President Turnover and Product Market Competition: Empirical Evidence
from Japanese Manufacturing Firms

Yessica, C.Y. Chung1

Preliminary version
Abstract
This study uses Japanese data to examine the competition effect on managerial
incentive contract, which is measured by president turnover and turnover patterns.
The findings obtained in empirical analyses are consistent with the assertion that there
are distinct differences between the rate of president turnover, and turnover patterns incompetitive markets and concentrated markets. More detailed, the rate of president
turnover is greater in competitive market than in less competitive market. Moreover,firms in competitive markets are more likely to take disciplinary action to remove
their presidents than firms in concentrated markets. The presence of a dominant firmin the industry also enhances the probability of disciplinary president turnover.
Consequently, these findings are consistent with Schmidt’s argument that thecompetition causes a threat of firm’s liquidation and therefore reduces managerial
shirk, suggesting that presidents face different contracts between competitive markets
and concentrated markets.

JEL classification: L16; L25.
Keywords: President turnover; Disciplinary turnover; Market competition; Manufacturing
Industry; Japan.

1

Associate Researcher, JICA Research Institute ; chiuyuehc@hotmail.com

1. Introduction
The corporate governance literature has highlighted various mechanisms, both internaland external, to reduce agency problems between shareholders and managers. Suchmechanisms include, for example, providing managers with shares in the company,
monitoring by large shareholders, having outside directors on the board, and the threat ofexternal takeovers. However, a number of studies, such as Hoshi, Kashyap and Scharfstein(1990) and Morck and Nakamura (1999) suggest that in Japan, these “conventional”
mechanisms described in the literature do not appear to play an important role, raising
the question whether there exists other mechanisms in Japan for the effective
monitoring of management. In Japanese firms, the president is often the mostpowerful figure among the board members.2 He normally identifies his successor andin practice has the final authority over personnel matters such as appointing andremoving directors/officers.3 Given this, without effective control, the president may
not run the firm in the interest of shareholders and perhaps select a successor or
promote an officer to the president position for selfish interest rather than with theinterest of shareholders in mind.
In order to avoid the conflict of interests between manager and sharholder, somestudies suggest managerial equity ownership can serve to align the interests ofmangers with those of shareholders and thus increase firm value (Jensen and

2

The directors in Japanese firms are ranked as chairperson (kaicho in Japanese), president(shacho in Japanese), vice-president, senior executives (senmu in Japnese), executives (joumu inJapanese) and non-titled directors. Nevertheless, in most firms the chairman is as an informal
position for the retiring president, who has no power to control the succession process. Hence, thepresident is conventionally viewed as the equivalent of CEO in the U.S.
3

Bonazzi and Islam point out that Japan’s corporate law empowers shareholders to choose
the board of directors. However, in practice, shareholders almost always vote for the slate
proposed by management. Moreover, this slate is approved by, if not chosen by, the very CEO
these directors are supposed to monitor.

Meckling, 1976; Morck et al., 1988, Morck et al., 2000).4 Yet, in Japan, the president
typically owns only a small stake in the firm. 5 Meanwhile, the threat of takeover
rarely happens in Japan, in this case, institutional shareholders are therefore
considered as the effective outside governance mechanisms to reduce agency cost,discipline managers (Aoki, 1988; Prowse, 1990; Kaplan and Minton, 1994). About
two-thirds of all shares of listed firms in Japan are held by corporate blockholders(Hodder and Tschoegl, 1992). Such corporate blockholders seldom sell their sharesand consistently support management. What is more, in the event that a company
encounters financial difficult, desirable from an efficiency point of view (Hoshi et al.,
1990; Morck and Nakamura, 1999). Therefore, rather than serving as a mechanism ofmonitoring managers, such stable relationships entrench mangers and serve as a formof insurance against liquidation of the firm. Consequently, in this type of set-up, it isdifficult to oust the incumbent management (Coffee, 1991).
One strand of the theoretical literature claims that product-market competition
has an important effect on managerial incentive. Machlup (1967) points out that there
is no scope for slack if a firm operates in a perfectly competitive output market. This
assertion is confirmed by Hart (1983), who developed a model that suggests that
average managerial slack is lower under competition than if there is a single
nonprofit-maximizing monopolistic firm. Scharfstein (1988), on the other hand,argues that the effect of competition on managerial incentives depends on thespecification of managerial preferences, and hence competition may exacerbate the4Berle and Means (1932) point out that when managers hold little equity in the firm andshareholders are too dispersed to enforce value maximization, corporate assets may be deployed tobenefit managers rather than shareholders. Jensen and Meckling (1976) argue that the costs ofdeviation from value maximization declines as management ownership rises. More recently,
Morck, Nakamura and Shivdasani (2000) have shown that the relationship between the managerial
ownership and firm value is monotonic for Japanese firms.
5

In the 1990s, the median (mean) shares of directors’ equity stake in the company they work
for was 1.9 percent (5.6 percent).

managerial agency problem when firm’s market profit target is low but its managerial
productivity is high. In this case, the manager has a greater incentive to underreport
his productivity. Scharfstein concludes that the effect of competition on managerial
incentives remains ambiguous. Seeking to reconcile the differences between Hart’s
and Scharfstein’s arguments, Schmidt (1997) argues that competition reduces
managerial slack, but this relation is not monotonic. He demonstrates that competition
increases the probability of liquidation, which has a positive effect on managerial
effort, but also reduces that firm’s profits, which may make the managerial position
less attractive to induce high effort. In a monopoly market, managerial effort may
increase as additional competitors enter the market, but will eventually decrease whencompetition becomes too intense.6
Numerous theoretical studies have investigated the relationship between
product market and managerial incentives, but the little empirical studies have
explored the relationship between competition and managerial incentive contract.7 To
fill the gaps on the empirical research, this analysis uses Japanese data to examine thecompetition effect on managerial incentive contract, which is measured by president
turnover and turnover patterns.

6

The example Schmidt provides is that in the 1990s, productivity improvements in theautomobile and computer industries dramatically exceeded average productivity growth.
7

However, although there is no direct evidence shown to support Schmidt’s argument,
several empirical studies indirectly demonstrate that regulatory and political constraints can have asignificant effect on top management incentive and governance, since regulations weaken the
incentives of shareholders and outsiders to discipline effectively top managers of large publicly
held corporations. The results of these studies show that managerial pay levels and payperformance sensitivities are lower for regulated industries than for unregulated industries.
Together, management turnover rate and turnover-performance sensitivities are lower for
regulated industries than for unregulated industries (Joskow et al, 1993; Cragg and Dyck, 1999).
Also, Porter (1990) argues that domestic competition generates world-beating industries. For
example, the Japanese success stories (e.g., cars, motorcycles, cameras) are precisely thoseindustries in which domestic competition is intense. On the other hand, those Japanese industries
in which domestic competition is feeble have shown little or no international success (e.g.,construction, commodity chemicals, and paper).

The empirical analysis here uses variations in product market competition acrossindustries and a comprehensive data set, consisting of 1,916 observations on
announcements of changes of president from 1991 to 2001. Japanese data setting
provides two advantages on exploring this issue. (1) The presence of various types ofcorporate governance in Japan provides the advantage on comparison of thesegovernance structures between the long-term relationship system and market-oriented
system. (2) Most Japanese listed firms release the news of president turnovers, andthis can avoid self-selection bias.
The findings obtained here are consistent with the assertion that there are distinct
differences between the rate of president turnover, and turnover patterns incompetitive markets and concentrated markets. More detailed, the rate of president
turnover is greater in competitive market than in less competitive market. Moreover,firms in competitive markets are more likely to take disciplinary action to remove
their presidents than firms in concentrated markets. The presence of a dominant firmin the industry also enhances the probability of disciplinary president turnover.
Consequently, these findings are consistent with Schmidt’s argument that thecompetition causes a threat of firm’s liquidation and therefore reduces managerial
shirk, suggesting that presidents face different contracts between competitive markets
and concentrated markets.
The remainder of this study is structured as follows: Section 2 outlines therelationship between market competition and management incentives as well as
related competition hypotheses. Section 3 describes the sample and data used in thisanalysis. Section 4 then presents descriptive statistics of the main variables as well as
the empirical results. Finally, section 5 concludes.

