Impact of Split Share Structure Reform in China on CEO
Accountability to Corporate Fraud
Douglas Cumming, Wenxuan Hou and Edward Lee
Schulich School of Business, York University, Canada; Durham Business School, University of
Durham, UK; Manchester Business School, University of Manchester, UK
ABSTRACT We examine the influence of state ownership on CEO accountability to corporate fraud
using the unique setting of the Split Share Structure Reform in China. This reform enables state
shareholders to trade their shares in the stock market, which increases the sensitivity of their wealth to
the market value of their firms. Therefore, this reform aligns the incentives of state and private
shareholders to monitor and discipline managers against opportunistic behavior that could reduce
firms‟ market value. We observe less CEO turnover following corporate fraud among state-controlled
firms prior to this reform, except for serious fraud cases that could affect firm reputation or public
outrage. Following the reform, we observe increased CEO turnover following corporate fraud among
state-controlled firms, especially among those more willing to participate in the reform process. Our
evidence suggests that the Split Share Structure Reform improved managerial accountability and
contributes to corporate fraud deterrence in China.
Keywords: Corporate fraud; CEO turnover; State ownership; Split Share Structure Reform; China
Corresponding author: Douglas Cumming, Schulich School of Business, York University, 4700
Keele Street, Toronto, Ontario, Canada, M4P 2A7 (dcumming@schulich.yorku.ca).
0
INTRODUCTION
We examine the impact of the Split Share Structure Reform in China on CEO accountability to
corporate fraud. China is an increasing influential emerging country that is aspiring to become one of
the largest economies in the world. Corporate fraud can impede this economic development due to the
serious consequences to stakeholders (Davidson and Worrell, 1988), employees (Zahra et al., 2005),
and society (Szwajkowski, 1985). Existing studies confirm that top management is an important
antecedent of corporate fraud (Daboub et al., 1995; Donoher et al., 2007; Dunn, 2004) and is held
accountable for its consequences (Karpoff et al., 2008; Person, 2006). Despite these facts, the
association between corporate fraud and managerial accountability in China has not been well
examined. While existing studies of corporate fraud in China (Chen et al., 2006; Jia et al., 2009)
largely focus on the influence of corporate governance, previous studies on Chinese CEO turnover
mainly investigate the link with firm performance (Conyon and He, 2008; Firth et al., 2006b; Kato
and Long, 2006a, 2006b; Shen and Lin, 2009). We fill this literature gap by exploiting the unique
research setting of stock market reform in China.
The Split Share Structure Reform that started in 2005 marks a major change in the institutional
setting of the Chinese stock market. Before this reform, state shareholders held restricted shares that
cannot be traded freely in the stock market as the shares held by private shareholders. This split share
structure generates a conflict of interest between state and private shareholders since the former group
is deprived of the wealth implication of share price movement in the stock market. As a result, the
widespread concentration of state ownership in Chinese listed firms induces less incentive alignment
effect and more entrenchment effect among state shareholders and impedes corporate governance.
The reform eliminates this split share structure and increases the sensitivity of state shareholders‟
wealth to share price movement. This is expected to should align the incentive of state and private
shareholders to monitor and discipline managers against opportunistic behaviors that could decrease
market value of their firms.
Based on the assumption that political connections reduce managerial accountability in
1
state-controlled Chinese listed firms (Bruton and Lau, 2008; Judge and Bretz, 1994; Wei et al., 2010)
and that this effect is moderated by external public opinion pressures (Chen et al., 2005; Liebman and
Milhaupt, 2008) as well as corporate ownership reform (Connelly et al., 2010), we make the
following predictions. First, the propensity of CEO turnover following regulatory enforcement action
against corporate fraud is lower among state-controlled Chinese listed firms than their
privately-controlled counterparts. Second, the propensity of CEO turnover following enforcement
actions is likely to be similar between state- and privately-controlled Chinese listed firms only for
serious fraudulent cases, as state shareholders need to maintain firm reputation and avoid public
outrage. Third, the propensity of CEO turnover following enforcement actions should increase
among state-controlled listed firms after the Split Share Structure Reform, which increases the
incentives of controlling shareholders to prevent fraudulent behaviors that could reduce firm value.
Finally, if this reform indeed increases the CEO turnover propensity following enforcement actions
among state-controlled listed firms, then this impact is expected to be greater among such firms with
greater willingness to participate in the reform process.
We confirm these hypotheses through a sample of Chinese listed firms over the period of 1999
to 2008, which includes 409 cases of regulatory enforcements actions against corporate fraud each
matched with comparable firms by year, industry, and size. Our findings have the following
implications. First, while some existing studies argue that political connection is a managerial
resource that benefits Chinese firms (Luo, 2003; Xin and Pearce, 1996), we show that it can also
impede managerial accountability. Second, consistent with previous studies that suggest state
ownership impedes corporate governance (Megginson and Netter, 2001; Tihanyi and Hegarty, 2007),
we find that state controlling shareholders in Chinese firms have less incentives to discipline
fraudulent executives, except in cases of pronounced external pressure. Finally, in line with studies
showing that state-owned enterprises in China are adapting to market-oriented economy (Lin and
Germain, 2003; Ralston et al., 2006), we provide original evidence that aligning the state
shareholders‟ wealth to their firms‟ market value benefits private shareholders.
2
CORPORATE FRAUD AND REGULATORY ENFORCEMENT IN CHINA
Existing studies have identified several antecedents of corporate fraud. External factors include
industry cultures (Baucus and Near, 1991), industry concentration (McKendall and Wanger, 1997),
environmental hostility (Baucus and Baucus, 1997), and environmental dynamism (Hansen et al.,
1996). Internal factors includes top management (Ashforth and Anand, 2003; Baucus, 1994), board
composition (Dunn, 2004), and organization culture (McKendall and Wanger, 1997). Black (2005)
classifies fraud into reactive and opportunistic. The former occurs when executives responds to
declining firm performance by window dressing financial statements and the latter occurs when
executives seizes an opportunity for further gain by manipulating disclosure. Schnatterly (2003)
suggest that traditional corporate governance mechanisms such as blockholders, boards, and CEO
compensation have limited effect on reducing corporate fraud. Berenson (2003) suggest that despite
of decades of continued effort to reform corporate governance, to align managers‟ incentives with
shareholders‟ interest, and impose code of conduct for managerial ethics, corporate fraud remains
uncurbed in the US.
Corporate fraud common among Chinese listed firms ranges from delaying disclosure,
providing false statement, to embezzlement (Chen et al., 2005). Fraudulent behaviors are motivated
by two general factors. First, corporate fraud may be stimulated by regulatory pressure and financial
needs (Szwajkowski, 1985). In China, listing on the stock exchange is only allowed for firms with at
least two consecutive years of operating profit (Aharony et al., 2000) and listed firms must maintain a
minimum of 10% return on equity (ROE) for three continuous years before they can issue additional
shares (Chen and Yuan, 2004). Furthermore, listed firms with two consecutive years of losses will be
placed under special treatment and a further year of losses will result in such firms being suspended
from trading or delisted (Jiang and Wang, 2008). Although the Chinese authority imposes these rules
to guide outside capital toward well-performing firms, it also gives listed firms ample motivation to
carry out managerial misconduct. Second, corporate fraud may be more common in a dynamic and
3
rapidly evolving environment (Baucus and Near, 1991). Changing rules and weak legal institutions in
a transitional economy like China encourages firms to carry out opportunistic behavior. For instance,
Allen et al. (2005) suggest that China provides the weaker investor protection than other major
emerging countries.
