) (–0.89) (6.79) (4.98) Stock return 0.019 –0.062 –0.012 –0.014 (0.26) (–0.88) (–0.75) (–0.84) Stock volatility 0.108 –0.115 0.084 0.037 (0.31) (–0.34) (0.85) (0.38) ROA –0.437*** –0.354** –0.079** –0.069* (–2.75) (–1.99) (–2.09) (–1.82) Sales growth –0.098 –0.102 –0.047** –0.042** (–1.09) (–1.12) (–2.35) (–2.11) CEO age above 61 0.082 0.081 0.022 0.016 (1.29) (1.31) (1.56) (1.14) Year fixed effects Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Observations 388 397 3,745 3,810 Adjusted $$R^2$$ 0.038 0.019 0.021 0.016 Dependent variable CEO turnover CEO turnover Model Sample OLS Accelerating firms OLS All firms Window of analysis 2005–2006 2005–2006 (1) (2) (3) (4) Unvested option duration 0.006*** –0.000 (2.91) (–0.03) Unvested option moneyness 0.051* 0.008 (1.93) (1.31) Unvested option duration$$\times$$Accelerate 0.006*** (2.59) Unvested option moneyness$$\times$$Accelerate 0.017 (0.64) Accelerate –0.052 0.035 (–1.18) (0.93) Log assets 0.032** 0.030** 0.021*** 0.018*** (2.25) (2.06) (5.23) (4.75) Market/book ratio –0.029 –0.019 0.006*** 0.006*** (–1.46) (–0.89) (6.79) (4.98) Stock return 0.019 –0.062 –0.012 –0.014 (0.26) (–0.88) (–0.75) (–0.84) Stock volatility 0.108 –0.115 0.084 0.037 (0.31) (–0.34) (0.85) (0.38) ROA –0.437*** –0.354** –0.079** –0.069* (–2.75) (–1.99) (–2.09) (–1.82) Sales growth –0.098 –0.102 –0.047** –0.042** (–1.09) (–1.12) (–2.35) (–2.11) CEO age above 61 0.082 0.081 0.022 0.016 (1.29) (1.31) (1.56) (1.14) Year fixed effects Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Observations 388 397 3,745 3,810 Adjusted $$R^2$$ 0.038 0.019 0.021 0.016 The regressions contain all firm-fiscal year observations ending between January 2005 and December 2006, and all variables are measured at the firm-fiscal-year level. CEO turnover equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. Unvested option duration is the weighted average number of months until unvested option grants vest. Unvested option moneyness is the weighted average of the moneyness of all unvested option grants. Accelerate equals 1 if a firm accelerated option vesting during the fiscal year, and 0 in all other fiscal years. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. The year fixed effect equals 1 for firm-fiscal year observations ending in calendar year 2005, and 0 for firm-fiscal year observations ending in calendar year 2006. Industry fixed effects are based on the Fama-French 48 industry classification. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. 4.2 Acceleration and turnover: Main results One concern with Figure 4 is that the turnover patterns could be explained by reverse causality (firms accelerating the options of CEOs who had already decided to depart) or performance shocks that simultaneously caused firms to accelerate options and executives to leave. We therefore proceed to estimate the effect of option acceleration on turnover in Table 5 using our 2SLS strategy. We report results for CEO turnover, our two measures of voluntary CEO turnover, and top executive turnover. We report OLS regression results in Columns 1 through 3, and 2SLS regression results in the remaining columns. We measure option acceleration using both Frac. options accelerated and Accelerate. The sample contains all firm-fiscal-year observations ending between January 2005 and December 2006, except Column 7, which excludes all fiscal year observations that end in December. Table 5 Effect of option acceleration on CEO turnover Dependent variable CEO turnover CEO turnover Voluntary CEO turnover CEO turnover CEO turnover Voluntary CEO turnover CEO turnover Voluntary CEO turnover (JKPW) Executive turnover Model OLS 2SLS Sample All firms All firms All firms All firms All firms All firms Exclude Dec. FY firms ExecuComp firms All firms Window of analysis 2005–2006 2005–2006 (1) (2) (3) (4) (5) (6) (7) (8) (9) Frac. options accelerated 0.162*** 0.133*** 1.689*** 1.325*** 0.822** 2.346*** 1.027*** (3.06) (2.71) (4.59) (3.88) (2.21) (3.40) (4.02) Accelerate 0.044** 0.472*** (2.34) (5.09) Log assets 0.023*** 0.023*** 0.013*** 0.024*** 0.024*** 0.014*** 0.027*** 0.009 0.027*** (6.93) (7.36) (4.50) (6.27) (7.13) (4.22) (3.94) (1.43) (11.67) Market/book ratio 0.005*** 0.005*** 0.003*** 0.007*** 0.006*** 0.005*** 0.005*** 0.005*** 0.006*** (3.55) (3.60) (3.70) (6.49) (5.00) (5.28) (5.95) (3.45) (9.06) Stock return –0.002 –0.005 0.028** 0.061*** 0.040** 0.077*** 0.033 0.102** 0.020 (–0.15) (–0.34) (2.18) (2.80) (2.36) (3.95) (1.18) (2.57) (1.28) Stock volatility 0.080 0.086 –0.028 –0.022 0.048 –0.108 0.173 –0.066 0.018 (1.04) (1.16) (–0.44) (–0.23) (0.61) (–1.36) (1.03) (–0.29) (0.27) ROA –0.111*** –0.111*** –0.037 –0.126*** –0.141*** –0.048* –0.238*** 0.082 –0.015 (–3.52) (–3.62) (–1.40) (–3.49) (–4.38) (–1.66) (–3.31) (0.53) (–0.63) Sales growth –0.037** –0.041** –0.004 –0.039* –0.031* –0.006 –0.025 –0.058 –0.032** (–2.00) (–2.28) (–0.26) (–1.87) (–1.67) (–0.33) (–0.54) (–1.26) (–2.41) CEO age above 61 0.004 0.003 0.012 0.012 0.010 0.018 –0.027 0.071*** (0.37) (0.28) (1.08) (0.97) (0.82) (1.56) (–1.41) (3.60) Non-compete clauses –0.005** –0.005* –0.006*** –0.005* –0.004* –0.006** –0.006 –0.013*** –0.004* (–2.03) (–1.96) (–2.60) (–1.89) (–1.68) (–2.44) (–1.32) (–3.07) (–1.90) Distance to peers –0.000 –0.000 –0.000 –0.000 –0.000 –0.000 0.000 –0.000 –0.000 (–0.78) (–0.56) (–0.54) (–0.52) (–0.54) (–0.34) (0.36) (–0.82) (–0.02) Frac. executives above 61 –0.033** (–2.26) Year fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations 4,660 4,892 4,660 4,660 4,892 4,660 1,457 2,331 4,693 Adjusted $$R^2$$ 0.023 0.022 0.014 Dependent variable CEO turnover CEO turnover Voluntary CEO turnover CEO turnover CEO turnover Voluntary CEO turnover CEO turnover Voluntary CEO turnover (JKPW) Executive turnover Model OLS 2SLS Sample All firms All firms All firms All firms All firms All firms Exclude Dec. FY firms ExecuComp firms All firms Window of analysis 2005–2006 2005–2006 (1) (2) (3) (4) (5) (6) (7) (8) (9) Frac. options accelerated 0.162*** 0.133*** 1.689*** 1.325*** 0.822** 2.346*** 1.027*** (3.06) (2.71) (4.59) (3.88) (2.21) (3.40) (4.02) Accelerate 0.044** 0.472*** (2.34) (5.09) Log assets 0.023*** 0.023*** 0.013*** 0.024*** 0.024*** 0.014*** 0.027*** 0.009 0.027*** (6.93) (7.36) (4.50) (6.27) (7.13) (4.22) (3.94) (1.43) (11.67) Market/book ratio 0.005*** 0.005*** 0.003*** 0.007*** 0.006*** 0.005*** 0.005*** 0.005*** 0.006*** (3.55) (3.60) (3.70) (6.49) (5.00) (5.28) (5.95) (3.45) (9.06) Stock return –0.002 –0.005 0.028** 0.061*** 0.040** 0.077*** 0.033 0.102** 0.020 (–0.15) (–0.34) (2.18) (2.80) (2.36) (3.95) (1.18) (2.57) (1.28) Stock volatility 0.080 0.086 –0.028 –0.022 0.048 –0.108 0.173 –0.066 0.018 (1.04) (1.16) (–0.44) (–0.23) (0.61) (–1.36) (1.03) (–0.29) (0.27) ROA –0.111*** –0.111*** –0.037 –0.126*** –0.141*** –0.048* –0.238*** 0.082 –0.015 (–3.52) (–3.62) (–1.40) (–3.49) (–4.38) (–1.66) (–3.31) (0.53) (–0.63) Sales growth –0.037** –0.041** –0.004 –0.039* –0.031* –0.006 –0.025 –0.058 –0.032** (–2.00) (–2.28) (–0.26) (–1.87) (–1.67) (–0.33) (–0.54) (–1.26) (–2.41) CEO age above 61 0.004 0.003 0.012 0.012 0.010 0.018 –0.027 0.071*** (0.37) (0.28) (1.08) (0.97) (0.82) (1.56) (–1.41) (3.60) Non-compete clauses –0.005** –0.005* –0.006*** –0.005* –0.004* –0.006** –0.006 –0.013*** –0.004* (–2.03) (–1.96) (–2.60) (–1.89) (–1.68) (–2.44) (–1.32) (–3.07) (–1.90) Distance to peers –0.000 –0.000 –0.000 –0.000 –0.000 –0.000 0.000 –0.000 –0.000 (–0.78) (–0.56) (–0.54) (–0.52) (–0.54) (–0.34) (0.36) (–0.82) (–0.02) Frac. executives above 61 –0.033** (–2.26) Year fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations 4,660 4,892 4,660 4,660 4,892 4,660 1,457 2,331 4,693 Adjusted $$R^2$$ 0.023 0.022 0.014 The regressions contain all firm-fiscal year observations ending between January 2005 and December 2006, and all variables are measured at the firm-fiscal-year level. CEO turnover equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. Voluntary CEO turnover equals 1 if a firm experiences a voluntary CEO departure during the next fiscal year, and 0 in all other fiscal years. Voluntary CEO turnover (JKPW) equals 1 if a firm experiences a voluntary CEO departure during the next fiscal year that is identified using the JKPW database, and 0 in all other fiscal years. Executive turnover is the number of executives departing during the next fiscal year divided by the total number of top executives. Frac. options accelerated is the number of options accelerated during the fiscal year, divided by the number of options outstanding at the beginning of the fiscal year. Accelerate equals 1 if a firm accelerated option vesting during the fiscal year, and 0 in all other fiscal years. 2SLS regressions instrument Frac. options accelerated (Accelerate) using FAS 123-R takes effect. This variable equals 1 for firm-fiscal year observations ending between June 2005 and May 2006, and 0 for all other firm-fiscal year observations. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. The year fixed effect equals 1 for firm-fiscal year observations ending in calendar year 2005, and 0 for firm-fiscal year observations ending in calendar year 2006. Industry fixed effects are based on the Fama-French 48 industry classification. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. Table 5 Effect of option acceleration on CEO turnover Dependent variable CEO turnover CEO turnover Voluntary CEO turnover CEO turnover CEO turnover Voluntary CEO turnover CEO turnover Voluntary CEO turnover (JKPW) Executive turnover Model OLS 2SLS Sample All firms All firms All firms All firms All firms All firms Exclude Dec. FY firms ExecuComp firms All firms Window of analysis 2005–2006 2005–2006 (1) (2) (3) (4) (5) (6) (7) (8) (9) Frac. options accelerated 0.162*** 0.133*** 1.689*** 1.325*** 0.822** 2.346*** 1.027*** (3.06) (2.71) (4.59) (3.88) (2.21) (3.40) (4.02) Accelerate 0.044** 0.472*** (2.34) (5.09) Log assets 0.023*** 0.023*** 0.013*** 0.024*** 0.024*** 0.014*** 0.027*** 0.009 0.027*** (6.93) (7.36) (4.50) (6.27) (7.13) (4.22) (3.94) (1.43) (11.67) Market/book ratio 0.005*** 0.005*** 0.003*** 0.007*** 0.006*** 0.005*** 0.005*** 0.005*** 0.006*** (3.55) (3.60) (3.70) (6.49) (5.00) (5.28) (5.95) (3.45) (9.06) Stock return –0.002 –0.005 0.028** 0.061*** 0.040** 0.077*** 0.033 0.102** 0.020 (–0.15) (–0.34) (2.18) (2.80) (2.36) (3.95) (1.18) (2.57) (1.28) Stock volatility 0.080 0.086 –0.028 –0.022 0.048 –0.108 0.173 –0.066 0.018 (1.04) (1.16) (–0.44) (–0.23) (0.61) (–1.36) (1.03) (–0.29) (0.27) ROA –0.111*** –0.111*** –0.037 –0.126*** –0.141*** –0.048* –0.238*** 0.082 –0.015 (–3.52) (–3.62) (–1.40) (–3.49) (–4.38) (–1.66) (–3.31) (0.53) (–0.63) Sales growth –0.037** –0.041** –0.004 –0.039* –0.031* –0.006 –0.025 –0.058 –0.032** (–2.00) (–2.28) (–0.26) (–1.87) (–1.67) (–0.33) (–0.54) (–1.26) (–2.41) CEO age above 61 0.004 0.003 0.012 0.012 0.010 0.018 –0.027 0.071*** (0.37) (0.28) (1.08) (0.97) (0.82) (1.56) (–1.41) (3.60) Non-compete clauses –0.005** –0.005* –0.006*** –0.005* –0.004* –0.006** –0.006 –0.013*** –0.004* (–2.03) (–1.96) (–2.60) (–1.89) (–1.68) (–2.44) (–1.32) (–3.07) (–1.90) Distance to peers –0.000 –0.000 –0.000 –0.000 –0.000 –0.000 0.000 –0.000 –0.000 (–0.78) (–0.56) (–0.54) (–0.52) (–0.54) (–0.34) (0.36) (–0.82) (–0.02) Frac. executives above 61 –0.033** (–2.26) Year fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations 4,660 4,892 4,660 4,660 4,892 4,660 1,457 2,331 4,693 Adjusted $$R^2$$ 0.023 0.022 0.014 Dependent variable CEO turnover CEO turnover Voluntary CEO turnover CEO turnover CEO turnover Voluntary CEO turnover CEO turnover Voluntary CEO turnover (JKPW) Executive turnover Model OLS 2SLS Sample All firms All firms All firms All firms All firms All firms Exclude Dec. FY firms ExecuComp firms All firms Window of analysis 2005–2006 2005–2006 (1) (2) (3) (4) (5) (6) (7) (8) (9) Frac. options accelerated 0.162*** 0.133*** 1.689*** 1.325*** 0.822** 2.346*** 1.027*** (3.06) (2.71) (4.59) (3.88) (2.21) (3.40) (4.02) Accelerate 0.044** 0.472*** (2.34) (5.09) Log assets 0.023*** 0.023*** 0.013*** 0.024*** 0.024*** 0.014*** 0.027*** 0.009 0.027*** (6.93) (7.36) (4.50) (6.27) (7.13) (4.22) (3.94) (1.43) (11.67) Market/book ratio 0.005*** 0.005*** 0.003*** 0.007*** 0.006*** 0.005*** 0.005*** 0.005*** 0.006*** (3.55) (3.60) (3.70) (6.49) (5.00) (5.28) (5.95) (3.45) (9.06) Stock return –0.002 –0.005 0.028** 0.061*** 0.040** 0.077*** 0.033 0.102** 0.020 (–0.15) (–0.34) (2.18) (2.80) (2.36) (3.95) (1.18) (2.57) (1.28) Stock volatility 0.080 0.086 –0.028 –0.022 0.048 –0.108 0.173 –0.066 0.018 (1.04) (1.16) (–0.44) (–0.23) (0.61) (–1.36) (1.03) (–0.29) (0.27) ROA –0.111*** –0.111*** –0.037 –0.126*** –0.141*** –0.048* –0.238*** 0.082 –0.015 (–3.52) (–3.62) (–1.40) (–3.49) (–4.38) (–1.66) (–3.31) (0.53) (–0.63) Sales growth –0.037** –0.041** –0.004 –0.039* –0.031* –0.006 –0.025 –0.058 –0.032** (–2.00) (–2.28) (–0.26) (–1.87) (–1.67) (–0.33) (–0.54) (–1.26) (–2.41) CEO age above 61 0.004 0.003 0.012 0.012 0.010 0.018 –0.027 0.071*** (0.37) (0.28) (1.08) (0.97) (0.82) (1.56) (–1.41) (3.60) Non-compete clauses –0.005** –0.005* –0.006*** –0.005* –0.004* –0.006** –0.006 –0.013*** –0.004* (–2.03) (–1.96) (–2.60) (–1.89) (–1.68) (–2.44) (–1.32) (–3.07) (–1.90) Distance to peers –0.000 –0.000 –0.000 –0.000 –0.000 –0.000 0.000 –0.000 –0.000 (–0.78) (–0.56) (–0.54) (–0.52) (–0.54) (–0.34) (0.36) (–0.82) (–0.02) Frac. executives above 61 –0.033** (–2.26) Year fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations 4,660 4,892 4,660 4,660 4,892 4,660 1,457 2,331 4,693 Adjusted $$R^2$$ 0.023 0.022 0.014 The regressions contain all firm-fiscal year observations ending between January 2005 and December 2006, and all variables are measured at the firm-fiscal-year level. CEO turnover equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. Voluntary CEO turnover equals 1 if a firm experiences a voluntary CEO departure during the next fiscal year, and 0 in all other fiscal years. Voluntary CEO turnover (JKPW) equals 1 if a firm experiences a voluntary CEO departure during the next fiscal year that is identified using the JKPW database, and 0 in all other fiscal years. Executive turnover is the number of executives departing during the next fiscal year divided by the total number of top executives. Frac. options accelerated is the number of options accelerated during the fiscal year, divided by the number of options outstanding at the beginning of the fiscal year. Accelerate equals 1 if a firm accelerated option vesting during the fiscal year, and 0 in all other fiscal years. 2SLS regressions instrument Frac. options accelerated (Accelerate) using FAS 123-R takes effect. This variable equals 1 for firm-fiscal year observations ending between June 2005 and May 2006, and 0 for all other firm-fiscal year observations. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. The year fixed effect equals 1 for firm-fiscal year observations ending in calendar year 2005, and 0 for firm-fiscal year observations ending in calendar year 2006. Industry fixed effects are based on the Fama-French 48 industry classification. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. The OLS regressions show that firms that accelerated option vesting were more likely to experience a CEO departure during the next fiscal year. Column 3 indicates that a one-standard-deviation increase in Frac. options accelerated led to a (0.133 $$\times$$ 0.122=) 1.6 percentage-point increase in Voluntary CEO turnover, from 5% in the fiscal year before FAS 123-R took effect to 6.6% in the fiscal year afterward. The association between option acceleration and CEO turnover remains economically large and highly statistically significant in our 2SLS models. Column 6 implies that the voluntary CEO turnover rate rose by (1.325 $$\times$$ 0.122=) 16.2 percentage points for a one-standard-deviation increase in Frac. options accelerated. This implies an increase for accelerating firms from the pre-FAS 123-R unconditional mean of 5% to 21.2%. We find an economically smaller but still statistically significant effect also in Column 7 when excluding all firm-fiscal year observations that end in December. Our results also continue to hold in Column 8 when using our second measure of voluntary turnover among ExecuComp firms. Finally, Column 9 shows that option acceleration also led to a statistically significant increase in Executive turnover. The results imply that the top executive turnover rate rose by (1.027 $$\times$$ 0.122=) 12.5 percentage points for a one-standard-deviation increase in Frac. options accelerated, from the pre-FAS 123-R unconditional mean of 8.8% to 21.3%. Notably, we explain below (in Section 4.3) that the relatively large magnitudes of these 2SLS estimates likely reflect the LATE for the subsample of firms that accelerated due to FAS 123-R. Our identification in Table 5 compares adjacent sets of firms with fiscal years ending in the first or second half of a calendar year. Because option acceleration and executive turnover occurred more gradually, we conduct several additional tests using finer variation in timing. First, Figure 5 plots the relationship between the dates of option acceleration and CEO departure announcements. We obtain data from Capital IQ on the exact announcement dates for 68 voluntary CEO departures from accelerating firms. The figure shows a strong positive relationship ($$t$$-statistic=8.9) across calendar time between option acceleration and CEO turnover; firms that accelerated options earlier also experienced earlier CEO departures. Second, I.A. Table 3 instruments Frac. options accelerated using 12 dummy variables that each equal 1 when a firm-fiscal year observation ends in a given month between June 2005 and May 2006, rather than our coarser instrument FAS 123-R takes effect. Option acceleration continues to lead to higher CEO turnover in this 2SLS framework that uses finer monthly variation in FAS 123-R compliance. Finally, I.A. Table 4 shows that option acceleration led to significant increases in turnover also during the first 3, 6, and 9 months of the next fiscal year. These additional results are unlikely to be fully explained by macroeconomic shocks that cause turnover to rise among all firms at a single point in calendar time. Our results are robust to a variety of modifications to the 2SLS specification. I.A. Table 5 reports similar results for CEO turnover when controlling for corporate governance characteristics, industry-by-year fixed effects (which rule out bias from industry shocks coinciding with acceleration decisions), and firm fixed effects, and for executive turnover when excluding firm-fiscal year observations ending in December. The above results indicate that the decrease in departure costs due to option acceleration led executive turnover to rise. Next, in Table 6 we test whether the increase is larger among CEOs who experienced a larger decline in departure costs. Acceleration should have a greater impact on CEOs whose options were originally scheduled to vest over a longer time period (measured by Unvested option duration) and whose potential payoffs from accelerated options were higher (measured by Unvested option moneyness). Columns 1 and 2 regress CEO turnover on these variables for a sample of only accelerating firms. Consistent with our priors, turnover is significantly higher when options had a longer time until vesting or were more in the money. The estimates imply that CEO turnover rose by 0.6 percentage points for each one-month increase in Unvested option duration, and by 2.6 percentage points for an increase in Unvested option moneyness from 1 to 1.5. Next, Columns 3 and 4 repeat these tests across the entire sample. We interact Unvested option duration and Unvested option moneyness with Accelerate, to test whether the sensitivity of turnover to these variables is higher among accelerating than non-accelerating firms. The results indicate that this is the case for option duration. For moneyness, the interaction term coefficients are positive but insignificant, indicating that both accelerating and non-accelerating firms experience higher turnover when unvested options are more in the money. This result could be explained by higher performance among non-accelerating firms leading to a positive correlation between moneyness and turnover even in the absence of acceleration. If option acceleration led to a one-time rise in turnover, then accelerating and non-accelerating firms’ turnover rates should converge once CEOs have had ample time to pursue outside opportunities. Indeed, Figure 4 suggests that accelerating firms’ turnover rates fell back to pre-FAS 123-R levels after two fiscal years. I.A. Table 6 provides similar evidence using reduced form and 2SLS regressions—we find that the timing of FAS 123-R compliance, and also instrumented option acceleration, are unrelated to turnover in the second or third fiscal year after the regulation takes effect. 4.3 Interpretation of estimates Our 2SLS estimates measure the effect of vested options on CEO departures within the subset of “complier” firms that chose to accelerate options in the fiscal year before FAS 123-R took effect. These estimates likely represent the LATE of acceleration on executive turnover, rather than the average treatment effect across all sample firms. 2SLS identifies the LATE when treatment effects are heterogeneous across sample firms. This is likely in our setting, because all firms with unvested options faced accounting expenses under FAS 123-R, but only some (perhaps those with the lowest cost) decided to accelerate. Our estimates hence have little to say about the effect that option vesting would have had at firms that chose not to accelerate. One way to gauge the external validity of our estimates is to compare non-accelerating firms to complier firms. Table 7 presents key characteristics for both sets of firms during the fiscal years that ended between January 2001 and December 2004. The table shows that accelerating firms had relatively worse stock and accounting performance prior to FAS 123-R. However, despite this relative underperformance, the median accelerating firm earned positive stock returns and ROA.8 Accelerating firms were also smaller and had higher stock volatility. (Turnover was slightly lower at accelerating firms prior to FAS 123-R, but smaller firms generally have lower turnover; the difference is insignificant after controlling for size.) The difference in Unvested option duration is statistically significant but economically small, as the average time until options vested was less than one month longer at accelerating firms. The performance differences suggest that accelerating firms’ CEOs may have had lower ability than non-accelerating firms’ CEOs (assuming that firm performance is indicative of CEO ability). Firms that accelerated option vesting therefore may have considered the costs of acceleration to be relatively low, as CEO retention (and the effects of acceleration on turnover) was probably less important for them. In particular, accelerating firms’ boards may have presumed that their CEOs would be less likely to receive attractive outside offers, due to the relative past underperformance. Boards also may have expected that if turnover occurred, finding a replacement CEO with similar ability would not be too costly. As such, our estimates are most applicable to firms led by CEOs who are below average. They are less informative about the magnitude of unvested options’ retention incentives among firms with high-performing CEOs. Importantly, this interpretation does not imply that all CEOs at accelerating firms had below-average ability. In fact, the CEOs who chose to depart after option acceleration likely even had relatively high ability. Supporting this argument, we show below that many of these departing CEOs took new executive positions at other firms, and that accelerating firms’ stock prices fell when CEOs announced their departures. Table 8 provides further evidence suggesting that accelerating firms’ boards may have overemphasized the importance of reporting higher earnings relative to executive retention, as we find no evidence that boards replenished CEOs’ unvested option holdings on average. In the table we estimate regressions similar to those of Table 4, except that the window of analysis is shifted by one fiscal year because we examine option grants after acceleration. Columns 1 through 4 show that the value and PPS of CEOs’ unvested option holdings did not increase in the fiscal year after acceleration, relative to the value and PPS non-accelerating CEOs’ unvested options. Columns 5 and 6 further show that, on average, accelerating firms also did not increase CEO equity pay relative to non-accelerating firms. Instead, only those accelerating firms that experienced an executive departure subsequently adjusted pay (see below). Table 8 Non-replenishment of CEO incentives after option acceleration Dependent variable Log unvested option value $$\Delta$$Log unvested option value Log unvested option PPS $$\Delta$$Log unvested option PPS Log equity compensation $$\Delta$$Log equity compensation Model Sample OLS ExecuComp firms Window of analysis 2004–2008 2006–2007 2004–2008 2006–2007 2004–2008 2004–2008 (1) (2) (3) (4) (5) (6) Accelerate in previous fiscal year –0.183 –0.062 –0.139* –0.056 –0.270 –0.304 (–1.33) (–0.40) (–1.81) (–0.64) (–1.29) (–0.97) Log assets 0.604*** –0.068* 0.383*** –0.036* 0.580*** 0.079* (3.84) (–1.96) (4.33) (–1.84) (3.28) (1.83) Market/book ratio 0.052*** 0.008 0.027* 0.002 0.071*** –0.077 (2.83) (0.24) (1.94) (0.11) (3.75) (–1.26) Stock return 1.422*** 2.162*** 0.800*** 1.266*** –0.058 0.474** (15.13) (11.39) (15.22) (11.91) (–0.49) (2.04) Stock volatility 0.611 –0.247 –0.851 –0.192 1.455 1.025 (0.42) (–0.20) (–1.14) (–0.29) (0.94) (0.57) ROA –0.118 –0.955* –0.128 –0.497* 0.566 0.860 (–0.29) (–1.92) (–0.57) (–1.88) (1.15) (1.09) Sales growth 0.478*** 0.437* 0.289*** 0.262** 0.261 –0.273 (2.89) (1.88) (3.08) (2.10) (1.20) (–0.77) CEO age above 61 –0.384** –0.269*** –0.224** –0.178*** –0.553*** –0.246 (–2.52) (–2.62) (–2.52) (–3.19) (–3.57) (–1.62) Year fixed effects Yes Yes Yes Yes Yes Yes Industry fixed effects No Yes No Yes No Yes Firm fixed effects Yes No Yes No Yes No Observations 7,720 2,821 7,720 2,821 7,741 2,676 Adjusted $$R^2$$ 0.220 0.104 0.206 0.117 0.020 0.004 Dependent variable Log unvested option value $$\Delta$$Log unvested option value Log unvested option PPS $$\Delta$$Log unvested option PPS Log equity compensation $$\Delta$$Log equity compensation Model Sample OLS ExecuComp firms Window of analysis 2004–2008 2006–2007 2004–2008 2006–2007 2004–2008 2004–2008 (1) (2) (3) (4) (5) (6) Accelerate in previous fiscal year –0.183 –0.062 –0.139* –0.056 –0.270 –0.304 (–1.33) (–0.40) (–1.81) (–0.64) (–1.29) (–0.97) Log assets 0.604*** –0.068* 0.383*** –0.036* 0.580*** 0.079* (3.84) (–1.96) (4.33) (–1.84) (3.28) (1.83) Market/book ratio 0.052*** 0.008 0.027* 0.002 0.071*** –0.077 (2.83) (0.24) (1.94) (0.11) (3.75) (–1.26) Stock return 1.422*** 2.162*** 0.800*** 1.266*** –0.058 0.474** (15.13) (11.39) (15.22) (11.91) (–0.49) (2.04) Stock volatility 0.611 –0.247 –0.851 –0.192 1.455 1.025 (0.42) (–0.20) (–1.14) (–0.29) (0.94) (0.57) ROA –0.118 –0.955* –0.128 –0.497* 0.566 0.860 (–0.29) (–1.92) (–0.57) (–1.88) (1.15) (1.09) Sales growth 0.478*** 0.437* 0.289*** 0.262** 0.261 –0.273 (2.89) (1.88) (3.08) (2.10) (1.20) (–0.77) CEO age above 61 –0.384** –0.269*** –0.224** –0.178*** –0.553*** –0.246 (–2.52) (–2.62) (–2.52) (–3.19) (–3.57) (–1.62) Year fixed effects Yes Yes Yes Yes Yes Yes Industry fixed effects No Yes No Yes No Yes Firm fixed effects Yes No Yes No Yes No Observations 7,720 2,821 7,720 2,821 7,741 2,676 Adjusted $$R^2$$ 0.220 0.104 0.206 0.117 0.020 0.004 The regressions contain firm-fiscal year observations for ExecuComp firms that end between January 2004 and December 2008 (January 2006 and December 2007 in Columns 2 and 4). All variables are measured at the firm-fiscal-year level. Log unvested option value is the natural logarithm of the Black-Scholes value of a CEO’s unvested stock options at the end of the fiscal year. Log unvested option PPS is the natural logarithm of the change in the dollar value of a CEO’s unvested option holdings for a 1% change in the firm’s stock price. Log equity compensation is the natural logarithm of a CEO’s annual equity compensation. Accelerate in previous fiscal year equals 1 if a firm accelerated option vesting during the previous fiscal year, and 0 in all other fiscal years. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. Year fixed effects equal 1 for firm-fiscal year observations that end in the same calendar year. Industry fixed effects are based on the Fama-French 48 industry classification. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. Table 8 Non-replenishment of CEO incentives after option acceleration Dependent variable Log unvested option value $$\Delta$$Log unvested option value Log unvested option PPS $$\Delta$$Log unvested option PPS Log equity compensation $$\Delta$$Log equity compensation Model Sample OLS ExecuComp firms Window of analysis 2004–2008 2006–2007 2004–2008 2006–2007 2004–2008 2004–2008 (1) (2) (3) (4) (5) (6) Accelerate in previous fiscal year –0.183 –0.062 –0.139* –0.056 –0.270 –0.304 (–1.33) (–0.40) (–1.81) (–0.64) (–1.29) (–0.97) Log assets 0.604*** –0.068* 0.383*** –0.036* 0.580*** 0.079* (3.84) (–1.96) (4.33) (–1.84) (3.28) (1.83) Market/book ratio 0.052*** 0.008 0.027* 0.002 0.071*** –0.077 (2.83) (0.24) (1.94) (0.11) (3.75) (–1.26) Stock return 1.422*** 2.162*** 0.800*** 1.266*** –0.058 0.474** (15.13) (11.39) (15.22) (11.91) (–0.49) (2.04) Stock volatility 0.611 –0.247 –0.851 –0.192 1.455 1.025 (0.42) (–0.20) (–1.14) (–0.29) (0.94) (0.57) ROA –0.118 –0.955* –0.128 –0.497* 0.566 0.860 (–0.29) (–1.92) (–0.57) (–1.88) (1.15) (1.09) Sales growth 0.478*** 0.437* 0.289*** 0.262** 0.261 –0.273 (2.89) (1.88) (3.08) (2.10) (1.20) (–0.77) CEO age above 61 –0.384** –0.269*** –0.224** –0.178*** –0.553*** –0.246 (–2.52) (–2.62) (–2.52) (–3.19) (–3.57) (–1.62) Year fixed effects Yes Yes Yes Yes Yes Yes Industry fixed effects No Yes No Yes No Yes Firm fixed effects Yes No Yes No Yes No Observations 7,720 2,821 7,720 2,821 7,741 2,676 Adjusted $$R^2$$ 0.220 0.104 0.206 0.117 0.020 0.004 Dependent variable Log unvested option value $$\Delta$$Log unvested option value Log unvested option PPS $$\Delta$$Log unvested option PPS Log equity compensation $$\Delta$$Log equity compensation Model Sample OLS ExecuComp firms Window of analysis 2004–2008 2006–2007 2004–2008 2006–2007 2004–2008 2004–2008 (1) (2) (3) (4) (5) (6) Accelerate in previous fiscal year –0.183 –0.062 –0.139* –0.056 –0.270 –0.304 (–1.33) (–0.40) (–1.81) (–0.64) (–1.29) (–0.97) Log assets 0.604*** –0.068* 0.383*** –0.036* 0.580*** 0.079* (3.84) (–1.96) (4.33) (–1.84) (3.28) (1.83) Market/book ratio 0.052*** 0.008 0.027* 0.002 0.071*** –0.077 (2.83) (0.24) (1.94) (0.11) (3.75) (–1.26) Stock return 1.422*** 2.162*** 0.800*** 1.266*** –0.058 0.474** (15.13) (11.39) (15.22) (11.91) (–0.49) (2.04) Stock volatility 0.611 –0.247 –0.851 –0.192 1.455 1.025 (0.42) (–0.20) (–1.14) (–0.29) (0.94) (0.57) ROA –0.118 –0.955* –0.128 –0.497* 0.566 0.860 (–0.29) (–1.92) (–0.57) (–1.88) (1.15) (1.09) Sales growth 0.478*** 0.437* 0.289*** 0.262** 0.261 –0.273 (2.89) (1.88) (3.08) (2.10) (1.20) (–0.77) CEO age above 61 –0.384** –0.269*** –0.224** –0.178*** –0.553*** –0.246 (–2.52) (–2.62) (–2.52) (–3.19) (–3.57) (–1.62) Year fixed effects Yes Yes Yes Yes Yes Yes Industry fixed effects No Yes No Yes No Yes Firm fixed effects Yes No Yes No Yes No Observations 7,720 2,821 7,720 2,821 7,741 2,676 Adjusted $$R^2$$ 0.220 0.104 0.206 0.117 0.020 0.004 The regressions contain firm-fiscal year observations for ExecuComp firms that end between January 2004 and December 2008 (January 2006 and December 2007 in Columns 2 and 4). All variables are measured at the firm-fiscal-year level. Log unvested option value is the natural logarithm of the Black-Scholes value of a CEO’s unvested stock options at the end of the fiscal year. Log unvested option PPS is the natural logarithm of the change in the dollar value of a CEO’s unvested option holdings for a 1% change in the firm’s stock price. Log equity compensation is the natural logarithm of a CEO’s annual equity compensation. Accelerate in previous fiscal year equals 1 if a firm accelerated option vesting during the previous fiscal year, and 0 in all other fiscal years. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. Year fixed effects equal 1 for firm-fiscal year observations that end in the same calendar year. Industry fixed effects are based on the Fama-French 48 industry classification. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. 