2. President Turnover and Competition Hypotheses
This section discusses the theoretical background to the analysis, presents theresults of previous empirical hypotheses and present the hypotheses tested in theanalysis. Beginning with the theoretical considerations managerial incentive contracts
can be said to be designed to tie either manager’s compensation to firm performanceor manager’s employment to firm performance. A representative example of theformer type of contract is market-oriented contract typically found in the UnitedStates. In contrast, an example of the latter type of contract is the managerial contract
typically found in Japan, where managers’ salary is determined by the limits to thetotal salary amount set out in the statutes of the corporation. Overall, the literaturesuggests that Japanese corporate governance is more financial institution-oriented
rather than market-oriented. However, using firm-level data, the analysis here willshow that the situation is not as clear-cut as is often made out and that Japanese firms,
too, use contracts that are market-oriented.
The theoretical model applied in this analysis is based on Schmidt’s (1997)
argument outlined above, namely that the degree of competition shapes managerial
incentives. Specifically, the argument is that managerial effort increases withincreasing competition, but will eventually decrease when competition becomes too
intense. The link between competition and managerial incentive is the optimal
incentive scheme employed by the owner of company, which is affected by the degreeof competition of company’s operating environment.
One of the earliest studies on this issue is the influential paper by Jensen andMeckling (1976), which demonstrated that the intensity of competition does not affectmanagerial incentive contracts because managerial slack is enjoyed by the manager ofthe firm, not by its owner. Therefore, the owner of a monopoly has the same interest
to reduce agency costs as the owner of a competitive firm, and they both should offer
exactly the same incentive scheme. In contrast to Jensen and Mecklings’ argument,
several theoretical studies have developed models for proving that market competitionof a firm is influential on its principal-agent contract. Most of the studies develop
competition and managerial incentive contract based on difference in informationspillover between competitive market and concentrated market. Lazear and Rosen(1981), and Nalebuff and Stiglitz (1983) analyzed moral hazard in general form interms of tournaments, and demonstrated that the presence of competitors allows a firm
to use relative performance to evaluate the ability or effort of its managers. This isconsistent with the arguments modeled by Machlup (1967) and Hart (1983),8 who alsosuggested that there is less scope for managerial slack in companies that operate incompetitive markets than in companies that operated in more concentrated markets.
In other words, information-based assertions imply that managers in higher
competitive markets are more likely to experience more stringent incentive schemes
provided by owners of firms than managers in less competitive markets. If the rate ofmanagerial turnover reflects the outcome of firms’ implicit contracts, we would
expect that managerial turnover is higher in competitive markets and lower inconcentrated markets.
An alternative hypothesis suggests that competition affects the structure ofcontracts. Harris and Raviv (1979) and Lewis (1980), for example, provide models inwhich managers do not differ in their ability, but many nevertheless receive distinct
contracts in different markets. Harris and Ravivs’ work shows that under somemonitoring mechanisms available, the results of monitoring can be incorporated into
contracts. The example the give is that most employer-employee agreements stipulate
some remuneration to the employee provided that he is judged to have performed
adequately. As a result, managers whose companies operate in a competitive market
are more likely to be fired for poor performance than mangers in a less competitive

8

Machlup (1967) argued that there is no scope for managerial slack if a firm operates in aperfectly competitive output market, and therefore suggests that imperfect competition in markets
is a necessary condition for the existence of managerial slack. Hart (1983) provides a modelshowing that competition reduces managerial slack; he suggests, however, that this is only
satisfied when firms’ costs and product prices fall jointly, and hence this gives the manager less
opportunity for slack, but competition may increase managerial slack if the product costs of
his/her company had fallen alone whereas product prices in the market had not changed.

market. If this reasoning is correct, we would expect to observe a higher rate ofdisciplinary managerial turnover in competitive markets than in concentrated markets.
On the other hand, Scharfstein (1988) developed a hidden information model, andargued that the competition effect on managerial incentives as also depends on thespecification of managerial preferences. He argued that competition may exacerbate
the managerial agency problem when the market profit target is low but managerial
productivity is high. In this case, the manager has a greater incentive to underreport
his productivity. Scharfstein therefore concluded that the effect of competition on
managerial incentives remains ambiguous. Similar ambiguity arises in a model
developed by Hermalin (1992). 9 However, no such ambiguity arises in the model
proposed by Schimidt (1997). Focusing on the threat-of-liquidation effect onmanagerial incentives, Schimidt found that there was non-monotonic relationshipbetween competition and managerial incentive. He demonstrated that competition
increases the probability of liquidation, which has a positive effect on managerial
effort, but that it also reduces that firm’s profits (manager’s expected income), which
may make it less attractive to exert a high level of effort. That is, starting from amonopoly, managerial effort may increase as additional competitors enter the market,
but will eventually decrease when competition becomes too intense. If we view either
a high rate of managerial turnover or disciplinary turnover as a less attractive contract
for managers in a highly competitive environment, Schimidt’s model predicts that therate of managerial turnover and the number of disciplinary replacements initially
increase with the degree of market competition but then eventually decrease whenmarket competition becomes very intensive.
Although there is a considerable number of theoretical studies on the relationshipbetween market competition and managerial incentives, empirical studies somewhat

9Hermalin (1992) focused on the change in relative bargaining power between managers andshareholders with the level of competition, and showed that the competition effect on this relative
bargaining power is ambiguous.

scarce. An important exception is the attempt by Nickell (1996) to link competition
theory and corporate performance is a significant study in this field. Nickell used dataon 670 UK companies to examine the effect of market competition, measured by the
number of firm entries and monopoly rent, on performance, measured by total factor
productivity (TFP). The result of his analysis show that greater competition isassociated with, which provides empirical support for the assertion that market
competition affects managerial incentives. Another empirical study on competition
and managerial employment contracts is that of Fee and Hadlock (2000), who use
data on the U.S. newspaper industry for the period 1950 to 1993 to examine therelationship between management turnover and product market competition. The
empirical results show that turnover rates are greater in competitive markets.10 Their
explain for their results observing that managers may have an incentive to work hardin a competitive environment to avoid liquidation, but the threat of liquidation also
generates an incentive to pursue alternative job opportunities. However, they find noevidence that the sensitivity of turnover to performance varies with the productmarket environment, and hence suggest that competition does not change theimportance of managerial ability and/or effort in the determination of profits.
However, the focus on a single industry ignores important issues regarding the natureof managerial incentives across industries.
To sum up, three potential relationships between competition on the one hand andthe rate of managerial turnover and patterns of managerial change are suggested bytheoretical studies discussed. The first relationship suggested is that the rate ofmanagerial turnover is constant irrespective of the degree of market competition, but
the pattern of managerial turnover changes with competition intensity. As illustrated
in Jensen and Mecklings’ (1976) model, regardless of the level of market competition,

10

Fee and Hadlock (2000) viewed a firm as in a competitive market if there is rival in citywhere it was located, and the basic statistics show that 48.4 percent of firms were operating in acompetitive market.

all owners of corporations have the same incentive to reduce managerial slack, whichsuggests companies in highly competitive markets and companies in concentrated
markets should have the same rate of managerial turnover. Nevertheless, sincecompanies in concentrated markets are less likely to face financial distress thancompanies in highly competitive markets, therefore their owners are less likely to takedisciplinary action to remove managers who are slack but reluctant to leave theirposition. Instead, retirement age rules and tenure-limit rule are the more likely
mechanisms for removing incumbent manager.
The second argument is that managers are given stringent managerial incentive
schemes provided by owners of companies in competitive markets. That is, increases
in the level of competition lead to a high rate of managerial turnover, and furthermore
managers in those highly competitive markets are likely to be fired for disciplinary
reasons, such as bad performance.
Finally, the third possible relationship, as suggested by Schmidt (1997), is thatcompetition reduces managerial shirking, but greater competition also reduces firms’
profit, which may make the managerial position less attractive for managers. Hence,owners of firms in intensively competitive markets might be less likely to either
change their managers frequently or adopt strict approaches on removing managers.
To examine the above three possible relationships, the first hypothesis to betested in the empirical analysis is whether president turnover increases withcompetition intensity. Further, the second hypothesis is that the pattern of president
turnover varies with the level of competition.