The China Securities Regulatory Commission (CSRC) serves as the main regulator of securities
markets in China and is modeled after the Securities and Exchange Commission (SEC) in the US. As
part of the responsibility of CSRC to oversee the securities markets, it investigates and disciplines
corporate fraudulent behavior. The basic regulations against corporate fraud include the „Provisional
Regulations Against Securities Frauds’, „Temporary Rules for Stock Issuance and Stock Exchanges
Regulation‟, and „Solutions for Prohibiting Securities Fraud‟. The CSRC carries out this duty
through regular reviews and random inspections of firms. It also responds to information and
complaints of fraud allegations from investors, employees, and media. If misconduct is confirmed,
the CSRC‟s enforcement actions could range from internal and public criticism to criminal
prosecution. The CSRC have been criticized for being ineffective in identifying and prosecuting fraud
(Anderson, 2000). The power of CRSC may affected by political pressures since it is a ministry-level
commission that answers to the state (Chen et al., 2005; Liebman and Milhaupt, 2008).1
Existing studies of corporate fraud in China show consistent evidence of the influence of
corporate governance. Chen et al. (2006) document a lower propensity of fraud among firms with a
higher proportion of non-executive directors or with separate person serving as CEO and chairperson.
They interpret these findings as evidence that outside directors provide more effective monitoring
role and that CEO duality encourages abuse of managerial power. Jia et al. (2009) provide evidence
that firms with larger and more active supervisory boards are more likely to face severe CRSC
sanctions for fraud.
1
Similar issue also arise in the US. The SEC is funded by the US Government and are susceptible to political pressures
(Correia, 2009).
4
STATE OWNERSHIP AND CORPORATE GOVERNANCE IN CHINA
Ownership concentration exerts two counteracting effects on corporate governance (Claessens
et al., 2002; La Porta et al., 1999). First, there is an incentive alignment effect (Shleifer and Vishny,
1986) if large shareholders‟ interests and wealth are associated with the value of the firm that they
control. Incentive alignment discourages large shareholders from expropriating funds from their firm,
which could reduce its share value in the stock market. Second, there is an entrenchment effect
(Shleifer and Vishny, 1997) broadly similar to the consequence when managerial ownership increases
above an optimal level (Morck et al., 1998; Stulz, 1988). Due to the dominance of their control, large
shareholders can pressure the management to pursue their interests, and are insulated from the
discipline of outside investors through the stock market.
The literature based in western developed economies often associate large shareholders with
incentive alignment effect and are more motivated in monitoring executives (Jensen and Meckling,
1976; Shleifer and Vishny, 1986). For instance, Kaplan and Minton (1994) show that the presence of
large shareholders is associated with increased management turnover. Bertrand and Mullainathan
(2001) provide evidence that firms with large shareholders impose tighter control over executive
compensation. Hartzell and Starks (2003) find that institutional ownership concentration is
negatively related to the level of executive compensation, and positively related to the sensitivity of
executive compensation to performance.
Unlike western developed economies, in the context of developing countries like China, state
shareholders that control listed firms are more likely to be associated with the entrenchment effect
than incentive alignment effect, and more likely to hamper corporate governance at the expense of the
interests of outside minority investors (Fan et al., 2007). This negative role of state shareholders in
emerging countries like China is due to two reasons. First, since the managers of state-controlled
listed firms are appointed and/or influenced by the government, they are largely insulated from
monitoring by outside investors, and are expected to achieve political rather than profit-maximizing
objectives (Shleifer and Vishny, 1997). Second, the prevalence of state ownership fosters the
5
entrenchment effect and encourages collusion between executives to divert firm resources (Claessens
et al., 2002), and/or to extract benefits (Shleifer and Vishny, 1986) at the expense of outside investors.
To cover-up self-serving behavior, state-controlled listed firms in China may withhold unfavorable
information, and/or manage the release of price-sensitive information (Fan and Wong, 2005). As a
result of the lack of information and the high degree of state ownership, outside private investors in
Chinese listed firms also have fewer incentives to exercise their right to monitor the executives
(Tenev et al., 2002).
Empirical evidence generally confirms that state ownership impedes the corporate governance
of listed firms. For instance, Gul et al. (2010) report that the low stock price informativeness of listed
firms in China relative to other countries, as documented by Morck et al. (2000), is more pronounced
among state-controlled firms. Empirical studies also suggest such firms have greater earnings
management (Ding et al., 2007) and higher likelihood to choose small local auditors (Wang et al.,
2008). These findings suggest that corporate transparency is weak in China and especially among
firms controlled by state shareholders. Conyon and He (2008) find that CEO turnover is less sensitive
to share price performance in Chinese listed firms controlled by the state. This finding implies that
CEOs of such firms have greater job security and are less accountable for poor performance. Kato and
Long (2006a, 2006b) find that privately-controlled Chinese listed firms are more likely to experience
performance improvement after the replacement of CEO. This result suggests that such firms are
more able to appoint skillful or talented CEOs than the state-controlled listed firms. Finally, Chen et
al. (2008) document that firms which voluntarily switch from dominant state ownership to dominant
private ownership are associated with improved performance. They interpret this finding as evidence
that private control is superior to state control of listed firms in China.
THE SPLIT SHARE STRUCTURE REFORM IN CHINA
Since the early 1990s, many state owned enterprises in China became partially privatized and
issued shares that are traded on the stock exchanges. Nevertheless, the state (including central and
6
local government) often retained sufficient shares to maintain control of these listed firms. This
approach distinguishes China from other transitional economies, where the government has
relinquished all ownership (e.g., Russia). Today, a majority (nearly 70%) of firms listed on the
Chinese stock exchanges are still dominated by state ownership, with private investors playing the
role of minority shareholders.
Mainland China has two stock exchanges, i.e. Shanghai and Shenzhen, which currently list well
over 1,500 firms. There are four kinds of shares issued by Chinese listed firms. The A shares
(denominated in RMB) could only be traded by domestic investors originally, but can also be
accessed by Qualified Foreign Institutional Investors (QFII) since 5th November 2001. The B shares
(denominated in US$) could only be traded by foreign investors originally, but can also be traded by
domestic investors since 12th February 2001. The H shares (denominated in US$ and HK$) are issued
by firms that are listed on the Hong Kong stock exchange. The final type of shares is issued by firms
cross-listed abroad, such as on the New York (NYSE) and London (LSE) stock exchanges.
The A shares are further classified into two groups, i.e. the restricted shares and the
freely-tradable shares. This is known as the split share structure. Restricted shares are not freely
tradable on the stock exchanges and can only be transferred privately or auctioned, usually at a
discounted value relative to the firm‟s freely tradable shares (Chen and Xiong, 2001), which are
largely held by outside private investors. There are separate categories of restricted shares for state
and legal person. State restricted shares are held by central and local government through their
bureaucratic agencies or affiliated SOEs. Legal person restricted shares are held by any of the above
or by private entities.
The split share structure is based on the socio-political ideology in China. On the one hand, the
government still intends to retain some influence over firms to achieve political and social objectives.
On the other hand, the government also wants to transform the Chinese firms into modern enterprises
that are capable of raising their own capital in the market. However, studies reveal that the
maintenance of state ownership through split share structure reduces the quality of firms‟ corporate
7
governance and their performance efficiency (Sun and Tong, 2003; Wei et al., 2005). Since
controlling state shareholders held restricted shares that are not tradable, their wealth is not
determined by stock returns. Thus, the controlling shareholders have limited incentive to monitor
managers and ensure that they maximize firms‟ market value. For instance, Firth et al. (2006; 2007)
confirm that CEO compensation in state-controlled listed firms is not sensitive to share price
performance and only sensitive to operating performance. They also suggest that this sensitivity is
low, and unlikely to provide executives with incentives to increase profit and firm value.
Aware of the drawback of the split share structure, the CSRC announced on 29th April 2005 its
decision to gradually release of all restricted shares into the secondary market. As an initial pilot, two
batches of firms were selected in 9th May and 19th June 2005. Official guideline containing formal
operational procedures was issued on 12th September 2005. To prevent adverse market response,
which occurred in the previous reform attempt (Kim et al., 2003), negotiations with existing tradable
shareholders were carried out to agree on a satisfactory level of compensation (Firth et al., 2010).