4.4 Value effects of voluntary departures Next, we study how stock prices reacted to the announcement of voluntary CEO departures, separately for accelerating and non-accelerating firms. Table 9 reports raw and cumulative abnormal returns (CARs) based on the CAPM and 4-factor models, for different trading-day windows around the departure announcements. We report mean and median returns, with standard errors clustered by turnover event date. Data from Capital IQ allow us to identify the exact departure dates of 76 CEOs of accelerating firms and 294 CEOs of non-accelerating firms. Table 9 Effect of voluntary CEO turnover on firm value Stock returns around voluntary CEO departures Return adjustment method Raw returns CAPM FF4 Window of analysis [0] [$$-1$$,+3] [$$-3$$,+3] [0] [$$-1$$,+3] [$$-$$3,+3] [0] [$$-$$1,+3] [$$-$$3,+3] Mean returns Accelerating firms –0.47* –1.02** –1.11** –0.52* –1.19** –1.44*** –0.50* –1.26*** –1.45*** (–1.73) (–2.21) (–2.04) (–1.86) (–2.62) (–2.68) (–1.82) (–2.73) (–2.65) Non-accelerating firms 0.06 –0.14 –0.16 0.02 –0.08 –0.23 0.05 –0.13 –0.30 (–0.43) (–0.54) (–0.50) (–0.71) (–0.34) (–0.78) (–0.39) (–0.54) (–1.03) Difference in means 0.53* 0.89 0.96 0.54* 1.11** 1.21** 0.55* 1.12** 1.15* (–1.80) (–1.62) (–1.53) (–1.75) (–2.09) (–1.97) (–1.86) (–2.10) (–1.85) Median returns Accelerating firms –0.57* –0.97** –1.27** –0.28* –1.51*** –0.89*** –0.50* –1.30** –1.07** (–1.81) (–2.19) (–2.09) (–1.90) (–2.60) (–2.75) (–1.84) (–2.49) (–2.61) Non-accelerating firms 0.07 0.03 –0.04 –0.02 0.08 0.23 –0.01 0.18 0.28 (–0.76) (–0.10) (–0.36) (–0.05) (–0.02) (–0.16) (–0.29) (–0.10) (0.00) Difference in medians 0.64** 1.00** 1.23* 0.26* 1.59** 1.12** 0.49* 1.48** 1.45** (–2.01) (–2.09) (–1.95) (–1.88) (–2.29) (–2.47) (–1.85) (–2.24) (–2.42) Stock returns around voluntary CEO departures Return adjustment method Raw returns CAPM FF4 Window of analysis [0] [$$-1$$,+3] [$$-3$$,+3] [0] [$$-1$$,+3] [$$-$$3,+3] [0] [$$-$$1,+3] [$$-$$3,+3] Mean returns Accelerating firms –0.47* –1.02** –1.11** –0.52* –1.19** –1.44*** –0.50* –1.26*** –1.45*** (–1.73) (–2.21) (–2.04) (–1.86) (–2.62) (–2.68) (–1.82) (–2.73) (–2.65) Non-accelerating firms 0.06 –0.14 –0.16 0.02 –0.08 –0.23 0.05 –0.13 –0.30 (–0.43) (–0.54) (–0.50) (–0.71) (–0.34) (–0.78) (–0.39) (–0.54) (–1.03) Difference in means 0.53* 0.89 0.96 0.54* 1.11** 1.21** 0.55* 1.12** 1.15* (–1.80) (–1.62) (–1.53) (–1.75) (–2.09) (–1.97) (–1.86) (–2.10) (–1.85) Median returns Accelerating firms –0.57* –0.97** –1.27** –0.28* –1.51*** –0.89*** –0.50* –1.30** –1.07** (–1.81) (–2.19) (–2.09) (–1.90) (–2.60) (–2.75) (–1.84) (–2.49) (–2.61) Non-accelerating firms 0.07 0.03 –0.04 –0.02 0.08 0.23 –0.01 0.18 0.28 (–0.76) (–0.10) (–0.36) (–0.05) (–0.02) (–0.16) (–0.29) (–0.10) (0.00) Difference in medians 0.64** 1.00** 1.23* 0.26* 1.59** 1.12** 0.49* 1.48** 1.45** (–2.01) (–2.09) (–1.95) (–1.88) (–2.29) (–2.47) (–1.85) (–2.24) (–2.42) Raw and cumulative abnormal stock returns (CARs) are reported for different trading-day windows around voluntary CEO departures. The sample in this table contains 76 (294) CEO departure events at accelerating (non-accelerating) firms. Departures occurred between June 15, 2005 and June 15, 2007 (i.e., from the first FAS 123-R compliance date through 1 year after the last FAS 123-R compliance date). We report unadjusted returns, CARs based on the CAPM model, and CARs based on the Fama and French (1993) 3-factor model plus the Carhart (1997) momentum factor. Returns are measured in percentages. $$t$$-statistics for mean returns and $$z$$-statistics for median returns are shown in parentheses. Both are based on standard errors that are clustered by announcement date. ***, **. and * indicate significance levels of 1%, and 10%, respectively. Table 9 Effect of voluntary CEO turnover on firm value Stock returns around voluntary CEO departures Return adjustment method Raw returns CAPM FF4 Window of analysis [0] [$$-1$$,+3] [$$-3$$,+3] [0] [$$-1$$,+3] [$$-$$3,+3] [0] [$$-$$1,+3] [$$-$$3,+3] Mean returns Accelerating firms –0.47* –1.02** –1.11** –0.52* –1.19** –1.44*** –0.50* –1.26*** –1.45*** (–1.73) (–2.21) (–2.04) (–1.86) (–2.62) (–2.68) (–1.82) (–2.73) (–2.65) Non-accelerating firms 0.06 –0.14 –0.16 0.02 –0.08 –0.23 0.05 –0.13 –0.30 (–0.43) (–0.54) (–0.50) (–0.71) (–0.34) (–0.78) (–0.39) (–0.54) (–1.03) Difference in means 0.53* 0.89 0.96 0.54* 1.11** 1.21** 0.55* 1.12** 1.15* (–1.80) (–1.62) (–1.53) (–1.75) (–2.09) (–1.97) (–1.86) (–2.10) (–1.85) Median returns Accelerating firms –0.57* –0.97** –1.27** –0.28* –1.51*** –0.89*** –0.50* –1.30** –1.07** (–1.81) (–2.19) (–2.09) (–1.90) (–2.60) (–2.75) (–1.84) (–2.49) (–2.61) Non-accelerating firms 0.07 0.03 –0.04 –0.02 0.08 0.23 –0.01 0.18 0.28 (–0.76) (–0.10) (–0.36) (–0.05) (–0.02) (–0.16) (–0.29) (–0.10) (0.00) Difference in medians 0.64** 1.00** 1.23* 0.26* 1.59** 1.12** 0.49* 1.48** 1.45** (–2.01) (–2.09) (–1.95) (–1.88) (–2.29) (–2.47) (–1.85) (–2.24) (–2.42) Stock returns around voluntary CEO departures Return adjustment method Raw returns CAPM FF4 Window of analysis [0] [$$-1$$,+3] [$$-3$$,+3] [0] [$$-1$$,+3] [$$-$$3,+3] [0] [$$-$$1,+3] [$$-$$3,+3] Mean returns Accelerating firms –0.47* –1.02** –1.11** –0.52* –1.19** –1.44*** –0.50* –1.26*** –1.45*** (–1.73) (–2.21) (–2.04) (–1.86) (–2.62) (–2.68) (–1.82) (–2.73) (–2.65) Non-accelerating firms 0.06 –0.14 –0.16 0.02 –0.08 –0.23 0.05 –0.13 –0.30 (–0.43) (–0.54) (–0.50) (–0.71) (–0.34) (–0.78) (–0.39) (–0.54) (–1.03) Difference in means 0.53* 0.89 0.96 0.54* 1.11** 1.21** 0.55* 1.12** 1.15* (–1.80) (–1.62) (–1.53) (–1.75) (–2.09) (–1.97) (–1.86) (–2.10) (–1.85) Median returns Accelerating firms –0.57* –0.97** –1.27** –0.28* –1.51*** –0.89*** –0.50* –1.30** –1.07** (–1.81) (–2.19) (–2.09) (–1.90) (–2.60) (–2.75) (–1.84) (–2.49) (–2.61) Non-accelerating firms 0.07 0.03 –0.04 –0.02 0.08 0.23 –0.01 0.18 0.28 (–0.76) (–0.10) (–0.36) (–0.05) (–0.02) (–0.16) (–0.29) (–0.10) (0.00) Difference in medians 0.64** 1.00** 1.23* 0.26* 1.59** 1.12** 0.49* 1.48** 1.45** (–2.01) (–2.09) (–1.95) (–1.88) (–2.29) (–2.47) (–1.85) (–2.24) (–2.42) Raw and cumulative abnormal stock returns (CARs) are reported for different trading-day windows around voluntary CEO departures. The sample in this table contains 76 (294) CEO departure events at accelerating (non-accelerating) firms. Departures occurred between June 15, 2005 and June 15, 2007 (i.e., from the first FAS 123-R compliance date through 1 year after the last FAS 123-R compliance date). We report unadjusted returns, CARs based on the CAPM model, and CARs based on the Fama and French (1993) 3-factor model plus the Carhart (1997) momentum factor. Returns are measured in percentages. $$t$$-statistics for mean returns and $$z$$-statistics for median returns are shown in parentheses. Both are based on standard errors that are clustered by announcement date. ***, **. and * indicate significance levels of 1%, and 10%, respectively. Accelerating firms’ average 4-factor CARs were $$-$$0.5% on the CEO departure announcement day, widening to $$-$$1.45% in the 3-day window around the announcement. Other return models and median returns show similar losses. In contrast, non-accelerating firms’ returns are almost zero and statistically insignificant across all models. Our estimates imply that the average accelerating firm with a turnover event (and a market cap of $${\}$$2bn) experienced a drop in market value of (2 $$\times$$ 0.0145=) $${\}$$29m. This indicates that capital markets perceived voluntary CEO departures due to option acceleration to be costly and provides further evidence that the turnovers we capture likely do not reflect CEO firings. Compared to other sudden departures, accelerating firms’ losses are only slightly lower than the mean CAR of $$-$$1.82% that firms experience following a non-founder CEO’s sudden death (Jenter, Matveyev, and Roth 2017). This difference in magnitudes could be because markets anticipated some accelerated-induced turnover already prior to the actual departure, or because accelerating firms’ CEOs had slightly lower ability. Like in Jenter, Matveyev, and Roth (2017), the value losses that we document could reflect a reduction in match surplus between firms and CEOs, or frictions in the form of search and transition costs.9 Consistent with this interpretation, we find some evidence that the 76 accelerating firms that experienced a CEO departure subsequently incurred greater search costs. In untabulated tests, we find that 23.7% of these firms appointed an interim CEO following a departure, compared to 15% of non-accelerating firms (the $$t$$-stat of this difference is 3.3). Moreover, accelerating firms that hired an interim CEO spent 241 days on average searching for a permanent replacement, compared to 135 days for non-accelerating firms ($$t$$-stat of 3). 4.5 Departing executives’ new positions One concern with our analysis is that many departing executives may have either retired or been forced to leave. Table 10 indicates that this was rarely the case. Panel A presents data on new positions that CEOs and other top executives took after departing from accelerating firms. We identify these positions by hand-collecting data on each departing executive’s curriculum vitae, from various sources such as LinkedIn and Bloomberg. We could locate 94% of departing CEOs and 85% of other top executives. The panel shows that 44% of departing CEOs took executive positions at other firms, another 21% joined boards as non-executive directors (with 8% joining as chairmen), 10% started to work in consulting, and only 11% retired. Among other top executives, 57% took new executive positions, 8% accepted non-executive board positions, 6% joined consulting firms, and only 9% retired. These statistics show that executives chose to pursue a variety of outside opportunities after their departure costs fell due to option acceleration. The news sources that we examined while hand-collecting these data also confirm that the CEO departures we code as voluntary seem unlikely to be related to firings. Table 10 Departing executives at accelerating firms: New positions and age A. New positions after departure CEOs Top executives # Departures % Departures # Departures % Departures Executive 78 44 364 57 Non-executive director 23 13 52 8 Retirement 19 11 54 9 Consulting 18 10 40 6 Non-executive chairman 14 8 3 0 Private equity 7 4 8 1 Hedge fund 5 3 7 1 Other 3 2 8 1 No information on position 11 6 98 15 Total 178 100 634 100 B. Age upon departure CEOs Top executives Mean Median Mean Median Executive 51.6 51 48.5 47.5 Non-executive director 58.3 59.5 54.4 56 Retirement 65.4 63 59.9 59.5 Consulting 56.3 58 49.9 48 Non-executive chairman 61.7 62 51.3 50 Private equity 53.7 54 50.1 48.5 Hedge fund 56.6 57 53.4 53 Other 56 50 53.5 53 No information on position 54.7 56 52.9 49 Total 55.7 57 50.6 50 A. New positions after departure CEOs Top executives # Departures % Departures # Departures % Departures Executive 78 44 364 57 Non-executive director 23 13 52 8 Retirement 19 11 54 9 Consulting 18 10 40 6 Non-executive chairman 14 8 3 0 Private equity 7 4 8 1 Hedge fund 5 3 7 1 Other 3 2 8 1 No information on position 11 6 98 15 Total 178 100 634 100 B. Age upon departure CEOs Top executives Mean Median Mean Median Executive 51.6 51 48.5 47.5 Non-executive director 58.3 59.5 54.4 56 Retirement 65.4 63 59.9 59.5 Consulting 56.3 58 49.9 48 Non-executive chairman 61.7 62 51.3 50 Private equity 53.7 54 50.1 48.5 Hedge fund 56.6 57 53.4 53 Other 56 50 53.5 53 No information on position 54.7 56 52.9 49 Total 55.7 57 50.6 50 Panel A reports statistics on the positions that CEOs and top executives took after departing a firm that accelerated option vesting. Panel B reports statistics on executives’ age at departure. Table 10 Departing executives at accelerating firms: New positions and age A. New positions after departure CEOs Top executives # Departures % Departures # Departures % Departures Executive 78 44 364 57 Non-executive director 23 13 52 8 Retirement 19 11 54 9 Consulting 18 10 40 6 Non-executive chairman 14 8 3 0 Private equity 7 4 8 1 Hedge fund 5 3 7 1 Other 3 2 8 1 No information on position 11 6 98 15 Total 178 100 634 100 B. Age upon departure CEOs Top executives Mean Median Mean Median Executive 51.6 51 48.5 47.5 Non-executive director 58.3 59.5 54.4 56 Retirement 65.4 63 59.9 59.5 Consulting 56.3 58 49.9 48 Non-executive chairman 61.7 62 51.3 50 Private equity 53.7 54 50.1 48.5 Hedge fund 56.6 57 53.4 53 Other 56 50 53.5 53 No information on position 54.7 56 52.9 49 Total 55.7 57 50.6 50 A. New positions after departure CEOs Top executives # Departures % Departures # Departures % Departures Executive 78 44 364 57 Non-executive director 23 13 52 8 Retirement 19 11 54 9 Consulting 18 10 40 6 Non-executive chairman 14 8 3 0 Private equity 7 4 8 1 Hedge fund 5 3 7 1 Other 3 2 8 1 No information on position 11 6 98 15 Total 178 100 634 100 B. Age upon departure CEOs Top executives Mean Median Mean Median Executive 51.6 51 48.5 47.5 Non-executive director 58.3 59.5 54.4 56 Retirement 65.4 63 59.9 59.5 Consulting 56.3 58 49.9 48 Non-executive chairman 61.7 62 51.3 50 Private equity 53.7 54 50.1 48.5 Hedge fund 56.6 57 53.4 53 Other 56 50 53.5 53 No information on position 54.7 56 52.9 49 Total 55.7 57 50.6 50 Panel A reports statistics on the positions that CEOs and top executives took after departing a firm that accelerated option vesting. Panel B reports statistics on executives’ age at departure. Panel B reports the age of departing CEOs and top executives, separately for each type of new position. On average, departing CEOs were 55.7 years old and other top executives were 50.6 years old. The youngest departing executives mostly accepted new executive positions at other firms, while executives who joined consulting firms, hedge funds, or corporate boards were usually in their mid-50s. The few executives who retired were about ten years older than the average departing executive. 5. Effects of Turnover on Compensation Policies Next, we examine how firms responded to executive departures following option acceleration. We first study whether accelerating firms, after experiencing turnover, adjusted compensation for remaining and newly hired executives. An executive who contemplates an outside option trades off its expected utility against the expected utility from future income at the current employer. Firms can alter this trade-off and reduce departure rates by increasing pay. We therefore hypothesize that firms that unexpectedly experienced turnover following option acceleration subsequently adjusted pay to stem a further loss of talent. This response may be optimal if departures signal that the firm had underestimated the value of executives’ outside options. Table 11, panel A, compares pay levels in the two fiscal years before and after option acceleration, separately for accelerating firms that did and did not experience an executive departure. The sample contains top executives of ExecuComp firms and excludes non-accelerating firms. We study total and equity pay and examine pay changes for top executives who remained at the firm following option acceleration.10 To do this, we create two independent variables. The first variable, Firm with turnover, equals 1 in all fiscal years for a firm that experienced a top executive departure (in the fiscal year after acceleration), and 0 in all fiscal years for a firm that experienced no departure. The second variable, Post-acceleration, equals 1 in fiscal years after option acceleration, and 0 in all other fiscal years. A positive coefficient on Post-acceleration$$\times$$Firm with turnover would indicate that firms increased pay after an acceleration-induced departure, relative to accelerating firms that experienced no departure. Column 1 shows that remaining executives’ pay rose 11% in the fiscal year after a departure, relative to executives of accelerating firms that experienced no departure. Column 2 shows that much of this increase came from higher equity pay. In both columns the sum of the coefficients on Firm with turnover and Post-acceleration $$\times$$ Firm with turnover is positive, indicating that departure firms raised remaining executives’ pay to exceed the pay levels at non-departure firms. Table 11 Compensation changes following executive departures A. Remaining executives B. Departing and newly hired CEOs Dependent variable Log total compensation Log equity compensation Log total compensation Log equity compensation Model Sample Window of analysis OLS Accelerating firms in ExecuComp Two fiscal years around option acceleration (1) (2) (3) (4) Post-acceleration$$\times$$Firm with turnover 0.114** 0.481** (2.36) (2.18) Post-acceleration$$\times$$Firm with CEO turnover 0.323** 1.518*** (2.46) (3.10) Post-acceleration 0.046 –0.162 0.042 0.189 (0.61) (–0.45) (0.27) (0.29) Firm with turnover –0.031 –0.324* (–0.62) (–1.96) Firm with CEO turnover –0.231** –0.709** (–2.15) (–2.10) Log assets 0.423*** 0.592*** 0.428*** 0.652*** (28.47) (11.70) (15.29) (6.46) Market/book ratio 0.139*** 0.263*** 0.131*** 0.117 (5.53) (4.10) (2.72) (0.87) Stock return –0.046 –0.061 0.062 0.144 (–1.26) (–0.35) (0.86) (0.52) Stock volatility 1.322*** 1.355 1.492** 4.323* (3.38) (1.00) (2.13) (1.88) ROA 0.219 0.387 0.239 0.300 (1.58) (1.06) (1.05) (0.47) Sales growth 0.179*** 0.653*** 0.109 0.625 (2.79) (3.22) (0.91) (1.41) Frac. executives above 61 0.230 –0.600 (1.57) (–1.01) CEO age above 61 –0.132 –1.019** (–0.88) (–2.46) Year fixed effects Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Observations 6,676 6,676 912 912 Adjusted $$R^2$$ 0.432 0.186 0.442 0.176 A. Remaining executives B. Departing and newly hired CEOs Dependent variable Log total compensation Log equity compensation Log total compensation Log equity compensation Model Sample Window of analysis OLS Accelerating firms in ExecuComp Two fiscal years around option acceleration (1) (2) (3) (4) Post-acceleration$$\times$$Firm with turnover 0.114** 0.481** (2.36) (2.18) Post-acceleration$$\times$$Firm with CEO turnover 0.323** 1.518*** (2.46) (3.10) Post-acceleration 0.046 –0.162 0.042 0.189 (0.61) (–0.45) (0.27) (0.29) Firm with turnover –0.031 –0.324* (–0.62) (–1.96) Firm with CEO turnover –0.231** –0.709** (–2.15) (–2.10) Log assets 0.423*** 0.592*** 0.428*** 0.652*** (28.47) (11.70) (15.29) (6.46) Market/book ratio 0.139*** 0.263*** 0.131*** 0.117 (5.53) (4.10) (2.72) (0.87) Stock return –0.046 –0.061 0.062 0.144 (–1.26) (–0.35) (0.86) (0.52) Stock volatility 1.322*** 1.355 1.492** 4.323* (3.38) (1.00) (2.13) (1.88) ROA 0.219 0.387 0.239 0.300 (1.58) (1.06) (1.05) (0.47) Sales growth 0.179*** 0.653*** 0.109 0.625 (2.79) (3.22) (0.91) (1.41) Frac. executives above 61 0.230 –0.600 (1.57) (–1.01) CEO age above 61 –0.132 –1.019** (–0.88) (–2.46) Year fixed effects Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Observations 6,676 6,676 912 912 Adjusted $$R^2$$ 0.432 0.186 0.442 0.176 The regressions contain observations for executives of accelerating firms in ExecuComp, for the two fiscal years before to two fiscal years after each option acceleration event. All variables are measured at the executive-fiscal year or firm-fiscal-year level. Panel A shows pay for top executives that remained at the firm both before and after option acceleration. Panel B shows pay for all CEOs of accelerating firms, including those who departed or were hired after option acceleration. Log total compensation is the natural logarithm of an executive’s annual total compensation. Log equity compensation is the natural logarithm of an executive’s annual equity compensation. Post-acceleration equals 1 in fiscal years after a firm accelerated option vesting, and 0 in all other fiscal years. Firm with turnover equals 1 in all fiscal years for a firm that experienced a top executive departure in the fiscal year after acceleration, and 0 in all other fiscal years. Firm with CEO turnover equals 1 in all fiscal years for a firm that experienced a CEO departure in the fiscal year after acceleration, and 0 in all other fiscal years. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. Year fixed effects equal 1 for firm-fiscal year observations that end in the same calendar year. Industry fixed effects are based on the Fama-French 48 industry classification. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. Table 11 Compensation changes following executive departures A. Remaining executives B. Departing and newly hired CEOs Dependent variable Log total compensation Log equity compensation Log total compensation Log equity compensation Model Sample Window of analysis OLS Accelerating firms in ExecuComp Two fiscal years around option acceleration (1) (2) (3) (4) Post-acceleration$$\times$$Firm with turnover 0.114** 0.481** (2.36) (2.18) Post-acceleration$$\times$$Firm with CEO turnover 0.323** 1.518*** (2.46) (3.10) Post-acceleration 0.046 –0.162 0.042 0.189 (0.61) (–0.45) (0.27) (0.29) Firm with turnover –0.031 –0.324* (–0.62) (–1.96) Firm with CEO turnover –0.231** –0.709** (–2.15) (–2.10) Log assets 0.423*** 0.592*** 0.428*** 0.652*** (28.47) (11.70) (15.29) (6.46) Market/book ratio 0.139*** 0.263*** 0.131*** 0.117 (5.53) (4.10) (2.72) (0.87) Stock return –0.046 –0.061 0.062 0.144 (–1.26) (–0.35) (0.86) (0.52) Stock volatility 1.322*** 1.355 1.492** 4.323* (3.38) (1.00) (2.13) (1.88) ROA 0.219 0.387 0.239 0.300 (1.58) (1.06) (1.05) (0.47) Sales growth 0.179*** 0.653*** 0.109 0.625 (2.79) (3.22) (0.91) (1.41) Frac. executives above 61 0.230 –0.600 (1.57) (–1.01) CEO age above 61 –0.132 –1.019** (–0.88) (–2.46) Year fixed effects Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Observations 6,676 6,676 912 912 Adjusted $$R^2$$ 0.432 0.186 0.442 0.176 A. Remaining executives B. Departing and newly hired CEOs Dependent variable Log total compensation Log equity compensation Log total compensation Log equity compensation Model Sample Window of analysis OLS Accelerating firms in ExecuComp Two fiscal years around option acceleration (1) (2) (3) (4) Post-acceleration$$\times$$Firm with turnover 0.114** 0.481** (2.36) (2.18) Post-acceleration$$\times$$Firm with CEO turnover 0.323** 1.518*** (2.46) (3.10) Post-acceleration 0.046 –0.162 0.042 0.189 (0.61) (–0.45) (0.27) (0.29) Firm with turnover –0.031 –0.324* (–0.62) (–1.96) Firm with CEO turnover –0.231** –0.709** (–2.15) (–2.10) Log assets 0.423*** 0.592*** 0.428*** 0.652*** (28.47) (11.70) (15.29) (6.46) Market/book ratio 0.139*** 0.263*** 0.131*** 0.117 (5.53) (4.10) (2.72) (0.87) Stock return –0.046 –0.061 0.062 0.144 (–1.26) (–0.35) (0.86) (0.52) Stock volatility 1.322*** 1.355 1.492** 4.323* (3.38) (1.00) (2.13) (1.88) ROA 0.219 0.387 0.239 0.300 (1.58) (1.06) (1.05) (0.47) Sales growth 0.179*** 0.653*** 0.109 0.625 (2.79) (3.22) (0.91) (1.41) Frac. executives above 61 0.230 –0.600 (1.57) (–1.01) CEO age above 61 –0.132 –1.019** (–0.88) (–2.46) Year fixed effects Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Observations 6,676 6,676 912 912 Adjusted $$R^2$$ 0.432 0.186 0.442 0.176 The regressions contain observations for executives of accelerating firms in ExecuComp, for the two fiscal years before to two fiscal years after each option acceleration event. All variables are measured at the executive-fiscal year or firm-fiscal-year level. Panel A shows pay for top executives that remained at the firm both before and after option acceleration. Panel B shows pay for all CEOs of accelerating firms, including those who departed or were hired after option acceleration. Log total compensation is the natural logarithm of an executive’s annual total compensation. Log equity compensation is the natural logarithm of an executive’s annual equity compensation. Post-acceleration equals 1 in fiscal years after a firm accelerated option vesting, and 0 in all other fiscal years. Firm with turnover equals 1 in all fiscal years for a firm that experienced a top executive departure in the fiscal year after acceleration, and 0 in all other fiscal years. Firm with CEO turnover equals 1 in all fiscal years for a firm that experienced a CEO departure in the fiscal year after acceleration, and 0 in all other fiscal years. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. Year fixed effects equal 1 for firm-fiscal year observations that end in the same calendar year. Industry fixed effects are based on the Fama-French 48 industry classification. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. Table 11, panel B, provides a similar analysis but examines responses to CEO departures using Firm with CEO turnover instead of Firm with turnover. We test whether firms paid newly hired CEOs more than the departing ones, relative to firms that continued to employ the same CEO. In Column 3, the negative coefficient on Firm with CEO turnover implies that CEOs who departed after option acceleration were at the time earning 23% less than CEOs of accelerating firm who did not leave. These CEOs’ outside options thus may have exceeded the value of remaining at the firm. Following these departures, firms then increased total pay and equity pay for their newly hired CEOs. The estimates in Column 3 imply that new CEOs’ pay was 32% ($${\}$$0.7m) higher than that of departing CEOs, who earned $${\}$$2.1m on average (we verified that this increase is not limited to a signing bonus in the first year). Overall, these results suggest that departures signaled to firms that they were underpaying executives, leading to upward adjustments to compensation.11 Consistent with this interpretation, in untabulated tests we find that the median executive who departed to take another managerial position after option acceleration received total annual pay of $${\}$$4.5m at the new firm, almost double their previous $${\}$$2.4m income. One implication is that acceleration-induced turnover, while costly, allowed boards to update their beliefs about executives’ outside options. This may be one channel by which compensation converges to market values in equilibrium. I.A. Table 7 provides additional support by showing that accelerating firms were also more likely to emphasize executive retention issues to investors following option acceleration. The table reports an increase in both the likelihood and extent of discussing executive retention in proxy filings. We further examine whether non-accelerating firms updated their beliefs about retention incentives after watching peer firms allow for accelerated vesting. We collect data from Equilar on non-accelerating firms that included an accelerating firm in their compensation peer group when benchmarking executive pay. I.A. Table 8 shows that these firms increased the unvested equity holdings of their CEOs and other top executives after a peer firm accelerated options, relative to firms that did not have an accelerating peer. In economic terms, firms increased the unvested equity holdings of their CEOs by 15% and of their top executives by 7%. This suggests that non-accelerating firms also learned about executives’ outside options from observing the consequences of option acceleration. 6. Placebo and Robustness Tests 6.1 Placebo test: Turnover prior to acceleration A concern with our analysis is that our 2SLS estimates may be biased by unobservable differences between early and late fiscal-year-end firms that also affect turnover. We examine this possibility in Table 12 using a placebo analysis based on Rothstein (2010) that tests whether acceleration is positively associated with turnover that occurred during previous years. We continue to instrument option acceleration using firms’ fiscal year-ends in 2005 and 2006, but examine turnover during firm-fiscal years that ended between January 2001 and December 2004. If option acceleration led to higher turnover because executives could depart with their newly vested options, then we should not observe an effect on turnover years before any firm accelerated options. Indeed, Table 12 shows that no such relationship exists. Therefore, a confounding variable could only explain our results if it affects both option acceleration and turnover, and further correlates with firms’ fiscal year-ends only when FAS 123-R took effect. Table 12 Placebo test: Executive turnover in previous years Dependent variable CEO turnover Executive turnover CEO turnover Executive turnover Model Sample 2SLS All firms Window of analysis 2001–2002 2003–2004 (1) (2) (3) (4) Frac. options accelerated in 2005/2006 –0.340 –0.003 –0.383 0.352 (–0.69) (–0.01) (–1.02) (1.46) Log assets 0.017*** 0.027*** 0.020*** 0.027*** (4.91) (13.72) (7.73) (17.52) Market/book ratio 0.000 0.004 –0.003*** –0.001* (0.07) (1.32) (–3.17) (–1.76) Stock return –0.018 –0.017** –0.036*** –0.023*** (–1.29) (–1.98) (–2.67) (–2.74) Stock volatility 0.059 0.103** 0.153** 0.050 (1.10) (2.20) (2.06) (0.96) ROA –0.055* –0.026 –0.117*** –0.086*** (–1.84) (–1.12) (–4.19) (–4.48) Sales growth –0.024 0.012 –0.035** –0.026*** (–1.18) (0.79) (–2.45) (–2.84) CEO age above 61 0.016 –0.008 (0.99) (–0.88) Non-compete clauses 0.001 0.003 0.001 –0.000 (0.18) (1.44) (0.76) (–0.16) Distance to peers 0.000 0.000 0.000 0.000** (0.01) (0.86) (1.16) (2.27) Frac. executive above 61 0.025 –0.029*** (1.27) (–3.06) Year fixed effects Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Observations 1,874 2,038 4,119 4,416 Dependent variable CEO turnover Executive turnover CEO turnover Executive turnover Model Sample 2SLS All firms Window of analysis 2001–2002 2003–2004 (1) (2) (3) (4) Frac. options accelerated in 2005/2006 –0.340 –0.003 –0.383 0.352 (–0.69) (–0.01) (–1.02) (1.46) Log assets 0.017*** 0.027*** 0.020*** 0.027*** (4.91) (13.72) (7.73) (17.52) Market/book ratio 0.000 0.004 –0.003*** –0.001* (0.07) (1.32) (–3.17) (–1.76) Stock return –0.018 –0.017** –0.036*** –0.023*** (–1.29) (–1.98) (–2.67) (–2.74) Stock volatility 0.059 0.103** 0.153** 0.050 (1.10) (2.20) (2.06) (0.96) ROA –0.055* –0.026 –0.117*** –0.086*** (–1.84) (–1.12) (–4.19) (–4.48) Sales growth –0.024 0.012 –0.035** –0.026*** (–1.18) (0.79) (–2.45) (–2.84) CEO age above 61 0.016 –0.008 (0.99) (–0.88) Non-compete clauses 0.001 0.003 0.001 –0.000 (0.18) (1.44) (0.76) (–0.16) Distance to peers 0.000 0.000 0.000 0.000** (0.01) (0.86) (1.16) (2.27) Frac. executive above 61 0.025 –0.029*** (1.27) (–3.06) Year fixed effects Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Observations 1,874 2,038 4,119 4,416 The regressions contain all firm-fiscal year observations ending between January 2001 and December 2002 (Columns 1 and 2) or January 2003 and December 2004 (Columns 3 and 4). All variables are measured at the firm-fiscal-year level. CEO turnover equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. Executive turnover is the number of executives departing during the next fiscal year divided by the total number of top executives. Frac. options accelerated in 2005/2006 is the number of options accelerated in the fiscal years ending between January 2005 and December 2006 (i.e., two or four years into the future) divided by the number of options outstanding at the beginning of the fiscal year. 2SLS regressions instrument Frac. options accelerated in 2005/2006 using FAS 123-R takes effect in 2005/2006. This variable equals 1 in Columns 1 and 2 when FAS 123-R compliance begins four years after the firm-fiscal year observation, 1 in Columns 3 and 4 when FAS 123-R compliance begins two years after the firm-fiscal year observation, and 0 in all other firm-fiscal year observations. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. Year fixed effects equal 1 for firm-fiscal year observations that end in the same calendar year. Industry fixed effects are based on the Fama-French 48 industry classification. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. Table 12 Placebo test: Executive turnover in previous years Dependent variable CEO turnover Executive turnover CEO turnover Executive turnover Model Sample 2SLS All firms Window of analysis 2001–2002 2003–2004 (1) (2) (3) (4) Frac. options accelerated in 2005/2006 –0.340 –0.003 –0.383 0.352 (–0.69) (–0.01) (–1.02) (1.46) Log assets 0.017*** 0.027*** 0.020*** 0.027*** (4.91) (13.72) (7.73) (17.52) Market/book ratio 0.000 0.004 –0.003*** –0.001* (0.07) (1.32) (–3.17) (–1.76) Stock return –0.018 –0.017** –0.036*** –0.023*** (–1.29) (–1.98) (–2.67) (–2.74) Stock volatility 0.059 0.103** 0.153** 0.050 (1.10) (2.20) (2.06) (0.96) ROA –0.055* –0.026 –0.117*** –0.086*** (–1.84) (–1.12) (–4.19) (–4.48) Sales growth –0.024 0.012 –0.035** –0.026*** (–1.18) (0.79) (–2.45) (–2.84) CEO age above 61 0.016 –0.008 (0.99) (–0.88) Non-compete clauses 0.001 0.003 0.001 –0.000 (0.18) (1.44) (0.76) (–0.16) Distance to peers 0.000 0.000 0.000 0.000** (0.01) (0.86) (1.16) (2.27) Frac. executive above 61 0.025 –0.029*** (1.27) (–3.06) Year fixed effects Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Observations 1,874 2,038 4,119 4,416 Dependent variable CEO turnover Executive turnover CEO turnover Executive turnover Model Sample 2SLS All firms Window of analysis 2001–2002 2003–2004 (1) (2) (3) (4) Frac. options accelerated in 2005/2006 –0.340 –0.003 –0.383 0.352 (–0.69) (–0.01) (–1.02) (1.46) Log assets 0.017*** 0.027*** 0.020*** 0.027*** (4.91) (13.72) (7.73) (17.52) Market/book ratio 0.000 0.004 –0.003*** –0.001* (0.07) (1.32) (–3.17) (–1.76) Stock return –0.018 –0.017** –0.036*** –0.023*** (–1.29) (–1.98) (–2.67) (–2.74) Stock volatility 0.059 0.103** 0.153** 0.050 (1.10) (2.20) (2.06) (0.96) ROA –0.055* –0.026 –0.117*** –0.086*** (–1.84) (–1.12) (–4.19) (–4.48) Sales growth –0.024 0.012 –0.035** –0.026*** (–1.18) (0.79) (–2.45) (–2.84) CEO age above 61 0.016 –0.008 (0.99) (–0.88) Non-compete clauses 0.001 0.003 0.001 –0.000 (0.18) (1.44) (0.76) (–0.16) Distance to peers 0.000 0.000 0.000 0.000** (0.01) (0.86) (1.16) (2.27) Frac. executive above 61 0.025 –0.029*** (1.27) (–3.06) Year fixed effects Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Observations 1,874 2,038 4,119 4,416 The regressions contain all firm-fiscal year observations ending between January 2001 and December 2002 (Columns 1 and 2) or January 2003 and December 2004 (Columns 3 and 4). All variables are measured at the firm-fiscal-year level. CEO turnover equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. Executive turnover is the number of executives departing during the next fiscal year divided by the total number of top executives. Frac. options accelerated in 2005/2006 is the number of options accelerated in the fiscal years ending between January 2005 and December 2006 (i.e., two or four years into the future) divided by the number of options outstanding at the beginning of the fiscal year. 2SLS regressions instrument Frac. options accelerated in 2005/2006 using FAS 123-R takes effect in 2005/2006. This variable equals 1 in Columns 1 and 2 when FAS 123-R compliance begins four years after the firm-fiscal year observation, 1 in Columns 3 and 4 when FAS 123-R compliance begins two years after the firm-fiscal year observation, and 0 in all other firm-fiscal year observations. t-statistics, shown in parentheses, are based on standard errors that are clustered at the firm level. Year fixed effects equal 1 for firm-fiscal year observations that end in the same calendar year. Industry fixed effects are based on the Fama-French 48 industry classification. ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively. The variable appendix provides the variable definitions. 6.2 Placebo test: Acceleration and outside director turnover Next, we examine whether the increase in turnover could be explained by unobserved performance shocks that coincide with FAS 123-R’s compliance dates. I.A. Table 9 tests whether acceleration affected turnover among outside board directors. In the mid-2000s, these directors held few stock options in their firms (Yermack 2004), and hence their retention incentives likely were not affected by option acceleration (outside director turnover also did not vary across fiscal year-ends prior to FAS 123-R). However, directors often depart after performance shocks to preserve their monitoring reputations (Harford 2003; Yermack 2004; Fahlenbrach, Low, and Stulz 2017). Therefore, outside director turnover should not be correlated with option acceleration unless accelerating firms experienced unobserved performance shocks. Indeed, we find no change in outside director turnover. 6.3 Alternative explanation: Missed earnings forecasts and downgrades Another possibility is that FAS 123-R affected CEO turnover for reasons other than option acceleration. Option expensing caused firms to report lower corporate earnings in the fiscal year that FAS 123-R took effect, and led some firms to miss analyst earnings forecasts and experience stock price declines (Cronqvist, Ladika, and Sautner 2018). This could lead to an increase in CEO turnover that would follow the same staggered timing that our 2SLS tests exploit. There are two reasons why this alternative channel likely does not explain our results. First, it is not clear why missed earnings forecasts would explain the rise in voluntary turnover following option acceleration. Second, I.A. Table 10 reports that option acceleration affected executive turnover among subsets of firms that did not miss earnings forecasts or did not experience analyst downgrades in the two years around acceleration. Furthermore, our results in the full sample are robust to controlling for changes in analysts’ forecasts or an indicator for firms that missed forecasts. 6.4 Robustness test: Excluding non-accelerating firms Finally, in I.A. Table 11 we re-estimate our baseline 2SLS regressions among the subset of firms that accelerated options in either 2005 or 2006. The sample excludes non-accelerating firms, which significantly differed in their performance and other characteristics prior to FAS 123-R. We find positive coefficients on both acceleration measures, indicating that the rise in CEO turnover corresponded to FAS 123-R’s compliance schedule among a set of firms with similar characteristics. 