FIRST YEAR IN OFFICE:

HOW DO NEW CEOS CREATE VALUE?

Yihui Pan David Eccles School of Business

University of Utah

Tracy Yue Wang

Carlson School of Management University of Minnesota

This version: April 2012 Key words: CEO turnover, post-turnover performance, external appointment, internal promotion, insider CEO, outsider CEO, forced turnover, managerial capital, physical capital JEL classification: G32, G34, M12, M51 * Yihui Pan: yihui.pan@business.utah.edu, (801) 578-9672. Tracy Wang: wangx684@umn.edu, (612) 624-5869. We thank Philip Bond, Rachael Hayes, Scott Schaefer, Michael Weisbach, Andrew Winton, and the seminar participants at University of Minnesota and University of Utah for helpful comments.

FIRST YEAR IN OFFICE:

HOW DO NEW CEOS CREATE VALUE?

Abstract

This paper examines firm value creation associated with CEO turnover. The literature has

focused on the heterogeneity in CEOs. We instead focus on the heterogeneity in post-turnover

firm strategies, which are significant changes in senior management and operations. We show

that the variation in strategy choices has significant explanatory power for the variation in post-

turnover performance. Examining strategies also advances our understanding of the relationship

between CEO types and firm performance, and the effect of strategy tends to subsume the effect

of CEO type. Within a firm, the value impact of personnel and operational shakeups is much

stronger in turnover years than in non-turnover years. This result is not driven by the prior firm

conditions that lead to the change of CEO, and is consistent with the agency view that CEO

turnover is part of an error correction process in a corporation. In the cross section, firms that

implement post-turnover shakeups outperform those that do not. One explanation supported by

the data is that not all firms that choose not to shake up behave optimally due to some agency

frictions. Overall, examining post-turnover strategy choices generates valuable new insights

because strategies reflect the impact of not only the new CEO but also the institutional

environment (e.g., agency frictions) that the new CEO operates in, both of which are relevant for

understanding value creation associated with CEO turnover.

1

1. INTRODUCTION

CEO turnovers are important events in a corporation because CEO, as the leader at the

very top of the corporate ladder, is one of the critical elements in corporate value creation. When

a new CEO is selected, the most important question is whether the new leader can create value

for shareholders. The corporate governance literature has extensively examined post-turnover

firm performance to assess the value creation associated with CEO turnover. Most existing

studies focus on the value impact of a small set of observable CEO or turnover attributes. For

example, a prominent finding in this literature is that the post-turnover firm performances are

significantly different between insider CEOs and outsider CEOs. 1 Differences in CEOs’

managing styles are also proposed as an explanation for differences in firm performance. 2

In this paper we try to understand shareholder value creation around CEO turnovers from

a different angle. Significant changes in personnel and operations tend to follow CEO turnovers

and are likely to be the channel of value creation post turnovers. Thus, instead of focusing on the

heterogeneity in CEOs, we focus on the heterogeneity in post-turnover firm strategies. That is,

we group firms based on the types of post-turnover strategies they implement rather than the

types of new CEOs they appoint, and try to understand how and why strategies affect post-

turnover firm performance. We show that the variation in strategies has significant explanatory

power for the variation in firm performance. Examining strategies can also advance our

understanding of the relationship between CEO types and firm performance, and the effect of

strategy tends to subsume the effect of CEO type. Our endeavors in understanding why strategies

matter for performance also generate valuable insights about how CEO turnover can create value

for shareholders.

However, there seems to be a big black box between a new CEO and the post-turnover firm

performance. Why CEO succession origin affects firm performance is still not well understood.

A large part of the heterogeneity in post-turnover firm performance still remains unexplained.

We define post-turnover strategies based on significant changes in two critical production

inputs in the firm during the very first year of the new CEO’s tenure: changes in managerial

capital and changes in physical capital. Specifically, we examine shakeups in the top

1 See, e.g., Huson, Malatesta, and Parrino 2004; Allgood and Farrell 2003; Parrino 1997; Bonnier and Bruner 1988. 2 Bertrand and Schoar (2003) find that managers’ managing styles (as reflected in manager fixed effects) matter for a wide range of corporate policies and firm performance. However, Fee, Hadlock, and Pierce (2011) find that manager fixed effects do not matter along these dimensions.

2

management team, operational downsizing, operational expansion, and changing operational

focus. To assess the value impact of a post-turnover strategy, we use both the change and the

level of industry-adjusted firm stock and accounting performances.

We find that the intensity of the top management shakeup right after CEO turnover

strongly and positively predicts firm performance in the three years following a CEO turnover.

On the operations side, downsizing operations has a positive value impact, while expansion and

changing focus have negative but insignificant value impact. Management shakeup and

operational downsizing are positively correlated, particularly following CEO turnover,

suggesting complementarities between these two strategies. Thus, it is not surprising to find that

implementing both strategies at the same time generates the strongest firm performance (in terms

of both the change and the level of performance) and this strategy substantially outperforms any

one-sided shakeup or no shakeup at all. All these results are robust to controlling for pre-turnover

firm conditions. Overall, different post-turnover strategy choices have significant explanatory

power for the variation in post-turnover firm performance.

Next, we use post-turnover strategy choices to explain the well-documented CEO

succession origin effect. We first examine whether outsider CEOs and insider CEOs tend to

choose different strategies. We find that a key difference between outsider and insider CEOs lies

in their differential propensities to shake up the top management team. The probability of

choosing a strategy that involves changing the top management is more than 10 percentage

points higher for outsider CEOs. On the operations side, an outsider CEO is more likely than an

insider CEO to downsize operations, but no more likely to expand operations or to change focus.

More interestingly, we find that conditioning on the strategy choice, outsider CEOs do not

outperform insider CEOs any more. Thus, it is the difference in strategy choices, not the CEO

type per se, that drives the difference in performance between outsider and insider CEOs.

After establishing the importance of post-turnover strategy in explaining post-turnover

firm performance, the next natural task is to understand why strategies matter for performance.

To isolate the value impact of strategy associated with CEO turnover, we compare and contrast

the value impact in turnover years and in non-turnover years. We find that for the same firm the

positive value impact of management shakeup and downsizing is much stronger and less

sensitive to prior firm performance in turnover years than in non-turnover years. The value

impact of these strategies also holds following both forced turnovers and relatively exogenous

3

turnovers related to death or retirement. These results suggest that management shakeup and

downsizing can be particularly valuable following CEO turnover, and this is not driven by the

prior firm conditions that lead to the change of CEO. Moreover, the within-firm variation shows

that just having a new CEO is not sufficient to create value. It is the combination of a new CEO

along with changes in managerial and operational capital that matters for performance.

The existing literature offers two types of explanations for these results. The first one is

the agency view. Boot (1992) theorizes that an unskilled manager is reluctant to divest because a

divestiture is essentially an admission of mistake or low ability. Therefore, on average there is

too little divestiture relative to the shareholders’ optimum. Boot further argues that takeovers can

create value by ousting the unskilled manager and enforcing optimal divestiture. Consistent with

Boot’s implications, Weisbach (1995) finds that the probability of divesting poorly-performing

assets increases dramatically following CEO turnover, including even retirement-related

turnovers. Both Boot (1992) and Weisbach (1995) imply that CEO turnover can create value

because it is part of the error correction process in a corporation. It often takes a new CEO to

reverse the bad decisions of the previous management. Under the agency view, post-turnover

shakeups in personnel and operations can create value because they are the actions of error

correction. The second explanation is the complementarities view. Complementarities (or good

match) between a new CEO and the firm’s managerial capital and physical capital are valuable.

Changes may be needed to establish these complementarities after a new CEO takes office (e.g.,

Hayes et al., 2005, Sheng 2009), and such changes can create value. Both explanations imply

that the firm’s need for change following CEO turnover may not be fully summarize in the pre-

turnover firm performance, which can explain why the positive value impact of shakeup holds

even when the firm performs well before the turnover.

Although there are good reasons to believe that management shakeup and downsizing can

be value-enhancing following CEO turnover, they do not necessarily imply that firms that choose

not to implement these changes would underperform those that do. This is because in a perfect

world in which all firms optimally choose strategies to maximize firm value, strategies cannot

explain performance. Different firms may select different strategies, but no strategies are better

than others. The fact that strategies matter for performance in the cross section leads to two

possible interpretations. The first interpretation is frictions. In the real world, at least some firms

that choose not to shake up behave suboptimally due to frictions. The second interpretation is

4

endogeneity. Firms optimally choose not to shake up based on some omitted condition, which

also drives the subsequent underperformance.

Under the friction-based interpretation, we hypothesize that agency-based frictions may

prevent some new CEOs from implementing value-enhancing changes. In particular, we examine

two frictions: the entrenchment of the old management team and the shadow influence of the

powerful old CEO. Old management entrenchment can directly influence the intensity of

management shakeup after a CEO turnover, which contributes to a key difference between

insider and outsider CEOs. Indeed, we find that incumbent managers that are entrenched due to

their long-time connections with the new CEO at work or their deep roots in the firm (as

reflected in their long tenure and board seats) are less likely to be shaken up after a CEO

turnover. The shadow influence of a powerful predecessor also makes personnel and operational

shakeups less likely to happen. The negative effect seems to concentrate on strategies related to

reversing the decisions made by the powerful predecessor (e.g., downsizing).

We find that outsider CEOs can effectively circumvent some of these frictions, which

offers an explanation for their higher shakeup propensities relative to insider CEOs. However,

even an outsider CEO can find it difficult to shake up entrenched managers who sit on the board

or to downsize operations when the predecessor is the founder of the company or stays as the

Chairman of the Board. The significant relationship between strategy choices and agency-related

frictions suggests that the strategy choice may not reflect the optimal response of the firm to

changes in economic or managerial labor market conditions. If part of the firms that choose not

to shake up behave suboptimally due to frictions, then on average firms that do not shake up will

underperform those that do.

Under the endogeneity-based interpretation, firms that choose not to shake up are

optimally responding to some omitted condition, and it is such omitted condition that causes the

poor subsequent performance. One candidate for the omitted condition is the firm’s need for

shakeup at the time of CEO turnover. The need for shakeup can arise for various reasons,

including the need to improve performance, to correct past errors, and to establish

complementarities with the new CEO. If such need does not exist, then the optimal strategy

should be no shakeup. However, it is hard to argue that no need for shakeup causes subsequent

underperformance. Another possible omitted condition is corporate governance. Poorly governed

firms choose not to shake up, and poor governance leads to future poor performance. However,

5

our analysis suggests that poor governance is more likely to prevent optimal shakeup from

happening (the friction interpretation) than to imply that it is optimal for these firms not to shake

up. Controlling for governance also does not explain away the value impact of strategy.

Our study contributes to the corporate governance literature in the following ways. This

is the first paper that systematically examines the role of post-turnover firm strategies in

explaining post-turnover firm performance.3

The rest of the article is structured as follows. Section 2 describes our empirical

specification. Section 3 discusses the value impact of various post-turnover strategies. Section 4

uses strategy choices to understand the performance difference between outsider CEOs and

insider CEOs. Sections 5 and 6 examine why strategies matter for performance from different

angles. Section 7 concludes.

We show that examining the heterogeneity in firm

strategies can shed new light on value creation associated with CEO turnover beyond studies that

focus on the heterogeneity in CEOs. Post-turnover strategy choices reflect the impact of not only

the new CEO but also the institutional environment that the new CEO operates in, both of which

are relevant for understanding value creation associated with CEO turnover. Not only who the

new CEO is matters, other parties such as the incumbent executives and the departing CEOs and

other aspects of the institutional environment such as corporate culture also play a crucial role in

explaining what the firm should do (optimal strategy), what it actually does (observed strategy),

and how well it performs following CEO turnover. Thus, our emphasis on post-turnover

strategies is a nice new addition to the literature that has focused on CEO selection and optimal

contracting. Our findings also suggest that CEO selection, CEO compensation and other

contracts should be designed to mitigate the effects of frictions and ensure that the optimal post-

turnover strategy is implemented.

2. EMPIRICAL SPECIFICATION

In this section we describe the key elements in our empirical analysis: the CEO turnover

sample, the measures for post-turnover firm strategies and performance, and the control variables. 3 Two existing studies also to some extent examine post-turnover strategies. Weisbach (1995) examines corporate divestiture following CEO turnovers. Although that paper does not link divestiture to firm performance, the findings do have implications for the source of value creation associated with CEO turnover, as we have discussed earlier. Denis and Denis (1995) find that forced management turnovers tend to be preceded by large declines in operating performance and followed by large improvements in performance. The authors also find that these firms significantly downsize their operations following the management changes. However, the focus of that paper is on the effectiveness of internal monitoring mechanisms.