Upon the completion of the negotiation process, the portion of restricted shares paid out as a
consideration to the minority private investors becomes immediately tradable. Twelve months later,
shareholders who possess less than 5% of the firm‟s total share value can trade any of their restricted
shares in the stock market. Twelve and twenty-four months after this date, larger shareholders are
allowed to trade up to 5% and 10% respectively of their restricted shares. Finally, thirty-six months
after the negotiation is completed, all restricted shares become fully tradable in the stock market.
Since all Chinese listed firms complete their negotiations by end of 2008, all of their restricted shares
became fully tradable by the end of 2011.
HYPOTHESES DEVELOPMENT
The aforementioned literature review highlights two key issues related to our study. First, the
motivation for corporate fraud is rife in China, possibly due to its rapidly changing the environment
as a transitional economy (Baucus and Near, 1991) and institutional environment (Firth et al., 2006).
8
Second, political connection reduces executive accountability (Bruton and Lau, 2008) and state
control impedes corporate governance (Tihanyi and Hegarty, 2007) among Chinese listed firms. We
intersect these two strands of literature to examine whether the accountability of CEOs to the
fraudulent behavior they instigate is influenced by state ownership among listed firms in China.
As mentioned earlier, the executives of state-controlled listed firms are appointed and/or
influenced by the state. Since both the CEO and controlling shareholders are not independent, this
encourages them to collude at the expense of the interest of private minority shareholders. The
maintenance of state ownership through restricted shares renders the wealth of controlling
shareholders of such firms indifferent to stock return performances, which further reduces their
incentives to monitor and ensure managers maximize firms‟ market value. Therefore, we expect
CEOs turnover in state-controlled Chinese listed firms to depend less on fraud than
privately-controlled listed firms. Therefore, we hypothesize that:
H1: The propensity of CEO turnover following regulatory enforcement actions against
corporate fraud is lower among state-controlled listed firms than privately-controlled listed
firms in China.
Although we expect CEOs of state-controlled Chinese listed firms to be less accountable to their
fraudulent behavior, it may be difficult for state controlling shareholders to justify more serious cases
such as those that invoke public outrage and severe regulatory enforcement actions. To reduce
damages to the firms‟ reputation and political capital, even state-controlled listed firms are likely to
distant itself from CEOs under such circumstances. Defending CEOs that deliberately seek to mislead
the public or are judged by regulatory authority to require criminal prosecution are more likely to
provoke adverse public opinion against the firm. Thus, we also hypothesize that:
H2: Evidence in favor of hypothesis H1 is more pronounced among less serious corporate
9
fraud or regulatory enforcement cases since these are less likely to provoke public outrage.
Following the Split Share Structure Reform, the restricted shares used to maintain state ownership
became gradually tradable in the stock market. This reform makes the wealth of controlling
shareholders in state-controlled Chinese listed firms more sensitive to stock return performance. As a
result, state shareholders are more concerned than before about the negative stock market reaction
that would ensue should they protect the job security of CEOs that instigate fraudulent behavior. In
other words, the accountability of CEO to corporate fraud is expected to increase after the reform.
Since the Split Share Structure Reform mainly affects the state shareholders, it provides a useful
setting of exogenous regulatory change to test the influence of state ownership on the relationship
between corporate fraud and CEO turnover. Thus, we hypothesize that:
H3: Evidence in favor of hypothesis H1 is less pronounced among state-controlled listed
firms after the Split Share Structure Reform.
It is possible that unidentified confounding effects influence the corporate governance incentives of
state-controlled listed firms and fraud separately. Thus, we consider whether the link between fraud
and CEO turnover is more pronounced among firms with a greater willingness to participate in the
reform. We assume that firms that payout more restricted shares as compensation to tradable
shareholders are more committed and responsive to the reform. Thus, we hypothesize that:
H4: Evidence in favor of hypothesis H3 is more pronounced among state-controlled listed
firms that agree to payout more restricted shares to tradable shareholders as compensation.
There are two possible arguments against our hypotheses H3 and H4. The first argument is that,
despite ending the trading restrictions, state shareholders will never trade their shares due to
10
government pressure. As a result, state shareholders will not increase their incentive to monitor and
ensure managers maximize firms‟ market value. However, this argument neglects an established
Chinese government policy known as “Zhua Da Fang Xiao”, which seeks to sustain state ownership
only in strategic enterprises (e.g., energy, transportation, aerospace, defense, etc.) and to reduce the
state control over less essential businesses.2 Anecdotal evidence from the media also confirm that
previously restricted shares held by state shareholders have been actively traded in the stock market
following this reform.3 Furthermore, even if all state shareholders do not suddenly flock to trade their
shares after the restriction is abolished, it does not imply they have absolutely zero motivation to
increase their firms‟ market performance. On the contrary, those that hold on to the shares in
anticipation of long-term growth prospects have even more incentives to monitor the executives.
Finally, the corporate governance benefit of this reform that we expect is directly generated through
the alignment of incentives between state and private shareholders and is not dependent on the change
in ownership structure from state to private shareholders.
The second counterargument is that there is no corporate governance incentive effect that is
possible until all the restricted shares of a firm have become fully tradable, i.e. thirty-six months after
the ratification of the firm‟s compensation plan. According to this argument, the effect of the reform
across all firms in the Chinese stock market can only be examined using a post-2011 sample.
Therefore, our study cannot capture the incentive effect associated with the reform. However, this
argument assumes that all restricted shareholders are too myopic and unsophisticated to prepare and
plan ahead. The CSRC‟s announcement in 2005 cleared away all ambiguity on the government‟s
2
For instance, this policy has been laid out in the Ninth Five-Year Plan for National Economic and Social Development
and the Outline for the Long-Range Objective Through the Year 2010.
3
We list a few recent financial news articles here by translating their Chinese language headlines into English language
and provide their web link for reference:
 “29 firms this year experienced local government stock ownership reduction”
http://finance.ifeng.com/stock/zqyw/20110827/4474686.shtml
 “Selling shares – July wave of government stock ownership reduction wave”
http://stock.hexun.com/2011-07-29/131890710.html
 “Local government July stock ownership reduction in 25 listed firms to cash in 3.3billion RMB”
http://www.beelink.com/20110808/2808514.shtml
.
11
intention to expand the reform across all Chinese listed firms. Eager restricted shareholders would be
expected to increase their pressure on managers to improve their firms‟ market value before their
shares become eligible for trading; the higher is the share price before they sell, the more they will
profit when trading is allowed. It is time consuming to identify and operate profitable investment
projects that could boost the market value of a firm. Thus, restricted shareholders are unlikely to wait
until their shares become tradable to begin this process. As mentioned earlier, restricted shareholders
can sell all or a portion of their holdings within the thirty-six months following ratification of the
compensation plan, depending on the proportion of ownership. Thus, this argument also naively
ignores the wealth implication of a rising share price for the restricted shareholders over this period.
SAMPLE AND METHODOLOGY
Sample Description
The data for regulatory enforcement actions against corporate fraud being disclosed, firms‟
ownership status, firms‟ characteristics and performance, as well as firms‟ corporate governance variables
are obtained either from the CCER/Sinofin (China Centre for Economic Research) or GTA/CSMAR
(China Stock Market and Accounting Research). Over the ten year sample period of 1999 to 2008, we
identified 409 fraud cases where valid data for all variables used in the analysis are available. These
variables include firm size, market-to-book ratio, return-on-asset, stock returns, special treatment status,
ownership concentration, proportion of restricted shares, foreign ownership, CEO duality, number of
board meetings, board size, board independence, and supervisory board size. We begin our sample from
1999 because our control variables are lagged relative to the dependent variable and among them the
corporate governance variables we use are only available since 1998. For each firm that committed fraud,
we identify a comparable firm that did not commit fraud by matching year, industry, and size following
Jia et al. (2009).4 Thus our full sample contains 818 observations, i.e. 409 × 2.