7. Conclusion We show that a sudden reduction in executives’ retention incentives leads to a substantial increase in voluntary turnover. We document this effect by exploiting a unique event that prompted 723 firms to accelerate option vesting to avoid an accounting expense under FAS 123-R. This allowed CEOs to retain 33% more options on average when departing the firm. To identify causality, we exploit the staggered timing of FAS 123-R—the acceleration deadline was in calendar year 2005 for firms with fiscal years ending in June through December, but only in 2006 for firms with fiscal years ending in January through May. These two sets of firms were observationally identical before the regulation took effect, but they eliminated vesting restrictions in different years. Our tests instrument for option acceleration using fiscal year-ends, allowing us to estimate turnover effects that are unaffected by endogenous matching of executives to firms, or by firms’ endogenous acceleration decisions. Firms that accelerated options experienced a sharp increase in executive turnover. Strikingly, the increase in turnover corresponded exactly to firms’ staggered FAS 123-R compliance dates. Our 2SLS estimates suggest that a one-standard-deviation increase in the percentage of accelerated options increased voluntary CEO turnover from 5% to 21.2%, and top executive turnover from 8.8% to 21.3%. Turnover rose more among firms that accelerated more options, and also among firms whose previously unvested options were more in the money. When these departures were announced, accelerating firms’ stock prices fell by $$-$$1.5%, reducing market values by $${\}$$29m on average. After experiencing departures, accelerating firms increased the pay of remaining executives as well as that of newly hired CEOs. Our results provide evidence that vesting periods are an important tool for retaining executives. This implication is important for firms that are designing recruitment and retention strategies, especially in industries with fierce competition for top talent. Our findings are also relevant for policymakers who are debating new regulations on executive compensation, such as requirements that banks defer the payout of their executives’ bonuses. Our setting may also be useful for future research on the extent to which labor market frictions affect the allocation of managerial talent across firms. We thank Andrew Karolyi (the Editor) and two anonymous referees for very helpful comments. We are grateful to Jack Ciesielski of R. G. Associates, Inc., for providing us with data on option acceleration; Preeti Choudhary for providing us with a list of firms that voluntarily adopted fair-value stock option expensing; and Dirk Jenter, Fadi Kanaan, Florian Peters, and Alexander Wagner for providing data that classify CEO turnover. We thank Murillo Campello, Kenneth Chay, Jeffrey Coles, Alex Edmans, Erasmo Giambona, Stuart Gillan, Charles Hadlock, Dirk Jenter, Kasper Nielsen, Robert Parrino, Enrico Perotti, Florian Peters, Shivaram Rajgopal, Rafael Ribas, Maria Strydom, Tilan Tang, Ed Van Wesep, João Vieito, and Vladimir Vladimirov; seminar participants at Erasmus University Rotterdam, ESSEC Paris, the Frankfurt School of Finance & Management, Goethe University, TU Munich, University of Amsterdam, University of Glasgow, University of Navarra, University of Piraeus, University of Zurich, and WHU Otto Beisheim School of Management; and participants at the 2015 Western Finance Association conference, 2015 FMA Europe conference, 2015 FMA Asia conference, 2015 IFABS Oxford Corporate Finance conference, 2015 Auckland finance meeting, 2016 PNC Kentucky finance conference, 2016 Michigan State University FCU conference, 2016 European Finance Association meeting, and 2016 FMA annual meeting for helpful comments. All errors are our own. Supplementary data can be found on The Review of Financial Studies web site. Appendix Variable definitions Variable Definition Source A. Measures of option acceleration and FAS 123-R compliance Frac. options accelerated Number of options accelerated during the fiscal year divided by the total number of options outstanding at the beginning of the fiscal year. The number of options accelerated is from the R. G. Associates Option Accelerated Vester Database. The number of options outstanding is Compustat data item OPTOSBY. R. G. Associates Accelerate Dummy that equals 1 if a firm accelerated option vesting during the fiscal year, and 0 in all other fiscal years. R. G. Associates Accelerate in previous fiscal year Dummy that equals 1 if a firm accelerated option vesting during the previous fiscal year, and 0 in all other fiscal years. R. G. Associates Post-acceleration Dummy that equals 1 in fiscal years after a firm accelerated option vesting, and 0 in all other fiscal years. R. G. Associates Frac. options accelerated in 2005/2006 Number of options accelerated in the fiscal years ending between January 2005 and December 2006 divided by the number of options outstanding at the beginning of the fiscal year. R. G. Associates Accelerator Dummy that equals 1 in all fiscal years if a firm accelerated option vesting, and 0 in all other fiscal years. Equilar, R. G. Associates Accelerator in peer group Dummy that equals 1 in all fiscal years if a firm has a company with an acceleration event among its compensation peer group, and 0 in all other fiscal years. Equilar, R. G. Associates Post-peer acceleration Dummy that equals 1 in fiscal years after the earliest acceleration event by a compensation peer, and 0 in all other fiscal years. R. G. Associates FAS 123-R takes effect Our instrument that accounts for the staggered compliance of FAS 123-R across calendar years. It equals 1 for firm-fiscal year observations ending between June 2005 and May 2006, and 0 for all other firm-fiscal year observations. Compustat FAS 123-R takes effect in 2005/2006 Our instrument in Table 12. It equals 1 when FAS 123-R compliance begins four years after the firm-fiscal year observation (for tests covering January 2001 to December 2002), 1 when FAS 123-R compliance begins two years after the firm-fiscal year observation (for tests covering January 2003 to December 2004), and 0 for all other firm-fiscal year observations. Compustat June 2005 FYR Dummy that equals 1 for firm-fiscal year observations ending in June 2005, and 0 for all other firm-fiscal year observations. All other month dummy variables are defined accordingly. Compustat B. Executive turnover measures CEO turnover Dummy that equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. We exclude interim or acting CEOs because their eventual replacement is not a substantive turnover event. We also exclude executives who are not actively involved in the firm’s management, such as former or emeritus CEOs. ExecuComp, BoardEx Voluntary CEO turnover (JKPW) Dummy that equals 1 if an ExecuComp firm experiences a voluntary CEO departure during the next fiscal year, and 0 for all other firm-fiscal year observations. A CEO departure is classified as voluntary if it is not listed in the JKPW database of forced departures. These data are only available for ExecuComp firms. Jenter and Kanaan 2015; Peters and Wagner 2014 Voluntary CEO turnover Dummy that equals 1 if a firm experiences a voluntary CEO departure during the next fiscal year, and 0 for all other firm-fiscal year observations. For ExecuComp firms, this variable is equal to Voluntary CEO turnover (JKPW). For BoardEx firms, we extrapolate this variable using a predictive model for forced CEO turnover. First, we regress CEO firings from the JKPW database on standard determinants of forced turnover, using a sample of ExecuComp firms with fiscal years ending between January 2001 and December 2004. The dependent variable in this model is a dummy that equals 1 if a firm experiences a CEO departure that is listed as forced in the JKPW database, and 0 for all other firm-fiscal year observations. Explanatory variables, measured in the fiscal year prior to the departure, are CEO age and CEO tenure, Log assets, Market/book ratio, Stock return (also 2-year-lagged values), Stock volatility (also 2-year-lagged values), ROA (also 2-year-lagged values), Sales growth (also 2-year-lagged values), CEO duality, Frac. independent directors, and industry and year fixed effects. Second, we use the resulting coefficient estimates to calculate fitted values for firm-fiscal year observations at all sample firms. We use the 80th percentile of the distribution of these fitted values as our threshold to classify a CEO departure as forced (i.e., we classify 20% of CEO departures as forced). We calibrate the threshold to the 80th percentile because 20% of CEO departures at ExecuComp firms are listed as forced in the JKPW database. Third, we calculate fitted values for firm-fiscal year observations at BoardEx firms. We classify CEO departures at BoardEx firms as voluntary if the fitted values are below the threshold from step 2. Fourth, we set Voluntary CEO turnover equal to 1 for BoardEx firms that experience such a voluntary departure during the next fiscal year, and 0 for all other firm-fiscal year observations. Jenter and Kanaan 2015; Peters and Wagner 2014; own calculations Executive turnover Number of executives departing during the next fiscal year divided by the total number of top executives at the end of the current fiscal year. ExecuComp, Boardex Firm with turnover Dummy that equals 1 in all fiscal years for a firm that experienced a top executive departure in the fiscal year after acceleration, and 0 in all other fiscal years. ExecuComp, Boardex Firm with CEO turnover Dummy that equals 1 in all fiscal years for a firm that experienced a CEO departure in the fiscal year after acceleration, and 0 in all other fiscal years. ExecuComp, Boardex CEO turnover in 2 fiscal years Dummy that equals 1 if a firm experiences a CEO departure two fiscal years in the future, 0 in all other fiscal years. ExecuComp, Boardex CEO turnover in 3 fiscal years Dummy that equals 1 if a firm experiences a CEO departure three fiscal years in the future, 0 in all other fiscal years. ExecuComp, Boardex Outside director turnover Number of outside directors departing during the next fiscal year divided by the number of outside directors at the end of the current fiscal year. An outside director is a non-executive board member. ExecuComp, Boardex CEO turnover (within 3 months) Dummy that equals 1 if a firm experiences a CEO departure during the first 3 months of the next fiscal year, and 0 in all other fiscal years. CEO turnover (within 6 months) and CEO turnover (within 9 months) are accordingly defined. ExecuComp, Boardex C. Executive compensation variables Unvested option duration Weighted average number of months until unvested option grants vest. To calculate this variable, first we collect data from Thomson Insiders on new options granted between 2000 and 2006. Second, in each fiscal year $$t$$ we identify currently unvested options by only looking at grants with (1) a grant date (Thomson Insiders data item TRANDATE) prior to fiscal year $$t$$ and (2) a vesting date (date item XDATE) after fiscal year $$t$$. Third, for each unvested option grant, we measure the remaining unvested option duration (in months) as the vesting date minus the end date of the current fiscal year. Fourth, we calculate average duration across all unvested option grants, weighting by the number of options in each grant. We use the number of options in each grant as weights, because this is less likely to understate the amount of deep-out-of-the-money options than value-weighting. We omit grants that are indirectly owned or have missing data on strike prices, vesting dates, or expiration dates. Thomson Reuters Insiders Unvested option moneyness Weighted average of the moneyness of unvested option grants. Moneyness is the option’s strike price divided by the firm’s stock price, and is measured at the end of the fiscal year. We compile unvested option holdings using the same procedure as for Unvested option duration. Thomson Reuters Insiders Vested option value Value of an executive’s vested stock options (in thousands of USD), measured at the end of the fiscal year. The value of stock options is measured using the Black-Scholes formula, with formula inputs obtained using the Core and Guay (2002) procedure. To single out the impact of option acceleration from other common changes to vested option holdings, we add back the value of options that are exercised during the year, and subtract the value of options that were scheduled to vest during the year. We compile data on option exercises from Thomson Insiders and omit exercises of grants that are indirectly owned or are missing data on strike prices, vesting dates, or expiration dates. We identify option vesting schedules from the vesting dates listed when the option is first granted (Thomson Insiders data item XDATE). These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Vested option PPS Pay-for-performance sensitivity (PPS) of an executive’s vested stock options (in thousands of USD), measured at the end of the fiscal year. PPS is measured as the change in the dollar value of stock options for a 1% change in the firm’s stock price. The value of stock options is measured using the Black-Scholes formula, with formula inputs obtained using the Core and Guay (2002) procedure. We account for common changes to vested option holdings using the same procedure as for Vested option value. These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Unvested option value Value of an executive’s unvested stock options (in thousands of USD), measured at the end of the fiscal year. The value of each unvested option grant is measured using the Black-Scholes formula, and these values are summed for all unvested grants pledged to an executive. We compile executives’ unvested option holdings using the same procedure as for Unvested options duration. The formula inputs include the option strike price (Thomson Insiders data item XPRICE) and time to expiration (based on data item TDATE). These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Unvested option PPS PPS of an executive’s unvested stock options (in thousands of USD), measured at the end of the fiscal year. PPS is calculated using the same procedure as for Vested option PPS. We compile executives’ unvested option holdings using the same procedure as for Unvested options duration. These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Total compensation Total compensation during the fiscal year (ExecuComp data item TDC1), measured in thousands of USD. These data are only available for ExecuComp firms. ExecuComp Equity compensation Equity compensation during the fiscal year (the sum of ExecuComp data items OPTION_AWARDS_BLK_VALUE and RSTKGRNT before 2006, and OPTION_AWARDS_FV and STOCK_AWARDS_FV after 2006), measured in thousands of USD. These data are only available for ExecuComp firms. ExecuComp Unvested equity value to total compensation The ratio of unvested equity to the CEO’s total compensation in the fiscal year (or the average ratio if all top executives are used). These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders D. Other dependent variables and controls Assets Total assets at the end of the fiscal year (Compustat data item AT), measured in millions of USD. Compustat Market/book ratio Sum of market capitalization and book value of liabilities (Compustat data item LT) at the end of the fiscal year, divided by book value of common equity (CEQ) and book value of liabilities (LT) at the end of the fiscal year. Market capitalization is PRCC multiplied by CSHO. Data are winsorized at the 1% and 99% level. Compustat Stock return The natural logarithm of 1 plus the fractional stock return over the fiscal year. The return equals the stock price at the end of the fiscal year (Compustat data item PRCC_F) plus dividends (DVPSX_F), divided by the stock price at the end of the previous fiscal year, minus 1. Data are winsorized at the 5% and 95% level. Compustat Stock volatility The standard deviation of fractional stock returns (CRSP data item RET) from the 48 months preceding the end of the fiscal year. This variable is set to missing when fewer than 12 months’ returns are available. Data are winsorized at the 5% and 95% level. CRSP ROA Net income (Compustat data item NI) and interest expense (XINT) divided by total assets (AT) at the end of the fiscal year. Interest expense is set to 0 when it is reported as missing and in the previous fiscal year the firm reported no debt due in one year. Data are winsorized at the 1% and 99% level. Compustat Sales growth Fiscal-year-on-fiscal-year fractional change in sales (Compustat data item SALE). Data are winsorized at the 5% and 95% level. Compustat CEO age above 61 Dummy that equals 1 if the CEO is 61 years or older at the end of the fiscal year, and 0 in all other fiscal years. Age is measured using ExecuComp data item AGE. If this value is missing, then age is calculated using BoardEx data as the current fiscal year minus date of birth (BoardEx data item DOB). ExecuComp, BoardEx Frac. executives above 61 Fraction of top executives aged 61 or older. Age is measured using ExecuComp data item AGE. If this value is missing, then age is calculated using BoardEx data as the current fiscal year minus date of birth (BoardEx data item DOB). ExecuComp, BoardEx Non-compete clauses State-level index that measures how difficult