6

2.1 CEO Turnover Events

We start with 24,780 firm-year observations from 1992 to 2007 that have identifiable

CEOs based on the information in the ExecuComp database. We use the information on job title,

the year becoming CEO, and CEO annual flag provided in ExecuComp to identify CEOs at the

firm-year level. Then for each firm, we compare the designated CEO in each fiscal year with the

CEO in the previous year to identify whether there is a CEO turnover in that year. We exclude

turnover events involving turnaround specialists and interim CEOs (with tenure shorter than 3

years) because we wish to focus on CEOs with long-term plans rather than transitory CEOs.

We differentiate CEOs based on succession origins. Using information on the time of a

CEO “joining company” from ExecuComp and “starting job” from Boardex, we classify CEOs

that are hired from outside the firm as outsiders. A new CEO who joins the company within 2

years before becoming the CEO is also considered an outsider. CEOs who have been employed

by the firm for at least two years before becoming CEOs are classified as insiders.

In the end we identify 2,221 CEO turnover events from 1992 to 2007, among which 659

new CEOs (or 30% of new CEOs) are considered as outsider CEOs.4

We also categorize turnover events based on the cause. We define an indicator variable

“Death & Retirement Related Turnover”, which equals 1 if the CEO turnover event is related to

exogenous reasons such as death or retirement. We classify a turnover to be death- or retirement-

related if the reason for leaving office in ExecuComp is “death” or “retirement”. We also classify

a turnover to be retirement-related if the outgoing CEO is older than 65. We identify forced

turnovers based on the turnover data in Jenter and Kanaan (2011), which includes 1,607 CEO

turnovers from 1993-2001 among which 383 turnovers are classified as forced turnovers. Our

Summary statistics for the

turnover events by Fama-French 10-industry classification and by year are listed in Table 1 Panel

A. Industries such as manufacturing, high-tech, and retails have more turnover events. The high-

tech industry and the healthcare industry are most likely to appoint CEOs from outside the

company. The energy industry is most likely to have internal successions. Over time, the number

of CEO turnovers seems pro-cyclical, peaking during 1999 and 2000.

4 There are 7 cases for which we are unable to tract career paths of the new CEOs and are thus not able to identify their insider/outsider status. Our outsider CEO number is consistent with the findings in other studies. For example, Cremers and Grinstein (2010) find that 30% of newly hired CEOs in their sample are from outside the company. Murphy and Zabojnik (2007) find the percentage of outsider CEOs to be 32.7% during the 2000–2005 period.

7

sample during the same time period includes fewer CEO turnovers because we exclude turnovers

related to turnaround specialists and interim CEOs. Thus our sample includes 1,049 total CEO

turnovers and 167 forced turnovers in Jenter and Kanaan’s data. The summary statistics are

reported in Table 1, Panel B.

2.2 Post-Turnover Strategies

We define post-turnover firm strategies based on two types of changes following a CEO

turnover: shaking up top executive team and changing the operations. These strategies are related

to the reallocation of two important production factors – managerial capital and physical capital.

We believe that any significant policy changes after a CEO turnover should be reflected in the

changes in these production factors. The reason to focus on a new CEO’s first year in office is

twofold. First, if changes are necessary, then we expect changes to happen soon after the new

CEO takes office. This crucial first year establishes the chief’s agenda for the company and,

ultimately, his (her) legacy. For similar reasons, the first year in office is commonly used to

assess a new leader’s vision and strength. Second, the first year in office provides a fixed time

frame for us to compare strategies across new CEOs.

2.2.1 Management Shakeup

The top management team plays an important role in the firm. Top executives serves as

the bridge between the CEO and the firm’s operations because they have direct contact with both

the CEO and the capital and labor used in the production. Therefore, establishing an effective

new bridge in a timely fashion should be one of the most important tasks for a new CEO.

To capture management team shakeup, we define the top management team as the top

four most highly paid non-CEO executives in a company. For each company-year, we rank

executives based on their total annual compensation (“tdc1” in ExecuComp) and identify the top

four non-CEO executives. Company-year observations that report annual compensation for

fewer than four non-CEO executives are dropped. Using a fixed size for the top management

team facilitates comparisons across firms.

We identify management shakeups by comparing the identities of top four executives

across years. An executive is considered “shaken up” in year t if this executive is in Top-4 in

year t-1 but not in year t or in any year after t during the time-t CEO’s tenure. We exclude

8

executive shakeups that are related to retirement or death. That is, if a shakeup is related to an

executive who is retired or older than 65 or deceased based on the information in ExecuComp,

then we do not count it as a management shakeup event. Then we calculate the fraction of year t-

1 Top-4 executives that are not in Top-4 at year t for non death or retirement related reasons, and

call it “Management Shakeup” at year t. Thus this variable can take values of 0, 0.25, 0.5, 0.75,

and 1, and it measures the intensity of the management shakeup in a given year.

According to our definition, a management shakeup is not necessarily a management

turnover. We do not require an executive to leave the company for it to be counted as a

management shakeup event. However, departure does seem to be the most likely outcome for

shaken-up executives as identified by our approach. Among the 18,303 management shakeup

events in our sample, we have information on the time the executive leaves the company

(“leftco” in ExecuComp) in 4,846 events. 5

Table 1 Panel C provides summary statistics of variables related to management shakeup

in CEO turnover years and in non-turnover years. The average management shakeup intensity is

0.182 in CEO turnover years, which is significantly higher than 0.147 in non-turnover years.

In these 4,846 events, 93% of the executives leave

the company in the year in which they are classified as shaken up.

6

2.2.2 Operational Shakeup

We examine three types of operational changes: downsizing, expansion, and changing

focus. “Downsizing” is an indicator variable that equals one if there is discontinuation/divestiture

of existing segments and divisions or if the company is reducing both operational expenditures

and employment. “Expansion” is an indicator variable that equals one if the company establishes

a new segment or acquires another company or enters a new industry. “Changing Focus” is an

indicator variable that equals one if the biggest segment or the most investment-intensive

segment of the company is changed. We find that firms that change focus often engage in both

downsizing and expansion at the same time. The existing literature has examined operational

changes that are related downsizing (e.g., Weisbach 1995, Denis and Denis 1995) around CEO

5 This variable is often missing in Execucomp. “Left company date” is missing for even 73% of the departing CEOs. 6 Besides changes in the personnel composition, the functional composition of the Top-4 management team is also more likely to be changed in a CEO turnover year. Unreported results show that among the four positions we examine, the status of a divisional head is most likely to change in a CEO turnover year (20%), followed by the status of CFO (18%). The probability of having a new CFO is also higher when the company has a new CEO.

9

turnovers. We believe that expansion and changing focus are also important operational

strategies, and including them provides a more complete picture of the operational shakeup.

For variables that are related to segment level changes, we use Compustat segment data

and define segments based on distinctive segment IDs. We only keep segments with positive

segment sales over the sample period. To identify discontinuation of operations, we use both the

segment data and the cash flow data from Compustat. If a distinct segment ID disappears in year

t and after, then we classify it as a discontinued/divested segment in year t. We also check

whether there is inflow/outflow of funds due to discontinuation of operations (item “DO” in

Compustat). To identify cost-cutting type of downsizing activities, we examine whether the

company has negative changes in both operating expenses and total employment. To identify

expansion, we examine whether a new segment ID appears in a given year and exists for at least

2 years, or whether there is an acquisition of full ownership of another company based on

information in SDC Platinum Database. To identify changing focus related activities, we

examine whether there is a change in the identity of the largest segment in the company by

segment sales or in the identity of the segment with the highest capital expenditure to sales ratio.

Table 1 Panel C shows that the probability of downsizing is significantly higher in CEO

turnover years (40%) than in non-turnover years (32.8%). A new CEO is also associated with a

higher likelihood of the company changing focus (28.5% vs. 24.4%). However, expansions are

less likely to happen in CEO turnover years than in non-turnover years.

One may argue that other corporate policies may substantially change as well around

CEO turnovers. The omitted policy changes may drive the post-turnover performance. However,

since the strategies we examine capture big directional changes, it is hard to come up with a clear

omitted policy change that can have a bigger performance impact. The existing literature has

examined corporate financial and investment policies such as leverage, capital expenditure ratio,

and R&D intensity (e.g., Bertrand and Schoar 2003; Fee, Hadlock and Pierce 2011). Fee,

Hadlock and Pierce (2011) find that there is no directional drift or abnormal variance in these

policies after a CEO turnover compared to various groups of matching firms. In addition, we

examine other financial policy changes such as net investment, net debt issues, net equity issues,

as well as the dividend payout ratio. In the last part in Table 1 Panel C, we compare the changes

in these policies in turnover years and in non-turnover years. Except for a larger decrease in

capital expenditures in turnover years than in non-turnover years, which is consistent with the

10

summary statistics on downsizing, we do not find any significant difference in other policy

changes between these two samples. Therefore, changes in these other policies are unlikely to

explain the changes in post-turnover firm performance.

Since we use annual fiscal year end information from ExecuComp and Compustat to

identify management shakeups and operational shakeups, another potential issue is whether the

shakeup intensity depends on when the new CEO takes office during the fiscal year. CEOs who

take office in the first fiscal quarter will have more time to make changes than CEOs who take

office in the last fiscal quarter. In our sample, 34% of the new CEOs take office in the first fiscal

quarter, 28% in the second quarter, 18% in the third, and 20% in the fourth quarter. Table 1

Panel D reports the average levels of management shakeup and operational shakeup conditional

on the fiscal quarter in which the new CEOs take office. We find that the intensity of shakeup

does not vary much with the timing of the new CEO taking office during a year. For example,

the management shakeup intensity is 0.173 for CEOs taking office in the first fiscal quarter, and

is 0.187 for those taking office in the last fiscal quarter. This result suggests that changes do

happen very quickly after a new CEO takes charge.

2.3 Post-Turnover Firm Performance and Controls

To assess the post-turnover firm performance, we examine both the change and the level

of industry-adjusted firm stock and accounting performance. The main performance variable is

the post-turnover change in industry-adjusted stock return or ROA. Let the turnover year be year

0. The post-turnover change in industry-adjusted stock return or ROA is the difference between

the average firm performance in the first three years (years 0, 1, 2) from the firm performance

before the turnover (year -1). Using the average performance in the first three years helps to

show a relatively long-term impact of CEOs’ strategies, and it also helps to mitigate the concern

that the new CEO window-dresses the short-term performance after taking office.

For each year in the event window [-1, 2], we compute the industry-adjusted stock return

and ROA. The industry adjustment is done using the value-weighted industry median stock

return in a year. Then “∆(Ind. Adj. Return) [0,2] vs. [-1]” is defined as the difference between

the average industry-adjusted stock return from year 0 to year 2 and the industry-adjusted stock

return in year -1. “∆(Ind. Adj. ROA) [1,2] vs. [-1]” is constructed in a similar fashion, except that

we do not include year 0 performance in this measure. This is because accounting information is

11

backward looking, and thus we do not expect accounting performance to be as responsive as

stock performance in incorporating new information. ROA is defined as earnings before interest,

tax, and depreciation scaled by the beginning of fiscal year total book assets. For robustness, we

also construct “∆(Ind. Adj. Return) [1,2] vs. [-1]”, which compare the average industry-adjusted

stock performance in years 1 and 2 with that in year -1.

Focusing on the change in industry-adjusted performance allows us to better isolate the

impact of new CEOs’ strategies because first differencing removes firm fixed effects in

performances and industry adjustment removes any potential industry trend. But for robustness,

we also use the levels of industry-adjusted performances in some tests. The summary statistics

for the performance variables are reported in Table 1 Panel E. The average change in industry-

adjusted returns around CEO turnovers is positive, but the average change in industry-adjusted

ROA is close to zero.

The common control variables we use in most regressions include the lagged change or

level of industry-adjusted firm performance, lagged investment intensity “Capx/Sales” (capital

expenditures scaled by sales), lagged market to book ratio of equity, lagged firm size measured

by the logarithm of book assets, 2-digit SIC industry fixed effects, and turnover year fixed

effects. We include the lagged change or level of industry-adjusted firm performance to control

for the existence of any trend in firm performance around CEO turnover years. The summary

statistics of the control variables are reported in Table 1 Panel F.

3. POST-TURNOVER STRATEGY AND FIRM PERFORMANCE

3.1 Value Impact of Strategies

Table 2 presents results for the performance effects of changing managerial and

operational capital in the CEO turnover sample. The dependent variable is the change in

industry-adjusted stock return in model (1) and the change in industry-adjusted ROA in model

(2). Model (1) shows that management shakeup in a turnover year is associated with significant

improvement in the firm’s stock performance after CEO turnover. The coefficient estimate for

Management Shakeup is 0.26, which means that a one standard deviation increase in

Management Shakeup is associated with a 6 percentage point increase in industry-adjusted

annual stock return from the level before turnover. Model (2) shows that management shakeup

12

also has a positive effect on the firm’s accounting performance, although the effect is smaller

than that on the stock performance.7

On the operations side, we find that downsizing is positively and significant related to

post-turnover firm performance. Firms that downsize operations immediately after the new

CEOs take office outperform those that do not by 9.9% in the industry-adjusted stock

performance and 1.6% in the industry-adjusted accounting performance. This result is consistent

with the finding in Weisbach (1995) that the new CEO is likely to divest poorly-performing

assets acquired by the previous CEO. We show that such reversal is value enhancing.