3 Sample and Data
A comprehensive dataset is constructed to examine the above hypotheses. The
dataset consists of four sub-datasets including firm-level information on board

structure, firms’ financial variables, industry-level indicators of the degree ofcompetition, and announcements changes of president reported in the press. The
analysis here focuses on manufacturing firms only for reasons of data comparability,
where manufacturing firms are defined as those firms with JIP 2006 codes 08 to 59(see Table 1 for a list of industries).11 Three manufacturing industries that have lessthan four firms at the JIP 2006 two-digit industry level (tobacco, leather, and leather
products) are dropped from sample. The final sample includes 48 industries
comprising 1,424 Japanese manufacturing companies, and the period covered is 1991
to 2001.
The main dataset on the board structure of listed firms is constructed from the
Toyo Keizai database. This comprehensive dataset includes the detailed personal
information on each director, such as the director’s full name, birthday, year of
becoming president, and former employment. Based on this dataset, we can identify
the year of president change took place, the tenure of removal president and whether
he moved on to less prestigious directorial position or departure from the company.
The other helpful piece of information concerns the former employment of eachpresident. Taking advantage of this information, a president is identified as an outsider
if he has experience working for other companies. As is well known, most “outside”
presidents in Japan come from other listed companies with which the company inquestion has business relationships. With regard to the pattern of president turnover,detailed data for the reason of the change in president are compiled fromannouncements in four major newspapers in Japan. In total, there are 1,916 instancesin the dataset on boards of directors indicating that a change of president took place.

11

The Japan Industrial Productivity Database (JIP2006) is based on survey data of the
Population Census, which is conducted every five years by the Research Institute of Economy,
Trade and Industry (RIETI). The JIP2006 classification contains 52 manufacturing industries at
the two-digit level. Thus, it has a wider coverage in term of number of industries than the JapaneseStandard Industry Classification (JSIC), which covers 24 manufacturing industries at the two-digit
level.

In addition to data on president turnover, measures of competition in a particularindustry are constructed. The sources for the relevant data are the JIP2006 database,and the Development Bank of Japan database, which provides financial data on
individual companies. The following sub-section present a detailed discussion of thedefinition of variables used in the analysis which will be important for theinterpretation of the results.
3.1 Competition Variables
This study uses several different measures of competition intensity: HirschmanHerfindahl Index (HHI), three import and export indices, price-cost margin (PCM),
and finally dominant-firm dummy. The first measure, HHI, is calculated at the
JIP2006 two-digit industrial level. This index measures industry concentration and isa widely used measure of industry competition.12 It is calculated as the sum of thesquares of firms’ market shares and a low value implies a low level of industry
concentration.13 Based on the HHI for 1996 (HHI96), the 48 manufacturing industries
in the JIP database are divided into quintiles, with the group of industries in which
competition is most intense labeled as Competition 1 and the group of industries
which are the most concentrated labeled as Competition 5. Each group contains
around 10 industries. The reason that the 48 industries are divided into five groups isthat using constant value as a proxy variable for dynamic alternation maybe

12

According to Sleuwaegen and Wim’s (1986) theoretical work, choosing between the HHI
and the concentration ratio (e.g., four-firm ratio) may provide empirically very different
information to assess industry performance. Therefore, in addition to the HHI, the four-firm ratio
is used as well to measure market competition. Yet, the competition intensity of individual
industry does not have substantial difference between HHI and four-firm ratio, and hence theindustry coverage in each category does not change much, either. The four-firm ratio was first
introduced by Saving (1970). The data for the calculation of the four-firm ratio used in this chapter
are also obtained form theJIP2006 database.
13

The value of HHI equals 10000 when there is only a single firm in the industry and tends
towards zero when there are more firms and greater degree of equality in market shares. A lower
index value signifies greater competition.

impropriety. HHI used in the analysis has been reported by RIETI every five years,
using the value of HHI96 of each industry for the competition in each year might
misrepresent the real competition among industries. For instance, perhaps the mostcompetitive industry among the manufacturing industries in 1996 was not the mostcompetition industry in 1998, but still fall into the highly competitive industry
category. Therefore, dividing the 48 industries into 5 groups rather than using theabsolute value of HHI96 is considered a better approach to define the market
competition in the analysis.
The 48 industries, and their HHI, are listed in Table 1. As can be seen, the HHI
ranges from 1.23 to 1531.77. The HHI of 1.23 for the steel industry, indicating thatcompetition is the most intense in the former, while the latter is the most concentrated.

(Insert Table 1)

However, the degree of competition in an industry varies over time. Thus, inaddition to the degree of competition over time are likely to also have an effect onpresident turnover. Three alternative measures of competition, which are compiled
annually, are also used in the analysis. The three measures are Import penetration, theExport-import ratio, and an Import-advantage dummy. These are expected to capture
the pressure of international competition and are calculated at the two-digit industry
level using data from JIP2006 database. Import penetration is calculated as the valueof imports divided by the value of all domestics plus imports minus exports. The
Export-Import ratio is calculated as the value of exports divided by the value ofimports. The Import-advantage dummy is equal to one if the value of import in thatindustry is greater than the value of export, and zero otherwise.
In addition, an industry is considered to be competitive industry if it has lowmonopoly rents. Monopoly rents are measured as the difference between price andmarginal cost in efficiency theory. The fundamental condition for the competitivemarket is that marginal cost equals price. By contrast, under monopoly or oligopoly,
the allocation of output will be inefficient because price will exceed marginal cost.
Therefore the measure of price-cost margin is used here to capture the monopoly rentsof markets. The calculation follows Lerner’s measure of monopoly power measuredas (P-MC)/P.14 In practice, it is difficult to observe marginal cost. Therefore, instead of
marginal cost, average cost (AC) is used here to draw inferences about monopoly
rents. Therefore, monopoly rent (PCM) is calculated as follows: 15

PCM= (P*Q- AC (Middle input, Labor cost, Capital cost)*Q) / P*Q.
Finally, because above measures of competition are calculated at the two-digit
industry level, which maybe too aggregated to represent the “market”, to address thisproblem, firms’ market share at the four-digit SIC level is employed as an additional
measure to capture more precise market information. The variable calculated at fourdigit SIC level is labeled as Dominant-firm dummy. This dummy variable takes avalue of one if a company operates in a market which exists a dominant firm who had
accounted for the largest market share throughout observed 11 years and zero if acompany operates in a market without a dominant firm. Even if a market iscompetitive, if one firm managers to reduce costs while the others do not, it will
become a monopolist. On the other hand, if there is a strong dominant firm in aconcentrated market, then all other firms are less likely to enjoy monopoly rents. A

14

15

The concept of PCM comes from Lerner’s index (1934), P=MCThe measure of PCM here is not calculated as exactly same way in the theory. See Hall(1988) for details of the calculation of PCM, and Cowling and Waterson (1976) for the
relationship between market share (e.g. HHI) and PCM.

further variable included is a dummy for internationalized firm that takes a value of
one if it exports, and zero otherwise. The inclusion of this variable is based on theempirical observation that many oligopolistic industries are under enormous pressure
to reduce costs. For example, in the automobile and computer industries productivity
improvements dramatically exceeded average productivity growth in recent years.
These industries liquidation became a serious threat even for industrial giants like GM
or IBM partly due to increased competition from abroad.

3.2 President Attributes and Firm Characteristics
In order to investigate the relationship between president turnover andcompetition, it is necessary to control for presidents’ personal attributes as well ascompanies’ attributes. First, the tenure and age of removal president havedemonstrated fairly consistent positive relationship with president turnover. As apresident’s length of tenure increases and/or he/she reaches retirement age, theprobability increases that he/she will leave voluntarily. Hence, length of tenure, age,and the squares of these two are included as variables. Second, several variables tocontrol for company characteristics, such as firm size, board size, and board
characteristics, are included. It is expected that greater firm size is associated withhigher president turnover. Moreover, according to previous research (Yermack, 1996),
larger boards experience more difficulties in accomplishing firm objectives. If this is
the case, smaller boards may tend to have lower rate of president departure due to thefact that they have fewer decision-making and communication problems. In addition,agency theory suggests that directors who sit on large boards may be less inclined toresign from the board than directors that sit on small boards. Slack presidents withlittle equity shares can be easily removed by disgruntled institutional investors orousted by hostile raiders attracted by a depressed share price. However, presidents
with large blocks of equity cannot be casted out in these ways. Hence, Directors’shares_ratio is added as a variable to capture the effect of equity ownership onpresident turnover. A further control variable is the ratio of outside directors to total
directors (Outsider ratio), since firms with a high ratio of outside directors are likely
to have higher president turnover. Besides, previous empirical research has identified
the prior industry relative performance and industry performance as potentially
important determinants of president turnover. Industry-relative ROA, Adjfirmperformance, is a proxy variable for firm performance, computed as the sample
firm’s return on assets, minus the industry (4-digit SIC) median return on assets.
Industry median returns on assets are based on the population listed firms in industry.
It is expected to observe that presidents who performer badly would be asked to leave
before tenure is accrued. Industry performance is also controlled.