4
Kothari et al. (2005) suggest that matching is superior since does not impose a specific functional form on the
relationship between the variable of interest and the control variables. Barber and Lyon (1996) also suggest that matching
firms yields well-specified and powerful test statistics
12
Table I presents the yearly (Panel A) and industry (Panel B) distributions of the corporate fraudulent
activities and the firms that committed them. In each panel, we report the number of fraud cases (Fraud
Cases), the number of firms involved (Fraud Firms), the proportion of fraud committing firms among all
listed firms in the stock market (Fraud/Total Firms), the proportion of fraud committing firms that are
state-controlled (State/Fraud Firms), the proportion of fraud committing state-controlled firms among all
state-controlled listed firms in the stock market (Fraud/Total State Firms), and the proportion of
state-controlled firms among all listed firms in the stock market (State/Total Firms). Panel A reveals that
Fraud Cases and Fraud Firms increased substantially from 2001 onward. The State/Fraud Firm ratio
peaks in 2002 even though State/Total Firm ratio is highest in 1999. Thus, we control for year effect in
our analysis. Panel B suggest that the Materials and Consumer Discretionary are the two sectors with the
highest Fraud Cases and Fraud Firms and the Telecommunication sector has the highest Fraud/Total
State Firms ratio. Thus, we control for industry effect in our analysis.
-----------------------------------INSERT TABLE I ABOUT HERE
----------------------------------------------
Hypotheses Tests
To test hypotheses H1 to H2, which contain our predictions concerning the impact of state
control of listed firms on the relationship between regulatory enforcement actions against corporate
fraud and subsequent CEO turnover propensity, we apply logistic regression analyses based on
Equation 1 below on the full sample and sub-samples partitioned by fraud and enforcement type:
Turnoveri ,t   0   1 Fraud i ,t 1   2 State i ,t 1   3 Fraud i ,t 1  State i ,t 1
  4 MVi ,t 1   5 PBi ,t 1   6 ROAi ,t 1   7 RETi ,t 1   8 STi ,t 1
  9 OWNC i ,t 1  a10 FOWN i ,t 1  a11 RESH i ,t 1  a12 DUAL i ,t 1
  13 BMEETt i ,t 1  a14 BSIZE i ,t 1  a15 BINDi ,t 1  a16 SBSIZE i ,t 1
 Industry  Year   i ,t
13
(1)
The dependent variable Turnover equals 1 if CEO turnover occurred in the fiscal year and 0 otherwise.
Fraud equals 1 if the firm experience regulatory enforcement actions against corporate fraud in the
fiscal year and 0 otherwise. State equals 1 if the firm is state-controlled and 0 otherwise. MV is firm
size measured as log market capitalization. PB is firm growth measured as price-to-book ratio. ROA
is firm profitability measured as industry-adjusted return-on-asset. RET is annual stock return over
risk free rate. STPT equals 1 for firms on the verge of special treatment (i.e. those with two
consecutive years of losses) and 0 otherwise. OWNC is ownership concentration measured by the
Herfindahl index and based on the ownership held by the ten largest shareholders in the firm. FOWN
is the proportion of shares held by foreign shareholders. RESH is the ratio of restricted shares to total
shares. DUAL equals 1 for firms with CEO also serving as board chairman and 0 otherwise. BMeet
equals 1 for firms with above median number of board meetings and 0 otherwise. BSIZE equals to 1
for firms with board size above the cross-sectional median and 0 otherwise.. BIND equals 1 for firms
whose proportion of independent directors is above the cross-sectional median and 0 otherwise.
SBSIZE equals 1 for firms with supervisory board size above the cross-sectional median and 0
otherwise. In this analyses, α1 indicates whether current year CEO turnover is related to past year
regulatory enforcement action corporate fraud among privately-controlled listed firms. In this test, α3
indicates whether state control of listed firms has an incremental effect on the relationship between
current year CEO turnover and past year regulatory enforcement action corporate fraud. If α3 < 0, this
indicates the propensity of CEO turnover following corporate fraud is lower among state-controlled
than privately-controlled listed firms in China, which confirms our prediction in H1. To confirm H2,
we need to observe α3 < 0 only among less serious fraud cases, i.e. those that do not involve
misleading public through information disclosure and those that are only penalized by verbal
warnings.
To test hypothesis H3, which contain our predictions concerning the impact of the Split Share
Structure Reform on the effect that state control exerts on the relationship between regulatory
14
enforcement actions against corporate fraud and subsequent CEO turnover propensity, we apply
logistic regression analyses based on Equation 2 below on sub-samples partitioned into state- and
privately-controlled listed firms and further into above and below level of payout consideration
among state-controlled listed firms:
Turnoveri ,t   0   1 Fraud i ,t 1   2 Post i ,t 1   3 Fraud i ,t 1  Post i ,t 1
  4 MVi ,t 1   5 PBi ,t 1   6 ROAi ,t 1   7 RETi ,t 1   8 STi ,t 1
  9 OWNC i ,t 1   10 FOWN i ,t 1   11 RESH i ,t 1
  12 RESH i ,t 1  Post i ,t 1   13 DUAL i ,t 1   14 BMEETt i ,t 1
  15 BSIZE i ,t 1   16 BINDi ,t 1   17 SBSIZE i ,t 1
 Industry  Year   i ,t
(2)
In Equation 2, Post equals 1 for years after the firm has been selected to carry out the Split
Share Structure Reform negotiation procedure and 0 otherwise. All variables used in Equations 1 and
2 are defined in Table II. We include an interaction term RESH×POST to control for the effect of
restricted share gradual restricted share reduction after the reform process begins. In this analyses, β1
indicates whether current year CEO turnover is related to past year regulatory enforcement action
corporate fraud before the reform. In this test, β 3 indicates whether the reform has an incremental
effect on the relationship between current year CEO turnover and past year regulatory enforcement
action corporate fraud. If the β3 > 0 only among state-controlled listed firms, this indicates the
propensity of CEO turnover following corporate fraud has increased among state-controlled after the
reform, which confirms our prediction in H3. If β3 > 0 only among state-controlled listed firms that
payout more considerations for the reform, this indicates the propensity of CEO turnover following
corporate fraud has increased only among state-controlled with higher willingness to participate in
the reform, which confirms our prediction in H4.
-----------------------------------INSERT TABLE II ABOUT HERE
----------------------------------------------
15
EMPIRICAL FINDINGS
Descriptive Statistics and Correlation
Table III presents the summary statistics of the variables used in our analyses. Panels A, B, and
C report the full sample, fraud committing firm subsample, and the matched firm subsample
respectively. Table III reveals that the fraud firms have significantly higher CEO turnover propensity
(Turnover) relative to their comparable firms. Fraud firms also have significantly higher
price-to-book (PB) ratio and lower industry adjusted return-on-asset (ROA), and are more likely to be
in distress (i.e. on the verge of special treatment as indicated by ST). This finding implies that poor
performance and distress firms that are overpriced by the market have greater tendency to commit
corporate fraud.
-----------------------------------INSERT TABLE III ABOUT HERE
----------------------------------------------Table IV presents the correlation analyses between variables used in our analyses. CEO
turnover (Turnover) is has significantly positive relationship with corporate fraud (Fraud), special
treatment likelihood (ST) and significantly negative relationship with firm size (MV), profitability
(ROA), ownership concentration (OWNC), and supervisory board size (SBSIZE). This suggests that
on average CEOs are held accountable to corporate fraud and poor performance. CEOs also have less
job security in firms that are smaller, have low ownership concentration, and have smaller
supervisory board. State-controlled listed firms (State) tend to be larger, more profitable, and less
special treatment likelihood. One possible explanation is that state-controlled firms tend to get
favorable treatment from the government in terms of contracts and bail-outs. However, they also have
higher ownership concentration and higher proportion of restricted to total shares (RESH), which
indicates weaker governance mechanisms. Notice that the correlation between State and either
Turnover or Fraud are statistically insignificant. This insignificance suggests that the propensity of
16
CEO turnover and corporate fraud are not necessarily higher among state-controlled listed firms than
their privately-controlled counterparts. In other words, these two groups of firms are on level playing
field in terms of these two variables. Thus, our subsequent analyses of the turnover to fraud
relationship are not biased in favor of any particular group.