Other operational changes, although all reflect substantial changes in operations, have no

consistently significant value impact. Expansion appears to reduce stock performance post

turnovers, but has no significant impact on accounting performance. Changing focus in general

does not significantly affect firm performance. This suggests that not all post-turnover

operational shakeups are necessarily value-enhancing. Since this paper aims to identify the

channel of value creation after CEO turnovers, in the rest of the analysis we focus on the value-

increasing operational change–downsizing.

In model (3), we use the alternative performance measure, the level of industry-adjusted

return in year 1, as the dependent variable. Controlling for lagged performance (level), the

positive value impact of management shakeup and downsizing remains strong. Thus, these

changes in personnel and operations are associated with not only larger improvement in

performance but also higher level of performance post turnover.

Since our operational shakeup measure is constructed mainly using segment data, a

reasonable concern is that by construction there will be less operational shakeup in single-

segment firms, which may cause underestimation of the performance effect of operational

shakeup. As a robustness check, we perform subsample analysis using only multi-segment firms,

and also add the number of segments as an additional control. Results are similar to those

obtained in the full sample.

In summary, our results suggest that shaking up top management team and downsizing

operations in the new CEO’s first year in office are value enhancing.

7 In untabulated robustness tests, we replace ∆(Ind. Adj. Return) [0,2] vs. [-1] with ∆(Ind. Adj. Return) [1,2] vs. [-1] and find that the effect of management shakeup is still positive and significant (0.257, p-value<0.001) and similar in magnitude as that reported in Table 2 Panel A. This suggests that the performance effect of management shakeup is unlikely to be driven by short-term window-dressing or announcement effects in the CEO turnover year.

13

3.2 Value Impact of Combined Strategy

A new CEO may choose to shake up the management team, or the operations, or both.

Complementarities between managerial capital and physical capital can stem from the bridging

effect of the top management team. The top executive team has close contacts with both the CEO

and the firm’s operations. The team helps the CEO manage the physical capital in the firm. Thus,

management shakeup may happen to facilitate operational shakeup, and operational changes may

happen as a result of management changes. If this is true, then we should observe a high

correlation or clustering of management shakeup and operational shakeup. In an unreported

univariate analysis, we find that the correlation between management shakeup and downsizing is

0.11 in non-turnover years, and it increases to 0.23 in turnover years. But the correlation between

management shakeup and expansion (-0.02) or changing focus (0.04) is low in both non-turnover

years and turnover years. The same pattern holds in a multivariate regression setting. In Table 3

Panel A, after controlling for firm prior conditions, we find that the intensity of management

shakeup is significantly and positively related to the intensity of downsizing in the CEO turnover

years, but not significantly related to the intensity of expansion or changing focus. These results

suggest that there exist complementarities between management shakeup and operational

downsizing.

Do such complementarities increase firm value? If the answer is yes, then we expect a

strategy combining the two types of shakeups to have a much stronger effect on firm

performance than does a one-sided shakeup. Thus we construct strategies based on four different

combinations of Management Shakeup and Downsizing in the new CEO’s first year in office.

The strategy (Mgmt. Shakeup=0 & Downsizing=0) means no value-increasing strategy is

implemented. We find that firms that implement this strategy are also less likely to engage in

other operational shakeups such as expansion and changing focus. Thus we also call this passive

strategy maintaining status quo. (Mgmt. Shakeup>0 & Downsizing=0) means there is

management shakeup but no downsizing. (Mgmt. Shakeup=0 & Downsizing>0) means there is

downsizing but no management shakeup. Finally, (Mgmt. Shakeup>0 & Downsizing>0) means

there are both management shakeup and operational downsizing.

Table 3 Panel B reports the frequency of each strategy in our sample. About 36% of the

new CEOs choose to maintain status quo based on our definition. About 24% of the new CEOs

14

choose to both shake up the management and downsize, another 24% choose to shake up

management only, and 16% choose to downsize only. Panel B also tabulates the average

industry-adjusted firm performance from year -1 to year 1 for each combined strategy. We find

that the strategy that involves both management shakeup and downsizing is associated with not

only the largest improvement in industry-adjusted stock performance from year -1 to year 1 (a 26

percentage-point increase), but also the strongest level of performance in year 1. One-sided

shakeups deliver very moderate or even no performance improvement. The strategy of

maintaining status quo is associated with deterioration in performance.

In Table 3 Panel C we compare the performance effects of the three active strategies with

that of maintaining status quo in a multivariate regression framework. We use the post-turnover

performance change as the dependent variable in models (1) and (2), and the performance level

as the dependent variable in model (3). The coefficient estimate of a strategy indicator shows

whether a strategy is significantly better or worse in improving firm performance than is

maintaining status quo. We find that strategy 1 (involving both shaking up management and

downsizing) significantly and substantially outperforms the baseline strategy (maintaining status

quo) and the two strategies involving only one-sided shakeups, no matter whether we look at the

change in performance or the level of performance post turnover. Compared to maintaining

status quo, strategy 1 is related to a 20 percentage-point bigger increase in the industry-adjusted

stock return, a 2.4 percentage-point bigger increase in the industry-adjusted ROA, and an 11

percentage-point higher level of industry-adjusted return.

In unreported robustness tests, we include additional firm characteristics such as leverage,

cash holding, and corporate governance characteristics such as total institutional holdings, board

size, and the percentage of outside directors. Our results are robust to having these additional

controls. We also control for the firm fixed effects in models using the level of industry-adjusted

performance as the dependent variable, because the change in performance already differences

out the firm fixed effects in performance. Our results hold. Further, to address potential concerns

related to using lagged dependent variable as control and the short time dimension and large firm

dimension feature in the panel data, we re-estimate Table 3 Panel A using the Arellano–Bond

Dynamic Panel GMM Estimators. Our results are again robust.

4. STRATEGY AND EFFECT OF CEO SUCCESSION ORIGIN

15

So far, we show that the variation in post-turnover strategies can help explain the

variation in the post-turnover firm performance. A prominent finding in the literature is that

outsider CEOs tend to outperform insider CEOs. Studies have found that outsider CEOs are

associated with more positive market reaction at appointment (e.g., Borokhovich, Parrino and

Trapani 1996) and better post-turnover firm accounting performance (e.g., Parrino 1997; Huson,

Malatesta, and Parrino 2004). Other studies find an increasing trend of external CEO

appointments instead of internal promotions (e.g., Frydman 2005; Murphy and Zabojnik 2004

and 2007). These findings suggest that the market believes that an outsider CEO tends to create

more shareholder value than does an insider CEO. However, why and how outsider CEOs create

more value is not well understood.

In this section we examine whether post-turnover strategies can help us understand the

value effect of CEO succession origin. We examine whether outsider CEOs and insider CEOs

tend to choose different strategies (Section 4.1), and whether it is the difference in strategy

choices that generate the observed difference in post-turnover firm performances between these

two types of CEOs (Section 4.2).

4.1 Strategy Choice: External Appointment vs. Internal Promotion

We first examine whether outsider CEOs are more or less likely than insider CEOs to

shake up the top management team, to downsize operations, to expand operations, and to change

operational focus. Table 4, Panel A shows that outsider CEOs are significantly more likely to

shake up the top management team and to downsize operations in their first year in office.8

8 Results from OLS regressions are reported in the table. Untabulated results show that the results are robust to using ordered Logit and Probit models that account for the binary nature of the dependent variables related to operations.

However, they are no more likely to expand operations or to change operational focus relative to

insider CEOs. Note that we have excluded turnaround specialists (all outsiders) and interim

CEOs (usually insiders) from our CEO turnover sample. Thus our findings are not driven by the

behavior of these transitory chief executives. Interestingly, outsider CEOs are more likely to

engage in changes that we have shown to improve firm performance, but no more likely to

undertake changes that have little value impact. These results already offer some insights about

why outsider CEOs can deliver better post-turnover firm performance.

16

Next, we examine a new CEO’s strategy choice among the combined strategies between

management shakeup and downsizing. We estimate a multi-nomial logit regression of each

combined strategy on the new CEO type, controlling for past firm performance and other firm

characteristics as well as year and industry fixed effects. The baseline strategy in the multi-

nomial logit regression is no management shakeup and no downsizing, or maintaining status quo.

Then the coefficient estimate of the outsider CEO indicator variable associated with each non-

baseline strategy tells us whether outsider CEOs are more (positive coefficient estimate) or less

(negative coefficient estimate) likely than an insider CEO to choose that strategy over the

baseline strategy.

Results in Table 4, Panel B show that the coefficient estimates of Outsider CEO are

significantly positive for all non-baseline strategies, which imply that an outsider CEO is

significantly more likely than an insider to choose an active strategy instead of keeping status

quo. However, the estimated marginal effects of Outsider CEO suggest that the biggest

difference between outsider CEOs and insider CEOs relies in the probability of choosing

strategies 2 and 3, both of which involve management shakeup. Compared to insider CEOs,

outsider CEOs on average have a 10 to 12 percentage-point higher probability of choosing a

strategy that involves shaking up the top management team. In Table 4 we find that all three

strategies, strategy 3 in particular, outperform maintaining status quo. Thus, outsider CEOs’

higher propensity to choose these strategies could explain why they tend to outperform insider

CEOs. We will further examine this hypothesis in the next subsection.

4.2 Strategy or CEO Type?

So far we have established two sets of findings. Shaking up the management team and

downsizing operations soon after the arrival of a new CEO generate substantial improvement in

firm performance. An outsider CEO is significantly more likely to implement these changes than

is an insider CEO. Now we put these two sets of findings together. Is it the CEO type per se or

the strategy choice that drives the better post-turnover performance associated with outsider

CEOs? Conditional on the strategy choice, do outsider CEOs and insider CEOs generate similar

firm performance?

The result in Table 4, Panel B, model (1) replicates the well-known fact that outsiders on

average outperform insiders. The achievement of the outsider CEOs in our sample is pretty

remarkable. Outsider CEOs are on average associated with an 8.3 percentage-point larger

17

improvement in the firm’s post-turnover stock performance than are insider CEOs, which more

than doubles the average post-turnover performance improvement (3.5%).

In model (2) we control for the strategy choices and their interaction with the outsider

CEO indicator. The effects of strategies on performance are still strong and significant. But

interestingly, the strategy variables completely explain away the outsider CEO effect on firm

performance. After controlling for the strategy choice, the estimated coefficient of Outsider CEO

decreases to 0.022 and becomes statistically insignificant. Further, the interaction terms between

strategies and the succession origin are all insignificant. This implies that conditional on the

strategy choice, outsider CEOs deliver no significantly better performance than do insider CEOs.

In untabulated robustness tests, we also divide the full sample into four subsamples based on the

four combined strategies between management shakeup and downsizing. Thus in each subsample,

outsider CEOs and insider CEOs choose the same strategy, and we find that outsiders do not

outperform insiders.

The firm’s choice between an outsider CEO and an insider CEO is clearly not random.

Outsider CEOs may choose to make changes, or they are chosen (by the board) to make changes.

Who desires to make changes is not important in our study because we focus on the impact of

change. Our results suggest that it is the difference in strategy choices, not the CEO type per se,

that drives the difference in post-turnover firm performances between outsider and insider CEOs.

It may not be surprising that outsider CEOs are more likely to shake up the firm. However, this

does not make our finding trivial because we show that this is exactly how outsiders create value.

In section 6, we will examine an agency-based hypothesis for why outsider CEOs are associated

with more changes.

5. WHEN DO STRATEGIES MATTER FOR PERFORMANCE?

The previous sections show that post-turnover firm strategies have significant

explanatory power for post-turnover firm performance. In the following sections we try to

understand why strategies matter for performance. Why do firms that implement management

shakeup and operational downsizing have better post-turnover performance? In this section we

examine subsample variation in the value impact of management shakeup and operational

downsizing to understand why these changes are value enhancing for firms that implement them.

In the next section we address why there is a return to post-turnover shakeup in the cross section.

18

5.1 Turnover Years vs. Non-Turnover Years

The strategies that we examine can be implemented post CEO turnover or in any non-

turnover years. Thus we compare and contrast the value impact of strategy in turnover years and

non-turnover years to see whether there is anything special about CEO turnover. In Table 5 Panel

A, we use the entire panel data of our sample firms. The dependent variables are post-turnover

performance change in models (1) and (2) and performance level in model (3). The explanatory

variables include strategies, CEO turnover indicator, and the interaction terms between two. In

all models, we control for lagged performance (change or level), firm size, growth potential, and

investment. We also add firm fixed effect to focus on the within firm variation of value impact at

different points of time.

