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FRAUDULENT FINANCIAL
REPORTING IN CHINA: EVIDENCE
FROM RENAMING BEHAVIOUR
Yefeng Zhang
Master of Philosophy
Submitted in fulfilment of the requirements for the degree of
Master of Philosophy
School of Accountancy
QUT Business School
Queensland University of Technology
July 2019
Fraudulent Financial Reporting in China: Evidence from Renaming Behaviour i
Keywords
Financial Reporting Fraud
Corporate Renaming
Corporate Governance
China
Fraudulent Financial Reporting in China: Evidence from Renaming Behaviour ii
Abstract
Using a sample of listed companies in China during 2010-2017, this study examines
the association between corporate’s renaming behaviour and fraudulent financial
reporting activities (FFRs). The moderating role of state-owned enterprises (SOEs) and
powerful directors in mitigating the association between corporate renaming and
financial reporting fraud is further investigated. The results suggest that companies with
renaming experience are more prone to commit financial reporting fraud. The positive
association between corporate renaming and FFRs is less pronounced for SOEs than
for non-SOEs. Reported results also show that the power of board of directors positively
moderates the association between renaming behaviour and the likelihood of FFRs.
This study provides a new “red flag” for the regulators to investigate financial fraud.
The findings are timely and relevant to the contentious regulation and development of
the capital market in China. Results are expected to be generalizable across emerging
capital markets.
Fraudulent Financial Reporting in China: Evidence from Renaming Behaviour iii
Table of Contents
Keywords ....................................................................................................................... i
Abstract ........................................................................................................................ ii
List of Figures .............................................................................................................. vi
List of Tables .............................................................................................................. vii
Statement of Original Authorship .......................................................................... viii
Acknowledgements ..................................................................................................... ix
CHAPTER 1 INTRODUCTION ................................................................................ 1
1.1 Purpose of the study ...................................................................................................... 1
1.2 Motivations ..................................................................................................................... 2
1.3 Findings........................................................................................................................... 6
1.4 Contributions ................................................................................................................. 8
1.5 Structure of the thesis .................................................................................................. 11
CHAPTER 2 LITERATURE REVIEW .................................................................. 12
2.1 Institutional Background ............................................................................................ 12
2.2 Corporate Renaming ................................................................................................... 13
2.2.1 Reasons for a corporate name change .................................................................... 13
2.2.2 Capital market reactions to a corporate name change ............................................ 15
2.3 Financial Reporting Fraud ......................................................................................... 21
2.3.1 Definitions of financial reporting fraud .................................................................. 21
2.3.2 Theoretical explanations for financial reporting fraud ........................................... 23
2.3.3 Accounting literature on financial reporting fraud ................................................. 25
2.3.4 Financial reporting fraud in China: an overview of the literature .......................... 34
CHAPTER 3 HYPOTHESES DEVELOPMENT................................................... 38
3.1 Corporate renaming and fraud .................................................................................. 38
3.2 Ownership structure, corporate renaming, and financial reporting fraud ............ 42
3.3 Board power and risk of financial fraud from corporate renaming ....................... 46
Fraudulent Financial Reporting in China: Evidence from Renaming Behaviour iv
CHAPTER 4 RESEARCH DESIGN ....................................................................... 49
4.1 Data and Sample .......................................................................................................... 49
4.2 Research Method and Model ...................................................................................... 51
CHAPTER 5 RESULTS ............................................................................................ 60
5.1 Descriptive statistics .................................................................................................... 60
5.2 Results of Correlations ................................................................................................ 67
5.3 Regression Results ....................................................................................................... 70
5.3.1 Corporate renaming and financial reporting fraud ................................................. 70
5.3.2 Corporate renaming and financial fraud: the role of government ownership (SOE
vs non-SOE) .................................................................................................................... 73
5.3.3 Corporate renaming and financial fraud: the moderating role of powerful ............ 76