-----------------------------------INSERT TABLE IV ABOUT HERE
----------------------------------------------
Test of Hypotheses H1 and H2
Table V presents our results from the test of hypothesis H1 based on logistic regression of
current year CEO turnover propensity on lagged indicator of corporate fraud, and conditional on state
control. Across Regressions 1 to 3, the marginal effect of Fraud is consistently and statistically
significantly positive. For instance, Regression 3 where all control variables are applied suggests
19.71% (t-statistics = 3.590) increase in the probability of current year CEO turnover associated with
past year corporate fraud among privately-controlled Chinese listed firms. However, the marginal
effect of Fraud×State is significantly negative throughout. For instance, in Regression 3 it is –15.30
(t-statistics = –2.380). This indicates that CEOs of state-controlled Chinese listed firms incrementally
less accountable to corporate fraud than their counterparts in privately-controlled listed firms. The
sum of the estimates for Fraud and Fraud×State is statistically insignificant, which indicates that
there are no relationship in state-controlled listed firms between current year turnover and lagged
fraud. In other words, the data support H1, which predicts that state control reduces the relationship
between CEO turnover propensity and corporate fraud regulatory enforcement actions. Our results
are robust to controls of firm characteristics, performance, and governance, as well as industry and
year effects.
-----------------------------------17
INSERT TABLE V ABOUT HERE
---------------------------------------------Tables VI and VII present our results from the test of hypothesis H2, which predicts that the
lack of turnover to fraud relation in state-controlled Chinese listed firms concentrates mainly in fraud
cases that are less likely to provoke public outrage. In Table VII, we partition our sample by fraud
type into those that deliberately seek to mislead investors (Panel A) through information disclosure
misconduct and other types of fraud (Panel B). Notice that throughout both panels, the marginal effect
of Fraud is consistently significantly positive, which indicates that the current turnover to lagged
fraud relation in privately-listed Chinese firms is not statistically sensitive to fraud types. However,
the economic significance is smaller for information disclosure fraud than other types of fraud. For
instance, in Regression 2 where both industry and year effects are controlled, it is 16.53% (t-statistics
= 2.540) in Panel A and 23.50% (t-statistics = 3.440) in Panel B. Moreover, the marginal effect of
Fraud×State is consistently and significantly negative only in Panel B and not for Panel A. Based on
Regression 2 it is –14.43% (t-statistics = –1.930) in Panel B and –12.32% (t-statistics = –1.570) in
Panel A. This indicates that the lack of CEO accountability to corporate fraud in state-controlled
Chinese listed firms we observe in Table V is indeed mainly concentrated in fraud cases that are less
likely to provoke public outrage, which is in line with our prediction in hypothesis H2.
---------------------------------INSERT TABLE VI ABOUT HERE
-------------------------------------------In Table VII, we partition our sample by regulatory enforcement type into those that involves
actual material penalty (Panel A) and those that only invoke verbal warning (Panel B). The marginal
effect of Fraud is significantly positive in both panels. For instance, in Regression 2 where both
industry and year effects are controlled, it is 18.46% (t-statistics = 2.710) in Panel A and 22.50%
(t-statistics = 2.52) in Panel B. This indicates that the accountability of CEOs to corporate fraud in
18
privately-controlled Chinese listed firms is not sensitive to enforcement type. In contrast, the
marginal effect of Fraud×State is economically and statistically significantly negative only in Panel
B but not in Panel A. For instance, based on Regression 2 it is –21.69% (t-statistics = –2.210) in Panel
B and only –7.78% (t-statistics = –0.860). This suggests that the lack of current turnover to lagged
fraud relationship among state-controlled Chinese listed firms only exists when the regulatory
enforcement involves light penalty that are less likely to provoke adverse public opinion. In other
words, this reconfirms our prediction in hypothesis H2. Our results are robust to controls of firm
characteristics, performance, and governance, as well as industry and year effects.
-----------------------------------INSERT TABLE VII ABOUT HERE
----------------------------------------------
Test of hypothesis H3 and H4
Table VIII presents our results from the test of hypothesis H3 based on logistic regression of
current year CEO turnover propensity on lagged indicator of corporate fraud, and conditional on the
Split Share Structure Reform. The marginal effect of Fraud, which indicates the current turnover to
lagged fraud relation prior to the reform, is statistically significantly positive only among
privately-controlled Chinese listed firms (Regression 1 is 27.10%, t-statistics = 3.420) and not their
state-controlled counterparts (Regression 2 is –1.36%, t-statistics = –0.290). Thus, prior to the
reform, CEOs are more likely to preserve their jobs security even after committing fraud is they work
for state-controlled listed firms. The marginal of Fraud×Post, which indicates the incremental
relation between current turnover and lagged fraud following the reform, is statistically significantly
positive only in the state-controlled listed firms as shown in Regression 2 (27.0%, t-statistics = 1.740)
and not the privately-controlled listed firms as shown in Regression 1 (–8.33%, t-statistics = –0.720).
This indicates a significant increase in the accountability of CEO to corporate fraud among
19
state-controlled listed firms after the Split Share Structure Reform, which is in line with our
prediction in hypothesis H3 and also consistent with improved corporate governance once controlling
state shareholders‟ becomes sensitive to stock market performance. The fact that Fraud×State is
significantly positive only in state-controlled listed firms, which are more sensitive to the reform, and
not their privately-controlled counterparts strengthens our inference that this is the effect of the Split
Share Structure Reform.
-----------------------------------INSERT TABLE VIII ABOUT HERE
---------------------------------------------Table IX presents our results from the test of hypothesis H4 based on logistic regression of
current year CEO turnover propensity on lagged indicator of corporate fraud, and conditional on the
Split Share Structure Reform. In this case, we implement the analyses only among state-controlled
Chinese listed firms and partition them into those that payout below and above median level of
restricted shares as compensation to freely tradable shareholders. The marginal effect pertaining to
Fraud is insignificant in both below and above median payout groups. In other words, there is no
accountability of CEO to fraud in state-controlled listed firms prior to the reform in both groups.
However, the marginal effect of Fraud×Post is statistically significantly positive only among above
median payout group (46.86%, t-statistics = 2.410) as shown in Regression 2, and not statistically
significant in the below median payout group (13.65%, t-statistics = 0.590) in Regression 1. This
indicates that the post-reform increase of current turnover and lagged fraud relation that we observe in
state-controlled listed firms in Table VIII exist only in firms that payout more restricted shares as
compensation for freely tradable shareholders to enable the reform process. In other words,
state-controlled listed firms with greater willingness to participate in the reform are associated with
an increase in CEO accountability to fraud, which is in line with our prediction in hypothesis H4 and
is consistent with the reform increasing the incentive of controlling state shareholders to supervise
20
and ensure managers maximize firms‟ market value. Our finding that a reform related variable
determines the current turnover to lagged fraud relation further strengthens our inference that this
effect brought about by the Split Share Structure Reform.
-----------------------------------INSERT TABLE IX ABOUT HERE
----------------------------------------------
Discussion and Conclusion
From corporate scandals to financial crisis, the experiences in developed countries over the past
decade have demonstrated the importance of managerial accountability and corporate governance to the
well-being of the capital market, which in turn affects the wider economy. As China ascends toward
becoming one of the largest economies in the world, the capital market is set for a vital role since the
efficient allocation of financial resources is a key determinant of economic development and growth.