3.3 Turnover Patterns
Since the removal of the president is one of the most drastic and visible actions
taken by a company when it is confronted with increasing competition, the analysis
here also examines whether output market competition leads to an increases in thedisciplinary replacements of presidents. In order to examine patterns in president
turnover, the reasons underlying the change in president in the 1916 president
turnover events in the database are identified and divided into three groups:
disciplinary replacements, non-disciplinary replacements, and residual replacements.
The reasons for a change in president are determined on the basis of new releases
Turnover reasons of each firm are searched in the Nikkei News database. This
database covers the daily issues of the Nihon Keizai Shimbun, Nikkei Kinyu Shimbun,
Nikkei Sangyo Shimbun, and Nikke Ryutu Shimbun (business papers similar to theWall Street Journal). The classification of reasons for the replacement of a president
follows the example of Kang and Shivdasani (1995). Disciplinary replacements
include those for corporate losses, a worsening of business performance, andcorporate restructuring. In contrast, a president replacement is considered to be a nondisciplinary succession when it follows the tenure rules of the organization. Therefore
non-disciplinary replacements include presidents resigning for reasons other than age,retirement, long tenure (more than 6 years) or illness. The final group consists of allresidual replacements, such as when the only reason cited was the need for younger
management, no reasons were given at all, or no news could be found regarding a
specific replacement. Included in this final group are also instances where a newpresident was names as a result of a scandal or the death of the incumbent president.
Before dividing the residual turnovers into disciplinary and non-disciplinary
turnovers, it is worthy knowing the custom of president turnover in Japan. In general,
there are two types of tenure rules that are followed by many Japanese firms: The
two-year unit term rule or tenure-limit rule is an inflexible rule that stipulates that apresident be replaced after a fixed period of time. Japanese presidents are typicallyawarded a two-year contract and likely to be offered a renewal based on two-yearbasis. The term of tenure may vary across firms, yet it is common for a president toresign at the end of the two-year term, not in the middle of the term. Therefore, in theannouncement, the tenure of president change is often described as two-term-fouryear or three-term-six-year, meaning the president has served for two or three 2-year,
making four or six years in total. Thus, taking these Japanese customs into account, it
seems reasonable to assume that a replacement of president is likely to fall into thedisciplinary category when his tenure is less than six years and into the nondisciplinary category otherwise.
In addition to the tenure-limit rule, the most common tenure rule among large
firms in Japan is the retirement age rule. The age of sixty-five is a socially accepted
retirement age that is widely adopted by Japanese firms. Individuals described as
retiring are symmetrically distributed around the age commonly used in retirement
policies (65) and the mean retirement age of total sample is 65.33.

Table 3 lists the reasons reported in the four Nikke-related newspapers forchanges in president among listed manufacturing listed firms in Japan. Of the total
1916 cases, 595 fall into the disciplinary category, with poor company performance
being mentioned in 225 cases, the need for a young manager mentioned in 102 cases,
the need for new management with certain required skills mentioned in 100 cases,
strong ties with major shareholder or other companies mentioned in 61 cases,
increasing industry competition mentioned in 47 cases, corporate restructuringmentioned in 31 cases, and the president taking a job in another firms mentioned in 18
cases. 759 cases fall into the non-disciplinary categories, with long tenure (298 cases)
and company stabilized or performing well (252 cases) given as the most frequentreasons. Other common reasons include old age or the reaching of the retirement age(108 cases) and poor health or illness (74 cases). Listing in the First Section of thestock exchange and anniversary of the company were cited in 18 cases and 9 cases,
respectively.
503 cases fall into the residual category, with no reason provided in 443 cases.
Finally, in 59 cases, the reason for replacement was the death of the presidents. These
cases are excluded from the analysis below.

(Insert Table 3)

4. Empirical methodology and results
The first hypothesis, whether president turnover increases with competition
intensity, is tested by panel logit models where the dependent variable is a dummy
variable taking a value of one if a change in president took place and zero otherwise.
The following logit model is employed.
P( y  1| X )  G( X )  p( X )(1)

In the analysis here, (1) can be rewritten as
P(turnover  1 | president attributes , firm characteristics , industry performance, competitio n)

The probability of a change in president change isG( X )  exp( X ) /[1  exp( X )]where

X  x1 , x2 , xi(2)

In the case of continuous explanatory variables, such as president tenure, age,
firm performance and the PCM, the partial effect (marginal effect) of x i on p(X ) isp( X )
 g ( X )  i
xi

where

g ( X ) dG( X )d ( X )(3)

On the other hand, in the case of discrete explanatory variables, such ascompetition intensity, the dominant-firm dummy and the international firm dummy,
the marginal effect of x i on p(X ) is simplyG( x1 1  xi  i )  G( x1 1  xi 1  i 1 )(4)

For ease of interpretation, instead of coefficients  i , the marginal effects, (3) and(4), are reported as the derivative of the probability of president turnover with respect
to the corresponding right-hand-side variable computed at the mean of the dependent
variable. This represents the marginal impact of a change in the explanatory variable.

To examine the effect of competition on president turnover, the HHI and thedominant-firm dummy are included as proxy variables for competition in the logit
regressions shown in Table 5. The dominant-firm dummy takes a value of one if thecompany operating in a market where there existed one company who had accounted
for the largest market share throughout the observed period 1991 to 2001, and zerootherwise. Three specifications are used that differ in the inclusion of interaction
terms between competition indicators and firm characteristics.
The results presented in Table 5 show that, as expected, the likelihood of a change
in president significantly increases with length of tenure. Moreover, the effects of firm
size and the ratio of outside directors are positively and statistically significant. Not
surprisingly, firm performance and industry performance are always jointly negativeand significant, indicating the underperformance in the market encourages firms tochange presidents. However, the marginal effect on the equity shares owned bydirectors is not statistically significant.
The results of the competition effect on president turnover indicate that the rate ofpresident turnover increases with the level of market competition. In specification (1),
we observe that the marginal effect of Competition 2 is -0.0192, that of Competition 3-0.0195, and that of Competition 5 -0.0216, indicating that in a highly competitivemarket (Competition 1) the rate of president turnover is significantly higher than in
the other markets, while it is lowest in the most concentrated markets (Competition 5).
This indicates that there is a positive correlation between competition intensity andthe rate of president turnover. However, this relationship is not monotonic. In
specification (2), interaction terms between the dominant firm dummy and thecompetition intensity variables are included to examine whether the existence of adominant firm in a competitive market decreases the probability of a change inpresident. A negative sign of interaction terms would support this hypothesis.
However, the results are not significant, that is, they do not support this assertion.

Next, in specification (3), interaction terms between the industry-adjusted firm
performance variable and the competition variables are added. It the marginal effectsof these interaction terms turn out to be negative and decreasing with the degree ofcompetition, this would indicate that president turnover is more sensitive to bad
performance in a competitive market than in a concentrated one. In other words, anegative and highest marginal effect of Competition 1*Adj-firmperformance among
five categories supports threat-of-liquidation argument that the probability ofliquidation increases the rate of president turnover. The results for specification (3)indicate that turnover rates indeed vary with the degree of competition but do notsupport the hypothesis that president turnover in a competitive market is moresensitive to bad performance than in a less competitive market. Interestingly, themarginal effect of interaction between Competition 5 and industry-adjusted firm
performance on the turnover rate is positive and significant, suggesting that a firmwith superior performance in a concentrated market is more likely to change itspresident frequently than a firm with a superior performance in a competitive market.
This result implies that the determinants of president change vary with competition
intensity. Therefore, we further investigate the effect of competition on turnover
pattern in various markets in the next section.

(Insert Table 5)

Before examining the pattern of president turnover across competition degrees,
several alternative measures of competition are used for a robustness check. The
marginal effect of competition variables on president turnover is estimated and theresults are shown in Table 6. In specification (1), the competition variables based on
the HHI are replaced with the PCM takes replace with HHI. In specification (2) andspecification (3), the international firm dummy is included. As Porter (1990) hasconvinced, Japan’s success stories are those industries in which domestic competition
is intense, while those industries in which domestic competition is feeble have little orno international success. Thus, if international firms face greater pressure fromoverseas competitors than domestic firms, we should observe that international firms
display a high rate of president turnover. However, the results presented in Table 6 do
not provide evidence to support this argument, suggesting that alternative measures ofcompetition do not affect president turnover.

(Insert Table 6)

4.1 Competition and the Pattern of President Turnover
The results above (Table 6) provided no support for the hypothesis that the degreeof competition, as measured price-cost margins, import penetration, or the presence ofa dominant firm in the industry, increases the probability of president turnover. There
are at least two possible explanations. The first is that, at the two-digit industry level,
these indicators are too aggregate to accurately reflect the degree of competition in
output markets. The second is that, rather than increases the probability of president
turnover, competition changes the pattern of president turnover. To examine the latterargument, we further explore the relationship between competition and three different
types of turnovers, namely disciplinary turnover, non-disciplinary turnover andresidual turnover. Multinomial logistist regressions are employed to the analysis here.
The methodology is applied to cases where an unordered response has more than two
outcomes. An individual chooses one alternative from the group of choices, and thelabeling of the choices is arbitrary (Wooldridge, 2001). Here, Y denotes a randomvariable referring to the outcome “disciplinary turnover,” “non-disciplinary turnover,”or “residual turnover,” while X denotes a set of conditioning variables which include
president attributes, firm characteristics, industry performance, and competition. Asusual, ( xi , y i ) is a random variable draw from the population. Like the logit model inTable 6, the multinomial logit model in Table 7 explains how the changes in theelements of X affect the probabilities of disciplinary, non-disciplinary, and residual
president turnovers.
Taking non-disciplinary turnover as a benchmark, the probabilities of disciplinary,
non-disciplinary and residual president turnover are as follows:P(Y  disciplinary | X )  exp( X disciplinary ) /[1  exp( X disciplinary )  exp( X residual]P(Y  non  disciplinary | X )  1 /[1  exp( X disciplinary )  exp( X residual]P(Y  residual | X )  exp( X residual) /[1  exp( X disciplinary )  exp( X residual]

(5)
(6)
(7)

Where the dependent variables take a value of one if the type of turnover wascoded as “disciplinary,” “non-disciplinary,” or “residual”. Each group performs three
specifications which differ in the interaction terms. The marginal effects as thederivatives of the probability of type of president turnover with respect to thecorresponding x i computed at the mean of the dependent variable are reported inTable 7. 16
The results in Table 7 indicate that a greater degree of competition increases theprobability of a disciplinary change in president. On the other hand, there is no
significant impact of the degree of competition on non-disciplinary president changes.
Overall, the probability of disciplinary turnover increases with poor firm performanceand poor industry performance. Both non-disciplinary and residual turnovers increase
with the superior firm performance. However, non-disciplinary turnover is positively

16

The expression of marginal effect for multinomial logit model is omitted here. See

Woodldridge (2002) for details.

related to industry performance, while residual turnover is not associated withindustry performance. In addition, firms with more outside directors are more likely
not to release news when their president changes than other firms.

(Insert Table 7)

With regard to the probability of a disciplinary change in CEO, the dominant-firmdummy is positive and significant in two of the specifications. This result is consistent
with the argument of Schmidt (1997) that if a dominant firm is successful in reducing
costs while all other firms are not, competition will drive profits down to zero.
Consequently, in order to compete with the dominant firm on market share, firms arelikely to dismiss slack managers. This suggests that the peer in the industry is a
substitute mechanism for corporate governance. Interestingly, we observe a positivecoefficient on the interaction term between the degree of competition and thedominant-firm dummy in specification 2. This implies that the presence of a dominantfirm in less competitive markets raises the probability of a disciplinary change inpresident, whereas in intensively competitive markets, the presence of a dominantfirm increases the likelihood of disciplinary replacement. This result also indirectly
supports Schimidt’s argument that when competition becomes too intense, firms’
profits are driven to zero, which may make the managerial position less attractive tomanagers. Consequently, firms operating in highly competitive markets are less likely
to force a president to leave, since otherwise they may face difficulties in hiring a newpresident.
Next, alternative measures of competition to the HHI are used to rerun the
regressions shown in Table 6. The results are shown in Table 8a to 8c. The results
show that monopoly rents (PCM) has adverse effect on disciplinary president change,
but positive effect on with non-disciplinary turnover. However, both relationships arenot significant. In specification (2) in Table 8a, the international-firm dummy, theimport penetration variable and the interaction term between these are included. The
positive coefficient on the import penetration variable indicates that competitive
pressure from international rivals spurs firms to take the most drastic and visible
actions to change slack managers. Further evidence of the effect of international
competition on disciplinary president turnover is provided by the significantly
negative coefficient on Export-Import ratio in specification (3) and the fact that thecoefficient on the import-advantage dummy remains significantly positive in
specification (4). However, the estimate of international firm dummy is statisticallysignificant.
Taken as a whole, the evidence reported in Table 8a appears to weakly support the
hypothesis that competition as measured by import penetration, the export-importratio, and the import-advantage dummy at two-digit level increases the probability of
disciplinary turnover. However, the presence of a dominant firm in an industry does
not appear to have an effect on disciplinary president turnover.

(Insert Tables 8a, 8b, 8c)

5. Conclusion
Using several measures of competition, this analysis provides examined whether
increased competition in product market increases the probability of president
turnover. Controlling for CEOs’ age and tenure, several firm attributes, theperformance from of the industry in which a firm operates, and the deviation of thefirm’s performance from industry performance, the results show that the probability ofpresident turnover is greater in highly competitive industries than in lowly
competitive industries. This result is consistent with the argument of the competitioneffect on managerial incentive contracts. This conclusion is further supported by thefact that the degree of competition in an industry has a significant effect on theprobability of a disciplinary change in president. These results hold not only when the
HHI is used as the measure of competition, but also when alternative measures areused, such as import penetration or the ratio of export sales to import sales. The
presence of a dominant-firm also has a significant positive effect on the likelihood of
disciplinary turnover, indicating that the presence of a dominant firm in the industry
increases effort incentives because the all firms face intensive competition on gaining
market share. Conclusively, the findings in this analysis support that competition nonmonotonically reduces managerial shrink and further suggest that managerial
incentive contracts in Japan are designed on the basis of the market competition.

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Table 1. List of the 48 industries in JIP 2006 used in this research ranked interms of the HHI for 1996
SIC
15
17
16
41
58
19
33
20
59
40
43
11
44
13
57
37
12
51
52
8
45
42
46
53
29
28
24
30
50
54
55
34
35
22
39
49
25
26
10
18
56
48
32
38
47
23
27
36

competition
Competition 1
Competition 1
Competition 1
Competition 1
Competition 1
Competition 1
Competition 1
Competition 1
Competition 1
Competition 2
Competition 2
Competition 2
Competition 2
Competition 2
Competition 2
Competition 2
Competition 2
Competition 2
Competition 2
Competition 3
Competition 3
Competition 3
Competition 3
Competition 3
Competition 3
Competition 3
Competition 3
Competition 3
Competition 3
Competition 4
Competition 4
Competition 4
Competition 4
Competition 4
Competition 4
Competition 4
Competition 4
Competition 4
Competition 4
Competition 5
Competition 5
Competition 5
Competition 5
Competition 5
Competition 5
Competition 5
Competition 5
Competition 5

HHI96

Industry name
Number of Firms
1.23 Textiles
71
3.5 Furniture12
3.62 Lumber
10
4.43 Other metal products
426.03 Plastic products
33
6.93 Paper products
13
8.23 Clay products
22
9.23 Publisnh and printing
15
9.48 Other manufacturing36
12.95 Metal products
38
13.76 Special machinery equipment
96
14.48 Other foods
70
16.51 Other general machinery products
24
29.05 Beverages
23
32.18 Precision machinery & equmipment
4332.3 Other steel
41
36.23 Fertilizers
6
39.53 Semiconductor devices, integrated circuits
939.53 Electronic parts
68
47.73 Livestock products
17
52.35 Office and services
25
55.89 General machinery equipment
6272.27 Electrical machinery
30
73.45 Other electrical machinery
675.73 Other chemical products
46
81.62 Chemical final products
55
85.48 Organic chemical basic products
32
90.17 Petroleum products
896.48 Electric measuring instruments
27
99.6 Motor vehicles
12
99.6 Motor vehicles, components
8699.7 Stone products
11
99.7 Other stone, clay & glass products
23
101.03 Rubber products
21
106.43 Non-ferrous metals processed products
30
110.6 Wired communication equipment, radio communication equipment, other31
communication
139.93 Non-organic chemical basic products
5
139.93 Organic chemical products
46
151.65 Rice polishing flour milling7158.39 Pulp, paper
22163.03 Other transportation equipment (ships)
29
163.73 Electric computing equipment (main parts, accessort equipment)
14
187.44 Glass products
11244.73 Non-ferrous metals
15244.74 Equipment and supplies for household use
32
270.21 Chemical fertilizers
4
819.73 Chemical fibers
51531.73 Steel manufacturing
16

Source: Research Institute of Economy, Trade and Industry, “JIP Database 2006,” online:
http://www.rieti.go.jp/en/database/d05.html.
Note: Industry competition categories are ranked based upon the square root of the HHI for 1996.
Processed marine products, tobacco, leather and leather products, and coal products are dropped
from the sample since the number of firm is less than four, which may cause sample bias in theanalysis.

Table 2. Descriptive statistics on all observations used in analysis from 1991 to 2001
1
1

2

1

3

4

5

6

7

8

9

10

2
3

0.038
0.007

1
0.937

1

4
5

0.236
0.244

0.227
0.250

0.237
0.261

1
0.995

1

6
7
8

0.019
0.030
-0.001-0.086-0.1260.011-0.060-0.105
0.010

0.105
0.115
-0.0350.099
0.110-0.03310.800
1-0.023 -0.023

9
10

0.073
-0.012-0.181-0.015-0.140-0.004

0.063
0.069

0.049
0.071

-0.2680.546-0.1970.393-0.012-0.0201-0.276

1

11
12
13
14
15

-0.059-0.0480.003
0.018-0.018

0.085
0.063
0.005
-0.093
0.007

0.074
0.041
0.002
-0.097-0.011

0.005-0.0310.020
0.066-0.0140.009-0.0270.017
0.063-0.010

0.072
0.021
0.108
0.153
0.059

0.037
0.040
0.113
0.141
0.024

-0.004-0.0210.011-0.012-0.008-0.031-0.045-0.0570.085-0.037

16
17

0.007
0.024

-0.030-0.046-0.023-0.035

0.071
0.035

0.070
0.032

0.186
0.372

0.171
0.431

0.001
-0.00618
19
200.005 -0.028
0.019 -0.009-0.0008 0.014-0.0270.013
0.015-0.0250.020-0.008-0.0300.021-0.0040.095-0.006-0.0490.099-0.044-0.045-0.013
0.013
0.009

11

12

13

14

15

16

17

0.058
0.032
0.030
0.031
0.058

1
-0.1371-0.014 0.065
1-0.005 -0.062 0.053
0.038 0.252 -0.062

1
0.007

1

-0.073-0.087

0.161
0.116

-0.0420.020

0.109-0.009-0.047
0.074

0.124
0.117

-0.013-0.048

1
0.189

1

0.101
-0.038-0.0890.045
0.011-0.041-0.0340.022-0.007-0.007-0.2080.123

0.025-0.054
0.063

0.231
0.055
-0.223-0.235-0.1750.148

0.201-0.015-0.2680.135-0.002-0.100

Variables
6 Log assets
7 Board size
8 Directors' shares_ratio
9 Outsider ratio
10 Listed market#

Variables
11 Adj-firmperformance
12 Industry performance
13 Dominant firm dummy
14 HHI
15 PCM

#

18

19

20

1
-0.378-0.554

1
0.250

1

1

Name of Variables#

Variables
1 Turnover
2 Tenure
3 Tenure^2
4 Age
5 Age^2#

Variables
16 International firm dummy
17 Firm export
18 Export-import ratio
19 Import penetration
20 Import-advantage dummyTable 3. Reasons cited for replacement of president among manufacturing firms whose president changed during 1991-2001

Stated Reasons
Disciplinary
Poor company performance
Need for younger management
Need for new management with required skills
Strong ties with major shareholder or other companies
Increasing industry competition
Corporate restructing
Take job in another firms
Merge
Subtotal
Non-disciplinaryLong tenure
Company stabilized or performaing well
Old age or retirement age
Poor health or illness
Listing in upper section of stock exchange
Anniversary of company
Subtotal
Residual
No reasons given
No news released
ScandalSubtotal
Death
Total

Insider->Insider

Insider->Outsider Outsider->Insider Outsider->Outsider

Total number ofpresident changes

103
49
66
10
33
9
9
4
283

38
4
6
11
3
9
2
3
76

23
11
8
8
3
6
3
0
62

61
38
20
32
8
8
4
3
174

225
102
100
61
47
32
18
10
595

171
131
61
47
9
7
426

31
24
9
4
1
1
70

17
34
15
8
1
1
76

79
63
23
15
7
0
187

298
252
108
74
18
9
759

108
18
17
143
29
881

44
1
1
46
9
201

39
10
0
49
13
200

185
11
2
198
8
567

443
40
20
503
59
1916

Table 4. Descriptive statistics on financial and governance characteristics.
Characteristic

Obs

Mean

MedianMax

Min

Turnover=0
Turnover
TenureTenure^2AgeeAge^2Log assets
Board size
Directors' shares_ratio
Outsider ratio
Listed market
Adj-firmperformance
Industry performance
Dominant firm dummyCompetition Intensity
PCM
International firm dummy
Firm export (million)
Export-import ratio
Import penetration
Import-advantage dummy
Turnover
TenureTenure^2AgeeAge^2Log assets
Board size
Directors' shares_ratio
Outsider ratio
Listed market
Adj-firmperformance
Industry performance
Dominant firm dummyCompetition intensity
PCM
International firm dummy
Firm export (million)
Export-import ratio
Import penetration
Import-advantage dummy

11809
0
11777
7.52
11777
129
11807
61.7
11807
3855
11786
17.8
11539
17.2
11809
3.2
11539
0.176
11809
0.599
11785
0.0017711800
0.0252
11809
0.709
11809
2.75
11795
6.98
11809
0.453
11809
21.9
11795
3.29
11795
0.080811809
0.304
Turnover=1
1916
1
1912
8.45
1912
135
1909
66.3
1909
4427
1911
17.8
1910
17.8
1916
2.99
1910
0.21
1916
0.582
1911
-0.0108
1916
0.0215
1916
0.713
1916
2.81
1916
6.57
1916
0.463
1916
31.2
1916
3.34
1916
0.0851
1916
0.303

0
4
16
63
3969
17.6
16
0
0.133
1
0.00134
0.0266
1
3
5.15
0
0
1.93
0.0616
0

0
52
2704
90
8100
22.8
61
7354
0.864
1
1.59
0.105
1
5
46.7
1
3840
26.4
0.533
1

0
1
1
34
1156
13.5
4
0
0
0
-3.73
-0.121
0
1
-26
0
-75.4
0.006310.00169
0

1
6
36
67
4489
17.6
16
0
0.175
1
-0.00179
0.0228
1
3
4.72
0
0
1.95
0.0632
0

1
53
2809
91
8281
22.7
61
3736
0.852
1
0.627
0.105
1
5
46.7
1
4100
26.4
0.533
1

1
1
1
36
1296
14.1
4
0
0
0
-1.76
-0.11901-26
000.006310.001690Note: The sample consists of 1,424 Japanese manufacturing firms. The time period covered fiscal 1991
to 2001. Turnover takes a value of one if a change of president occurred and 0 otherwise.