In Panel A the direct effect of a strategy reflects its value impact for a firm when there is

no CEO turnover. The interaction effect between a strategy and CEO turnover reflects the value

impact of the strategy when the firm has a new CEO. The results show that strategy 1 (combined

management shakeup and downsizing) has a positive and significant value impact in non-

turnover years as well. However, the interaction effect is also positive and significant and large

in magnitude, which suggests that the value impact of shakeup is much stronger in turnover years

than in non-turnover years. For example, in model (1) the estimated interaction effect is 0.118,

which means that implementing strategy 1 increases the firm’s industry-adjusted return by about

12 percentage points more in turnover years than in non-turnover years. The direct effect of CEO

turnover is close to zero and statistically insignificant. This means that after controlling for post-

turnover strategies, CEO turnover itself has no value impact. In other words, value is created not

just be the presence of a new CEO, but through the changes that the new CEO carries out.

The results in Table 5 Panel A suggest that shakeups are particularly valuable following

CEO turnovers. One possible explanation is that the timing of CEO turnover is endogenous. If

CEO turnovers tend to follow poor firm performance, then the poor prior performance implies

greater need for shakeup and also a larger return to shakeup. In Panel B we examine how much

the value impact of shakeup depends on the prior firm performance in both turnover years and

non-turnover years. We split the sample firms into two subsamples based on whether they

underperform or outperform their industry median peers in the year before the strategy is

implemented. Interestingly, we find that following CEO turnover the value impact of shakeup is

19

positive and significant in both the underperforming subsample (0.155) and outperforming

subsample (0.113), and the magnitudes are also not very different. This suggests that the value

impact of shakeup in turnover years is not sensitive to the prior firm performance. When the firm

has a new CEO, changes seem valuable even when the firm seems to do reasonably well. In

contrast, when there is no CEO turnover, shakeups are valuable only when the firm is not doing

well. Thus prior firm performance does not explain why shakeups are particularly valuable

following CEO turnover.9

Forced CEO turnovers are clearly endogenous because they generally follow very

disappointing firm performance and reflect strong desires of the board or shareholders to change

the course of the firm. CEO turnovers due to death or retirement are relatively exogenous. In

Table 5 Panel C we compare the value impact of strategy following forced turnovers and death-

and retirement-related turnovers. We find that shakeups are associated with better performance

following both types of turnovers, although intuitively the effect is stronger for the forced

turnovers. The fact that changes still add value following relatively exogenous CEO turnovers,

together with the results in Panel B, suggest that the large return to shakeup following CEO

turnover is not driven by the prior firm conditions that lead to the change of CEO.

5.2 Sources of Value Impact

Results in Table 5 suggest that management shakeup and downsizing can be particularly

value-enhancing following CEO turnover, regardless of the pre-turnover firm performance and

turnover reason. The existing literature offers two types of explanations for these results.

The first explanation is the agency view. Boot (1992) theorizes that a manager has private

information about his own ability to identify profitable projects, and he strategically manipulates

others’ perceptions of his ability. Thus, an unskilled manager is reluctant to divest because a

divestiture is essentially an admission of mistake or low ability. Boot’s theory implies that on

average there is too little divestiture relative to the shareholders’ optimum, giving rise to the

positive value impact of downsizing. Boot further argues that takeovers can create value by

ousting the unskilled manager and enforcing optimal divestiture. Consistent with Boot’s 9 In unreported robustness checks, we use the level of performance as the dependent variable and interact Management Shakeup and Downsizing with the pre-turnover level of performance. Results are similar to those reported in Table 5 Panel B. In the turnover sample the interaction terms have no significant effects, while the direct effects of these changes hold. In the non-turnover sample, the direct effects of strategies are positive but smaller, and the interaction effects are negative and significant.

20

implications, Weisbach (1995) finds that the probability of divesting poorly-performing assets

increases dramatically following CEO turnover, including even retirement-related turnovers.

Both Boot (1992) and Weisbach (1995) imply that CEO turnover can create value because it is

part of the error correction process in a corporation. It often takes a new CEO to reverse the bad

decisions of the previous management. The high correlation between management shakeup and

operational downsizing in turnover years suggests that changing the top management can also be

part of the error correction process. Under the agency view, post-turnover shakeups in personnel

and operations can create value because they are the actions of error correction. Such error

correction can create value, even if the firm does not appear to underperform.

The second explanation is the complementarities view. Complementarities (or good

match) between a new CEO and the firm’s managerial capital and physical capital are valuable.

Changes may be needed to establish these complementarities after a new CEO takes office, and

such changes can create value. The finance literature has examined the match between the CEO

and the firm’s physical capital. For example, Sheng (2009) find that CEOs in diversified

conglomerates are more likely to divest divisions that they are less experienced to manage, and

such match-improving divestitures generate better firm performance. The management literature

has emphasized the complementarities between the CEO and the immediate subordinates. For

example, Hayes et al. (2005) find evidence for the tenure-related complementarities between new

CEOs and their subordinates. Succession of a long-tenured manager as CEO has a larger effect

on turnover probability for a short-tenured executive than for a long-tenured executive.

In Table 6 we offer some simple facts about the existence of complementarities between

the CEO and the top management team. Panel A examines gender-related complementarities. In

the full ExecuComp database, only 5.5% of non-CEO executives are female. However, the

probability of having a female executive increases to 15.8% if the CEO is a female, and it

decreases to 5.4% if the CEO is a male. Similarly, in the CEO turnover years the probability of a

female executive being promoted to the Top-4 management team is 20.3% if the new CEO is a

female, but it is only 7.3% if the new CEO is a male. Thus it is very clear that a female CEO is

much more likely than a male CEO to promote female managers to important positions in the

company. When the new CEO is a female, management shakeup likely leads to more presence of

female executives in the top management team.

21

In Panel B we explore age-related complementarities between CEOs and their immediate

subordinates. In the CEO turnover sample, the average age of executives who are newly

promoted to Top-4 is 48 when the new CEO is relatively young (younger than 50), and is 50

when the new CEO is relatively old (50 or above). The difference in age cross these two groups

is not impressive but still statistically significant. Results are similar if we use different CEO age

cutoffs. Thus, younger CEOs are more likely to promote younger managers. When the new CEO

is young, management shakeup likely leads to more presence of younger executives in the top

management team. The age of the CEO has been related to risk attitude and innovativeness in the

existing literature (e.g., Bertrand and Schoar 2003; Graham, Harvey and Puri 2009; Ouimet and

Zarutskie 2011). Complementarities could arise from similarities in these attributes.

In Panel C, we present results for the employment-related complementarities. We find

that new outsider CEOs are more likely to promote top executives with short tenure in the

company just like himself (herself), and they are substantially more likely than insider CEOs to

hire top executives from outside the company. These results are consistent with the findings in

Hayes et al. (2005). Given that outsider CEOs are likely to bring in fresh ideas and new

perspectives, new outsider executives may share similar perspectives.

Do these complementarities increase firm value? In Panel D we find some limited

evidence. While female new CEOs do not appear to be associated with value increase in general,

having more female executives on the management team is good for firm performance after a

new female CEO takes office. Appointing an outsider CEO is associated with improvement in

performance, which is a well-documented finding in the literature. However, following an

outsider CEO succession the firm does not seem to benefit from having more outsider executives

in the top management team. We also do not find any significant value impact from age-related

complementarities.

The results in Table 6 suggest that complementarities between a new CEO and the top

management team exist, and establishing them can lead to management shakeup following CEO

turnover. But they do not seem to have much power in explaining the positive value impact of

management shakeup. Admittedly, capturing the complementarities between the CEO and the

top management team in a comprehensive fashion is difficult, given the limited information

(usually only biographic) we observe on the composition of the management team.

22

In summary, both the agency view and the complementarities view imply that the need

for change and the value to change following CEO turnover can arise for various reasons,

including the need to correct past errors and to establish good CEO-firm match. The pre-turnover

firm performance may not fully summarize these needs for change, which explains why the

value impact of change is not very sensitive to pre-turnover firm performance.

6. VALUE IMPACT OF STRATEGY: FRICTIONS OR ENDOGENEITY?

The previous section suggests that there are good reasons to believe that post-turnover

shakeup can be value-enhancing. However, they do not necessarily imply that firms that choose

not to implement these changes would underperform those that do. This is because in a perfect

world in which all firms optimally choose strategies to maximize firm value, strategies cannot

explain performance in the cross section. Different firms may select different strategies, but no

strategies are better than others. Thus, the key is to understand the underperformance of firms

that choose not to shake up following CEO turnover. We explore two possible explanations. The

first one is based on frictions. In the real world, not all firms that choose not to shake up behave

optimally due to some frictions. The second explanation is based on endogeneity. Firms

optimally choose not to shake up based on some omitted condition, which also drives the

subsequent underperformance. We discuss each interpretation in detail.

6.1 The Effect of Frictions

Under the friction-based interpretation, we hypothesize that some agency-based frictions

may prevent some new CEOs from implementing value-enhancing changes. Suppose that we are

in the world of Boot (1992) and Weisbach (1995) in which the incumbent management may

make wrong decisions and may also hesitate to admit and correct the mistakes. This creates the

need for shakeup when the new CEO comes in. At the time of the CEO turnover we can have

three types of firms. The G-firms are not subject to the error correction issue because the

incumbent management either have not made mistakes or have corrected them in a timely

fashion. Thus the G-firms do not need to shake up, optimally choose not to shake up, and

continue to perform well. The B-firms are subject to the need for error correction. However,

some of them will shake up and correct errors when the new CEOs come in (BS-firms) and

experience improvement in performance, and others do not (BN-firms) because of frictions and

23

continue to perform poorly. This simple framework has two main implications. First, the

difference between BS-firms and BN-firms imply that on average the existence of frictions is

associated with a lower likelihood of post-turnover shakeup. Second, on average firms that shake

up (BS-firms) will outperform those that do not (a mix of G-firms and BN-firms) post CEO

turnover. We already find empirical support for the second implication. In this section we test the

first implication.

While frictions due to corporate structure, corporate culture, and external managerial

labor market may all affect personnel and operational changes, in this paper we focus on two

measurable agency-related frictions: the entrenchment of the old management team and the

shadow influence from the outgoing CEO. We examine how these frictions affect the new

CEO’s propensity to shake up the old management team and the operations. We also examine

whether outsider CEOs can effectively circumvent these frictions.

6.1.1 Entrenched Old Management

Intuitively, it is difficult for a new CEO to shake up an entrenched old management team.

The incumbent managers can be entrenched due to their long time connection with the new CEO

at work. This type of entrenchment will clearly affect an insider CEO’s decision much more than

that of an outsider CEO, since by definition an outsider CEO should have little employment-

based connection with the incumbent management team. The entrenchment of the incumbent

managers can also be due to their power in the company. They may have worked in the company

for a long time and thus have deep roots. They may sit on the board of directors and thus

influence the selection and evaluation of the new CEO.

We construct three measures of old management entrenchment. “Avg. Tenure Overlap

[old mgt., new CEO]” is the average of the tenure overlap (in terms of years) at the time of

turnover between the new CEO and each of the old Top-4 executives (the team before turnover).

“Avg. Tenure [old mgt.]” is the average tenure duration of the old Top-4 executives one year

before turnover. “% On Board [old mgt.]” is the fraction of the old Top-4 executives sitting on

board one year before turnover. Table 1 Panel E reports the summary statistics of these variables.

Table 7 Panel A shows that more entrenched old management is indeed associated with

less management shakeup after CEO turnovers. Model (1) shows that the coefficient estimate of

Avg. Tenure Overlap [old mgt., new CEO] is negative and significant (-0.006, p-value<.001).

24

This implies that when a new CEO has a longer-time connection with the old top management

team at work, he or she implements less management shakeup after taking office. This result

holds even within the insider CEO subsample, as shown in model (2). Thus among the internally

promoted new CEOs, those with longer career overlap with the old management team tend to

shake up the management less. But the magnitude of the coefficient estimate in the insider CEO

sample is smaller than that in the full sample (0.002 vs. 0.006), suggesting that the explanatory

power of this friction for the intensity of management shakeup lies mainly in the difference

between outsider CEOs and insider CEOs.

Models (3) and (4) show that when the top management team on average has longer

tenure in the company and when more top managers sit on the board, the intensity of

management shakeup is lower after CEO turnovers. The top management’s directorship has a

particularly strong impact on the intensity of post-turnover management shakeup. If one of the

Top-4 executives sits on board rather than none (i.e., % on Board equals 25% rather than zero),

then the intensity of post-turnover management shakeup decreases by 5 percentage points (=–

0.196*25%). In untabulated analysis we find that an individual top executive’s directorship

reduces that executive’s probability of being shaken up by 17 percentage points in CEO turnover

years. These results are intuitive because top managers sitting on the board may directly

influence the selection of the new CEO. They are likely to nominate a new CEO who will be

friendly to them.

A natural question is that whether an outsider CEO can more effectively shake up

entrenched old management. In Table 7 Panel B we answer this question by adding the outsider

CEO indicator and its interaction with the management entrenchment proxies. We do not interact

Outsider CEO with Avg. Tenure Overlap [old mgt., new CEO] because by definition outsider

CEOs should have little tenure overlap with incumbent management. Panel B model (1) shows

that average tenure of the old management team has a much smaller effect on the management

shakeup intensity when the new CEO comes from outside the company (-0.004+0.003 = 0.001).

This implies that outsider CEOs are not reluctant to shake up managers who have been in the

company for a long time. In model (2), the direct effect of % on Board [old mgt.] is still negative

and significant. But its interaction with Outsider CEO has an insignificant effect on the intensity

of management shakeup. This implies that outsider CEOs are not significantly more likely than

insider CEOs to shake up executives who sit on the board. This suggests that sitting on the board

25

is an effective way for incumbent managers to entrench themselves, no matter whether the new

CEO comes from inside or outside the company.

One concern is that our measures of management entrenchment may also reflect some

value-enhancing elements in the management team. For example, a top executive who has a

long-time connection with the new CEO through employment may be entrenched, but may also

have established strong complementarities with the new CEO. Similarly, a top executive who sits

on the board or has a long employment history in the company may be entrenched, but may also

possess a lot of firm-specific expertise. Thus is the old management team entrenched at the cost

of shareholder value following CEO turnover? In Table 7 Panel C, we examine the relationship

between management entrenchment and the post-turnover change in firm performance. In

models (1)-(3), we find that all three measures of management entrenchment are negatively

related to the post-turnover firm performance. These results suggest that following CEO turnover

the entrenchment effect captured in these measures dominates any value-enhancing effect.

Further, results is models (4)-(6) show that once we control for strategy, agency frictions do not

impact performance anymore. Thus, management entrenchment does not affect performance

beyond their effect on strategy. The results are consistent with our findings that post-turnover

management shakeup is value-enhancing. Frictions that hinder such changes could destroy value.

6.1.2 Powerful Old CEO

Next, we examine the influence of a powerful old CEO on the strategy implemented after

the CEO turnover. A dominant and powerful old CEO may leave a legacy that is hard for the

newcomer to change. A powerful old CEO could be the founder of the company, or someone

who stays as the Chairman of the Board after stepping down as the chief executive, or one who

simply has served a long tenure in the company as the CEO. These types of old CEOs are more

likely to add their own marks on the fundamentals of the company such as the corporate mission,

the corporate culture, and the organizational structure. They are also more likely to overshadow

the decision making of the new CEO, particularly if the new CEO is an heir apparent, possibly

promoted by the old CEO, or if the new CEO has long career overlap with the old CEO. A

tighter connection between the new CEO and the old CEO implies that the new CEO is more

influenced by the old CEO and thus less likely to change the structure set up by the old CEO.

This was certainly the main concern of the visionary founder and CEO Steve Job before

26

his death. His dying wish for Apple was to avoid the same fate as the Walt Disney Company.

After the legendary leader Walt Disney passed away, the company became effectively

“paralyzed” because everyone in the company was so concerned with what Walt would do if he

were still alive that they failed to take chances. Steve Job warned the new internally promoted

CEO Time Cook not to be overshadowed by him.

We construct three variables to capture powerful old CEOs. “Tenure [old CEO]” is the

tenure duration of the outgoing CEO in the company. “Founder [old CEO]” is an indicator

variable that equals one if the outgoing CEO is the founder of the company. “Stay As Chairman

[old CEO]” is an indicator variable that equals one if the outgoing CEO serves as the Chairman

of the Board during the first year of the new CEO’s tenure. We construct two variables to capture

the connection between the new CEO and the old CEO. “Tenure Overlap [old CEO, new CEO]”

is the career overlap (in terms of years) between the new CEO and the outgoing CEO in the same

company. “Was Heir [new CEO]” is an indicator variable that equals one if the new CEO is the

heir apparent before he or she becomes the CEO. The upper echelons literature in management

science argues that heirs apparent tend to share similar cognitive orientations with their

predecessors (e.g., Bigley and Wiersema 2002). Empirically, following Naveen (2006), the heir

apparent is defined to be an executive who holds the title “president” or “chief operating officer

(COO)” or both and is distinct from the CEO and the chairman.10

In Table 8 Panel A we first explore how the connection between the new CEO and the

old CEO affects the intensity of management shakeup in model (1). We find that new CEOs who

have longer tenure overlap with the old CEOs and who are heirs apparent before becoming

CEOs implement less shakeup in management. By definition, a new outsider CEO has little

tenure overlap with the old CEO and is not an heir apparent before becoming the CEO. Thus our

results in model (1) may mainly reflect the difference in the shakeup propensity between outsider

CEOs and insider CEOs. In model (2) we examine the new insider CEO subsample only. We

find that insider CEOs who are heirs apparent before turnovers still implement less management

shakeup than those who are not, supporting the predictions in the upper echelons literature.

The summary statistics of

these variables are reported in Table 1 Panel F.

10 Existing studies have found that the executive in such a position is more likely to be promoted to the CEO than executives in any other internal positions (e.g., Naveen 2006; Cremers and Grinstein 2010). We also use an alternative definition in which we restrict the heir apparent to be younger than the current CEO. Our results are even stronger under this alternative definition of heir apparent.

27

In Panel A model (3) we find that the longer tenure of the old CEO in the company is

related to less management shakeup after the turnover. When the old CEO is the founder of the

company and when the old CEO stays as the chairman, the new CEO also implement less

personnel changes, although the effects are not statistically significant. In model (4) we examine

whether a new outsider CEO is less influenced by a powerful old CEO with long tenure in the

firm by interacting the new outsider CEO indicator with the old CEO’s tenure. The direct effect

of the old CEO’s tenure is still negative and significant. The interaction effect is positive and

significant and similar in absolute magnitude to the direct effect of the old CEO’s tenure. This

implies that if the new CEO is an outsider, then the tenure of the old CEO has no impact on the

post-turnover management shakeup (-0.002+0.002=0).

If a new CEO’s propensity to change the management team could be influenced by a

powerful old CEO, then his or her propensity to change operations could also be influenced in

similar ways, especially when the decision involves reversing the decisions made by the old

CEO. In Table 8 Panels B and C we examine how a new CEO’s propensity to downsize

operations or to expand operations is affected by the existence of a powerful old CEO, and

whether an insider CEO and an outsider CEO are affected differently. Panel B shows that all the

proxies for a powerful old CEO are associated with a significantly lower probability of

downsizing. Panel C shows that the existence of a powerful old CEO tends to increase the

probability of expansion after a CEO turnover. The contrasting effects of a powerful old CEO on

a new CEO’s propensity to downsize and to expand imply that it is particularly difficult for a

new CEO to reverse the decisions of a powerful predecessor.

Further, in both panels, the interaction effects between the outsider CEO indicator and the

proxies for a powerful old CEO have the right signs but are generally insignificant, suggesting

that even outsider CEOs cannot be effectively shielded from the influences of powerful old

CEOs when making these operational decisions.

In summary, the results in Section 6.1 suggest that agency-related frictions are an

important reason for why some firms choose not to shake up the management team and

operations after CEO turnover. These frictions can destroy shareholder value by preventing new

CEOs from implementing value-enhancing changes. Thus, the existence of these frictions

provides an explanation for the positive value impact of shakeup in the cross section. Firms that

choose not to shake up on average underperform because at least some of them should shake up

28

but fail to do so due to the existence of frictions. Internally promoted new CEOs are generally

more subject to these frictions than externally appointed ones, which can be one reason for the

higher shakeup propensity of outsider CEOs.

6.2 Endogeneity as an Explanation

Under the endogeneity-based interpretation, all firms that choose not to shake up the

management and downsize operations are optimally responding to some omitted condition, and it

is such omitted condition that generates the poor subsequent performance.

The omitted condition could be some omitted need for shakeup at the time of the CEO

turnover. The need for shakeup can arise for various reasons, including the need to improve

performance, to correct errors made by the previous management, or to establish

complementarities with the new CEO. If such need does not exist, then the optimal strategy

should be no shakeup. However, it is hard to argue that no need for shakeup causes subsequent

poor firm performance. For example, firms that perform well before CEO turnover may not need

any significant changes in personnel or operations. However, we need substantial mean reversion

in performance in the three years following turnover (regardless of strategies implemented) for

prior performance to explain away the value impact of strategy. We already know from Section 5

that the value impact of post-turnover strategy is not even sensitive to prior firm performance.

Another possible omitted condition is the corporate governance quality. We find that

firms implementing no post-turnover shakeups tend to have an insider-dominant governance

structure in the sense that they have lower institutional ownership, lower percentage of outside

directors, and higher insider ownership compared to firms that implement shake up. However, it

is hard to argue that such insider-dominant governance structure is the omitted condition, even if

we assume that the structure leads to poor future performance. First, we find that controlling of

these characteristics does not explain away the value impact of strategy. Second, our analysis in

Section 6.1 suggests that these governance characteristics are more likely to prevent optimal

shakeup from happening in some firms (the friction interpretation) than to imply that it is optimal

for firms with these characteristics not to shake up (the endogeneity interpretation).

One may also argue that the omitted condition is the quality of the new CEO. When the

quality of the CEO is low, then it may be optimal for the firm to choose no shakeup, and low

29

quality CEO delivers poor subsequent performance. However, here the link between the CEO

quality and the strategy choice is not straightforward.

Lastly, it is worthwhile noting that our empirical strategy follows a clear timeline. There

is a CEO turnover event in year 0 and we observe some actions being implemented. Then we

observe firm performance in years 0, 1, and 2. This event sequence at least mitigates certain

endogeneity concerns such as reverse causality and simultaneity.

7. CONCLUSION

In this paper, we try to understand how firm value is created around CEO turnover by

examining the value impact of various post-turnover firm strategies (i.e., significant changes in

personnel and operations). The existing literature has focused on the heterogeneity in CEOs as an

explanation for the heterogeneity in post-turnover firm performance (e.g., insider vs. outsider

CEOs). We show that shifting the focus to the heterogeneity in strategies can shed important new

light on our understanding of value creation associated with CEO turnovers.

We find that in the cross section firms that shake up the top management team and

downsize operations shortly after a new CEO takes office significantly and substantially

outperform those that do not. The differential propensity to shakeup between outsider CEOs and

insider CEOs also explains away the performance difference between the two. Within a firm, we

find that shakeups are particularly valuable when the firm has a new CEO. This result is not

driven by the prior firm conditions that lead to the change of CEO, and is consistent with the

agency view that CEO turnover is part of the error correction process in a corporation. Post-

turnover shakeups in personnel and operations can be viewed as the actions of error correction.

We also find that agency-related frictions affect firms’ post-turnover strategy choices, suggesting

that the strategy choices may not be the optimal responses to firm conditions for firms that are

exposed to these frictions. Thus, the existence of agency frictions can explain why strategies

matter for performance in the cross section.

Overall, we believe that examining post-turnover firm strategies is a fruitful approach.

Post-turnover strategy choices reflect the impact of not only the new CEO but also the

institutional environment (e.g., agency frictions) that the new CEO operates in, both of which are

relevant for understanding value creation associated with CEO turnover. Our study suggests that

the existence of agency frictions in a corporation has important implications for how we should

30

think about value creation associated with CEO turnover. The recent Olympus scandal clearly

shows the relevance of this viewpoint. Michael Woodford, the new outsider CEO at Olympus,

faced tremendous amount of resistance to his intent to shake up the struggling Japanese company.

The challenges soon led to his forced departure by the board after only two weeks of his

promotion to the CEO post. This event shows that even outsider CEOs are subject to frictions in

the company’s institutional environment, which put constraints on what they can or cannot do.

Our approach offers new insights to the literature and complements studies that examine

the impact of CEO characteristics. We believe that this topic deserves more future research. For

example, the significant value impact of management shakeup suggests that the role of

managerial capital besides the CEO deserves more attention in understanding the value creation

process within the firm.

31

REFERENCES

Allgood, Sam and Kathleen A. Farrell , 2003. “The match between the CEO and the firm”, Journal of Business, 76(2), 317-342 Bertrand, Marianne and Antoinette Schoar, 2003. “Managing with style: The effect of managers on firm policies,” Quarterly Journal of Economics, 118(4), 1169-1208. Bigley, Gregory A. and Margarethe F. Wiersema, 2002. “New CEOs and corporate strategic refocusing: How experiences as heir apparent influences the use of power,” Administrative Science Quarterly 47, 707-727. Bonnier, Karl-Adam and Robert F. Brunner, 1988. “An analysis of stock price reaction to management change in distressed firms”, Journal of Accounting and Economics, 11, 95-106.

Boot, Arnoud W.A., 1992. “Why hang on to losers? Divestitures and takeovers”, Journal of Finance 47, 1401-1423.

Borokhovich, Kenneth A., Robert Parrino and Teresa Trapani, 1996. “Outside directors and CEO selection,” The Journal of Financial and Quantitative Analysis, 31(3), 337-355.

Cremers, Martijn and Yaniv Grinstein, 2010. “The market for CEO talent: Implications for CEO compensation,” Working paper Denis, David J. and Diane K. Denis, 1995. “Performance changes following top management dismissals,” The Journal of Finance, 50(4), 1029-1057. Fee, C. Edward and Charles J. Hadlock, 2004. “Management turnover across the corporate hierarchy,” Journal of Accounting and Economics, 37(1), 3-38 Fee, C. Edward, Charles J. Hadlock, and Joshua R. Pierce, 2011. “Managers who lack style: Evidence from exogenous CEO changes,” Working paper Frydman, Carola, 2005. “Rising through the ranks: The evolution of the market for corporate executives, 1936-2003.” Working paper Graham, John R, Campbell R. Harvey, and Manju Puri, 2009. “Managerial attitudes and corporate actions”, working paper Hayes, Rachel M, Paul Oyer and Scott Schaefer, 2005. "Coworker complementarity and the stability of top-management teams," Journal of Law, Economics and Organization, 22(1), 184-212.

Huson, Mark R, Paul H.Malatesta and Robert Parrino, 2004. “Managerial succession and firm performance,” Journal of Financial Economics, 74, 237–275.

32

Jenter, Dirk and Fadi Kanaan, 2011. “CEO Turnover and Relative Performance Evaluation,”, Journal of Finance, forthcoming. Murphy, Kevin J. and Ján Zábojník, 2004. “CEO pay and turnover: A market based explanation for recent trends." American Economic Review (Papers and Proceedings) 94, 192-196. Murphy, Kevin J. and Ján Zábojník, 2007. “Managerial capital and the market for CEOs”, Working paper

Naveen, Lalitha, 2006. “Organizational Complexity and Succession Planning”, Journal of Financial and Quantitative Analysis, 41(3), 661-683.

Ouiment, Page and Rebecca Zarutskie, 2011, “Who Works for Startups? The Relation between Firm Age, Employee Age and Growth.” Working paper. Parrino, Robert, 1997. “CEO turnover and outside succession: A cross-sectional analysis,” Journal of Financial Economics, 46, 165-197. Sheng, Huang, 2009. “CEO characteristics, corporate decisions and firm value: Evidence from corporate refocusing.” Working paper. Weisbach, Michael S., 1995. “CEO turnover and the firm’s investment decisions,” Journal of Financial Economics, 37, 159-188.

33

Appendix: Variable Definitions

Panel A: Strategy, performance, and control variables

Management Shakeup the fraction of year t-1 Top-4 executives that are not in Top-4 at year t for non death or retirement related reasons

Downsizing an indicator that =1 if there is discontinuation/divestiture of existing segments and divisions or if the company is reducing both operational expenditures and employment

Expansion an indicator that =1 if the company establishes a new segment or acquires another company or enters a new industry

Changing Focus an indicator that =1 if the biggest segment or the most investment-intensive segment of the company is changed

Status Quo no management shakeup and no operational downsizing Capital Expenditure Intensity capital expenditure scaled by sales R&D Intensity R&D expenses scaled by sales Leverage (Debt in Current Liabilities + Long-term Liabilities)/assets Net Investment (capital expenditures + acquisitions – sale PPE + increase

in investments– sale of investments)/ start-of-period assets Net LT Debt Issuance =1 if (long-term debt issues– long-term debt reduction) /start-of-period

assets is greater than or equal to 2% Net Equity Issuance =1 if (sale of common and preferred stock – purchase of common and

preferred stock ) / start-of-period assets is greater than or equal to 2% Dividend Payout Ratio Dividend/Net Income Return annual stock return ROA earnings before interest, tax, and depreciation scaled by the beginning of

fiscal year total book assets ∆(Ind. Adj. Return) [0,2] vs. [-1] the difference between the average industry-adjusted annual stock return

from year 0 to year 2 and the industry-adjusted stock return at year -1 (Ind. Adj. Return) [t] industry (median)-adjusted stock return for year t ∆(Ind. Adj. ROA) [1,2] vs. [-1] the difference between the average annual stock return from year 1 to

year 2 and the stock return at year -1. Capx/Sales capital expenditure scaled by sales Market to Book of Equity market value of equity divided by book value of the equity Log(Assets) logarithm of the total book assets

34

Panel B: CEO and management attributes

Outsider CEO an indicator that = 1 if the CEO is hired from outside of the company Tenure Overlap [old CEO, new CEO] the length of tenure overlap between the old and the new CEO Tenure [old CEO] the tenure length of the old CEO

Founder [old CEO] an indicator that =1 if the outgoing CEO is the founder of the company

Heir Apparent an executive with the title “president” or “chief operating officer (COO)” or both who is distinct from the CEO and the chairman

Was Heir [new CEO] an indicator that =1 if the new CEO is an heir apparent before becoming the CEO

Stay As Chairman [old CEO] an indicator that =1 if the old CEO stays as the Chairman of the Board during the first year of the new CEO’s tenure

Avg. Tenure Overlap [old mgt., new CEO] the average length of overlap between the old management team and the new CEO

Avg. Tenure [old mgt.] the average tenure length of the old management team % On Board [old mgt.] the % of the old management that serves as directors on the board

35

Table 1: Summary Statistics

Panel A: CEO Turnovers This panel presents the number of CEO turnovers in the sample by industry and by year, as well as the percentage of outsider CEOs for each industry.

# of CEO Turnovers % of Outside CEO Fama-French 10 Industries Non-Durables 148 0.262 Durables 79 0.241 Manufacturing 390 0.307 Energy 82 0.195 Hi-Tech 362 0.369 Telecom 43 0.326 Shops 285 0.306 Health 142 0.378 Utilities 166 0.307 Other 524 0.233 Full Sample 2,221 0.298

Year # of CEO turnovers

1992 50 1993 97 1994 131 1995 127 1996 119 1997 127 1998 142 1999 160 2000 188 2001 190 2002 133 2003 145 2004 142 2005 156 2006 139 2007 175

36

Panel B: Turnover Type Indicators This panel presents summary statistics of various turnover type indicators. “Outsider succession” equals to 1 if the new CEO is from outside of the company (see Appendix A, Panel B). “Death & Retirement Related Turnover” equals to 1 if the CEO turnover event is related to exogenous reasons such as death or retirement. We classify the turnover reason to be retirement if the CEO is older than 65 years. “Forced Turnover” equals to 1 if the departure of the incumbent CEO was reported by the press as fired, forced out, or retires or resigns due to policy differences or pressure, following Parrino (1997) and Jenter and Kanaan (2011).

Turnover Type Indicators N Mean Outsider Succession 2,214 0.298 Death & Retirement Related Turnover 2,221 0.286 Forced Turnover 1,049 0.159

Panel C: Post-Turnover Firm Strategies

This panel presents the average change in the Top-4 management team, operations and other policies for the CEO turnover years and for the non-turnover years. All variable definitions are in Appendix A. The difference between the two sample means and the Wilcoxon signed ranked statistics are also included.

Turnover Year Non-Turnover Year Difference

Wilcox Z for

Difference N Mean N Mean Change in Top Mgt. Team Management Shakeup 2,221 0.182 22,559 0.147 0.035 5.785*** Change in Operations Downsizing 2,221 0.399 22,559 0.328 0.071 6.774*** Expansion 2,221 0.321 22,559 0.340 -0.019 -1.85* Changing Focus 2,221 0.285 22,559 0.244 0.041 4.261*** Change in Other Policies Capital Expenditures Ratio 1,973 -0.004 1,973 -0.002 -0.001 -3.203*** R&D Intensity 1,163 -0.027 11,515 -0.046 0.019 1.317 Net Investment 1,111 -0.013 13,435 -0.013 0 -0.695 Net LT Debt Issuance 2,025 0.492 22,139 0.494 -0.002 0.225 Net Equity Issuance 1,958 0.354 21,563 0.373 -0.019 1.68 Leverage 1,886 0.003 19,646 0.005 -0.002 -1.581 Dividend Payout 2,215 -0.254 24,447 0.030 -0.284 0.964

37

Panel D: Changes by the Fiscal Quarter of CEO Turnovers This panel presents average changes by the fiscal quarter of when the new CEO takes office.

Became CEO Quarter (fiscal) # of obs. Management

Shakeup Downsizing Expansion Change Focus

1 749 0.173 0.358 0.326 0.291 2 602 0.195 0.429 0.344 0.304 3 401 0.185 0.419 0.309 0.264 4 427 0.187 0.431 0.295 0.281

Panel E: Post-Turnover Firm Performance

“∆(*) [0,2] vs. [-1]” means the difference between the average level from year 0 to year 2 and the level at year -1. “∆(*) [1,2] vs. [-1]” means the difference between the average level from year 1 to year 2 and the level at year -1. (*) [t] means the industry-adjusted performance level at year t.

N mean p25 p50 p75 ∆(Ind. Adj. Return) [0,2] vs. [-1] 2,070 0.035 -0.212 0.032 0.309 ∆(Ind. Adj. ROA) [0,2] vs. [-1] 2,024 -0.003 -0.031 0.000 0.028 ∆(Ind. Adj. Return) [1,2] vs. [-1] 2,070 0.025 -0.240 0.017 0.310 ∆(Ind. Adj. ROA) [1,2] vs. [-1] 2,024 -0.004 -0.038 -0.002 0.033 (Ind. Adj. Return) [1] 2,181 0.018 -0.236 -0.042 0.168 (Ind. Adj. Return) [-1] 2,109 -0.043 -0.314 -0.091 0.124

Panel F: Control Variables and Management Attributes

Control variables are measured as of year -1. Management attributes are measured at the executive team level, or CEO level, or executive-team-CEO level, as indicated in the square brackets.

Control variable N mean p25 p50 p75 Capx/Sales 2,020 0.083 0.025 0.044 0.085 Market to Book of Equity 2,079 3.177 1.455 2.140 3.494 Log(Assets) 2,126 7.586 6.312 7.470 8.715 # of Segments 1,827 2.492 1 2 3 Management Attributes

Tenure Overlap [old CEO, new CEO] 1,277 8.428 1 5 13 Tenure [old CEO] 1,485 18.569 7 16 30 Founder [old CEO] 2,242 0.062 0 0 0 Was Heir [new CEO] 2,242 0.205 0 0 0 Stay As Chairman [old CEO] 2,242 0.288 0 0 1 Avg. Tenure Overlap [old mgt., new CEO] 1,495 6.562 0 4 10.750 Avg. Tenure [old mgt.] 1,744 9.803 4 8 13.667 % On Board [old mgt.] 1,919 0.288 0.250 0.250 0.500

38

Table 2: Performance Effect of Changing Managerial and Operational Capital

“∆(*) [0,2] vs. [-1]” means the difference between the average level from year 0 to year 2 and the level at year -1. All variable definitions are in Appendix. All management and operational shakeup variables are measured as of the CEO turnover year and all control variables are measured as of one year before the turnover. When using the performance change as the dependent variable, lagged performance change is used as a control variable. When using the performance level as the dependent variable, lagged performance level is used as a control variable. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively.

∆(Ind. Adj. Return)

[0,2] vs. [-1] ∆(Ind. Adj. ROA)

[1,2] vs. [-1] (Ind. Adj.

Return) [1] (1) (2) (3) Mgmt. Shakeup 0.232*** 0.032*** 0.105** (0.044) (0.011) (0.048) Downsizing 0.083** 0.012** 0.068** (0.038) (0.006) (0.028) Expansion -0.067* -0.001 -0.005 (0.034) (0.007) (0.036) Changing Focus -0.039 0.003 -0.038 (0.025) (0.004) (0.033) (Ind. Adj. Return) lagged (change in 1&2, level in 3) -0.500*** 0.009*** -0.130*** (0.026) (0.003) (0.044) (Ind. Adj. ROA) lagged (change in 1&2, level in 3) -0.391* 0.279*** -0.242 (0.208) (0.050) (0.147) Capx/Sales -0.068 -0.035 0.038 (0.077) (0.033) (0.071) Market to Book -0.020*** -0.002 -0.004 (0.005) (0.001) (0.006) Log(Assets) 0.002 -0.001 -0.018* (0.007) (0.001) (0.009) Year Fixed Effects x x x Adj. R-Squared 0.463 0.087 0.059 Observations 1,800 1,798 1,933

39

Table 3: Value Impact of Combined Strategies

Panel A: Complementarity Among Strategies

All strategies are measured as of year 0 (i.e., the turnover year). All control variables are measured as of one year before the turnover. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively. Mgt. Shakeup [0] Downsizing [0] 0.062*** (0.014) Expansion [0] 0.009 (0.014) Changing Focus [0] 0.008 (0.010) (Ind. Adj. Return) [-1] -0.035*** (0.009) (Ind. Adj. ROA) [-1] -0.273*** (0.037) Capx/Sales -0.037 (0.033) Market to Book 0.003 (0.002) Log(Assets) 0.006** (0.003) Year and Industry Fixed Effects x Adj. R-Squared 0.211 Observations 1,921

Panel B: Combined Straetgies and Industry-adjusted Returns

This Panel presents the frequency of the four combined strategies and the sample average of industry-adjusted stock returns at year -1, 0 (turnover year), and 1 for each staretgy.

Frequency % of Total Year -1 Year 0 Year 1 Strategy 1 (Mgmt. Shakeup>0 & Downsizing>0) 528 23.77 -0.147 -0.001 0.113 Strategy 2 (Mgmt. Shakeup>0 & Downsizing=0) 534 24.04 -0.049 0.006 -0.002 Strategy 3 (Mgmt. Shakeup=0 & Downsizing>0) 358 16.12 -0.047 0.039 -0.052 Strategy 4 (Mgmt. Shakeup=0 & Downsizing=0) 801 36.06 0.038 0.021 -0.014

40

Panel C: Effects of Combined Strategies on Performance

Strategy i is an indicator variable that equals 1 if if the strategy specified in the parenthesis is implemented in the turnover year. For example, if the new CEO implements both management shakeup and downsizing at the turnover year, Strategy 1 equals 1 and Strategy 2 and 3 both equal 0. All control variables are measured as of one year before the turnover. When using the performance change as the dependent variable, lagged performance change is used as a control variable. When using the performance level as the dependent variable, lagged performance level is used as a control variable. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively.

∆(Ind. Adj. Return)

[0,2] vs. [-1] ∆(Ind. Adj. ROA)

[1,2] vs. [-1] (Ind. Adj.

Return) [1] (1) (2) (3)

Strategy 1 (Mgmt. Shakeup>0 & Downsizing>0) 0.197*** 0.024*** 0.110*** (0.034) (0.005) (0.032) Strategy 2 (Mgmt. Shakeup>0 & Downsizing=0) 0.089*** 0.007 -0.015 (0.031) (0.006) (0.038) Strategy 3 (Mgmt. Shakeup=0 & Downsizing>0) 0.075*** 0.005 -0.035 (0.032) (0.007) (0.028) (Ind. Adj. Return) lagged (change in 1&2, level in 3) -0.465*** 0.008** -0.074*** (0.031) (0.004) (0.025) (Ind. Adj. ROA) lagged (change in 1&2, level in 3) -0.277 0.264*** -0.262* (0.242) (0.051) (0.136) Capx/Sales -0.046 -0.035 0.085 (0.058) (0.036) (0.078) Market to Book -0.019*** -0.002 -0.001 (0.004) (0.001) (0.006) Log(Assets) -0.003 -0.001 -0.013** (0.007) (0.001) (0.006) Year Fixed Effects x x x Adj. R-Squared 0.416 0.104 0.054 Observations 1,800 1,798 1,911

41

Table 4: Strategy Choices: External Appointment vs. Internal Promotion

Panel A: Effect of CEO Succession Origin on Post-Turnover Strategies

“Outsider CEO” is an indicator variable that equals 1 if the CEO is hired from outside of the company. All control variables are measured as of one year before the turnover. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively.

Mgt. Shakeup Downsizing Expansion Change Focus

(1) (2) (3) (4)

Outsider CEO 0.086*** 0.101*** -0.008 0.019 (0.012) (0.023) (0.023) (0.019) (Ind. Adj. Return) lagged -0.037*** -0.064*** 0.036** 0.012 (0.009) (0.022) (0.016) (0.016) (Ind. Adj. ROA) lagged -0.272*** -0.624*** 0.177*** -0.123 (0.042) (0.122) (0.064) (0.094) Capx/Sales -0.055 -0.308*** 0.154*** -0.201*** (0.036) (0.088) (0.057) (0.050) Market to Book 0.003 -0.004 0.007** -0.002 (0.002) (0.004) (0.003) (0.003) Log(Assets) 0.011*** 0.042*** 0.014*** 0.048*** (0.003) (0.007) (0.004) (0.008) Year and Industry Fixed Effects x x x x Adj. R-Squared 0.135 0.138 0.027 0.070 Observations 1,916 1,916 1,916 1,916

42

Panel B: Multinomial Logistic Regression of Succession Origin on Strategy

This panel presents results for the multinomial logit regression. The baseline strategy is the status quo (no mgt. shakeup or downsizing in the turnover year). All control variables are measured as of one year before the turnover. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. The estimated marginal effects are reported in square brackets. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively.

Status Quo (Mgmt. Shakeup=0 & Downsizing=0)

Strategy 1 Strategy 2 Strategy 3

Mgmt. Shakeup=0 &

Downsizing>0 Mgmt. Shakeup>0 &

Downsizing=0 Mgmt. Shakeup>0 &

Downsizing>0 Outsider CEO 0.766*** 0.938*** 1.084*** (0.196) (0.158) (0.196) [0.012] [0.097] [0.119] (Ind. Adj. Return) lagged -0.346*** -0.311*** -0.612*** (0.099) (0.107) (0.190) [-0.006] [-0.025] [-0.067] (Ind. Adj. ROA) lagged -3.316*** -1.657*** -5.091*** (0.808) (0.621) (1.035) [-0.065] [-0.088] [-0.579] Capx/Sales -1.345* -0.424 -2.107** (0.731) (0.398) (0.883) [-0.027] [-0.002] [-0.246] Market to Book 0.019 0.037*** -0.008 (0.026) (0.014) (0.031) [0.0004] [0.005] [-0.002] Log(Assets) 0.161*** 0.060 0.309*** (0.052) (0.037) (0.052) [0.003] [0.0002] [0.036] Year and Industry Fixed Effects x x x

43

Panel C: Strategy or Turnover Type?

“Mgmt. Shakeup>0 & Downsizing>0” is an indicator variable indicating whether the new CEO implements the strategy at the turnover year. “Mgmt. Shakeup>0 & Downsizing=0” is an indicator variable indicating whether the new CEO implements the strategy (mgt. shakeup only, no downsizing) at the turnover year, and so on. “Strategy X (Turnover indicator)” interacts the strategy indicator and the turnover indicators (Outsider, Death & Retirement related, or Forced). All control variables are measured as one year before the turnover year. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry.

∆(Ind. Adj. Return) [0,2] vs. [-1] (1) (2) Outsider CEO 0.083*** 0.032 (0.025) (0.058) Mgmt. Shakeup>0 and/or Downsizing>0

0.099***

(0.027) (Mgmt. Shakeup>0 and/or Downsizing>0) X (Outsider CEO)

0.041

(0.066) Controls x x Year F.E. x x Observations 1,798 1,798 Adjusted R-squared 0.453 0.458

44

Table 5: When Does Strategy Matter?

Panel A: Value Impact of Strategy: Turnover vs. No Turnover

“(*) [t]” (t = -1, 0, 1) means the variable is measured at year t (year 0 being the turnover year). “∆(*) [0,2] vs. [-1]” means the difference between the average level from year 0 to year 2 and the level at year -1. All variable definitions are in Appendix. All management and operational shakeup variables are measured as of the CEO turnover year and all control variables are measured as of one year before the turnover. When using the performance change as the dependent variable, lagged performance change is used as a control variable. When using the performance level as the dependent variable, lagged performance level is used as a control variable. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively.

∆(Ind. Adj. Return)

[0,2] vs. [-1] ∆(Ind. Adj. ROA)

[1,2] vs. [-1] (Ind. Adj.

Return) [1] (1) (2) (3) Strategy 1 (Mgmt. Shakeup>0 &

Downsizing>0) 0.100*** 0.012*** 0.043***

(0.013) (0.002) (0.014) Strategy 2 (Mgmt. Shakeup>0 &

Downsizing=0) 0.025*** -0.002 -0.019*

(0.009) (0.002) (0.010) Strategy 3 (Mgmt. Shakeup=0 &

Downsizing>0) 0.053*** 0.004 0.016

(0.012) (0.002) (0.013) Strategy 1 X CEO Turnover 0.118*** 0.016** 0.098** (0.037) (0.007) (0.041) Strategy 2 X CEO Turnover 0.077** 0.016** 0.015 (0.035) (0.007) (0.036) Strategy 3 X CEO Turnover 0.046 0.004 0.045 (0.039) (0.007) (0.039) CEO Turnover -0.007 0.001 0.010 (0.021) (0.004) (0.021) Controls x x x Firm Fixed Effects x x x Year Fixed Effects x x x Adj. R-Squared 0.463 0.179 0.024 Observations 19,754 19,704 23,340

45

Panel B: Prior Performance and Value Impact of Strategies

“(*) [t]” (t = -1, 0, 1) means the variable is measured at year t (year 0 being the turnover year). All control variables are measured as of one year before the turnover. “∆(*) [1,2] vs. [ -1]” means the difference between the average level from year 1 to year 2 and the level at year -1. Outperforming or underperforming is benchmarked on industry average performance. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively.

∆(Ind. Adj. Return) [0,2] vs. [-1] Turnover Sample Non-Turnover Sample

Underperformi

ng in [-1] Outperformi

ng in [-1] Underperformi

ng in [-1] Outperformi

ng in [-1] (1) (2) (3) (4)

Strategy 1 (Mgmt. Shakeup>0 & Downsizing>0) 0.155*** 0.113* 0.086*** 0.012 (0.029) (0.059) (0.018) (0.019) Strategy 2 (Mgmt. Shakeup>0 & Downsizing=0) 0.049* 0.045 0.009 0.012 (0.028) (0.035) (0.009) (0.013) Strategy 3 (Mgmt. Shakeup=0 & Downsizing>0) 0.069 0.050 0.029** 0.008 (0.044) (0.046) (0.014) (0.013) ∆(Ind. Adj. Return) lagged -0.129*** -0.503*** -0.142*** -0.480*** (0.021) (0.059) (0.012) (0.017) ∆(Ind. Adj. ROA) lagged 0.247 -0.136 0.032 -0.406*** (0.222) (0.297) (0.061) (0.116) Capx/Sales -0.017 -0.236** 0.005 0.025 (0.055) (0.110) (0.037) (0.036) Market to Book -0.010** -0.017*** -0.008*** -0.023*** (0.004) (0.005) (0.002) (0.004) Log(Assets) -0.041*** 0.018 -0.030*** 0.032*** (0.008) (0.014) (0.004) (0.004) Year Fixed Effects x x x x Adj. R-Squared 0.135 0.526 0.131 0.462 Observations 1,113 687 10,253 7,702

46

Panel C: Forced Turnovers versus Death- and Retirement-Related Turnovers

“(*) [t]” (t = -1, 0, 1) means the variable is measured at year t (year 0 being the turnover year). All control variables are measured as of one year before the turnover. “∆(*) [1,2] vs. [ -1]” means the difference between the average level from year 1 to year 2 and the level at year -1. “Death-and-Retirement Related Turnovers” sample consists of CEO turnover events that are related to exogenous reasons such as death or retirement. We classify the turnover reason to be retirement if the CEO is older than 65 years. “Forced Turnovers” consists turnovers if the departure of the incumbent CEO was reported by the press as fired, forced out, or retires or resigns due to policy differences or pressure, following Parrino (1997) and Jenter and Kanaan (2010). The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively.

∆(Ind. Adj. Return) [0,2] vs. [-1]

Forced

Turnovers Death-and-Retirement Related

Turnovers (1) (2) Strategy 1 (Mgmt. Shakeup>0 & Downsizing>0) 0.259** 0.117** (0.120) (0.044) Strategy 2 (Mgmt. Shakeup>0 & Downsizing=0) 0.181* 0.097** (0.106) (0.038) Strategy 3 (Mgmt. Shakeup=0 & Downsizing>0) 0.161 0.023 (0.142) (0.039) ∆(Ind. Adj. Return) lagged -0.605*** -0.481*** (0.102) (0.065) ∆(Ind. Adj. ROA) lagged 0.112 -0.812** (0.516) (0.371) Capx/Sales -0.216 -0.207 (0.166) (0.204) Market to Book -0.011 -0.010* (0.010) (0.005) Log(Assets) 0.018 0.009 (0.027) (0.014) Year Fixed Effects x x Adj. R-Squared 0.486 0.478 Observations 131 583

47

Table 6: Complementarities between New CEO and the Top Management Team

Panel A: Gender Distribution of Executives

This Panel presents summary statistics of the gender distribution of non-CEO top executives for various (sub)samples. “Firm-year with Female/Male CEO” consists of firm-year observations when the incumbent CEO is female/male. “Firm-year with Female/Male NEW CEO” consists of firm-year observations when there is a new female/male CEO. “All Non-CEO Executives” captures all the non-CEO executives in the sample. “Newly promoted to Top-4” captures the new non-CEO executives promoted during the CEO turnover year.

All Non-CEO Executives Sample Female Executives Male Executives Percent of Female Full Execucomp Sample 6,265 107,231 5.52% Firm-year with Female CEO 285 1,515 15.83% Firm-year with Male CEO 5,940 104,636 5.37% Newly Promoted to Top-4 Sample Female Executives Male Executives Percent of Female Firm-year with Female New CEO 12 47 20.34% Firm-year with Male New CEO 187 2,387 7.26%

Panel B: Average Age of Executives

This Panel presents the average age of non-CEO executives for various (sub-)samples. “Young CEO” consists of firm-year observations when the CEO is younger than 50. “Old CEO” consists of firm-year observations when the CEO is 50 or older. “All Non-CEO Executives” captures all the non-CEO executives in the sample. “Newly promoted to Top-4” captures the new non-CEO executives promoted during the CEO turnover year.

Sample All Non-CEO

Executives Sample Newly Promoted to

Top-4 Full Execucomp Sample 51 All New CEO 49 Young CEO 49 Young New CEO 48 Old CEO 52 Old New CEO 50 Wilcox Z for Difference: Young vs. Old 39.091***

Wilcox Z for Difference: Young vs. Old 5.261***

48

Panel C: Tenure Length of the Executives

This Panel presents the tenure length of non-CEO executives for various (sub-)samples. “Outside New CEO” consists of firm-year observations when the new CEO is an outsider (see Appendix A, Panel B). “Insider CEO” consists of firm-year observations when the CEO is promoted from inside of the company. “All Non-CEO Executives” captures all the non-CEO executives in the sample. “Newly promoted to Top-4” captures the new non-CEO executives promoted during the CEO turnover year.

Sample All Non-CEO

Executives Newly Promoted/Hired to

Top-4

% of New Top-4 Executives Hired from

outside Full Execucomp Sample 9.77 5.54 39.83% All New CEO 10.45 5.97 37.03% Outsider new CEO 8.01 3.81 53.64% Insider new CEO 11.50 7.15 28.90% Wilcox Z for Difference: Outsider vs. Insider 14.861*** 11.166***

49

Panel D: Value Impact of Complementarities

This table presents the value impact of complementarities between the new CEO and other senior executives. “Female Executive” is the number of female executives in the top-4 senior (non-CEO) executives. “Outsider Executive” is the number of outsider executives (tenure length less than 2 years) in the top-4 senior (non-CEO) executives. “Young Executive” is the number of young executives (age less than 47) in the top-4 senior (non-CEO) executives. All control variables are measured as of one year before the turnover. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively. ∆(Ind. Adj. Return) [0,2] vs. [-1] (1) (2) (3) Female CEO -0.176***

(0.056) Female Executive -0.016 (0.022) Female CEO x Female Exec 0.140*** (0.049) Outsider CEO

0.070**

(0.031) Outsider Executive

0.014

(0.021) Outsider CEO x Outsider Exec.

0.010

(0.029) Young CEO

-0.026

(0.038) Young Executive

-0.004

(0.018) Young CEO x Young Exec.

0.021

(0.026) ∆(Ind. Adj. Return) lagged -0.465*** -0.503*** -0.501*** (0.031) (0.026) (0.026) ∆(Ind. Adj. ROA) lagged -0.345 -0.441** -0.476** (0.233) (0.210) (0.212) Capx/Sales -0.069 -0.101 -0.090 (0.062) (0.082) (0.080) Market to Book -0.020*** -0.021*** -0.022*** (0.005) (0.005) (0.005) Log(Assets) 0.002 0.007 0.005 (0.007) (0.007) (0.006) Year Fixed Effects x x x Adj. R-Squared 1,800 1,798 1,800 Observations 0.404 0.453 0.450

50

Table 7: Entrenched Old Management

Panel A: Are entrenched managers less likely to be shaken up?

“Mgmt. Shakeup” measures the intensity of management shakeup in the CEO turnover years. “Full sample” consists of all firm-year observations with CEO turnovers. “Insider CEO sample” consists of firm-year observations with CEO turnovers and insider new CEOs. “Avg. Tenure Overlap [old mgt., new CEO]” measures the average length of overlap between the old mgt. team and the new CEO. “Avg. Tenure [old mgt.] measures the average tenure length of the old management team. “% on Board [old mgt.]” measures the percentage of the old management that also serves as directors on board. All control variables are measured as of one year before the turnover. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively.

Mgmt. Shakeup [0]

(Full sample) (Insider CEO

sample) (Full sample) (Full sample) (1) (2) (3) (4) Avg. Tenure Overlap [old mgt., new CEO] -0.006*** -0.002** (0.001) (0.001) Avg. Tenure [old mgt.] -0.004*** -0.001 % On Board [old mgt.] -0.196*** (0.024) ∆(Ind. Adj. Return) lagged -0.005 -0.013 -0.012* -0.011* (0.010) (0.011) (0.007) (0.006) ∆(Ind. Adj. ROA) lagged -0.178** -0.211** -0.228*** -0.200*** (0.071) (0.104) (0.074) (0.069) Capx/Sales -0.023 -0.038 -0.021 -0.012 (0.037) (0.050) (0.033) (0.033) Market to Book -0.000 0.002 0.000 0.000 (0.002) (0.002) (0.002) (0.002) Log(Assets) 0.014*** 0.012** 0.011*** 0.009** (0.004) (0.005) (0.004) (0.004) Year and Industry Fixed Effects x x x x Adj. R-Squared 0.067 0.047 0.061 0.078 Observations 1,342 874 1,546 1,679

51

Panel B: Are outsider CEOs more likely to change entrenched management?

“Avg. Tenure [old mgt.] X Outsider CEO” interacts the average tenure length of the old management team with the outsider CEO indicator. “% on Board [old mgt.] x Outsider CEO” interacts the percentage of the old management that are on board with the dummy of outsider new CEOs. All control variables are measured as of one year before the turnover. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively.

Mgmt. Shakeup (1) (2) Outsider CEO 0.065*** 0.068*** (0.021) (0.019) Avg. Tenure [old mgt.] -0.004*** (0.001) Avg. Tenure [old mgt.] x Outsider CEO 0.003* (0.002) % On Board [old mgt.] -0.187*** (0.022) % On Board [old mgt.] x Outsider CEO 0.076 (0.072) ∆(Ind. Adj. Return) lagged -0.011 -0.011* (0.009) (0.006) ∆(Ind. Adj. ROA) lagged -0.222*** -0.188*** (0.074) (0.068) Capx/Sales -0.028 -0.019 (0.039) (0.033) Market to Book 0.001 0.001 (0.002) (0.002) Log(Assets) 0.013*** 0.011*** (0.004) (0.004) Year and Industry Fixed Effects x x Adj. R-Squared 0.096 0.108 Observations 1,544 1,677

52

Panel C: Value Impact of Management Entrenchment

“Avg. Tenure Overlap [mgt.,CEO]” is the average tenure overlap between the (contemporaneous) management team and the CEO. “Avg. Tenure [mgt.]” is the average tenure length of the management team. “% on Board [mgt.]” is the percentage of the management that sits on the board. All control variables are measured as of one year before the turnover. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively.

∆(Ind. Adj. Return) [0,2] vs. [-1] (1) (2) (3) (4) (5) (6) Avg. Tenure Overlap [mgt., CEO] -0.004**

-0.002

(0.002)

(0.002) Avg. Tenure [mgt.]

-0.002*

-0.001

(0.001)

(0.001) % On Board [mgt.]

-0.131**

-0.075

(0.051)

(0.049) Mgmt. Shakeup>0 & Downsizing>0

0.180*** 0.185*** 0.161***

(0.040) (0.042) (0.039) Mgmt. Shakeup>0 & Downsizing=0

0.091** 0.084* 0.069**

(0.036) (0.043) (0.033) Mgmt. Shakeup=0 & Downsizing>0

0.088** 0.096*** 0.078**

(0.035) (0.033) (0.031) Controls x x x x x x Year Fixed Effects x x x x x x Adj. R-Squared 0.490 0.460 0.452 0.498 0.469 0.480 Observations 1,394 1,647 1,800 1,394 1,647 1,800

53

Table 8: Powerful Old CEOs

Panel A: Impact of old CEOs on personnel change after turnovers

“Tenure Overlap [old CEO, new CEO]” measures the employment overlap between the old and new CEO in the firm. “Was Heir [new CEO]” is an indicator that equals 1 if the new CEO is an heir apparent before becoming the CEO. “Tenure [old CEO]” measures the tenure length of the old CEO. “Tenure [old CEO] xOutsider CEO” interacts the tenure length of the old CEO with the outsider CEO indicator. Founder [old CEO] indicates whether the old CEO is the founder of the company. “Stay as chairman [old CEO]” is an indicator that equals 1 if the old CEO stays in the company as the chairman of the board after stepping down as the chief executive. All control variables are measured as of one year before the turnover.

Mgmt. Shakeup

(1) (2) (3)

Tenure Overlap [old CEO, new CEO] -0.004*** (0.001) Was Heir [new CEO] -0.065*** (0.017) Tenure [old CEO] -0.002*** -0.002*** (0.001) (0.001) Tenure [old CEO] x Outsider CEO 0.002** (0.001) Outsider CEO 0.055** (0.023) Founder [old CEO] -0.006 (0.029) Stay As Chairman [old CEO] -0.006 (0.012) ∆(Ind. Adj. Return) lagged -0.011 -0.011** -0.010* (0.009) (0.006) (0.006) ∆(Ind. Adj. ROA) lagged -0.208*** -0.302*** -0.297*** (0.075) (0.090) (0.081) Capx/Sales -0.063* -0.072* -0.081** (0.034) (0.040) (0.040) Market to Book -0.000 0.001 0.001 (0.002) (0.002) (0.002) Log(Assets) 0.015*** 0.011** 0.014*** (0.004) (0.005) (0.005) Year and Industry Fixed Effects x x x Adj. R-Squared 0.083 0.048 0.088 Observations 1,148 1,316 1,315

54

Panel B: Impact of old CEO on downsizing after turnovers

All control variables are measured as of one year before the turnover. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively.

Downsizing

(1) (2) (3) (4)

Tenure Overlap [old CEO, new CEO] -0.006**

(0.002)

Was Heir [new CEO] -0.064*

(0.035)

Tenure [old CEO]

-0.003**

(0.001)

Tenure [old CEO] x Outsider CEO

0.003*

(0.002)

Stay As Chairman [old CEO] -0.076** (0.030) Stay As Chairman [old CEO] x Outsider CEO 0.057 (0.052) Founder [old CEO] -0.081** (0.039) Founder [old CEO] x Outsider CEO 0.054 (0.100) Outsider CEO 0.087* 0.107*** 0.124*** (0.052) (0.026) (0.026) ∆(Ind. Adj. Return) lagged 0.005 -0.009 -0.001 -0.002 (0.017) (0.013) (0.013) (0.013) ∆(Ind. Adj. ROA) lagged -0.115 -0.168 -0.242 -0.254* (0.193) (0.168) (0.153) (0.151) Capx/Sales -0.458*** -0.530*** -0.246** -0.238** (0.151) (0.139) (0.113) (0.108) Market to Book -0.010** -0.010* -0.008** -0.009** (0.005) (0.005) (0.004) (0.004) Log(Assets) 0.050*** 0.048*** 0.048*** 0.045*** (0.010) (0.008) (0.007) (0.006) Year and Industry Fixed Effects x x x x Adj. R-Squared 0.111 0.110 0.114 0.111 Observations 1,148 1,315 1,822 1,822

55

Panel C: Impact of old CEO on expansion after turnovers

“Expansion” is an indicator variable that indicates whether or not there is expansion at the turnover year. All control variables are measured as of one year before the turnover. The Huber-White-Sandwich robust standard errors (in parentheses) are clustered by industry. ***, ** and * indicate significance at the 1%, 5% and 10% levels respectively.

Expansion (1) (2) (3) (4) Tenure Overlap [old CEO, new CEO] 0.002* (0.001) Was Heir [new CEO] 0.029 (0.028) Tenure [old CEO] 0.001 (0.002) Tenure [old CEO] x Outsider CEO -0.003* (0.002) Stay As Chairman [old CEO] 0.056** (0.025) Stay As Chairman [old CEO] x Outsider CEO -0.012 (0.034) Founder [old CEO] 0.085* (0.048) Founder [old CEO] x Outsider CEO -0.092 (0.080) Outsider CEO 0.015 -0.011 -0.013 (0.039) (0.019) (0.022) ∆(Ind. Adj. Return) lagged -0.010 -0.003 -0.007 -0.006 (0.014) (0.012) (0.010) (0.010) ∆(Ind. Adj. ROA) lagged -0.011 0.018 0.043 0.050 (0.148) (0.146) (0.138) (0.135) Capx/Sales 0.118 0.135 0.129* 0.121* (0.172) (0.157) (0.072) (0.071) Market to Book 0.009** 0.009*** 0.009*** 0.009*** (0.004) (0.003) (0.003) (0.003) Log(Assets) 0.008 0.011* 0.012** 0.014*** (0.006) (0.006) (0.004) (0.004) Year and Industry Fixed Effects x x x x Adj. R-Squared 0.018 0.015 0.021 0.019 Observations 1,148 1,315 1,822 1,822