it is to enforce a non-compete clause in an employment contract. Index values are based on the firm’s headquarters (Compustat data item STATE). Smaller index numbers indicate that it is more difficult to enforce a non-compete clause. Garmaise 2011, Compustat Distance to peers Number of Compustat firms in the same Fama-French 48 industry within 150 miles radius around the headquarters of a firm. The 150-mile radius is calculated using the GPS coordinates of firms’ headquarters. Compustat, own calculations Frac. independent directors Fraction of a board’s directors that are classified as independent (ISS Directors data item CLASSIFICATION equal to “I”) at the end of the fiscal year. ISS Directors, Equilar CEO duality Dummy that equals 1 if the firm’s CEO is also board chairman at the end of the fiscal year, and 0 in all other fiscal years. Dual CEO-Chairmen are identified using ISS Directors data items EMPLOYMENT_CEO and EMPLOYMENT_CHAIRMAN. ISS Directors, Equilar Retention key words in CD&A section Dummy that equals 1 if a firm’s Compensation Disclosure & Analysis (CD&A) section of its proxy statement in a given fiscal year contains key words related to executive retention, and 0 in all other fiscal years. The list of executive retention related key words include management retention; management turnover; turnover of management; turnover among management; retention of management; executive retention; executive turnover; turnover of executive; turnover among executive; retention of executive; turnover of key; turnover among key; and retention of key. SEC EDGAR, own calculations # Retention key words in CD&A section The number of key words related to executive retention in the firm’s CD&A. The list of executive retention related key words is the same as for Retention key words in CD&A section. SEC EDGAR, own calculations $$\Delta$$ Consensus analyst forecasts Change in the median consensus forecast for firms’ earnings per share (EPS) between 2004 and 2006. I/B/E/S Missed analyst consensus forecast Dummy that equals 1 if a firm missed the analyst consensus EPS forecast, and 0 in all other fiscal years. I/B/E/S Variable Definition Source A. Measures of option acceleration and FAS 123-R compliance Frac. options accelerated Number of options accelerated during the fiscal year divided by the total number of options outstanding at the beginning of the fiscal year. The number of options accelerated is from the R. G. Associates Option Accelerated Vester Database. The number of options outstanding is Compustat data item OPTOSBY. R. G. Associates Accelerate Dummy that equals 1 if a firm accelerated option vesting during the fiscal year, and 0 in all other fiscal years. R. G. Associates Accelerate in previous fiscal year Dummy that equals 1 if a firm accelerated option vesting during the previous fiscal year, and 0 in all other fiscal years. R. G. Associates Post-acceleration Dummy that equals 1 in fiscal years after a firm accelerated option vesting, and 0 in all other fiscal years. R. G. Associates Frac. options accelerated in 2005/2006 Number of options accelerated in the fiscal years ending between January 2005 and December 2006 divided by the number of options outstanding at the beginning of the fiscal year. R. G. Associates Accelerator Dummy that equals 1 in all fiscal years if a firm accelerated option vesting, and 0 in all other fiscal years. Equilar, R. G. Associates Accelerator in peer group Dummy that equals 1 in all fiscal years if a firm has a company with an acceleration event among its compensation peer group, and 0 in all other fiscal years. Equilar, R. G. Associates Post-peer acceleration Dummy that equals 1 in fiscal years after the earliest acceleration event by a compensation peer, and 0 in all other fiscal years. R. G. Associates FAS 123-R takes effect Our instrument that accounts for the staggered compliance of FAS 123-R across calendar years. It equals 1 for firm-fiscal year observations ending between June 2005 and May 2006, and 0 for all other firm-fiscal year observations. Compustat FAS 123-R takes effect in 2005/2006 Our instrument in Table 12. It equals 1 when FAS 123-R compliance begins four years after the firm-fiscal year observation (for tests covering January 2001 to December 2002), 1 when FAS 123-R compliance begins two years after the firm-fiscal year observation (for tests covering January 2003 to December 2004), and 0 for all other firm-fiscal year observations. Compustat June 2005 FYR Dummy that equals 1 for firm-fiscal year observations ending in June 2005, and 0 for all other firm-fiscal year observations. All other month dummy variables are defined accordingly. Compustat B. Executive turnover measures CEO turnover Dummy that equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. We exclude interim or acting CEOs because their eventual replacement is not a substantive turnover event. We also exclude executives who are not actively involved in the firm’s management, such as former or emeritus CEOs. ExecuComp, BoardEx Voluntary CEO turnover (JKPW) Dummy that equals 1 if an ExecuComp firm experiences a voluntary CEO departure during the next fiscal year, and 0 for all other firm-fiscal year observations. A CEO departure is classified as voluntary if it is not listed in the JKPW database of forced departures. These data are only available for ExecuComp firms. Jenter and Kanaan 2015; Peters and Wagner 2014 Voluntary CEO turnover Dummy that equals 1 if a firm experiences a voluntary CEO departure during the next fiscal year, and 0 for all other firm-fiscal year observations. For ExecuComp firms, this variable is equal to Voluntary CEO turnover (JKPW). For BoardEx firms, we extrapolate this variable using a predictive model for forced CEO turnover. First, we regress CEO firings from the JKPW database on standard determinants of forced turnover, using a sample of ExecuComp firms with fiscal years ending between January 2001 and December 2004. The dependent variable in this model is a dummy that equals 1 if a firm experiences a CEO departure that is listed as forced in the JKPW database, and 0 for all other firm-fiscal year observations. Explanatory variables, measured in the fiscal year prior to the departure, are CEO age and CEO tenure, Log assets, Market/book ratio, Stock return (also 2-year-lagged values), Stock volatility (also 2-year-lagged values), ROA (also 2-year-lagged values), Sales growth (also 2-year-lagged values), CEO duality, Frac. independent directors, and industry and year fixed effects. Second, we use the resulting coefficient estimates to calculate fitted values for firm-fiscal year observations at all sample firms. We use the 80th percentile of the distribution of these fitted values as our threshold to classify a CEO departure as forced (i.e., we classify 20% of CEO departures as forced). We calibrate the threshold to the 80th percentile because 20% of CEO departures at ExecuComp firms are listed as forced in the JKPW database. Third, we calculate fitted values for firm-fiscal year observations at BoardEx firms. We classify CEO departures at BoardEx firms as voluntary if the fitted values are below the threshold from step 2. Fourth, we set Voluntary CEO turnover equal to 1 for BoardEx firms that experience such a voluntary departure during the next fiscal year, and 0 for all other firm-fiscal year observations. Jenter and Kanaan 2015; Peters and Wagner 2014; own calculations Executive turnover Number of executives departing during the next fiscal year divided by the total number of top executives at the end of the current fiscal year. ExecuComp, Boardex Firm with turnover Dummy that equals 1 in all fiscal years for a firm that experienced a top executive departure in the fiscal year after acceleration, and 0 in all other fiscal years. ExecuComp, Boardex Firm with CEO turnover Dummy that equals 1 in all fiscal years for a firm that experienced a CEO departure in the fiscal year after acceleration, and 0 in all other fiscal years. ExecuComp, Boardex CEO turnover in 2 fiscal years Dummy that equals 1 if a firm experiences a CEO departure two fiscal years in the future, 0 in all other fiscal years. ExecuComp, Boardex CEO turnover in 3 fiscal years Dummy that equals 1 if a firm experiences a CEO departure three fiscal years in the future, 0 in all other fiscal years. ExecuComp, Boardex Outside director turnover Number of outside directors departing during the next fiscal year divided by the number of outside directors at the end of the current fiscal year. An outside director is a non-executive board member. ExecuComp, Boardex CEO turnover (within 3 months) Dummy that equals 1 if a firm experiences a CEO departure during the first 3 months of the next fiscal year, and 0 in all other fiscal years. CEO turnover (within 6 months) and CEO turnover (within 9 months) are accordingly defined. ExecuComp, Boardex C. Executive compensation variables Unvested option duration Weighted average number of months until unvested option grants vest. To calculate this variable, first we collect data from Thomson Insiders on new options granted between 2000 and 2006. Second, in each fiscal year $$t$$ we identify currently unvested options by only looking at grants with (1) a grant date (Thomson Insiders data item TRANDATE) prior to fiscal year $$t$$ and (2) a vesting date (date item XDATE) after fiscal year $$t$$. Third, for each unvested option grant, we measure the remaining unvested option duration (in months) as the vesting date minus the end date of the current fiscal year. Fourth, we calculate average duration across all unvested option grants, weighting by the number of options in each grant. We use the number of options in each grant as weights, because this is less likely to understate the amount of deep-out-of-the-money options than value-weighting. We omit grants that are indirectly owned or have missing data on strike prices, vesting dates, or expiration dates. Thomson Reuters Insiders Unvested option moneyness Weighted average of the moneyness of unvested option grants. Moneyness is the option’s strike price divided by the firm’s stock price, and is measured at the end of the fiscal year. We compile unvested option holdings using the same procedure as for Unvested option duration. Thomson Reuters Insiders Vested option value Value of an executive’s vested stock options (in thousands of USD), measured at the end of the fiscal year. The value of stock options is measured using the Black-Scholes formula, with formula inputs obtained using the Core and Guay (2002) procedure. To single out the impact of option acceleration from other common changes to vested option holdings, we add back the value of options that are exercised during the year, and subtract the value of options that were scheduled to vest during the year. We compile data on option exercises from Thomson Insiders and omit exercises of grants that are indirectly owned or are missing data on strike prices, vesting dates, or expiration dates. We identify option vesting schedules from the vesting dates listed when the option is first granted (Thomson Insiders data item XDATE). These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Vested option PPS Pay-for-performance sensitivity (PPS) of an executive’s vested stock options (in thousands of USD), measured at the end of the fiscal year. PPS is measured as the change in the dollar value of stock options for a 1% change in the firm’s stock price. The value of stock options is measured using the Black-Scholes formula, with formula inputs obtained using the Core and Guay (2002) procedure. We account for common changes to vested option holdings using the same procedure as for Vested option value. These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Unvested option value Value of an executive’s unvested stock options (in thousands of USD), measured at the end of the fiscal year. The value of each unvested option grant is measured using the Black-Scholes formula, and these values are summed for all unvested grants pledged to an executive. We compile executives’ unvested option holdings using the same procedure as for Unvested options duration. The formula inputs include the option strike price (Thomson Insiders data item XPRICE) and time to expiration (based on data item TDATE). These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Unvested option PPS PPS of an executive’s unvested stock options (in thousands of USD), measured at the end of the fiscal year. PPS is calculated using the same procedure as for Vested option PPS. We compile executives’ unvested option holdings using the same procedure as for Unvested options duration. These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Total compensation Total compensation during the fiscal year (ExecuComp data item TDC1), measured in thousands of USD. These data are only available for ExecuComp firms. ExecuComp Equity compensation Equity compensation during the fiscal year (the sum of ExecuComp data items OPTION_AWARDS_BLK_VALUE and RSTKGRNT before 2006, and OPTION_AWARDS_FV and STOCK_AWARDS_FV after 2006), measured in thousands of USD. These data are only available for ExecuComp firms. ExecuComp Unvested equity value to total compensation The ratio of unvested equity to the CEO’s total compensation in the fiscal year (or the average ratio if all top executives are used). These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders D. Other dependent variables and controls Assets Total assets at the end of the fiscal year (Compustat data item AT), measured in millions of USD. Compustat Market/book ratio Sum of market capitalization and book value of liabilities (Compustat data item LT) at the end of the fiscal year, divided by book value of common equity (CEQ) and book value of liabilities (LT) at the end of the fiscal year. Market capitalization is PRCC multiplied by CSHO. Data are winsorized at the 1% and 99% level. Compustat Stock return The natural logarithm of 1 plus the fractional stock return over the fiscal year. The return equals the stock price at the end of the fiscal year (Compustat data item PRCC_F) plus dividends (DVPSX_F), divided by the stock price at the end of the previous fiscal year, minus 1. Data are winsorized at the 5% and 95% level. Compustat Stock volatility The standard deviation of fractional stock returns (CRSP data item RET) from the 48 months preceding the end of the fiscal year. This variable is set to missing when fewer than 12 months’ returns are available. Data are winsorized at the 5% and 95% level. CRSP ROA Net income (Compustat data item NI) and interest expense (XINT) divided by total assets (AT) at the end of the fiscal year. Interest expense is set to 0 when it is reported as missing and in the previous fiscal year the firm reported no debt due in one year. Data are winsorized at the 1% and 99% level. Compustat Sales growth Fiscal-year-on-fiscal-year fractional change in sales (Compustat data item SALE). Data are winsorized at the 5% and 95% level. Compustat CEO age above 61 Dummy that equals 1 if the CEO is 61 years or older at the end of the fiscal year, and 0 in all other fiscal years. Age is measured using ExecuComp data item AGE. If this value is missing, then age is calculated using BoardEx data as the current fiscal year minus date of birth (BoardEx data item DOB). ExecuComp, BoardEx Frac. executives above 61 Fraction of top executives aged 61 or older. Age is measured using ExecuComp data item AGE. If this value is missing, then age is calculated using BoardEx data as the current fiscal year minus date of birth (BoardEx data item DOB). ExecuComp, BoardEx Non-compete clauses State-level index that measures how difficult it is to enforce a non-compete clause in an employment contract. Index values are based on the firm’s headquarters (Compustat data item STATE). Smaller index numbers indicate that it is more difficult to enforce a non-compete clause. Garmaise 2011, Compustat Distance to peers Number of Compustat firms in the same Fama-French 48 industry within 150 miles radius around the headquarters of a firm. The 150-mile radius is calculated using the GPS coordinates of firms’ headquarters. Compustat, own calculations Frac. independent directors Fraction of a board’s directors that are classified as independent (ISS Directors data item CLASSIFICATION equal to “I”) at the end of the fiscal year. ISS Directors, Equilar CEO duality Dummy that equals 1 if the firm’s CEO is also board chairman at the end of the fiscal year, and 0 in all other fiscal years. Dual CEO-Chairmen are identified using ISS Directors data items EMPLOYMENT_CEO and EMPLOYMENT_CHAIRMAN. ISS Directors, Equilar Retention key words in CD&A section Dummy that equals 1 if a firm’s Compensation Disclosure & Analysis (CD&A) section of its proxy statement in a given fiscal year contains key words related to executive retention, and 0 in all other fiscal years. The list of executive retention related key words include management retention; management turnover; turnover of management; turnover among management; retention of management; executive retention; executive turnover; turnover of executive; turnover among executive; retention of executive; turnover of key; turnover among key; and retention of key. SEC EDGAR, own calculations # Retention key words in CD&A section The number of key words related to executive retention in the firm’s CD&A. The list of executive retention related key words is the same as for Retention key words in CD&A section. SEC EDGAR, own calculations $$\Delta$$ Consensus analyst forecasts Change in the median consensus forecast for firms’ earnings per share (EPS) between 2004 and 2006. I/B/E/S Missed analyst consensus forecast Dummy that equals 1 if a firm missed the analyst consensus EPS forecast, and 0 in all other fiscal years. I/B/E/S Variable definitions Variable Definition Source A. Measures of option acceleration and FAS 123-R compliance Frac. options accelerated Number of options accelerated during the fiscal year divided by the total number of options outstanding at the beginning of the fiscal year. The number of options accelerated is from the R. G. Associates Option Accelerated Vester Database. The number of options outstanding is Compustat data item OPTOSBY. R. G. Associates Accelerate Dummy that equals 1 if a firm accelerated option vesting during the fiscal year, and 0 in all other fiscal years. R. G. Associates Accelerate in previous fiscal year Dummy that equals 1 if a firm accelerated option vesting during the previous fiscal year, and 0 in all other fiscal years. R. G. Associates Post-acceleration Dummy that equals 1 in fiscal years after a firm accelerated option vesting, and 0 in all other fiscal years. R. G. Associates Frac. options accelerated in 2005/2006 Number of options accelerated in the fiscal years ending between January 2005 and December 2006 divided by the number of options outstanding at the beginning of the fiscal year. R. G. Associates Accelerator Dummy that equals 1 in all fiscal years if a firm accelerated option vesting, and 0 in all other fiscal years. Equilar, R. G. Associates Accelerator in peer group Dummy that equals 1 in all fiscal years if a firm has a company with an acceleration event among its compensation peer group, and 0 in all other fiscal years. Equilar, R. G. Associates Post-peer acceleration Dummy that equals 1 in fiscal years after the earliest acceleration event by a compensation peer, and 0 in all other fiscal years. R. G. Associates FAS 123-R takes effect Our instrument that accounts for the staggered compliance of FAS 123-R across calendar years. It equals 1 for firm-fiscal year observations ending between June 2005 and May 2006, and 0 for all other firm-fiscal year observations. Compustat FAS 123-R takes effect in 2005/2006 Our instrument in Table 12. It equals 1 when FAS 123-R compliance begins four years after the firm-fiscal year observation (for tests covering January 2001 to December 2002), 1 when FAS 123-R compliance begins two years after the firm-fiscal year observation (for tests covering January 2003 to December 2004), and 0 for all other firm-fiscal year observations. Compustat June 2005 FYR Dummy that equals 1 for firm-fiscal year observations ending in June 2005, and 0 for all other firm-fiscal year observations. All other month dummy variables are defined accordingly. Compustat B. Executive turnover measures CEO turnover Dummy that equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. We exclude interim or acting CEOs because their eventual replacement is not a substantive turnover event. We also exclude executives who are not actively involved in the firm’s management, such as former or emeritus CEOs. ExecuComp, BoardEx Voluntary CEO turnover (JKPW) Dummy that equals 1 if an ExecuComp firm experiences a voluntary CEO departure during the next fiscal year, and 0 for all other firm-fiscal year observations. A CEO departure is classified as voluntary if it is not listed in the JKPW database of forced departures. These data are only available for ExecuComp firms. Jenter and Kanaan 2015; Peters and Wagner 2014 Voluntary CEO turnover Dummy that equals 1 if a firm experiences a voluntary CEO departure during the next fiscal year, and 0 for all other firm-fiscal year observations. For ExecuComp firms, this variable is equal to Voluntary CEO turnover (JKPW). For BoardEx firms, we extrapolate this variable using a predictive model for forced CEO turnover. First, we regress CEO firings from the JKPW database on standard determinants of forced turnover, using a sample of ExecuComp firms with fiscal years ending between January 2001 and December 2004. The dependent variable in this model is a dummy that equals 1 if a firm experiences a CEO departure that is listed as forced in the JKPW database, and 0 for all other firm-fiscal year observations. Explanatory variables, measured in the fiscal year prior to the departure, are CEO age and CEO tenure, Log assets, Market/book ratio, Stock return (also 2-year-lagged values), Stock volatility (also 2-year-lagged values), ROA (also 2-year-lagged values), Sales growth (also 2-year-lagged values), CEO duality, Frac. independent directors, and industry and year fixed effects. Second, we use the resulting coefficient estimates to calculate fitted values for firm-fiscal year observations at all sample firms. We use the 80th percentile of the distribution of these fitted values as our threshold to classify a CEO departure as forced (i.e., we classify 20% of CEO departures as forced). We calibrate the threshold to the 80th percentile because 20% of CEO departures at ExecuComp firms are listed as forced in the JKPW database. Third, we calculate fitted values for firm-fiscal year observations at BoardEx firms. We classify CEO departures at BoardEx firms as voluntary if the fitted values are below the threshold from step 2. Fourth, we set Voluntary CEO turnover equal to 1 for BoardEx firms that experience such a voluntary departure during the next fiscal year, and 0 for all other firm-fiscal year observations. Jenter and Kanaan 2015; Peters and Wagner 2014; own calculations Executive turnover Number of executives departing during the next fiscal year divided by the total number of top executives at the end of the current fiscal year. ExecuComp, Boardex Firm with turnover Dummy that equals 1 in all fiscal years for a firm that experienced a top executive departure in the fiscal year after acceleration, and 0 in all other fiscal years. ExecuComp, Boardex Firm with CEO turnover Dummy that equals 1 in all fiscal years for a firm that experienced a CEO departure in the fiscal year after acceleration, and 0 in all other fiscal years. ExecuComp, Boardex CEO turnover in 2 fiscal years Dummy that equals 1 if a firm experiences a CEO departure two fiscal years in the future, 0 in all other fiscal years. ExecuComp, Boardex CEO turnover in 3 fiscal years Dummy that equals 1 if a firm experiences a CEO departure three fiscal years in the future, 0 in all other fiscal years. ExecuComp, Boardex Outside director turnover Number of outside directors departing during the next fiscal year divided by the number of outside directors at the end of the current fiscal year. An outside director is a non-executive board member. ExecuComp, Boardex CEO turnover (within 3 months) Dummy that equals 1 if a firm experiences a CEO departure during the first 3 months of the next fiscal year, and 0 in all other fiscal years. CEO turnover (within 6 months) and CEO turnover (within 9 months) are accordingly defined. ExecuComp, Boardex C. Executive compensation variables Unvested option duration Weighted average number of months until unvested option grants vest. To calculate this variable, first we collect data from Thomson Insiders on new options granted between 2000 and 2006. Second, in each fiscal year $$t$$ we identify currently unvested options by only looking at grants with (1) a grant date (Thomson Insiders data item TRANDATE) prior to fiscal year $$t$$ and (2) a vesting date (date item XDATE) after fiscal year $$t$$. Third, for each unvested option grant, we measure the remaining unvested option duration (in months) as the vesting date minus the end date of the current fiscal year. Fourth, we calculate average duration across all unvested option grants, weighting by the number of options in each grant. We use the number of options in each grant as weights, because this is less likely to understate the amount of deep-out-of-the-money options than value-weighting. We omit grants that are indirectly owned or have missing data on strike prices, vesting dates, or expiration dates. Thomson Reuters Insiders Unvested option moneyness Weighted average of the moneyness of unvested option grants. Moneyness is the option’s strike price divided by the firm’s stock price, and is measured at the end of the fiscal year. We compile unvested option holdings using the same procedure as for Unvested option duration. Thomson Reuters Insiders Vested option value Value of an executive’s vested stock options (in thousands of USD), measured at the end of the fiscal year. The value of stock options is measured using the Black-Scholes formula, with formula inputs obtained using the Core and Guay (2002) procedure. To single out the impact of option acceleration from other common changes to vested option holdings, we add back the value of options that are exercised during the year, and subtract the value of options that were scheduled to vest during the year. We compile data on option exercises from Thomson Insiders and omit exercises of grants that are indirectly owned or are missing data on strike prices, vesting dates, or expiration dates. We identify option vesting schedules from the vesting dates listed when the option is first granted (Thomson Insiders data item XDATE). These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Vested option PPS Pay-for-performance sensitivity (PPS) of an executive’s vested stock options (in thousands of USD), measured at the end of the fiscal year. PPS is measured as the change in the dollar value of stock options for a 1% change in the firm’s stock price. The value of stock options is measured using the Black-Scholes formula, with formula inputs obtained using the Core and Guay (2002) procedure. We account for common changes to vested option holdings using the same procedure as for Vested option value. These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Unvested option value Value of an executive’s unvested stock options (in thousands of USD), measured at the end of the fiscal year. The value of each unvested option grant is measured using the Black-Scholes formula, and these values are summed for all unvested grants pledged to an executive. We compile executives’ unvested option holdings using the same procedure as for Unvested options duration. The formula inputs include the option strike price (Thomson Insiders data item XPRICE) and time to expiration (based on data item TDATE). These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Unvested option PPS PPS of an executive’s unvested stock options (in thousands of USD), measured at the end of the fiscal year. PPS is calculated using the same procedure as for Vested option PPS. We compile executives’ unvested option holdings using the same procedure as for Unvested options duration. These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Total compensation Total compensation during the fiscal year (ExecuComp data item TDC1), measured in thousands of USD. These data are only available for ExecuComp firms. ExecuComp Equity compensation Equity compensation during the fiscal year (the sum of ExecuComp data items OPTION_AWARDS_BLK_VALUE and RSTKGRNT before 2006, and OPTION_AWARDS_FV and STOCK_AWARDS_FV after 2006), measured in thousands of USD. These data are only available for ExecuComp firms. ExecuComp Unvested equity value to total compensation The ratio of unvested equity to the CEO’s total compensation in the fiscal year (or the average ratio if all top executives are used). These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders D. Other dependent variables and controls Assets Total assets at the end of the fiscal year (Compustat data item AT), measured in millions of USD. Compustat Market/book ratio Sum of market capitalization and book value of liabilities (Compustat data item LT) at the end of the fiscal year, divided by book value of common equity (CEQ) and book value of liabilities (LT) at the end of the fiscal year. Market capitalization is PRCC multiplied by CSHO. Data are winsorized at the 1% and 99% level. Compustat Stock return The natural logarithm of 1 plus the fractional stock return over the fiscal year. The return equals the stock price at the end of the fiscal year (Compustat data item PRCC_F) plus dividends (DVPSX_F), divided by the stock price at the end of the previous fiscal year, minus 1. Data are winsorized at the 5% and 95% level. Compustat Stock volatility The standard deviation of fractional stock returns (CRSP data item RET) from the 48 months preceding the end of the fiscal year. This variable is set to missing when fewer than 12 months’ returns are available. Data are winsorized at the 5% and 95% level. CRSP ROA Net income (Compustat data item NI) and interest expense (XINT) divided by total assets (AT) at the end of the fiscal year. Interest expense is set to 0 when it is reported as missing and in the previous fiscal year the firm reported no debt due in one year. Data are winsorized at the 1% and 99% level. Compustat Sales growth Fiscal-year-on-fiscal-year fractional change in sales (Compustat data item SALE). Data are winsorized at the 5% and 95% level. Compustat CEO age above 61 Dummy that equals 1 if the CEO is 61 years or older at the end of the fiscal year, and 0 in all other fiscal years. Age is measured using ExecuComp data item AGE. If this value is missing, then age is calculated using BoardEx data as the current fiscal year minus date of birth (BoardEx data item DOB). ExecuComp, BoardEx Frac. executives above 61 Fraction of top executives aged 61 or older. Age is measured using ExecuComp data item AGE. If this value is missing, then age is calculated using BoardEx data as the current fiscal year minus date of birth (BoardEx data item DOB). ExecuComp, BoardEx Non-compete clauses State-level index that measures how difficult it is to enforce a non-compete clause in an employment contract. Index values are based on the firm’s headquarters (Compustat data item STATE). Smaller index numbers indicate that it is more difficult to enforce a non-compete clause. Garmaise 2011, Compustat Distance to peers Number of Compustat firms in the same Fama-French 48 industry within 150 miles radius around the headquarters of a firm. The 150-mile radius is calculated using the GPS coordinates of firms’ headquarters. Compustat, own calculations Frac. independent directors Fraction of a board’s directors that are classified as independent (ISS Directors data item CLASSIFICATION equal to “I”) at the end of the fiscal year. ISS Directors, Equilar CEO duality Dummy that equals 1 if the firm’s CEO is also board chairman at the end of the fiscal year, and 0 in all other fiscal years. Dual CEO-Chairmen are identified using ISS Directors data items EMPLOYMENT_CEO and EMPLOYMENT_CHAIRMAN. ISS Directors, Equilar Retention key words in CD&A section Dummy that equals 1 if a firm’s Compensation Disclosure & Analysis (CD&A) section of its proxy statement in a given fiscal year contains key words related to executive retention, and 0 in all other fiscal years. The list of executive retention related key words include management retention; management turnover; turnover of management; turnover among management; retention of management; executive retention; executive turnover; turnover of executive; turnover among executive; retention of executive; turnover of key; turnover among key; and retention of key. SEC EDGAR, own calculations # Retention key words in CD&A section The number of key words related to executive retention in the firm’s CD&A. The list of executive retention related key words is the same as for Retention key words in CD&A section. SEC EDGAR, own calculations $$\Delta$$ Consensus analyst forecasts Change in the median consensus forecast for firms’ earnings per share (EPS) between 2004 and 2006. I/B/E/S Missed analyst consensus forecast Dummy that equals 1 if a firm missed the analyst consensus EPS forecast, and 0 in all other fiscal years. I/B/E/S Variable Definition Source A. Measures of option acceleration and FAS 123-R compliance Frac. options accelerated Number of options accelerated during the fiscal year divided by the total number of options outstanding at the beginning of the fiscal year. The number of options accelerated is from the R. G. Associates Option Accelerated Vester Database. The number of options outstanding is Compustat data item OPTOSBY. R. G. Associates Accelerate Dummy that equals 1 if a firm accelerated option vesting during the fiscal year, and 0 in all other fiscal years. R. G. Associates Accelerate in previous fiscal year Dummy that equals 1 if a firm accelerated option vesting during the previous fiscal year, and 0 in all other fiscal years. R. G. Associates Post-acceleration Dummy that equals 1 in fiscal years after a firm accelerated option vesting, and 0 in all other fiscal years. R. G. Associates Frac. options accelerated in 2005/2006 Number of options accelerated in the fiscal years ending between January 2005 and December 2006 divided by the number of options outstanding at the beginning of the fiscal year. R. G. Associates Accelerator Dummy that equals 1 in all fiscal years if a firm accelerated option vesting, and 0 in all other fiscal years. Equilar, R. G. Associates Accelerator in peer group Dummy that equals 1 in all fiscal years if a firm has a company with an acceleration event among its compensation peer group, and 0 in all other fiscal years. Equilar, R. G. Associates Post-peer acceleration Dummy that equals 1 in fiscal years after the earliest acceleration event by a compensation peer, and 0 in all other fiscal years. R. G. Associates FAS 123-R takes effect Our instrument that accounts for the staggered compliance of FAS 123-R across calendar years. It equals 1 for firm-fiscal year observations ending between June 2005 and May 2006, and 0 for all other firm-fiscal year observations. Compustat FAS 123-R takes effect in 2005/2006 Our instrument in Table 12. It equals 1 when FAS 123-R compliance begins four years after the firm-fiscal year observation (for tests covering January 2001 to December 2002), 1 when FAS 123-R compliance begins two years after the firm-fiscal year observation (for tests covering January 2003 to December 2004), and 0 for all other firm-fiscal year observations. Compustat June 2005 FYR Dummy that equals 1 for firm-fiscal year observations ending in June 2005, and 0 for all other firm-fiscal year observations. All other month dummy variables are defined accordingly. Compustat B. Executive turnover measures CEO turnover Dummy that equals 1 if a firm experiences a CEO departure during the next fiscal year, and 0 in all other fiscal years. We exclude interim or acting CEOs because their eventual replacement is not a substantive turnover event. We also exclude executives who are not actively involved in the firm’s management, such as former or emeritus CEOs. ExecuComp, BoardEx Voluntary CEO turnover (JKPW) Dummy that equals 1 if an ExecuComp firm experiences a voluntary CEO departure during the next fiscal year, and 0 for all other firm-fiscal year observations. A CEO departure is classified as voluntary if it is not listed in the JKPW database of forced departures. These data are only available for ExecuComp firms. Jenter and Kanaan 2015; Peters and Wagner 2014 Voluntary CEO turnover Dummy that equals 1 if a firm experiences a voluntary CEO departure during the next fiscal year, and 0 for all other firm-fiscal year observations. For ExecuComp firms, this variable is equal to Voluntary CEO turnover (JKPW). For BoardEx firms, we extrapolate this variable using a predictive model for forced CEO turnover. First, we regress CEO firings from the JKPW database on standard determinants of forced turnover, using a sample of ExecuComp firms with fiscal years ending between January 2001 and December 2004. The dependent variable in this model is a dummy that equals 1 if a firm experiences a CEO departure that is listed as forced in the JKPW database, and 0 for all other firm-fiscal year observations. Explanatory variables, measured in the fiscal year prior to the departure, are CEO age and CEO tenure, Log assets, Market/book ratio, Stock return (also 2-year-lagged values), Stock volatility (also 2-year-lagged values), ROA (also 2-year-lagged values), Sales growth (also 2-year-lagged values), CEO duality, Frac. independent directors, and industry and year fixed effects. Second, we use the resulting coefficient estimates to calculate fitted values for firm-fiscal year observations at all sample firms. We use the 80th percentile of the distribution of these fitted values as our threshold to classify a CEO departure as forced (i.e., we classify 20% of CEO departures as forced). We calibrate the threshold to the 80th percentile because 20% of CEO departures at ExecuComp firms are listed as forced in the JKPW database. Third, we calculate fitted values for firm-fiscal year observations at BoardEx firms. We classify CEO departures at BoardEx firms as voluntary if the fitted values are below the threshold from step 2. Fourth, we set Voluntary CEO turnover equal to 1 for BoardEx firms that experience such a voluntary departure during the next fiscal year, and 0 for all other firm-fiscal year observations. Jenter and Kanaan 2015; Peters and Wagner 2014; own calculations Executive turnover Number of executives departing during the next fiscal year divided by the total number of top executives at the end of the current fiscal year. ExecuComp, Boardex Firm with turnover Dummy that equals 1 in all fiscal years for a firm that experienced a top executive departure in the fiscal year after acceleration, and 0 in all other fiscal years. ExecuComp, Boardex Firm with CEO turnover Dummy that equals 1 in all fiscal years for a firm that experienced a CEO departure in the fiscal year after acceleration, and 0 in all other fiscal years. ExecuComp, Boardex CEO turnover in 2 fiscal years Dummy that equals 1 if a firm experiences a CEO departure two fiscal years in the future, 0 in all other fiscal years. ExecuComp, Boardex CEO turnover in 3 fiscal years Dummy that equals 1 if a firm experiences a CEO departure three fiscal years in the future, 0 in all other fiscal years. ExecuComp, Boardex Outside director turnover Number of outside directors departing during the next fiscal year divided by the number of outside directors at the end of the current fiscal year. An outside director is a non-executive board member. ExecuComp, Boardex CEO turnover (within 3 months) Dummy that equals 1 if a firm experiences a CEO departure during the first 3 months of the next fiscal year, and 0 in all other fiscal years. CEO turnover (within 6 months) and CEO turnover (within 9 months) are accordingly defined. ExecuComp, Boardex C. Executive compensation variables Unvested option duration Weighted average number of months until unvested option grants vest. To calculate this variable, first we collect data from Thomson Insiders on new options granted between 2000 and 2006. Second, in each fiscal year $$t$$ we identify currently unvested options by only looking at grants with (1) a grant date (Thomson Insiders data item TRANDATE) prior to fiscal year $$t$$ and (2) a vesting date (date item XDATE) after fiscal year $$t$$. Third, for each unvested option grant, we measure the remaining unvested option duration (in months) as the vesting date minus the end date of the current fiscal year. Fourth, we calculate average duration across all unvested option grants, weighting by the number of options in each grant. We use the number of options in each grant as weights, because this is less likely to understate the amount of deep-out-of-the-money options than value-weighting. We omit grants that are indirectly owned or have missing data on strike prices, vesting dates, or expiration dates. Thomson Reuters Insiders Unvested option moneyness Weighted average of the moneyness of unvested option grants. Moneyness is the option’s strike price divided by the firm’s stock price, and is measured at the end of the fiscal year. We compile unvested option holdings using the same procedure as for Unvested option duration. Thomson Reuters Insiders Vested option value Value of an executive’s vested stock options (in thousands of USD), measured at the end of the fiscal year. The value of stock options is measured using the Black-Scholes formula, with formula inputs obtained using the Core and Guay (2002) procedure. To single out the impact of option acceleration from other common changes to vested option holdings, we add back the value of options that are exercised during the year, and subtract the value of options that were scheduled to vest during the year. We compile data on option exercises from Thomson Insiders and omit exercises of grants that are indirectly owned or are missing data on strike prices, vesting dates, or expiration dates. We identify option vesting schedules from the vesting dates listed when the option is first granted (Thomson Insiders data item XDATE). These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Vested option PPS Pay-for-performance sensitivity (PPS) of an executive’s vested stock options (in thousands of USD), measured at the end of the fiscal year. PPS is measured as the change in the dollar value of stock options for a 1% change in the firm’s stock price. The value of stock options is measured using the Black-Scholes formula, with formula inputs obtained using the Core and Guay (2002) procedure. We account for common changes to vested option holdings using the same procedure as for Vested option value. These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Unvested option value Value of an executive’s unvested stock options (in thousands of USD), measured at the end of the fiscal year. The value of each unvested option grant is measured using the Black-Scholes formula, and these values are summed for all unvested grants pledged to an executive. We compile executives’ unvested option holdings using the same procedure as for Unvested options duration. The formula inputs include the option strike price (Thomson Insiders data item XPRICE) and time to expiration (based on data item TDATE). These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Unvested option PPS PPS of an executive’s unvested stock options (in thousands of USD), measured at the end of the fiscal year. PPS is calculated using the same procedure as for Vested option PPS. We compile executives’ unvested option holdings using the same procedure as for Unvested options duration. These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders Total compensation Total compensation during the fiscal year (ExecuComp data item TDC1), measured in thousands of USD. These data are only available for ExecuComp firms. ExecuComp Equity compensation Equity compensation during the fiscal year (the sum of ExecuComp data items OPTION_AWARDS_BLK_VALUE and RSTKGRNT before 2006, and OPTION_AWARDS_FV and STOCK_AWARDS_FV after 2006), measured in thousands of USD. These data are only available for ExecuComp firms. ExecuComp Unvested equity value to total compensation The ratio of unvested equity to the CEO’s total compensation in the fiscal year (or the average ratio if all top executives are used). These data are only available for ExecuComp firms. ExecuComp, Thomson Reuters Insiders D. Other dependent variables and controls Assets Total assets at the end of the fiscal year (Compustat data item AT), measured in millions of USD. Compustat Market/book ratio Sum of market capitalization and book value of liabilities (Compustat data item LT) at the end of the fiscal year, divided by book value of common equity (CEQ) and book value of liabilities (LT) at the end of the fiscal year. Market capitalization is PRCC multiplied by CSHO. Data are winsorized at the 1% and 99% level. Compustat Stock return The natural logarithm of 1 plus the fractional stock return over the fiscal year. The return equals the stock price at the end of the fiscal year (Compustat data item PRCC_F) plus dividends (DVPSX_F), divided by the stock price at the end of the previous fiscal year, minus 1. Data are winsorized at the 5% and 95% level. Compustat Stock volatility The standard deviation of fractional stock returns (CRSP data item RET) from the 48 months preceding the end of the fiscal year. This variable is set to missing when fewer than 12 months’ returns are available. Data are winsorized at the 5% and 95% level. CRSP ROA Net income (Compustat data item NI) and interest expense (XINT) divided by total assets (AT) at the end of the fiscal year. Interest expense is set to 0 when it is reported as missing and in the previous fiscal year the firm reported no debt due in one year. Data are winsorized at the 1% and 99% level. Compustat Sales growth Fiscal-year-on-fiscal-year fractional change in sales (Compustat data item SALE). Data are winsorized at the 5% and 95% level. Compustat CEO age above 61 Dummy that equals 1 if the CEO is 61 years or older at the end of the fiscal year, and 0 in all other fiscal years. Age is measured using ExecuComp data item AGE. If this value is missing, then age is calculated using BoardEx data as the current fiscal year minus date of birth (BoardEx data item DOB). ExecuComp, BoardEx Frac. executives above 61 Fraction of top executives aged 61 or older. Age is measured using ExecuComp data item AGE. If this value is missing, then age is calculated using BoardEx data as the current fiscal year minus date of birth (BoardEx data item DOB). ExecuComp, BoardEx Non-compete clauses State-level index that measures how difficult it is to enforce a non-compete clause in an employment contract. Index values are based on the firm’s headquarters (Compustat data item STATE). Smaller index numbers indicate that it is more difficult to enforce a non-compete clause. Garmaise 2011, Compustat Distance to peers Number of Compustat firms in the same Fama-French 48 industry within 150 miles radius around the headquarters of a firm. The 150-mile radius is calculated using the GPS coordinates of firms’ headquarters. Compustat, own calculations Frac. independent directors Fraction of a board’s directors that are classified as independent (ISS Directors data item CLASSIFICATION equal to “I”) at the end of the fiscal year. ISS Directors, Equilar CEO duality Dummy that equals 1 if the firm’s CEO is also board chairman at the end of the fiscal year, and 0 in all other fiscal years. Dual CEO-Chairmen are identified using ISS Directors data items EMPLOYMENT_CEO and EMPLOYMENT_CHAIRMAN. ISS Directors, Equilar Retention key words in CD&A section Dummy that equals 1 if a firm’s Compensation Disclosure & Analysis (CD&A) section of its proxy statement in a given fiscal year contains key words related to executive retention, and 0 in all other fiscal years. The list of executive retention related key words include management retention; management turnover; turnover of management; turnover among management; retention of management; executive retention; executive turnover; turnover of executive; turnover among executive; retention of executive; turnover of key; turnover among key; and retention of key. SEC EDGAR, own calculations # Retention key words in CD&A section The number of key words related to executive retention in the firm’s CD&A. The list of executive retention related key words is the same as for Retention key words in CD&A section. SEC EDGAR, own calculations $$\Delta$$ Consensus analyst forecasts Change in the median consensus forecast for firms’ earnings per share (EPS) between 2004 and 2006. I/B/E/S Missed analyst consensus forecast Dummy that equals 1 if a firm missed the analyst consensus EPS forecast, and 0 in all other fiscal years. I/B/E/S Footnotes 1 Xu and Yang (2016) find that upfront payments increase by 16 cents for each $${\}$$1 of unvested equity and thus replenish only some of an executive’s unvested holdings. Moreover, unvested equity may help firms to retain executives by creating a friction in the labor market, as executives with larger holdings are more costly to poach. 2 Managers who find it least costly to forfeit deferred compensation (such as those who expect to receive lucrative outside offers) may sort to firms that grant the most unvested equity. Such managers may also be more likely to subsequently switch jobs. 3 To illustrate, June fiscal-year-end firms had to accelerate options by June 30, 2005, whereas May fiscal-year-end firms could delay acceleration until May 31, 2006. In this example, the firms’ acceleration deadlines—and hence the treatment periods over which we measure turnover—are furthest apart in calendar time (11 months). Because most firms have a December fiscal-year end, our identification mostly comes from treatment periods that were much closer in calendar time. 4 We examine turnover in the next fiscal year because executives had to wait until acceleration actually occurred to depart with the newly vested equity. Notably, executives likely did not anticipate the timing of option acceleration, because FAS 123-R’s compliance schedule was unexpectedly delayed just 2 months before the regulation took effect. 5 Chen (2004) shows that firms that restrict option repricing experience higher turnover. Several papers also examine how compensation structure affects general employee turnover (Oyer and Schaefer 2005; Balsam, Gifford, and Kim 2007; Aldatmaz, Ouimet, and Van Wesep 2018). 6 Balsam, Reitenga, and Yin (2008) and Choudhary, Rajgopal, and Venkatachalam (2009) provide additional information about the U.S. history of accounting for stock options. 7 For firm-fiscal year observations ending in December 2005, we measure turnover rates from January to December 2006 (i.e., the following fiscal year). The control group for these firms is all firm-fiscal years ending between January and May 2005, for which turnover is measured from February 2005 to May 2006. A shock in calendar year 2006 could cause turnover to rise among the many December fiscal-year-end firms, while affecting only a small number of control firms. 8 The performance of accelerating firms was below average, but not concentrated in the lowest tail of the sample distribution. When we sort firms into quintiles based on stock returns from 2001 to 2004, we find that 25% of firms in the lowest quintile and 20% of firms in the second lowest quintile subsequently accelerated options. However, accelerating firms also make up 16% and 20% of firms in two highest return quintiles, respectively. (The distribution is similar for ROA.) We also find that the median accelerating firm earned higher returns than 42% of non-accelerating firms. 9 A reduction in match surplus occurs when a firm’s value is higher under the departing CEO than under the next-best CEO that replaces him (assuming that the initial assignment of CEOs to firms was competitive and frictionless). 10 The sample contains 292 executive departures (including 52 CEOs) at ExecuComp firms after option acceleration. 11 An alternative interpretation is that the marginal value to the firm of retaining the remaining executives rose following the CEO’s departure. References Aboody, D., Barth, M. E. and Kasznik. 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# The Retention Effects of Unvested Equity: Evidence from Accelerated Option Vesting

The Review of Financial Studies, Volume 31 (11) – Nov 1, 2018
45 pages