5.4 Additional and robustness tests .................................................................................. 78
5.4.1 The association between corporate renaming and different types of fraud ............ 78
5.4.2 The association between corporate renaming and fraud by year............................ 83
5.4.3 Extend testing windows .......................................................................................... 86
5.4.4 The financial fraud and subsequent renaming behaviour ....................................... 88
5.4.5 Addressing potential endogeneity........................................................................... 94
CHAPTER 6 CONCLUSION ................................................................................... 96
6.1 Summary of findings and discussion .......................................................................... 96
6.2 Contributions and practical implications .................................................................. 98
6.3 limitations and future research avenue ...................................................................... 99
REFERENCES ......................................................................................................... 101
Fraudulent Financial Reporting in China: Evidence from Renaming Behaviour vi
List of Figures
Figure 2.1 Fraud triangle.............................................................................................. 23
Fraudulent Financial Reporting in China: Evidence from Renaming Behaviour vii
List of Tables
Table 4.1 Sample selection........................................................................................... 51
Table 4.2 Variable defination and measurement .......................................................... 58
Table 5.1 Sample distributions ..................................................................................... 62
Table 5.2 Summary statistics ....................................................................................... 66
Table 5.3 Correlation matrix ........................................................................................ 69
Table 5.4 Corporate renaming and finanical reporting fraud ....................................... 72
Table 5.5 Corporate renaming and finanical reporting fraud: the moderation role of
government ownership ................................................................................................. 74
Table 5.6 Corporate renaming and finanical reporting fraud: the moderation role of
board power ................................................................................................................. 76
Table 5.7 Corporate renaming and different types of fraud ......................................... 79
Table 5.8 Corporate renaming and financial reporting fraud by year .......................... 83
Table 5.9 Corporate renaming and financial reporting fraud: extended testing
windows ....................................................................................................................... 85
Table 5.10 Financial reporting fraud and subsequent corporate renaming behaviour . 89
Table 5.11 Corporate renaming and financial reporting fraud: Heckman Test ............ 94
Fraudulent Financial Reporting in China: Evidence from Renaming Behaviour viii
Statement of Original Authorship
The work contained in this thesis has not been previously submitted to meet
requirements for an award at this or any other higher education institution. To the best
of my knowledge and belief, the thesis contains no material previously published or
written by another person except where due reference is made.
Signature: ______
Date: _________________________
QUT Verified Signature
Fraudulent Financial Reporting in China: Evidence from Renaming Behaviour ix
Acknowledgements
I would like to dedicate this section of my thesis to express my gratitude to those people
who supported me through this research journey. First of all, I wish to acknowledge my
sincere gratitude to my supervisors Dr. Yuyu Zhang and Dr. Troy Yao, for their
invaluable guidance, kindness and endless patience and ongoing support throughout
this research process. Yuyu, your comments and feedback on my study have provided
very important insights that enable me to develop my thesis to the next level. Troy, I
would not find myself writing this without your support. I feel truly blessed to have met
you and become one of your students. I also would like to express great thanks to the
administration staff of the School of Accountancy at QUT, Ms. Gayleen Furneaux and
Mr. Dennis O’Connell, for their continuous support.
I would also like to express my thanks to the HDR cohort of 2018. It has been a great
pleasure for me to know them all and to offer support to each other. In particular, I thank
Xiaohua Wu, Boshi Gao, Linda Bennison and George Filippov for their kindest support
and warmest friendship and their help and encouragement has contributed to the
accomplishment. I wish them all the best in their future research or careers.
Finally, I would like to thanks to my parents who has continuously provide ongoing
love, encouragement and financial support.
CHAPTER 1 INTRODUCTION 1
CHAPTER 1 INTRODUCTION
This chapter outlines the purpose of this research (section 1.1), and the motivations and
research issues (section 1.2). Section 1.3 summaries the findings. Section 1.4 includes
the contributions of this study.
1.1 Purpose of the study
This study examines the association between corporate renaming behaviour and
financial reporting fraud in China. A corporate name can be the most potent intangible
asset of a business and is an important form of external information disclosure. The
company’s name is not only related to the influence of the company in the industry, but
also related to the recognition of the corporate. If the company’s name conforms to the
characteristics of the industry and the current trends, the competitiveness of the
company is obviously different from the other companies in the same industry.