Table 5. Panel logit analysis of president turnover: Base-line regression
Estimated M odel:

Proability(Pres ident turnover)=f.(Pres ident attributes , firm performance,indus try performace,manufacturing performance,Competition)

Exp lanatory Variable
Comp etition2Comp etition3
Comp etition4
Comp etition5
Dominant firm dummy(1)-0.0192[2.64]***-0.0195[2.58]***-0.0181[2.40]**-0.0216[2.59]***-0.0002[0.03]

Comp etition2*Dominant firm dummyComp etition3*Dominant firm dummyComp etition4*Dominant firm dummyComp etition5*Dominant firm dummy(2)-0.0151[1.13]-0.0118[0.85]-0.0294[2.14]**-0.0291[2.08]**
0.0000[0.00]-0.006[0.38]-0.012[0.73]
0.018[0.83]
0.014[0.59]

Comp etition2*Adj-firmp erformance
Comp etition3*Adj-firmp erformance
Comp etition4*Adj-firmp erformance
Comp etition5*Adj-firmp erformance
TenureTenure^2AgeAge^2Log assets
Listed market
Board size
Directors' shares_ratio
Outsider ratio
Adj-firmp erformance
Industry p erformanceYear dummy
BIC
N

0.013
[10.83]***-0.0004[11.61]***
0.008
[1.1]
0.0001[0.82]
0.010[2.67]***-0.018[2.76]***
0.001[1.17]
0.00003[1.17]
0.148[9.03]***-0.247[6.94]***-0.532[4.51]***
Yes
9712
13367

0.013
[10.77]***-0.0004[11.60]***
0.008
[1.1]
0.0001[0.83]
0.010[2.67]***-0.019[2.80]***
0.001[1.15]
0.00003[1.18]
0.147[8.99]***-0.245[6.90]***-0.521[4.37]***
Yes
9747
13367

(3)
-0.0198[2.72]***-0.0195[2.59]***-0.0184[2.45]**-0.0204[2.43]**-0.0001[0.01]-0.104[1.05]-0.101[0.93]-0.140[1.12]
0.168[2.04]**
0.013[11.17]***-0.0004[11.87]***0.007[1.03]
0.0001[0.92]
0.009[2.63]***-0.017[2.59]***
0.001[1.19]
0.00003[1.1]
0.147[8.96]***-0.246[3.36]***-0.564[4.79]***
Yes
9734
13367

Note: The sample consists of 1,424 Japanese manufacturing firms. Time period covers fiscal years of 1991 to
2001. The dependent variable in the panel logit model is coded 1 if a change of president occurred and 0
otherwise. Instead of coefficients, the marginal effects of the regressors on the probabilities are shown in thetable.

Table 6. Panel logit estimate of president change: Alternative regression
Estimated Model:

Proability(President turnover)=f.(President attributes, firm performance,industry performace,manufacturing performance,Competition)

Explanatory Variable

Dominant-firm dummy

(1)

(2)

(3)

(4)

-0.003[0.35]

0.000[0.07]-0.006[0.73]

0.000[0.04]
0.001[0.13]

0.000[0.02]

International firm dummy
Firm export-value0[0.88]

PCM

0.000[0.75]

Import penetration

0.033[0.83]

Export-import ratio

0.001[0.82]

Import-advantage dummy

0.007[1.25]

Dominant-firm dummy *
PCM

0.000
[0.46]

International firm dummy * Import penetration

0.035[0.54]

International firm dummy * Export-import ratio-0.001[0.78]

Import-advantage dummy * Firm export
TenureTenure^2AgeAge^2Log assets
Listed market
Board size
Directors’ shares_ratio
Outsider ratio
Adj-firmperformance
Industry performanceYear dummy
BIC
Obs.

0.013
[10.82]***-0.0004[11.57]***0.008[1.08]
0.000[0.83]
0.009[2.40]**-0.018[2.72]***
0.001
[1.21
0.00003[1.24]
0.144[8.81]***-0.245[6.89]***-0.535[4.43]***
Yes
9702
13367

0.012
[9.58]***-0.0004[10.43]***0.010[1.38]
0.000[0.51]
0.007[1.91]*-0.016[2.46]**
0.001[1.47]
0.00003[1.15]
0.144[8.67]***-0.261[7.05]***-0.589[4.87]***
Yes
9950
13426

0.012
[9.56]***-0.0004[10.41]***0.010[1.32]
0.000[0.57]
0.007[1.88]*-0.016[2.46]**
0.001[1.46]
0.00003[1.17]
0.143[8.49]***-0.261[7.05]***-0.607[5.05]***
Yes
9951
13426

0.000
[0.77]
0.012[9.56]***-0.0004[10.40]***0.010[1.35]
0.000[0.53]
0.007[1.94]*-0.016[2.41]**
0.001[1.18]
0.00003[1.14]
0.147[8.79]***-0.260[7.04]***-0.607[5.04]***
Yes
9940
13426

Table 7. Estimated multinomial logit models of president turnover regressed oncompetition variables
Estimated M odel:

Proability(type of Pres ident turnover)=f.(Pres ident attributes , firm performance,indus try performace,manufacturing performance,Competition)
Dis ciplinary

Exp lanatory Variable

(1)

(2)

Comp etition2-0.044[1.39]
Comp etition3-0.056[1.72]*
Comp etition4-0.128[4.37]***
Comp etition5-0.061[1.68]*
Dominant firm
0.059
[2.44]**
Comp etition2*Dominant firm

-0.030[0.92]-0.048[1.39]-0.122[3.99]***-0.049[1.30]
0.057[2.37]**
1.033[1.78]*
Comp etition3*Dominant firm
0.607
[0.91]
Comp etition4*Dominant firm
0.539
[0.83]
Comp etition5*Dominan tirm
1.218
[1.81]*
Comp etition2*Adj-firmp erformance
Comp etition3*Adj-frmp erformance
Comp etition4*Adj-firmp erformance
Comp etition5*Adj-firmp erformance
Tenure0.001[0.14]
Tenure^2-0.0001[0.82]
Age-0.072[2.67]***
Age^20.0005[2.20]**
Log assets
0.023[1.48]
Board size
0.002
[0.61]
Directors' shares_ratio
0.001[0.35]
Outsider ratio-0.017[0.23]
Listed market
0.013[0.47]
Adj-firmp erformance-1.672[7.88]***
Industry Performance-2.105[3.73]***
Year dummy
Yes
BIC
3698
N
1824

0.001
[0.16]-0.0001[0.83]-0.075[2.77]***
0.0005[2.29]**
0.022[1.38]
0.002[0.69]
0.001[0.37]-0.015[0.21]
0.013[0.48]-2.384[5.00]***-2.232[3.98]***
Yes
3751
1824

Non-dis ciplinary(3)-0.024[0.40]-0.050[0.84]-0.164[2.64]***-0.081[1.21]
0.062[1.18]-0.037[0.54]-0.013[0.17]
0.055[0.54]
0.029
[0.3]
0.001
[0.17
-0.0001[0.86]-0.071[2.65]***
0.0005[2.19]**
0.023[1.49]
0.002[0.58]
0.001[0.32]-0.016[0.22]
0.012[0.42]-1.661[7.86]***-2.132[3.78]***
Yes
3755
1824

Res idual

(4)

(5)

(6)

(7)

(8)

-0.016[0.40]
0.014[0.34]
0.070[1.71]*
0.068[1.47]-0.039[1.41]-0.025[0.65]
0.007[0.18]
0.066[1.61]
0.060[1.29]-0.037[1.33]-1.120[1.67]*-0.080[0.10]-0.216[0.28]-0.794[0.92]-0.099[1.44]-0.033[0.46]
0.055[0.68]
0.042[0.49]-0.098[1.56]

0.059[1.79]*
0.042[1.21]
0.059[1.63]-0.007[0.18]-0.020[0.90]

0.056[1.68]*
0.040[1.15]
0.056[1.56]-0.011[0.29]-0.020[0.92]
0.087[0.17]-0.527[0.90]-0.323[0.55]-0.425[0.60]

0.015[3.03]***-0.0002[1.48]
0.049[1.36]-0.0003[1.06]
0.031[1.72]*-0.004[1.16]-0.001[0.36]-0.250[3.06]***
0.011[0.34]
1.266[5.19]***
2.260[3.51]***
Yes
3698
1824

0.015
[2.98]***-0.0002[1.43]
0.050[1.4]-0.0003[1.11]
0.033[1.82]*-0.004[1.28]-0.001[0.37]-0.250[3.06]***
0.010[0.32]
1.834[3.27]***
2.444[3.76]***
Yes
3751
1824

0.114
[1.44]
0.064[0.75]
0.007[0.07]
0.030
[0.3]
0.015
[2.94]***-0.0002[1.36]
0.047[1.31]-0.0003[1.02]
0.031[1.75]*-0.004[1.12]-0.001[0.33]-0.252[3.09]***
0.012[0.39]
1.253[5.15]***
2.319[3.57]***
Yes
3755
1824

-0.016[3.87]***
0.0003[2.80]***
0.024[0.84]-0.0002[0.80]-0.054[3.84]***
0.002[0.75]
0.001[0.36]
0.267[4.45]***-0.024[0.98]
0.406[2.27]**-0.155[0.32]
Yes
3698
1824

-0.016[3.82]***
0.0003[2.74]***
0.024[0.85]-0.0002[0.81]-0.054[3.86]***
0.002
[0.8]
0.001
[0.37]
0.265[4.40]***-0.023[0.96]
0.550[1.28]-0.212[0.44]
Yes
3751
1824

(1)
0.123
[1.98]**
0.084[1.32]
0.109
[1.5]
0.039
[0.52
0.036
[0.75]-0.077[1.49]-0.051[0.89]-0.061[1.02]-0.060[0.92]-0.016[3.79]***
0.0003[2.70]***
0.025[0.87]-0.0002[0.83]-0.055[3.88]***
0.002[0.73]
0.000[0.33]
0.268[4.45]***-0.024[0.98]
0.408[2.28]**-0.187[0.38]
Yes
3755
1824

Note: Instead of coefficients, the marginal effects of the repressors on the probabilities are shown in the table.
The values in brackets are the absolute value of z-statistics. *, **, *** indicate significance at the 10%; 5%;
and 1% level, respectively.

Table 8a. Estimated multinomial logit models of disciplinary president
turnover regressed on alternative measures of competition
Estimated Model:

(1)
0.036
[1.16]

Dominant firm dummyInternational firm dummy

(2)
0.053
[2.21]**
0.067[1.86]*(3)
0.053[2.22]**-0.061[1.82]*

Firm export

0.000[1.16]

PCM-0.002[0.72]

Import penetration

0.406[2.47]**

Export-import ratio-0.014[2.80]***

Import-advantage dummy

0.090[3.37]***

Dominant firm dummy*PCM

0.002
[0.8]

International firm dummy*Import penetration-0.526[1.83]*

International firm dummy*Export-import ratio

0.025[3.79]***

Import-advantage dummy*Firm export
TenureTenure^2AgeAge^2Log assets
Listed market
Board size
Directors' shares_ratio
Outsider ratio
Adj-firmperformance
Industry performanceYear dummy
BIC
Obs.

(4)
0.049
[1.99]**

0.001[0.15]-0.0001[0.77]-0.075[2.76]***
0.0005[2.29]**
0.022[1.41]
0.010[0.36]
0.001[0.29]
0.001[0.47]-0.052[0.71]-1.704[7.95]***-2.229[3.85]***
Yes
3683
1824

0.001
[0.21]-0.0001[0.82]-0.078[2.85]***
0.0005[2.37]**
0.020[1.29]
0.007[0.25]
0.001[0.27]
0.001[0.46]-0.043[0.59]-1.665[7.84]***-1.831[3.27]***
Yes
3693
1824

0.001
[0.13]-0.0001[0.77]-0.073[2.71]***
0.0005[2.23]**
0.024[1.53]
0.006[0.21]
0.000[0.06]
0.001[0.4]-0.045[0.61]-1.692[7.95]***-1.989[3.62]***
Yes
3685
1824

0.000
[1.00]
0.002[0.35]-0.0001[0.97]-0.073[2.67]***
0.0005[2.19]**
0.021[1.36]
0.018[0.63]-0.001[0.24]
0.001[0.35]-0.015[0.20]-1.690[7.91]***-2.302[4.18]***
Yes
3676
1824

Note: The dependent variable in the multinomial logit model is coded 1 if the president turnover
happened and 0 otherwise. In stead of coefficient, the marginal effects of the repressor on the probabilities
are shown in the table.

Table 8b. Estimated multinomial logit models of non-disciplinary president
turnover regressed on alternative measures of competition
Estimated Model:(1)-0.002[0.05]

Dominant firm dummyInternational firm dummy(2)-0.033[1.19]-0.029[0.73](3)-0.034[1.25]
0.088[2.37]**

Firm export

0.000[4.93]***

PCM

0.001
[0.34]

Import penetration-0.311[1.56]

Export-import ratio

0.011[2.20]**

Import-advantage dummy-0.064[2.24]**

Dominant firm dummy*PCM-0.005[1.60]

International_firm*Import_penetration

0.596[1.84]*

International_firm*Export-import ratio-0.020[2.74]***

Import-advantage dummy*Firm export
TenureTenure^2AgeAge^2Log assets
Listed market
Board size
Directors' shares_ratio
Outsider ratio
Adj-firmperformance
Industry performanceYear dummy
BIC
Obs.

(4)
-0.033[1.21]

0.015[2.94]***-0.0002[1.42]
0.052[1.45]-0.0003[1.14]
0.032[1.84]*
0.012[0.4]-0.003[1.05]-0.002[0.48]-0.216[2.68]***
1.334[5.36]***
2.498[3.73]***
Yes
3683
1824

0.015
[2.91]***-0.0002[1.38]
0.057[1.59]-0.0004[1.28]
0.032[1.84]*
0.010[0.32]-0.003[1.00]-0.001[0.46]-0.227[2.81]***
1.266[5.13]***
1.896[2.96]***
Yes
3693
1824

0.015
[2.92]***-0.0002[1.38]
0.053[1.48]-0.0003[1.18]
0.030[1.69]*
0.010[0.32]-0.003[0.82]-0.001[0.41]-0.229[2.80]***
1.292[5.24]***
2.018[3.19]***
Yes
3685
1824

0.000
[0.44]
0.014[2.71]***-0.0002[1.22]
0.053[1.47]-0.0003[1.16]
0.029-1.6200.008[0.25]-0.003[0.90]-0.001[0.36]-0.240[2.95]***
1.293[5.26]***
2.228[3.53]***
Yes
3676
1824

Note: The dependent variable in the panel multinomial logit model is coded 1 if the president turnover isdisciplinary change and 0 otherwise. In stead of coefficient, the marginal effects of the repressors on theprobabilities are shown in the table.

Table 8c. Estimated multinomial logit models of residual president turnover regressedon alternative measures of competition
Estimated Model:

Dominant_firm dummy(1)-0.034[1.20]

International_firm dummy(2)-0.021[0.94]-0.038[1.25](3)-0.019[0.87]-0.027[0.91]

Firm export
PCM

0.000
[9.96]***
0.001-0.460

Import penetration-0.095[0.60]

Export-import ratio

0.003-0.800

Import-advantage dummy
Dominat firm dummy*PCM-0.026[1.27]
0.003[1.12]

International firm*Import penetration-0.071[0.27]

International firm*Export-import ratio-0.005[0.88]

Import-advantage dummy*firm export
TenureTenure^2AgeAge^2Log assets
Listed market
Board size
Directors' shares_ratio
Outsider ratio
Adj-firmperformance
Industry performanceYear dummy
BIC
Obs.

(4)
-0.015[0.72]-0.016[3.78]***
0.0003[2.68]***
0.023[0.82]-0.0002[0.79]-0.054[3.90]***-0.022[0.93]
0.003[0.94]
0.001[0.47]
0.268[4.48]***
0.370[2.03]**-0.269[0.54]
Yes
3683
1824

-0.016[3.82]***
0.0003[2.70]***
0.020[0.72]-0.0002[0.68]-0.052[3.78]***-0.017[0.71]
0.002[0.91]
0.001[0.46]
0.270[4.54]***
0.398[2.17]**-0.065[0.13]
Yes
3693
1824

-0.015[3.73]***
0.0003[2.63]***
0.020[0.71]-0.0002[0.67]-0.053[3.85]***-0.016[0.66]
0.003[1.03]
0.001[0.41]
0.273[4.56]***
0.400[2.19]**-0.029[0.06]
Yes
3685
1824

0.000
[0.87]-0.015[3.80]***
0.0003[2.74]***
0.020[0.73]-0.0002[0.70]-0.050[3.59]***-0.025[1.07]
0.004[1.36]
0.000[0.36]
0.254[4.32]***
0.398[2.24]**
0.073-0.160
Yes
3676
1824

Note: The dependent variable in the multinomial logit model is coded 1 if the news of president turnover is notrevealed or not given and 0 otherwise. In stead of coefficient, the marginal effects of the repressors on theprobabilities are shown in the table.