Therefore, developing and strengthening managerial accountability and corporate governance in China
would be essential in this process to improve both investor protection and confidence, which in turn
enhances financial market liquidity. Academic researches that identify existing problems or verify the
impact of reform process could offer useful input to practitioners and regulators to formulate future
directions suitable for China‟s capital market development. Our study provides insight from both
perspectives.
We provide empirical evidence that state control of listed firms in China reduces the
accountability of CEOs to the corporate fraud they instigated. This is consistent with political
connection reducing corporate governance and exacerbating agency cost in China. We then show that
the lower CEO turnover propensity following corporate fraud among state-controlled listed firms
exist mainly in fraud that do not involve misleading the public through information disclosure or in
regulatory enforcement actions that only invoke verbal warnings against the perpetrator. In other
words, state-controlled Chinese listed firms still hold CEOs that commit relatively more serious
21
fraudulent behaviors accountable. This finding is consistent with such firms seeking to distant
themselves from public outrage in order to preserve reputation and political capital. Most of all, we
show an increase in the relationship between CEO turnover and corporate fraud among
state-controlled Chinese listed firms after the Split Share Structure Reform, which renders state
shareholders wealth more sensitive to stock return performance. This result is consistent with
increased corporate governance among such firms following improvement in controlling
shareholders‟ incentive to supervise and ensure that executives maximize firms‟ market value. Our
study contributes to the academic literature on management and corporate governance.
Some management studies suggest that political connection is a managerial resource beneficial
to Chinese firms. For instance, Xin and Pearce (1996) argue that it is a substitute for insufficient
institutional infrastructure, Lou (2003) suggests that it provide flexible resource allocation in a factor
mobility constrained environment, and Atuahene-Gima and Li (2002) argue that it facilitates business
in an uncertain environment. There are evidence that political connection influences market benefit
(Davies et al., 1995), competitive advantages (Tsang, 1998), and improves firm performance (Nee,
1992; Peng and Luo, 2000). However, our finding reveals that political connection reduces executive
accountability for instigating corporate fraud, and in this context is likely to have adverse effect for
the firms‟ stakeholders and reputation. Our result is more in line with the finding of Kato and Long
(2006a, 2006b) and Conyon and He (2008) that the inverse relationship between CEO turnover and
firm performance is less pronounced among state controlled Chinese listed firms. Our evidence does
not deny the value of managerial political connection in a transitional economy, but implies the need
for better corporate governance mechanism to reduce its potential negative effect.
Corporate governance literature based on studies of western economies often portrait large
shareholders as beneficial to firms since they are more effective and motivated to monitor executives.
For instance, management turnover is more frequent (Kaplan and Minton, 1994) and executive
compensation is tighter (Bertrand and Mullainathan, 2001; Hartzell and Starks, 2003) among firms
controlled by large shareholders. In emerging economies, large shareholders tend to be the state as a
22
result of weaker institutional environment and poorer protection of property rights (Dyck and
Zingales, 2004; La Porta et al., 2002). However, our evidence suggests that large shareholders
representing the state have less incentive to monitor executives in Chinese listed firms. This is in line
with previous studies suggesting that state ownership moderates the effectiveness of corporate
governance in reducing agency costs (Connelly et al., 2010; Tihanyi and Hegarty, 2007). Our finding
is also consistent with other empirical evidence from China, which implies that state ownership
reduces corporate governance (Ding et al., 2007; Gul et al., 2010; Wang et al., 2008). Our evidence
does not deny the contribution of state-owned enterprise to the development of the Chinese economy,
but implies that reforms are necessary to increase state controlling shareholders‟ incentives to monitor
executives.
Finally, studies of Chinese business development have revealed a sustained process of reform
seeking to evolve and adapt state-owned enterprise toward market orientation (Ralston et al., 2006).
At the early stage, bonus to reward performance has been reintroduced to motivate employees (Chen,
1995) and short-term renewable contracts have replaced life-long positions (Tenev et al., 2002).
Subsequently, the government has also introduced regulations to punish business failures (Steinfeld,
1998) and deregulated protected sectors (Panitchpakdi and Clifford, 2002). The introduction of the
Split Share Structure Reform starting from 2005 marks another major step in this process. In this case,
the aim is to abolish trading restrictions of shares held by the state to maintain government influence
of listed firms. In doing so, the state shareholders‟ wealth is sensitive to the stock market value of their
firms and aligned with the interest of private minority shareholders. Our study provides evidence that
this reform has indeed increased the incentive of the state shareholders to discipline executives who
instigate corporate fraud that reduces firms‟ market value. Thus, our study confirms the benefit of
on-going reform of the Chinese business and economy.
23
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Table I Sample description
This table presents the yearly (Panel A) and industry (Panel B) distribution of our corporate fraud sample. Fraud Cases is the number of fraud committed by listed firms that are disclosed.
Fraud Firms is the number of listed firms that committed the fraud. Fraud/Total Firms is the number of fraud committing listed firms to total number of listed firms in the stock market.
State/Fraud Firms is the proportion of fraud committing listed firms that are state controlled. Fraud/Total State Firms is the proportion of fraud committing state-controlled listed firms to
the total number of state-controlled listed firms in the stock market. State/Total Firms are the proportion of all listed firms in the stock market that are state controlled.
Fraud Cases
Fraud Firms
Fraud/Total
Firms (%)
State/Fraud
Firms (%)
Fraud/Total
State Firms (%)
State/Total
Firms (%)
13
17
73
60
56
70
100
97
79
39
13
17
67
50
45
60
69
71
61
35
1.43
1.62
5.96
4.19
3.58
4.44
5.11
5.04
4.00
2.19
53.85
64.71
73.13
80.00
68.89
55.00
49.28
45.07
44.26
51.43
0.91
1.27
5.30
4.31
3.36
3.53
3.64
3.49
2.93
1.89
84.30
82.92
82.22
77.87
73.43
69.08
69.13
64.96
60.35
59.66
17
100
88
113
76
41
45
87
7
20
10
14
81
72
94
61
32
38
66
4
16
10
4.13
3.24
2.79
3.51
6.41
3.62
3.77
5.47
16.00
2.88
51.82
50.00
64.20
56.94
69.15
63.93
40.63
55.26
45.45
50.00
75.00
0.00
2.47
2.65
2.19
3.48
5.60
2.47
3.65
4.00
11.11
2.40
0.00
83.48
78.48
72.56
69.70
73.29
59.50
57.09
62.14
72.00
90.11
50.00
Panel A: Year distribution
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Panel B: Industry distribution
Energy
Materials
Industrials
Consumer Discretionary
Consumer Staples
Health Care
Financials
Information Technology
Telecommunication
Utilities
Others
31
Table II Definition of variables used in the empirical analyses
Variable
Definition
Turnover
Equals 1 if CEO turnover occurred in the year and 0 otherwise
Fraud
Equals 1 if the firm experience regulatory enforcement actions against
corporate fraud in the fiscal year and 0 otherwise
State
Equals 1 if the firm is state-controlled and 0 otherwise
MV
Size measured as log market capitalization
PB
Growth measured as price-to-book ratio
ROA
Profitability measured as industry-adjusted return-on-asset
RET
Annual stock return over risk free rate
STPT
Equals 1 for firms on the verge of special treatment (i.e. those with two
consecutive years of losses) and 0 otherwise
OWNC
Ownership concentration measured by the Herfindahl index and based on
the ownership held by the ten largest shareholders in the firm
FOWN
Proportion of shares held by foreign shareholders
RESH
Ratio of restricted shares to total shares.
DUAL
Equals 1 for firms with CEO also serving as board chairman and 0
otherwise
BMeet
Equals 1 for firms with above median number of board meetings and 0
otherwise
BSIZE
Equals to 1 for firms with board size above the cross-sectional median and
0 otherwise
BIND
Equals 1 for firms whose proportion of independent directors is above the
cross-sectional median and 0 otherwise
SBSIZE
Equals 1 for firms with supervisory board size above the cross-sectional
median and 0 otherwise
32
Table III Summary statistics
Turnover
State
MV
PB
ROA
RET
ST
OWNC
FOWN
RESH
DUAL
BMEET
BSIZE
BIND
SBSIZE
Obs.