Therefore, many companies changed their corporate name to be associated with the
current popular industry and this biased information will directly affect the evaluation
of the company value by external information users, ultimately influencing the
CHAPTER 1 INTRODUCTION 2
economic decisions that users make. However, corporate renaming behaviour has had
limited study in the literature. Listed companies may either use renaming to
communicate specific business changes or strategically alter the corporate name to a
more appealing name hence to manipulate the public impression on the company.
1.2 Motivations
Prior research reveals that although nearly 90% of companies can obtain excess returns
in the short term after corporate renaming (Pensa, 2006; Lee, 2010), corporate renaming
behaviour often indicates impression management. In the context of the Chinese stock
market, from 2010 to 2017, there were 1,719 companies from 19 industries that changed
their corporate name. In the most recent year, the renaming case of “P2P” in Chinese
stock market aroused significant attention from regulators and other capital market
participants including investors. A company originally called “Duolun Industry”, a
company engaged in building materials, changed its name to “P2P Financial
Information Service”. Following the corporate name change, the company’s share price
has increased by nearly 60%. Interestingly, although the company changed its name,
CHAPTER 1 INTRODUCTION 3
the company’s ordinary business activities remained the same in the material industry,
and the company is not qualified to provide financial services. More noticeably, when
the stock price of “P2P” was at the highest point, the company’s management cut back
on a large amount of stocks and illegally cashed out 1.1 billion RMB (Chinese dollar).
China Securities Regulatory Commission (thereafter, CSRC) believes that this is a
fraudulent case. That is, “P2P” has artificially changed its corporate name to be
associated with the trendy industry to boost the company’s stock price, followed by an
illegal cash out. The case of “P2P” demonstrates that changing corporate’s name has
become an ‘achievable’ way for companies to conduct financial fraud in China, and
corporate renaming behaviour has raised attentions from the regulatory bodies. On
September 30, 2016, the Shanghai Stock Exchange issued the “Index of Listed
Companies Changing Securities Name” which was the first piece of regulation on
corporate renaming. Listed companies are required not to mislead investors by
artificially changing the name of the company.
Besides the frequent renaming practices among Chinese companies, financial reporting
CHAPTER 1 INTRODUCTION 4
fraud has also become a significant issue in China. Due to the institutional feature and
insufficient and underdeveloped legal environment in the Chinese stock market (Jiao et
al., 2015), financial scandals have increased dramatically over the past several decades
(Yu et al., 2015). The institutional background and country-level corporate governance
features in China can be summarised as follows. First, the legal environment in China
is weak compared to developed countries (e.g. U.S. and U.K.). Roe (2002) shows that
the legal environment of a country has a significant impact on companies’ performance
and corporate governance practices. The code law legal system in China thus provides
avenues for listed companies to engage in financial frauds. Second, Chinese stock
markets have serious asymmetric information problems (Morck, Yeung, and Yu, 2000),
including insufficiently knowledgeable managers, and the asymmetric information
between insiders and capital market participants. Third, the ownership structure of
Chinese listed companies is unique. China is a country where companies have a
concentrated ownership structure and a significant proportion of listed companies that
are owned by central or local governments (Cheung et al., 2010). Under such a
concentrated ownership structure, the primary agency conflict arises between majority
CHAPTER 1 INTRODUCTION 5
and minority shareholders.
To our best knowledge, no research has investigated whether corporate renaming
behaviour is associated with financial frauds. Therefore, this study is motived to add
new evidence to the corporate renaming and financial fraud literature by investigating
this question in the Chinese setting where the overall corporate governance is weaker.
This study argues that if the corporate name changes are the result of fundamental
changes in corporate structure (e.g. mergers or acquisitions) then the new corporate
name may provide signals to investor about the company’s updated business strategies
(‘signaling theory’). However, on the other hand, the renaming behaviour itself can also
be a case of misrepresentation of information and it may mislead the investors if
corporate names are changed without altering the business structure. As demonstrated
in the case of ‘P2P Financial Information Service’, the company used renaming effect
to obtain excess returns in a short period of time, followed by a large sell of company’s
stocks to achieve illegal cash out when the stock price reached the peak. Therefore, it
is hypothesised in this study that corporate renaming may be a ‘red flag’ of a financial
CHAPTER 1 INTRODUCTION 6
fraud.
1.3 Findings
Based on a sample of 20,516 company-year observations in the Chinese A-share market,
this study finds that companies are more likely to commit financial fraud subsequent to
their corporate name changes. Further, there is evidence that the impact of renaming
behaviour on the likelihood of fraudulent financial reporting is more pronounced in
non-state-owned enterprises (thereafter, non-SOEs) than in state-owned enterprises
(thereafter, SOEs). In other words, corporate renaming has reduced the likelihood of
fraudulent financial reporting when companies are owned by the government. Finally,
reported results suggest that the power of the board of directors positively moderated
the association between company renaming behaviour and the likelihood of fraudulent
financial reporting.
Several additional tests were undertaken to provide further evidence on the research
question. Firstly, this study classifies the frauds into 6 categories (e.g. false statement,
CHAPTER 1 INTRODUCTION 7
a major failure to disclosure information, illegal share buyback, a delay in disclosure,
inflated earnings, and others) and re-runs the main model, results show that renaming
companies are more likely to commit fraud related to information disclosure, such as
delay in disclosure or none disclosure of information. Secondly, when observing the
association between renaming and fraud in different years, this study finds that the
association between corporate renaming behaviour and financial reporting fraud
becomes insignificant in 2017. On September 30, 2016, the Shanghai Stock Exchange
issued the “Index of Listed Companies Changing Securities Name”, which emphasised
that the name of a listed company should be clear in meaning. Listed companies are not
allowed to mislead investors by changing the name of the company. This result provides
indirect evidence that the introduction of relevant renaming policies and regulations
have weakened the relation between the renaming and financial reporting fraud. Thirdly,
when the testing windows were extended, results show that renaming companies will
commit financial fraud in the short term after they changed the corporate name, and the
possibility to commit fraud will decline over the time. Fourthly, this study examines
whether the companies change their name after they committed fraud. The results
CHAPTER 1 INTRODUCTION 8
indicate that financial reporting fraud is positively associated with the subsequent
corporate renaming behaviour. This result may suggest that the association between
financial reporting fraud and corporate renaming may be confounded by the
endogenous nature. To address the endogeneity concerns, this study performs a two-
stage Heckman test and the results confirm the main findings of this study. Finally, this
study investigates whether the penalties imposed by CSRC would affect the corporate
renaming behaviour among fraud companies. The results suggest that companies
subject to CSRC penalties are more likely to change the company name subsequently.
1.4 Contributions
This study contributes to the literature in several dimensions. First, this study expands
the corporate renaming literature and is the first study empirically linking corporate
renaming behaviour to financial reporting fraud. The extant studies on the corporate
renaming focus on the market reactions (e.g. short-term and long-term share price
reaction) to the corporate name changes (Brown and Clift, 2005; Baker and Wurgler,
2006; Lemmon and Portniaguina, 2006). However, the evidence of how corporate
CHAPTER 1 INTRODUCTION 9
renaming impacts on fraudulent behaviour is limited. Thus, this study is motived to fill
the research gap by connecting two streams of literature on financial reporting fraud
and corporate renaming behaviour.
Second, the studies on the financial reporting fraud and corporate renaming are mainly
based on western countries. In contrast, this study focuses on the Chinese market
because of its unique institutional setting. La Porta et al. (2002) and Durnev and Kim
(2005) show that the legal environment of a country has a significant impact on
company performance and corporate governance. China’s legal enforcement and
investor protection level is relatively weak, and the penalties imposed for financial
frauds tend to be much lower. Corporate insiders in China have greater opportunities to
extract private benefits through a wide range of unethical behaviour at the expense of
outside minority shareholders. Thus, these unique corporate governance characteristics
and regulation deficiency in China provide a great opportunity to study financial fraud.
It is documented that some other developing countries seem to have the similar
institutional environment to that of China. Therefore, the findings of this paper are more
CHAPTER 1 INTRODUCTION 10
generalisable to other emerging markets.
Finally, this study has important policy implications on corporate renaming regulation
in the emerging markets. The results demonstrate that corporate renaming is associated
with the subsequent financial reporting fraud. Therefore, this research is timely and
relevant as it provides a new “red flag” for the regulators to investigate financial fraud
and promote the improvement, legislation and contentious development of the capital
market. Based on the results of this study, a few recommendations are made. Firstly,
the relevant regulatory bodies need to update corporate renaming policies and
regulations, to establish and improve the internal and external control system, and to
focus on building and improving information intermediaries, such as social media, to
reduce information asymmetry. Second, CSRC needs strict enforcement to improve the
seriousness of Security Laws and regulations. Companies that have changed their
corporate name illegally should be subject to sanctions to ensure the authenticity of
information disclosure in the capital market.
CHAPTER 1 INTRODUCTION 11
1.5 Structure of the thesis
The reminder of this thesis is structured as follows. Chapter 2 discusses previous
empirical studies on corporate renaming behaviour and financial reporting fraud. Based
on the literature summarised in Chapter 2 and applying agency theory and fraud triangle
theory, Chapter 3 develops hypotheses to examine the research question. Chapter 4
describes the sample selection, the test period and develops and defines the models and
variables used in the study. Chapter 5 reports the descriptive statistics and regression
results for the hypotheses developed in Chapter 3. Chapter 6 provides a conclusion of
this thesis. Several limitations and suggestions for future research are also discussed.
CHAPTER 2 LITERATURE REVIEW 12
CHAPTER 2 LITERATURE REVIEW
This chapter discusses previous empirical studies on corporate renaming and financial
reporting fraud. The chapter is organised as follows: Section 2.1 briefly presents the
institutional background. Section 2.2 discusses the reasons for corporate renaming and
summarises the findings of studies on capital market reactions to corporate renaming.
Section 2.3 provides a comprehensive review on the financial reporting fraud literature.
2.1 Institutional Background
Financial fraud in China is not uncommon, partially due to the rapid transformation in
Chinese economy in the last decade. Law enforcement institutions and market
regulators play a vital role in protecting investor rights and instilling confidence in the
stock market (La Porta et al., 2000; DeFond and Hung, 2004).
China is a civil law dominion and prior research suggests that shareholder interests are
less well guarded compared to common law countries like the US (La Porta et al., 2000).
Since the Securities Law took effect in December 1998, the CSRC has been the major
CHAPTER 2 LITERATURE REVIEW 13
regulator on corporate fraud for listed companies in China (Friedman, 2002). The
CSRC’s core responsibilities are to “establish policies and regulations, monitor China’s
centralized securities supervisory system, regulate securities issuing and trading, and
investigate and enforce penalties on activities that are in violation of the securities or
futures laws and regulations” (Huang, 2008). The CSRC is also “empowered to issue
Opinions, Guideline Opinions, and non-legally Binding Guidance for publicly traded
corporations” (Friedman, 2002). Since 2004, the role of the CSRC is further expanded
when Supreme People’s Court (PRC) stopped directly deal with securities-related
litigations and delegated this role to the CSRC (Yin, 2004). While more severe
fraudulent activities fall into the responsibilities of the CSRC, in addition, stock
exchanges in China, namely Shanghai and Shenzhen stock exchanges, watch over
minor and less severe violations (Jia et al., 2009).
2.2 Corporate Renaming
2.2.1 Reasons for a corporate name change
Corporate renaming is a common practice in the capital markets. According to the Wind
CHAPTER 2 LITERATURE REVIEW 14
database1, from 2010 to 2017, 1,306 Chinese companies listed on the A-share market
changed their corporate name. A few reasons have advanced for a corporate name
change. First, the most common reason for a corporate name change is a result of
mergers and acquisitions. Presumably it is changing its name as it is part of the other
business group. For example, Muzellec and Lambkin (2009) find that company name
changes often inform fundamental changes in the company’s structure and business
strategies arising from merges and acquisitions. Second, a company may decide to
change to a new corporate name because the company has entered a new line of
business (Andrikopoulos et al., 2007). Third, Morris and Reyes (1992) suggest that a
corporate name change may be a signal to the customers, competitors and investors
about its improvement in the growth prospects of the company. If the corporate name
is changed to serve as a credible signal, then the new corporate name could covey
important insider information.
1 The Wind economic database pairs over 1.3 million macroeconomic and industry time series with powerful graphics and data analysis tools to give financial professionals the most comprehensive insights into China’s economy.
CHAPTER 2 LITERATURE REVIEW 15
2.2.2 Capital market reactions to a corporate name change
Despite all the costs and risks associated with corporate name changes, many
companies decide to change their name because changing a corporate name can also
bring substantial benefits. To date, most of the studies in the accounting and finance
literature on corporate renaming investigate whether security prices react to corporate
renaming behaviour.
2.2.2.1 Corporate renaming announcement and stock price reactions
The first stream of studies conducted in the U.S. simply investigates the share price
movements to the corporate rename announcements using the event study methodology.
Results from these studies seem to suggest that stock price reacts positively to corporate
renaming, but the association is rather weak. Based on a sample of 121 companies
traded on the New York Stock Exchange (NYSE) and the American Stock Exchange
(ASE) that changed name between 1962-1980, Howe (1982) fails to find an association
between corporate renaming and weekly stock returns, concluding that market does not
react to a corporate name change. However, Howe (1982) indicates that companies
CHAPTER 2 LITERATURE REVIEW 16
operate in a dynamic business environment, and the absence of a significant market
reaction to a corporate renaming may be a result of other confounding events.
Bosch and Hirschey (1989) study 79 U.S. companies that changed their names between
1979 and 1986. They find that although a positive market reaction to name change
announcements is found, the effect is statistically weak, except for the companies
having undergone major corporate restructuring. They argue that there is a positive
(beneficial) effects of name change on stock price during the announcement period.
However, this effect is subsequently cancelled off by the negative valuation effects in
the post-announcement period. That is, for shareholders, the value of corporate
renaming information is substantial, but the overall effect is modest and transient.
Following the event study methodology, Horsky and Swyngedouw (1987) examine the
effect of corporate name change announced in the Dow Jones News Services on stock
price of 58 companies between 1981 and 1985. Similar to Howe (1982), they find that
corporate name change signals investors about value of the company, reflected in the
CHAPTER 2 LITERATURE REVIEW 17
stock price. Following the same methodology, Karpoff and Rankine (1994) challenge
the findings from Horsky and Swyngedouw (1987). They argue that Horsky and
Swyngedouw (1987) suffer from potential sample selection bias and provide evidence
that the effectiveness of corporate name change signaling in enhancing the value of the
company is only marginal.
Based on a sample of companies listed on the New York Stock Exchange, a relatively
recent study by Mayo (2013) shows a slightly positive impact on the quotations in the
30 days following the announcement of a company name change, similar to the findings
reported by Bosch and Hirschey (1989) and Karpoff and Rankine (1994).
2.2.2.2 Factors influencing the association between corporate renaming and stock price
reaction, evidence from the U.S.
The second stream of studies examine how the ‘features’ of corporate name or name
changes influence stock prices. Kashmiri and Mahajan (2015) suggest that marketing-
related factors are critical to creating value for company name changes. Those
CHAPTER 2 LITERATURE REVIEW 18
companies that make substantial marketing investments in renaming are better
perceived by investors. Companies that change names to leverage a strong brand in
their portfolio or to proactively communicate a change in their scope of business are
also rewarded on stock market reactions. That is, how corporate name is presented to
investors will ultimately influence their decisions.
Morris and Reyes (1992) study company name changes based on “functional name
characteristics” such as distinctiveness and memorability. They find that
unsophisticated investors had a statistically positive response to distinctive corporate
names and the distinctiveness of corporate names is interrelated to the ‘features’ of
relevance, memorability, flexibility and positive. When investigating thousands of
renaming cases in the U.S. market, Green and James (2013) provide evidence that
corporate name changes increase the average liquidity of shares. Changing the
corporate name into more ‘fluent’ and ‘easier pronounce’ names results in extension of
shareholding and the company’s value.
A study of U.S. companies listed on NASDAQ before and after 2000 presents some
CHAPTER 2 LITERATURE REVIEW 19
interesting results. Cooper et. al. (2005) discover that, in the internet boom period, there
is a positive and significant effect of ‘dot.com’ in corporate name on share price. Their
findings suggest that changing the corporate names to internet-related names
significantly increase the value of the company. The subsequent study carried out in the
market downturn period shows that, in the bust period, investors react positively to
name changes for companies that remove dot.com from their name. The two studies
hence provide supportive evidence that investors are influenced by corporate name
changes that are consistent with the market trend by cosmetic effects.
2.2.2.3 Factors influencing the association between corporate renaming and stock price
reaction: international evidence
The third stream of studies replicate and extend prior U.S.-based studies on corporate
renaming to other jurisdictions, such as UK, Hong Kong and Australia. However,
results are mixed. For example, using a sample of companies from the U.K., Mase
(2009) argues that information about name changes should be important to investors
CHAPTER 2 LITERATURE REVIEW 20
and will generate abnormal return after the corporate renaming announcements. Results
suggest that deleting an element from the company name is companied by a negative
stock price change, while adding an element to the name leads to an increased stock
price.
Based on observations from the Hong Kong market, Kot (2011) demonstrates that
investors respond positively to the corporate renaming behaviour due to mergers or
acquisitions that have restricted or shifted the company’s business. Name changes to
provide charity or for reputational reasons generate no stock price reaction. On the
contrary, in a study limited to Australian companies, Josev et al. (2004) find significant
but negative abnormal returns within 21 days of the name change announcement.
However, they limit the sample to those with self-defined “major” name changes. The
authors argue that the significant change in corporate name is often perceived as
negative information by investors.
To sum up, prior studies provide mixed results regarding the impact of corporate name
CHAPTER 2 LITERATURE REVIEW 21
changes on stock price reactions, probably due to the variation in the focus, sample,
and methodology. Most of these studies on corporate renaming are based on the U.S.,
U.K., Hong Kong and Australian markets where overall institutional-level corporate
governance is strong. As discussed earlier in Section 2.1.1, the phenomenon of
corporate renaming is common in China’s A-share market. However, studies on
corporate renaming is limited in the Chinese setting where the corporate governance
and regulations are relatively weak compared to developed countries. Therefore, the
findings from this study provide additional insights into corporate renaming literature
and have important policy implications on corporate renaming regulation in the
emerging markets.
2.3 Financial Reporting Fraud
2.3.1 Definitions of financial reporting fraud
Financial reporting fraud has different definitions in academic literature and in official
pronouncements by authoritative bodies. For example, Ernst and Young (2009) defines
fraud as “an act of deliberate action made by an entity, knowing that such action can
CHAPTER 2 LITERATURE REVIEW 22
result in a possession of unlawful benefits”. Financial reporting fraud is defined by the
Association of Certified Fraud Examiners (ACFE) as “the intentional, deliberate,
misstatement or omission of material facts, or accounting data which is misleading and,
when considered with all the information made available, would cause the reader to
change or alter his or her judgement or decision”.
The definition of fraud provided by CSRC in China is similar to that defined by ACFE.
CSRC believes financial reporting fraud occurs when a company deliberately deceives
or misleads capital market participants by preparing and disseminating materially
misstated financial statements. Based on this broad definition, CSRC divides financial
reporting frauds into the following six categories: (1) false statement(e.g. misealding
statements of important events and improper disclosure of information), (2) major
failure of disclose information(e.g. does not fully record the matters in the information
disclosure document), (3) illegal share buyback(e.g. illegal repurchasing of share of
stock by the company that issue them), (4) delay in disclosure(failure to disclose
importamt information within the prescribed time), (5) inflated earnings(e.g.
exaggerate current period earnings, or by deflating current period expenses), and (6)
CHAPTER 2 LITERATURE REVIEW 23
others2. This study collects financial reporting fraud data from CSRC website and their
announcements.
2.3.2 Theoretical explanations for financial reporting fraud
The fraud triangle is a commonly used model to explain the factors leading to the
financial frauds. It comprises of three factors, including pressure, opportunity, and
rationalisation (Cressey, 1953). First, pressure is a motivation or an incentive for
companies to commit financial fraud. Every fraudster is under pressure to commit
unethical behaviour (Mansor, 2015). These pressures can either be financial or non-
financial pressure. Albrecht et al. (2014) point out that because the pressure of fraud
may not be true, the use of the word “perceived pressure” is important. If the
perpetrators think they are under pressure, this believe may lead to fraud. Second,
because of ineffective control and governance systems, individual can obtain a good
opportunity to commit fraud. In the field of accounting, this is known as internal control
weakness. The concept of perceived opportunity shows that fraudsters will use
Fraud categorised as Others include: the fabrication of assets, the unauthorized change of fund usages, violations of fund provisions, embezzlement by a major shareholder
CHAPTER 2 LITERATURE REVIEW 24
advantage of circumstances available to them (Kelly and Hartley, 2010). The nature of
perceived opportunity is like perceived pressure. That is, the opportunity is not
necessarily true. In most cases, the lower the risk of being caught, the greater the
likelihood of fraud (Cressey, 1953). Third, rationalisation suggests that the perpetrator
must look for some morally acceptable ideas before committing fraud. Rationalisation
refers to the reasons and excuses for unethical behaviour and criminal activity. If a
person cannot prove that dishonesty is justified, then he or she is unlikely to commit
fraud. The graphic demonstration of fraud triangle theory is presented below in Figure
2.1.
CHAPTER 2 LITERATURE REVIEW 25
Figure 2.1 Fraud triangle
Source: From the element of fraud triangle theory by Cressey (1953)
2.3.3 Accounting literature on financial reporting fraud
There is a large body of accounting literature that explains the corporate financial
reporting fraud. Building upon prior literature, this study focuses on 3 most significant
strands of research. The first line of research focuses on various motivations to commit
financial reporting fraud. The second stream of studies investigate how institutional
characteristics such as weak corporate governance structures promote financial
reporting misconducts. The third group of studies examine the characteristics of
executives associated with the propensity of financial reporting fraud. Each stream of
CHAPTER 2 LITERATURE REVIEW 26
studies is summarised below.
2.3.3.1 Motivations for engaging in financial reporting fraud
According to the fraud triangle theory, pressure is a contributing factor to financial
reporting fraud. Thus, it is expected that companies under pressure are more likely to
commit to financial frauds. Research suggests that incentives to misstate earnings are
from various sources, including unsatisfactory financial performance, the pressure of
meeting analyst forecasts, motivation from the compensation and incentive structures,
and the pressure of external financing needs (Huang et al., 2017).
Financial performance and meeting analysts’ forecasts
Companies with poor financial performance are motivated to falsify the financial report.
Bell et al. (1991) find that poor financial performance increases the likelihood of
financial fraud. DeAngelo and DeAngelo (1990) and Beasley (1996) also show that if
a company has accounting losses and negative cash flows for two consecutive years,
such company is more likely to commit financial reporting fraud. Similar results are
CHAPTER 2 LITERATURE REVIEW 27
also documented in Dechow et al. (2011) that companies have deteriorating return on
assets are associated with increased propensity of financial reporting fraud. Chu et al.
(2016) show that earnings manipulators tend to be companies that have experienced
strong past performance, but whose operating performances began to weaken. Huang
(2006) adopt general indicators of performance such as return on assets (ROA), return
on equity (ROE), Tobin’s Q and operation revenue growth rate, to measure the
company’s financial pressure. There is evidence that companies with the financial
performance ranked lower than that of industry median are more likely to commit
financial reporting fraud. In the even worse situations, financial distress may be another
important factor explaining financial reporting frauds (Kirkos et al, 2007; Zhou and
Kapoor, 2011; