CEO Preferences and Acquisitions

A. CEOs’ Private Merger Costs

Prior literature shows that target CEOs typically lose their jobs during or shortly after a takeover, and that the departing CEO only rarely finds a comparable position in a public firm. Walkling and Long (1984), Martin and McConnell (1991), Agrawal and Walkling (1994), Hartzell, Ofek, and Yermack (2004), and Wulf and Singh (2011) all document that target CEOs suffer high turnover rates and poor career prospects following mergers.6 This suggests that being the target of a takeover bid can impose large career costs on the target CEO.

In addition, standard CEO compensation practices strongly suggest that acquisitions entail costs for target CEOs. Most CEO compensation contracts contain golden parachutes and special bonuses that generate additional income for CEOs in the event a firm is sold. These widespread arrangements, documented in detail by Hartzell, Ofek, and Yermack (2004), Bebchuk, Cohen, and Wang (2010), and Fich, Tran, and Walkling (2013), make little sense unless being acquired is costly for target CEOs.7

B. The Age-65 Effect

Labor economists have studied retirement decisions for decades and developed models predicting the retirement patterns of U.S. employees.8 A puzzling phenomenon, however, is that these models underpredict the frequency of retirements at age 65. For example, in one of the firms studied by Lumsdaine, Stock, and Wise (1996), 48% of men working at 64 retire at 65. This compares to 21% of men working at 63 who retire at 64.9 Lumsdaine et al. test a number of potential explanations for this age-65 effect. They conclude that the magnitude of the spike cannot be explained by the provisions of Social Security, Medicare, or pension plans. They also argue that, for a typical worker aged 64, the cost of retiring at 65 versus the optimal age is quite high, so that “rule-of-thumb” behavior is unlikely to explain the data. They conclude that “We are inclined to attribute the unexplained high age 65 departure rates to an ‘age-65 retirement effect,’ that is, to the influence of custom or accepted practice” (p. 81). Put differently, employees’ preferences for work versus retirement seem to change discretely (or at least rapidly) at age 65.

In this paper, we exploit the age-65 effect to test whether CEOs’ personal preferences affect the likelihood and outcomes of merger bids. Figure 1 shows that CEO turnovers spike at age 65, very similar to the pattern for rank-and-file employees. Moreover, departure rates are consistently higher after age 65 than before.10 There are a number of possible reasons why more CEOs retire around age 65. First, CEOs may have internalized customary retirement practices and their preferences for work versus leisure may change around 65, similar to what the literature suggests for other employees. Alternatively, boards may pressure CEOs to retire, perhaps because they believe that CEO skills deteriorate with age, or because they are trying to improve the incentives of potential successors. If board pressure increases sharply at 65, CEOs may experience a corresponding decline in utility from employment at that threshold.11

What are the implications of the many CEO retirements around age 65 for acquisitions? A straightforward implication is that many CEOs close to age 65 do not lose much by accepting a takeover bid. For younger CEOs, becoming the target of an acquisition usually implies an (involuntary) early retirement, as discussed in the previous section. For a CEO at or close to his expected retirement age, however, his cost of the firm being acquired should be small.

If CEOs are powerful enough to impose their personal preferences onto their firms’ policies, acquirers should prefer target CEOs who are ready to retire. The exact effect of target CEO age on acquisition patterns around age 65 depends on why, exactly, CEOs retire at this age. If CEOs’ preference for work over leisure gradually declines as they approach 65, their willingness to sell the firm should gradually increase, and so should the frequency of acquisition bids. Similarly, if CEOs are concerned about the loss of future income due to an involuntary early retirement, this concern should gradually diminish as they approach retirement, again leading to a gradual increase in acquisitions. However, if CEOs have a strong preference to stay in office until age 65, or if CEOs are pressured to retire at age 65 even though they still prefer to work, we may observe an abrupt increase in takeover activity as CEOs reach retirement age. Finally, acquirers might find it optimal to wait with an offer until target CEOs reach their desired retirement age, and in doing so cause an abrupt increase in takeover activity at age 65.

Independent of whether CEOs’ retirement preferences lead to a gradual or sudden increase in acquisitions around the age of 65, acquisition frequencies should decline after age 65. If most CEOs of desirable takeover targets sell their firm at age 65 (at the latest), firms run by even older CEOs are likely to not be desirable targets or to have CEOs who do not want to sell at any age.

C. The Age-65 Effect: Additional Predictions

C.2. Merger Waves and Overvaluation

In the middle of our sample period, merger activity reached unprecedented levels, rising from 25 to 65 mergers per month over the course of the 1990s. This merger wave overlapped with the stock market boom of the late 1990s, during which the S&P 500 nearly doubled over a three-year period (see Figure 2). The literature points to two potential causes of this merger wave. First, a regulatory or technological shock might have increased the synergies from mergers, causing the surge in deals (Mitchell and Mulherin (1996), Andrade, Mitchell, and Stafford (2001), Andrade and Stafford (2004)). Second, overvaluation might have prompted some firms to merge to take advantage of their temporarily inflated prices (Shleifer and Vishny (2003), Rhodes-Kropf and Viswanathan (2004)).

In either case, the rise in takeover activity during the late 1990s suggests a rise in the benefits of merging. This observation has two potential implications for the age-65 effect. First, target CEOs’ private merger costs become relatively less important, causing them to sell their firms earlier than they otherwise would. This suggests a weaker age-65 effect during the merger wave, especially if the additional merger benefits were expected to be short-lived. Second, if young CEOs had been blocking acquisitions of desirable takeover targets before the wave, and if the increased benefits of selling during the wave weakened their resistance, the rise in merger activity should be especially strong for young CEOs. As a result, the peak in merger activity predicted for CEOs close to 65 may have temporarily shifted to a younger age. To account for this possibility, the analysis below allows the relation between CEO age and mergers to differ between the merger wave and other years.

A. Data and Sample

We obtain a comprehensive panel of CEOs for U.S. public firms from 1989 through 2007 from Edward Fee, Charles Hadlock, and Joshua Pierce (see Fee, Hadlock, and Pierce (2013)). The data set was extracted from Compustat Research Insight (formerly Compustat PC Plus) CDs, which contain the names and ages of the top four executives for U.S. listed firms. The sample is limited to firms with at least $10 million in book assets and excludes financial firms, utilities, and firms incorporated outside the united states The timing of each CEO change reported in the database is cross-checked manually using information from 10K statements, annual reports, and news reports in the Factiva database. Further details on the Fee et al. data set are in the Appendix.

The acquisition data come from Securities Data Corporation's (SDC) U.S. Mergers and Acquisitions Database. To identify acquisition targets in the CEO panel, we start with a list of all bids for panel firms with announcement dates during the sample period. We exclude share repurchases, privatizations, exchange offers, recapitalizations, cases in which the bidder already owns 50% or more of the target's equity, and bids with missing data on the amount of target equity sought. The final sample contains 4,145 completed takeover bids for 3,956 firms.14 Based on this list, we identify the firm-years in the CEO panel in which the firm becomes an acquisition target. To do so, we first set the acquisition indicator to one for a fiscal year if the firm receives an ultimately successful takeover bid during that year. Then, if a fiscal year is a firm's final reported year, we set the acquisition indicator to one if the firm receives a successful bid either during that year or within the next year. This second step ensures the inclusion of cases in which the bid announcement occurs after the end of the firm's last reported fiscal year.

This procedure yields 3,397 firm-years in the CEO panel in which a firm is an acquisition target, corresponding to 4.7% of all panel years.15 After merging with financial statement information from Compustat and monthly stock return data from the Center for Research in Security Prices (CRSP), and after eliminating observations with missing data, the final panel comprises 56,183 firm-years, 2,966 of which are years in which the firm is a target. The sample used in the takeover premium analysis in Section 'Retirement Age and Takeovers'.C consists of 2,801 completed bids with available control variables and takeover premium data. Takeover premium information comes from SDC or, if missing, is approximated using announcement returns.

Some tests require data on board structures, CEO ownership, block ownership, and director ownership, which are provided to us by James Linck (see Linck, Netter, and Yang (2008)). The data set was compiled for a large sample of U.S. public firms from 1991 to 2004 using proxy statements available in the Disclosure database. Details on the data construction are described in the Appendix. To combine the governance data with the CEO panel, we merge each fiscal year in the panel with governance variables measured in the prior fiscal year or, if not available, in the fiscal year twice lagged. This procedure results in a panel with nonmissing governance variables of 22,532 firm-years (7,992 firms) from 1992 to 2006.

B. Descriptive Statistics

Descriptive statistics for the full sample and for the subsample with available governance data are in Table I. The average CEO is 54.1 years old and has been in office 6.2 years (the medians are 54.0 and 4.0). Firms with available governance data are somewhat larger and have slightly older and more seasoned CEOs. The average firm has 7.9 directors on its board, 32% of whom are insiders (the medians are 7.0 and 29%). The CEO is chairman of the board in 62% of the sample. Blockholders hold, on average, 34% of the firm's equity, while the average equity ownership by the CEO is 5.5% (the median is only 0.9%). These values are similar to those reported in Linck et al.

Table II, Panel A reports descriptive statistics for subsamples of firm-years based on CEO age, and Table II, Panel B does so for firms that are takeover targets in that year. Importantly, firms run by CEOs aged 64 to 66 are similar to firms run by CEOs aged 59 to 63, the next lower age group. Panel B shows that targets with retirement-age CEOs are somewhat smaller and have slightly higher book-to-market ratios. The two age groups are similar with respect to the proportion of cash-only acquisitions, hostile takeovers, tender offers, the incidence of toeholds, and the incidence of takeover contests. There is a noticeable difference in the frequency of LBOs, which is 12% for targets run by retirement-age CEOs but only 7% for targets run by CEOs aged 59 to 63. It is possible, and would be consistent with this paper's hypothesis, that private equity sponsors seek out targets with CEOs who have reached retirement age. Finally, Panel B shows that targets run by CEOs who are 67 or older are substantially smaller and earn lower takeover premiums and announcement returns than targets led by retirement-age CEOs.

A. The Retirement-Age Effect

This section establishes the effect of retirement-age CEOs on the likelihood of receiving a successful acquisition bid. Using the panel data set described in Section 'Data and Descriptive Statistics'.A, we estimate a logit model with the dependent variable equal to one if a firm becomes the target of an ultimately completed bid in a given fiscal year. The results are in Table III.

The main variable of interest is the retirement-age indicator RET_AGE, which is equal to one if the CEO is of age 64 to 66 at the time of the bid. The first four regressions include dummy variables for other CEO age groups, as well as firm and CEO characteristics, while the last four regressions control separately for CEO age and age squared. The analysis allows the effect of retirement age on bid frequencies to differ between the merger wave of 1997–1999 and other years.

Table III shows that the likelihood of receiving a successful takeover bid increases sharply at retirement age. The increase appears to be discrete, with a much smaller gradual rise as CEOs approach retirement age, and is caused entirely by takeovers outside of the merger wave. In the first regression, the coefficient on the retirement-age indicator is positive and highly significant (t = 4.08), while the coefficient on the interaction with the merger wave dummy is negative (t = –2.49).16 The second regression forces the effect of retirement age on bids to be the same throughout the sample period, which makes the retirement-age effect smaller but leaves it strongly significant (t = 2.66).

The next two columns show separate regressions for the sample without the merger wave and for only the merger wave. The implied bid frequencies, calculated at the means of the control variables, are plotted in Figure 3, Panels A and B. Outside the merger wave, the probability of a successful bid is 4% per year for CEOs in the 54 to 58 age group and 4.4% in the next older age group (59 to 53). The probability of a bid increases sharply to 5.8% at retirement age (a 32% increase in the odds), before falling again to 4.5% for CEOs aged 67 or older. There is no comparable jump in bid frequencies for any age group other than at retirement age.

During the merger wave, as shown in Figure 3, Panel B, the probability of younger CEOs receiving a successful bid nearly doubled (e.g., from 4.1% to 8.1% for age 54 to 58). Even though retirement-age CEOs also received more bids, the increase is substantially smaller (from 5.8% to 6.9%). As a result, bid frequencies peak in the 59 to 63 age group. This pattern is consistent with the paper's hypothesis and the discussion in Section 'CEOs’ Private Merger Costs and the Age-65 Effect'.C.2: before the wave, younger CEOs were more likely than retirement-age CEOs to block attractive deals. As the wave set in, the increased benefits from merging weakened this resistance, leading to larger increases in merger volume for the younger age groups. Firms run by younger CEOs might have also experienced a greater increase in merger benefits during the wave, contributing to the pattern in Figure 3, Panel B.

The last four columns of Table III repeat the analysis but replace the age group indicators (other than the indicator for retirement age) by linear and quadratic controls for CEO age. Controlling separately for CEO age and age-squared works against finding a retirement-age effect because CEO age itself should be correlated with CEOs’ private merger costs. Specifically, private merger costs should decline as CEOs get older, independent of any additional age-65 effect, though this relation may be confounded by correlated factors. For example, younger CEOs might have better career opportunities outside their firms and, consequently, view mergers as less costly. Younger CEOs might also lead more dynamic firms and therefore experience a more active takeover market.

These last four regressions show that the retirement-age effect on takeover frequencies is not caused by bids following a linear or even a quadratic trend in CEO age. The increase in M&A activity at retirement age (outside the merger wave) remains large and highly significant in this alternative, and arguably too conservative, specification. This result reinforces the finding that the incidence of successful takeover bids is elevated in a narrow window around age 65.

The analysis in Table III examines the probability of receiving an ultimately completed takeover bid. The Internet Appendix examines separately the probability of receiving a takeover bid (whether completed or not), and the likelihood that a bid, once made, is successful.17 The results further support the existence of a retirement-age effect in acquisitions: acquirers are more likely to approach targets led by retirement-age CEOs, and bids for targets with retirement-age CEOs are more likely to succeed. Outside of the merger wave, the likelihood of a bid increases from 6.2% for the median (54 to 58) age group to 8.0% for the retirement-age group, for an odds ratio of 1.29. The likelihood of bid completion increases from 76% for bids with a median-age CEO to 82% for bids with a retirement-age CEO, implying a probability of bid failure that is 24% lower for retirement-age CEOs.18

B. Corporate Governance and the Retirement-Age Effect

If, as we suspect, the increase in takeover activity at retirement age is due to young CEOs who are reluctant to sell their firms, then firms with better governance should see more sales by younger CEOs, and a smaller increase in sales at retirement age. This section therefore examines whether the relationship between CEO age and acquisition activity varies with target corporate governance.

A number of studies show that specific governance features, including higher block ownership, more independent and smaller boards, and higher CEO stock ownership, are associated with better outcomes for shareholders (Morck, Shleifer, and Vishny (1988), Yermack (1996), Cotter, Shivdasani, and Zenner (1997), Denis, Denis, and Sarin (1997), and Core, Holthausen, and Larcker (1999)). However, measuring governance quality is challenging. Several studies point out that the cross-sectional variation in governance attributes such as board size or independence is largely consistent with firms choosing their governance efficiently in response to the environments in which they operate (Coles, Daniel, and Naveen (2008), and Link, Netter, and Yang (2008)). In addition, firms typically have multiple governance mechanisms to choose from, so focusing on one mechanism in isolation provides an incomplete picture of overall governance strength.

To address these challenges, we jointly examine several governance characteristics available for a broad sample of firms. These variables measure stock ownership by the CEO, blockholders, and directors; board size; board independence; and an indicator for CEOs who are also chairmen of the board. Each governance measure is orthogonalized with respect to firm and CEO characteristics, and the residual (or “abnormal”) governance characteristic is used to explain acquisition behavior.19 In addition to examining the variables separately, we combine them into a broader index of governance quality, GOVQ. To construct the index, we sort each of the residual governance measures into terciles, with higher values indicating better governance, and cumulate the tercile ranks (0–2). The resulting index is again orthogonalized with respect to firm and CEO characteristics, and the residual index is used to explain acquisition behavior.

The results are reported in Table IV. Similar to the previous analyses, each regression estimates the likelihood that a firm becomes the target of an ultimately successful takeover bid in a given fiscal year. In addition to the retirement-age indicator and the usual controls, the first regression includes the governance quality index GOVQ and its interaction with retirement age. As predicted, the interaction effect with retirement age is negative and highly significant (t = –3.17). The dampening impact of good governance on the retirement-age effect is economically large: increasing GOVQ by one standard deviation around its mean diminishes the marginal effect of RET_AGE on the bid probability from 2.4% to 0.7% (t = 2.45).20

The coefficient on the governance quality indicator GOVQ itself is positive and significant (t = 3.69). The Internet Appendix shows that this effect is robust to alternative specifications, in particular to including an indicator for CEOs older than retirement age and interacting this indicator with GOVQ. In this specification, the coefficient on GOVQ, which now measures the effect of better governance for CEOs below retirement age, remains highly significant (t = 3.64). Hence, as predicted, better governance, as measured by GOVQ, is associated with more sales by CEOs younger than retirement age, and with a smaller increase in sales at retirement age.

The second regression in Table IV replaces the governance index with its individual components. A higher value of a component indicates better governance. Five out of the six components have a negative interaction coefficient with the retirement-age indicator, suggesting that better governance dampens the increase in acquisitions at retirement age. The strongest negative interaction effects are for CEO-chairman separation, small boards, and block ownership (with t-statistics of –2.02, –2.12, and –1.83, respectively).21 Directors’ stock ownership has a positive (but insignificant and close to zero) coefficient on the interaction term. In sum, Table IV shows that the increase in firm sales at retirement age is significantly smaller for better governed firms, consistent with the hypothesis that the retirement-age effect is due to conflicts of interest between target shareholders and their CEOs.22

C. Announcement Returns and Takeover Premiums

C.2. Price Run-Ups before the First Bid Announcement

Announcement returns and takeover premiums can differ across CEO age groups because of differences in pre-bid information leakage or takeover rumors. For example, if investors view firms led by retirement-age CEOs as more likely to receive takeover bids, they might watch these firms more attentively and spot signs of an impending bid earlier. To examine the role of pre-bid price movements, Figure 4 plots the cumulative industry-adjusted stock returns from trading days –30 to +20 around the first bid announcement for different CEO age groups.

Based on the figure, there are no significant pre-announcement price run-ups before day –20, which is the day from which we measure announcement returns. This result is consistent with Betton, Eckbo, and Thorburn (2008) and suggests that the comparison of announcement returns and premiums across CEO age groups is not affected by differences in information leakage or takeover rumors immediately before the announcement.

It is possible that differences in merger expectations formed in the more distant past affect the comparison of announcement returns and premiums. Section 'Alternative (or Complementary) Explanations for the Retirement-Age Effect'.A therefore provides a comparison of long-term pre-bid stock returns across CEO age groups. We find no statistically significant differences in stock returns over the two years before the first bid announcement, which again suggests that there are no differences in bid anticipation across CEO age groups.

A. Disciplinary Takeovers

CEOs close to age 65 who are unwilling to retire might experience more frequent disciplinary takeovers, which we define as takeovers aimed primarily at replacing the CEO. If a firm is run by an unsuitable CEO, potential acquirers might refrain from bidding if they expect the CEO soon to retire voluntarily. They may, however, swoop in with an offer once it becomes clear that the CEO intends to stay beyond the expected retirement age. This explanation can generate a spike in takeover activity for target CEOs close to 65, but proposes disciplinary rather than voluntary firm sales as the mechanism behind the spike.

Because disciplinary takeovers are usually preceded by bad performance, we test this hypothesis by examining the long-run pre-bid stock price and operating performance of takeover targets. Table VII reports regressions of pre-bid stock returns and return-on-assets (ROA) on the retirement-age indicator, other CEO age controls, and firm and CEO characteristics. Stock price performance is measured as the average industry-adjusted monthly stock return over one or two years ending three months before the first bid announcement. Operating performance is measured as the average ROA over the three years prior to the bid. To conserve on space, only coefficients and t-statistics for the CEO age variables are reported in the table.

The coefficients on the retirement-age indicator are statistically insignificant and are positive in four out of the six regressions. Thus, there is no evidence that retirement-age CEOs perform worse than younger CEOs before receiving successful takeover bids. As an additional test, columns one and two of Table VIII regress the probability of a successful takeover bid on target CEO age and interactions between the retirement-age indicator and past stock returns (column 1) or past ROA (column 2). Both interaction terms are positive and insignificant, suggesting that the retirement-age effect on bids is, if anything, weakly stronger if prior performance is better. This contradicts the hypothesis that the increase in firm sales around age 65 is caused by bad performers. Overall, the analysis provides little support for disciplinary takeovers as an explanation for the increase in takeovers at retirement age.

B. Firms with Succession Problems

Some firms with CEOs who want to retire at age 65 may have difficulties finding a successor. Merging with another firm can solve a CEO succession problem by giving the target firm access to the acquirer's managers. This explanation makes CEOs’ desire to retire itself the reason why more firm sales become optimal when CEOs reach age 65.

To explore whether succession problems can explain the spike in acquisitions at retirement age, we use several methods to identify firms for which replacing a retiring CEO may be more difficult. The first approach identifies industries in which CEO talent is scarce as industries with unusually high CEO pay. We measure abnormal industry-average CEO pay (Industry Pay) using the loadings on industry dummies from a regression of CEO pay on firm characteristics and two-digit SIC industry indicators.23 To test whether target CEO age matters more in high-paying industries, column 3 of Table VIII regresses the probability of receiving a successful takeover bid on CEO age, the usual controls, and the interaction between the retirement-age indicator and Industry Pay. The interaction effect is negative and not statistically significant (t = –0.96). The positive coefficient on RET_AGE itself, which now captures the effect of having a retirement-age CEO in an industry with average pay, remains large and significant.

Next, we try to identify extraordinarily skilled individual CEOs who may be difficult to replace. The departure of a highly skilled CEO can trigger a succession problem if the board insists on a successor who matches the predecessor's ability. The attempt to match ability can be optimal if the firm needs a highly skilled CEO, or it might reflect board irrationality. The fourth column of Table VIII replaces Industry Pay with CEO Performance, the average industry-adjusted stock price performance over the CEO's tenure. The interaction term is negative and significant (t = –2.07), indicating a weaker rather than stronger retirement-age effect for more successful CEOs.

Boards might find it more difficult to replace CEOs who have been in office for a long time and therefore opt for a company sale when the CEO retires. Column 5 of Table VIII tests whether the retirement-age effect is stronger for CEOs with tenure longer than six years. The interaction term between RET_AGE and Long Tenure is positive but statistically insignificant.24

In the same vein, boards might find it more difficult to replace retiring founders, and founders themselves might prefer selling the firm to passing it on to a successor, for psychological or liquidity reasons.25 Column 6 of Table VIII therefore interacts the retirement-age indicator with an indicator for founder CEOs. The interaction term is negative and insignificant. Hence, if anything, founders are associated with a smaller increase in firm sales at retirement age. Overall, the evidence in Table VIII provides little support for the idea that the increase in takeover activity when target CEOs reach retirement age is caused by succession problems.

C. CEO Illiquidity

Acquisitions frequently allow target CEOs to cash out their illiquid stock and option holdings in their firm. Cai and Vijh (2007) find evidence that CEOs with illiquid holdings are more likely to receive takeover bids and less likely to resist bids. Even though there is no reason to expect CEOs’ illiquidity problems to increase abruptly at age 65, illiquidity can explain why CEOs who are ready to retire might prefer an acquisition to a CEO succession.

To test whether the retirement-age effect on mergers is stronger for CEOs with larger equity holdings, we use two measures of CEO illiquidity: the natural logarithm of the dollar value of CEO stock holdings (Holdings ), and the fraction of company stock owned by the CEO (Holdings %). In columns 7 and 8 of Table VIII, we regress the probability of receiving a successful takeover bid on CEO age, the usual controls, and the interaction between the retirement-age indicator and the two illiquidity measures. Both interaction effects are negative and one is significant (t = –1.18 for Holdings % and t = –1.95 for Holdings $), indicating that the retirement-age effect is, if anything, weaker for CEOs with larger holdings. This is inconsistent with illiquidity concerns causing the retirement-age effect. It might, however, be consistent with larger equity holdings improving merger decisions by aligning CEOs’ incentives with shareholders’ (in line with the governance results in Table IV).

D. CEO Wealth Changes

A CEO's willingness to sell his firm might increase as he gets closer to retirement simply because his financial losses from selling become smaller, or even turn into gains. In this section, we explore whether changes in the monetary benefits of selling the firm might be responsible for the increased takeover activity at retirement age.

To estimate the effect of being acquired on target CEO wealth, we follow Cotter and Zenner (1994) and compute the change in wealth as the gain from stock and option ownership plus the value of golden parachutes minus the present value of lost future compensation. Because the necessary information on CEO compensation and stock and option holdings is not available for our sample, their values are imputed using ExecuComp data. The revaluation of equity holdings due to an acquisition is calculated assuming a takeover premium of 35% for all observations, which corresponds to the median premium in our sample. The Internet Appendix describes the details of the calculations and reports descriptive statistics for the estimated wealth effects.

The regressions, also reported in the Internet Appendix, estimate the probability of receiving a successful takeover bid as a function of CEO age and the usual controls, and include the estimated wealth effects as an additional control variable. Controlling for the predicted change in target CEO wealth has no significant impact on the retirement-age effect. The coefficients on the retirement-age indicator remain large and statistically significant, with t-statistics between 2.88 and 3.30. The marginal effects of the retirement-age dummy imply increases of 28% to 36% in the odds of receiving a successful takeover bid for retirement-age CEOs.

These results suggest that retirement-age CEOs’ greater willingness to sell is not explained by their smaller monetary losses (or larger gains) from acquisitions alone. Instead, it seems likely that the retirement-age effect is caused by nonmonetary benefits of control and status that CEOs are unwilling to give up prior to their planned retirement. This type of behavior would also be consistent with the apparent preference shift underlying the spike in retirements at age 65 for rank-and-file employees (see Section 'CEOs’ Private Merger Costs and the Age-65 Effect'.B).

E. Do the Additional Deals Accepted by Retirement-Age CEOs Create Value?

The evidence in this paper supports the idea that retirement-age CEOs have lower personal merger costs, be they monetary or nonmonetary, and therefore their interests are better aligned with those of shareholders. However, an alternative interpretation is that it is the younger CEOs who act in the best interest of shareholders, and that retirement-age CEOs are too eager to give up control.

The balance of evidence from prior studies, as well as the results in this paper, speak against this alternative explanation. More power of target managers vis-à-vis shareholders, due to larger equity stakes, insider-dominated boards, poison pills, or a lack of outside blockholders, is associated with fewer acquisitions (Mikkelson and Partch (1989), Shivdasani (1993), Song and Walkling (1993), North (2001)). This suggests that target managers are on average more reluctant than shareholders to sell their firms. Consistent with this conjecture, Section 'Retirement Age and Takeovers'.B shows that better governance is associated with more takeovers of firms led by young CEOs, and with a smaller increase in bids when CEOs reach retirement age. Moreover, the additional deals pursued by retirement-age CEOs earn premiums that are at least as high as those pursued by younger CEOs. These results suggest that young CEOs reject deals that create value for shareholders, and that the additional deals by retirement-age CEOs are in shareholders’ interest.

A. Sample and Data

We combine our CEO panel with data on takeover defenses compiled by Investor Responsibility Research Center (IRRC). This data set, described in detail in Gompers, Ishii, and Metrick (2003), contains information on 24 governance provisions that, to varying degrees, make it more difficult to take over a firm. The data are available for eight cross-sections of large U.S. firms from 1990 to 2006.26 Gompers, Ishii, and Metrick (2003) summarize information from all 24 provisions by combining them into a single governance index (G-index). The index increases by one for every provision that increases takeover defenses or decreases shareholder rights.27 Bebchuk, Cohen, and Ferrell (2009) propose a modified entrenchment index (E-index) using 6 out of the 24 provisions that, based on their evidence, are the more powerful deterrents. These provisions are poison pills, classified boards, golden parachutes, supermajority requirements, limits to amend corporate bylaws, and limits to amend corporate charters. Combining the IRRC data with the CEO panel yields a sample of 8,963 firm-years with available levels and 6,822 firm-years with available changes for the IRRC indicators. The changes are computed relative to the most recent year in which data are available. Details on the sample construction and descriptive statistics are in the Internet Appendix.

B. Regression Specifications

Table IX relates changes in the E-index to CEO age. The regressions are estimated using an ordered logit model with the dependent variable equal to one, zero, or minus one for an increase, no change, or decrease in the index, respectively. The key explanatory variable is the retirement-age indicator for CEOs aged 64 to 66. Other CEO and firm characteristics serve as control variables and are described in the table.

Takeover defenses might be adopted to deter both current and future takeover attempts. Thus, a CEO who is not yet retiring but is planning to do so soon might see little reason to boost takeover defenses. To capture the forward-looking nature of defense adoptions, Table IX regresses changes in takeover defenses in both year t–1 and t on CEO age in year t.28

The first two regressions in Table IX use the full CEO-IRRC panel. The other regressions limit the sample to firms that are more likely to be takeover targets, and thus to have a reason to adopt defenses. One simple way to do so is to focus on firms that have already been targeted, either recently or in the more distant past. In columns 3 and 4, the sample includes all firms for which we observe a bid for any amount of equity (completed or not) during the four years from the current year t to t–3. In columns 5 and 6, the sample includes all firms with a bid during years t–3 to t–6. Using bids from the more distant past mitigates the concern that they are affected by current changes to takeover defenses. The results are not sensitive to how we define targeted firms.

C. Regression Results

The relation between the retirement-age indicator and takeover defense adoptions is negative in all regressions in Table IX and statistically significant when the sample is limited to more likely takeover targets. When targeted firms are identified using contemporaneous and recent bids (columns 3 and 4), the coefficients on RET_AGE are –0.69 and the t-statistics are –2.36 (in the regression with age group indicators) or –2.46 (in the regression with age and age squared). Based on column 3, the implied probability of an increase in takeover defenses is 10% for retirement-age CEOs and 18% for other CEOs (estimated at the mean of the control variables). The effects are similar when targeted firms are identified using bids from several years ago (columns 5 and 6).

In the Internet Appendix we analyze each provision of the E-index separately and also examine the broader G-index (only regressions with firms targeted several years ago are reported). The coefficients on retirement age are negative for all components of the E-index but in most cases are not statistically significant. Retirement age is also negatively but insignificantly related to changes in the G-index, consistent with the E-index containing the more powerful defense provisions. The Internet Appendix further shows that the negative association between defense adoptions and retirement age is stronger for adoptions in year t–1 than for adoptions in year t (with age measured in year t), and that the contemporaneous relation between retirement age and adoptions is stronger when retirement age is defined as 63 to 65 rather than 64 to 66. These results suggest a decline in the incentives to adopt takeover defenses that occurs one to two years before CEOs reach age 65.

Overall, the results in this section provide further support for a retirement-age effect in acquisitions: firms appear less likely to increase takeover defenses when their CEOs are close to retirement age. If these provisions are used, at least in part, to deter bidders, this pattern suggests that the deterrence motive is weaker for retirement-age CEOs.

A. CEO Data from Fee, Hadlock, and Pierce (2013)

Fee, Hadlock, and Pierce (2013) construct a comprehensive panel of CEOs of U.S. public firms using information from the Compustat Research Insight CDs. These discs include data on each firm's top four executives taken from the firms’ U.S. Securities and Exchange Commission (SEC) filings. Fee et al. use discs from the summer of each year from 1990 to 2007. The sample excludes financial firms (SIC codes 6000–6999), utilities (SIC codes 4900–4949), and non-U.S. firms. The sample further excludes firms with less than $10 million in book value of assets (measured in 1990 dollars). Firms that cross the $10 million threshold are included in the sample until one year after they no longer meet the threshold. Fee et al. define a CEO as the executive holding the title of CEO or the dual titles of Chairman and President. When a firm drops from the files and later reappears with the CEO unchanged, they assume that no CEO turnover occurred during the omitted period. CEO changes are cross-checked manually using information from the firms’ financial statements and Factiva searches.

B. Board and Ownership Data from Linck, Netter, and Yang (2008)

The Linck, Netter, and Yang (2008) data are extracted from the Disclosure database and cover the 1991–2004 period. The database, currently offered by Thompson Research, contains SEC filings, insider trading filings, bankruptcy filings, and other documents for U.S. public companies. Linck et al. limit their data collection to firms covered by Disclosure that can be merged to Compustat and CRSP and that have data on board size and composition for more than two years. In addition, firms with fewer than three board members, financial firms, and utility companies are excluded. Data extracted from the proxy filings on Disclosure by Linck et al. include information on director ownership, block ownership, CEO ownership, and board characteristics. Director ownership is computed as the average percentage of shares held by nonexecutive directors. Block ownership is the percentage of shares owned by 5% blockholders. The board characteristics include board size (the number of directors on the board), insider representation (the proportion of executive directors on the board), and whether the CEO is also Chairman of the Board.