Panel A: Whole Sample
Panel B: Fraud committing firms Panel C: Matched firms
Median
Mean
Std Dev
Median
Mean
Std Dev
Median
Mean
Std Dev
0.000
0.300
0.458
0.000
0.364
0.482
0.000
0.235
0.424
1.000
0.619
0.486
1.000
0.601
0.490
1.000
0.636
0.482
20.104
20.124
0.947
20.124
20.145
0.938
20.072
20.103
0.956
3.191
4.557
5.445
3.362
4.936
5.884
2.922
4.178
4.946
-0.003
-0.013
0.030
-0.006
-0.019
0.032
-0.001
-0.007
0.028
-0.112
-0.010
1.041
-0.147
-0.022
0.860
-0.077
0.001
1.195
0.000
0.257
0.437
0.000
0.325
0.469
0.000
0.188
0.391
0.143
0.180
0.125
0.136
0.170
0.118
0.146
0.189
0.131
0.000
0.010
0.058
0.000
0.008
0.047
0.000
0.013
0.067
0.584
0.550
0.141
0.576
0.547
0.143
0.587
0.553
0.139
0.000
0.016
0.125
0.000
0.020
0.139
0.000
0.012
0.110
0.000
0.474
0.500
0.000
0.377
0.485
1.000
0.572
0.495
0.000
0.329
0.470
0.000
0.318
0.466
0.000
0.340
0.474
0.000
0.141
0.348
0.000
0.152
0.359
0.000
0.130
0.336
1.000
0.875
0.331
1.000
0.863
0.344
1.000
0.888
0.316
818
409
Panels B – C
mean difference
0.1296 ***
-0.034
0.042
0.758 *
-0.011 ***
-0.023
0.137 ***
-0.019 **
-0.005
-0.006
0.007
-0.196 ***
-0.022
0.022
-0.024
409
This table presents the summary statistics of the variables used in our analyses. Our sample period is 1999 to 2008. Panels A, B, and C reports the whole sample, fraud
committing firms sample, and the matched firm sample (i.e. non-fraud committing firms) respectively. All variables are defined in Table II.
33
Table IV Correlation analyses
Turnover
Fraud
State
MV
PB
ROA
RET
ST
OWNC
FOWN
RESH
DUAL
BMEET
BSIZE
BIND
SBSIZE
Turnover Fraud State
MV
PB
ROA
RET
ST
OWNC FOWN RESH
DUAL
BMEET BSIZE BIND
SBSIZE
1
0.142*
1
-0.042 -0.035
1
*
-0.108
0.022 0.117*
1
0.029 0.070*
0.022 0.269*
1
*
*
*
*
-0.160 -0.188
0.147
0.320
-0.052
1
*
*
0.011 -0.011 -0.043 0.379
0.262
0.184*
1
*
*
*
*
*
*
0.092
0.157 -0.138 -0.263
0.118 -0.148
-0.023
1
-0.086* -0.076* 0.343*
0.037 -0.049 0.177*
0.046 -0.067
1
-0.014 -0.040 -0.057
0.033 -0.020
0.020 -0.028 -0.040
0.041
1
*
*
*
*
*
0.022 -0.022 0.136 -0.296
0.007 0.077 -0.081
0.034 0.535
0.048
1
0.045
0.029 -0.021 -0.029
0.006
0.003
0.030
0.037 -0.037
0.013
-0.036
1
-0.039 -0.196*
0.045 -0.013 -0.046 0.098*
0.017 -0.037
0.058 -0.058
0.044
-0.003
1
*
*
*
-0.049 -0.023 0.084
0.073
0.025 -0.055 -0.023 -0.048 -0.073
-0.057
0.024
-0.047
0.023
1
*
0.058
0.032 0.086
-0.006 -0.036 -0.019
0.019
0.052 -0.004
0.001
0.063
-0.023
-0.004 0.091*
1
*
*
*
*
*
*
-0.101
-0.037 0.069
-0.029
0.024 -0.049 -0.067 -0.126
0.094
-0.038
0.097
0.048
0.032 0.091
0.025
1
This table presents the correlation analyses of the variables used in our analyses. * indicates statistically significant to 1% level.
34
Table V Relationship between CEO turnover and fraud conditional on state control
Regression 1
Fraud
State
Fraud×State
MV
PB
ROA
RET
ST
OWNC
FOWN
RESH
DUAL
BMEET
BSIZE
BIND
SBSIZE
Industry effect
Year effect
Pseudo R2
Obs.
0.2292
(4.330)
0.0612
-0.1554
(1.200)
(-2.480)
Regression 2
***
**
Regression 3
0.2003
(3.610)
***
0.1971
(3.590)
0.1135
-0.1506
-0.0387
0.0017
-1.6882
0.0265
0.0152
-0.3797
-0.0647
0.2414
0.1373
0.0002
-0.0470
0.0696
-0.1497
(2.040)
(-2.350)
(-1.870)
(0.530)
(-2.910)
(1.730)
(0.390)
(-2.120)
(-0.240)
(1.550)
(1.050)
(0.010)
(-1.290)
(1.510)
(-2.890)
**
0.1017
-0.1530
-0.0263
0.0021
-1.9950
0.0318
0.0295
-0.3936
-0.1197
0.2673
0.1257
0.0038
-0.0489
0.0547
-0.1572
(1.850)
(-2.380)
(-1.200)
(0.620)
(-3.270)
(2.180)
(0.730)
(-2.180)
(-0.460)
(1.690)
(0.840)
(0.110)
(-1.330)
(1.220)
(-2.890)
**
*
***
*
**
***
No
No
No
No
Yes
Yes
0.024
818
0.064
818
0.082
818
***
*
**
***
**
**
*
***
This table presents the logistic regression analyses of the relationship between CEO turnover and corporate fraud
conditional on state control. Marginal effects are reported. The t-statistics in parentheses are adjusted for
heteroskedasticity and ***, **, and * denote significance at the 1, 5, and 10 levels respectively.
35
Table VI Relationship between CEO turnover and fraud conditional on state control and fraud type
Panel A: Information disclosure related fraud Panel B: Other types of fraud
Regression 1
Fraud
State
Fraud×State
MV
PB
ROA
RET
ST
OWNC
FOWN
RESH
DUAL
BMEET
BSIZE
BIND
SBSIZE
Industry effect
Year effect
Pseudo R2
Obs.
0.1781
0.0849
-0.1329
-0.0074
0.0033
-1.8109
0.0247
0.0270
-0.3037
-0.1871
0.4470
0.1022
0.0061
-0.0499
0.0291
-0.1253
(2.700)
(1.280)
(-1.710)
(-0.280)
(0.850)
(-2.750)
(1.070)
(0.590)
(-1.490)
(-0.510)
(2.280)
(0.730)
(0.150)
(-1.120)
(0.550)
(-2.110)
Regression 2
***
*
***
**
**
0.1653
0.0606
-0.1232
0.0012
0.0050
-2.2084
0.0312
0.0428
-0.3189
-0.2326
0.4380
0.0970
0.0088
-0.0498
0.0091
-0.1299
(2.540)
(0.940)
(-1.570)
(0.040)
(1.270)
(-3.140)
(1.530)
(0.900)
(-1.530)
(-0.660)
(2.160)
(0.580)
(0.210)
(-1.120)
(0.180)
(-2.070)
Regression 1
**
***
**
**
0.2463
0.1754
-0.1986
-0.1020
-0.0033
-0.4303
0.0230
-0.0860
-0.7205
0.1366
-0.1746
0.3097
-0.0244
-0.0084
0.1569
-0.2383
(3.050)
(2.660)
(-2.200)
(-2.970)
(-0.680)
(-0.420)
(1.050)
(-1.600)
(-2.440)
(0.540)
(-0.820)
(1.220)
(-0.460)
(-0.150)
(1.850)
(-2.020)
Regression 2
***
***
**
***
**
*
**
0.2350
0.1627
-0.1443
-0.1146
-0.0037
0.0410
0.0253
-0.0581
-0.6183
0.3144
-0.2259
0.1692
0.0150
-0.0215
0.1639
-0.1221
No
No
Yes
Yes
No
No
Yes
Yes
0.052
612
0.077
612
0.206
206
0.282
202
(3.440)
(2.780)
(-1.930)
(-3.400)
(-0.860)
(0.040)
(1.520)
(-1.110)
(-2.260)
(1.260)
(-1.070)
(0.770)
(0.320)
(-0.460)
(1.940)
(-1.200)
***
***
*
***
**
*
This table presents the logistic regression analyses of the relationship between CEO turnover and corporate fraud conditional on state
control and fraud type. Marginal effects are reported. The t-statistics in parentheses are adjusted for heteroskedasticity and ***, **, and *
denote significance at the 1, 5, and 10 levels respectively.
36
Table VII Relationship between CEO turnover and fraud conditional on state control and enforcement type
Panel A: Material penalty
Regression 1
Fraud
State
Fraud×State
MV
PB
ROA
RET
ST
OWNC
FOWN
RESH
DUAL
BMEET
BSIZE
BIND
SBSIZE
Industry effect
Year effect
Pseudo R2
Obs.
0.1685
-0.0029
-0.0526
-0.0718
-0.0015
0.1852
0.0209
0.0200
-0.4910
0.2015
0.1044
0.3188
0.0238
0.0603
0.0035
-0.2954
(2.470)
(-0.040)
(-0.600)
(-2.850)
(-0.420)
(0.250)
(1.480)
(0.400)
(-1.690)
(0.690)
(0.530)
(1.670)
(0.510)
(1.130)
(0.050)
(-3.670)
Panel B: Verbal warning
Regression 2
**
***
*
*
***
0.1846
0.0089
-0.0778
-0.0652
-0.0008
0.2012
0.0254
0.0303
-0.5055
0.1135
0.1030
0.2772
0.0058
0.0678
0.0050
-0.3133
(2.710)
(0.110)
(-0.860)
(-2.450)
(-0.220)
(0.260)
(1.730)
(0.590)
(-1.760)
(0.370)
(0.510)
(1.440)
(0.120)
(1.270)
(0.080)
(-3.650)
Regression 1
***
**
*
*
***
0.2206
0.1896
-0.2158
-0.0378
0.0087
-4.0761
0.0876
0.0226
-0.1868
-0.0897
0.1502
-0.0797
-0.0080
-0.1158
0.1110
0.0096
(2.460)
(2.360)
(-2.200)
(-1.080)
(1.480)
(-4.160)
(2.050)
(0.370)
(-0.790)
(-0.220)
(0.620)
(-0.540)
(-0.160)
(-2.230)
(1.750)
(0.110)
Regression 2
**
**
**
***
**
**
*
0.2250
0.1834
-0.2169
-0.0271
0.0089
-4.5812
0.0881
0.0614
-0.1181
-0.0026
0.1602
-0.0612
0.0060
-0.1248
0.1145
-0.0165
No
No
Yes
Yes
No
No
Yes
Yes
0.112
390
0.142
390
0.103
428
0.140
428
(2.520)
(2.270)
(-2.210)
(-0.700)
(1.430)
(-4.450)
(1.960)
(0.930)
(-0.490)
(-0.010)
(0.630)
(-0.340)
(0.110)
(-2.340)
(1.740)
(-0.190)
**
**
**
***
*
**
*
This table presents the logistic regression analyses of the relationship between CEO turnover and corporate fraud conditional on state
control and enforcement type. Marginal effects are reported. The t-statistics in parentheses are adjusted for heteroskedasticity and ***, **,
and * denote significance at the 1, 5, and 10 levels respectively.
37
Table VIII Relationship between CEO turnover and fraud conditional on the Split Share
Structure Reform and state control
Regression 1
Regression 2
Privately-controlled listed firms
Fraud
Post
Fraud×Post
MV
PB
ROA
RET
ST
OWNC
FOWN
RESH
RESH×Post
DUAL
BMEET
BSIZE
BIND
SBSIZE
Industry effect
Year effect
Pseudo R2
Obs.
0.2710
0.5535
-0.0833
-0.0721
0.0001
0.4458
0.0069
0.0200
-0.2713
0.7183
0.6857
-1.1697
0.4117
-0.0020
-0.0233
0.1065
-0.2952
(3.420)
(2.060)
(-0.720)
(-1.670)
(0.020)
(0.460)
(0.370)
(0.310)
(-0.480)
(1.470)
(1.790)
(-2.420)
(1.960)
(-0.030)
(-0.330)
(1.100)
(-3.260)
***
**
*
*
**
*
***
State-controlled listed firms
-0.0136
-0.0984
0.2704
-0.0084
0.0038
-4.0655
0.0967
0.0230
-0.3086
-1.0299
0.1572
-0.4883
-0.0926
-0.0098
-0.0681
0.0331
-0.0836
Yes
Yes
Yes
Yes
0.016
312
0.135
506
(-0.290)
(-0.470)
(1.740)
(-0.260)
(0.760)
(-4.510)
(2.220)
(0.400)
(-1.470)
(-0.980)
(0.610)
(-1.140)
(-0.640)
(-0.220)
(-1.540)
(0.580)
(-1.090)
*
***
**
This table presents the logistic regression analyses of the relationship between CEO turnover and corporate fraud
conditional on the Split Share Structure Reform and state control. Marginal effects are reported. The t-statistics in
parentheses are adjusted for heteroskedasticity and ***, **, and * denote significance at the 1, 5, and 10 levels
respectively.
38
Table IX Relationship between CEO turnover and fraud among state-controlled
listed firms conditional on the Split Share Structure Reform and payout
Fraud
Post
Fraud×Post
MV
PB
ROA
RET
ST
OWNC
FOWN
RESH
RESH×Post
DUAL
BMEET
BSIZE
BIND
SBSIZE
Intercept
Industry effect
Year effect
Pseudo R2
Obs.
Regression 1
Regression 2
Below median
restricted share payout
Above median
restricted share payout
-0.0578
-0.4271
0.1365
-0.0136
-0.0053
-5.0149
0.0602
0.3386
-0.3611
-0.2354
-0.6590
0.6666
0.1203
0.0545
-0.0861
0.0693
-0.3248
-0.0578
(-0.630)
(-1.020)
(0.590)
(-0.210)
(-0.470)
(-2.970)
(0.520)
(2.860)
(-1.140)
(-0.430)
(-1.070)
(0.530)
(0.290)
(0.640)
(-0.970)
(0.730)
(-2.000)
(0.720)
***
***
**
0.0036
-0.0034
0.4686
-0.0026
0.0049
-2.2035
0.0624
-0.0960
-0.1608
-15.4763
0.1368
-0.6336
-0.0840
-0.0325
-0.0075
-0.0289
-0.0191
0.0036
Yes
Yes
Yes
Yes
0.275
182
0.179
324
(0.100)
(-0.020)
(2.410)
(-0.120)
(1.380)
(-3.180)
(2.000)
(-2.590)
(-0.950)
(-0.180)
(0.740)
(-1.910)
(-0.940)
(-1.020)
(-0.230)
(-0.770)
(-0.370)
(0.010)
**
***
**
**
*
This table presents the logistic regression analyses of the relationship between CEO turnover and corporate fraud
among state controlled listed firms conditional on the Split Share Structure Reform and payout. Marginal effects are
reported. The t-statistics in parentheses are adjusted for heteroskedasticity and ***, **, and * denote significance at the
1, 5, and 10 levels respectively.
39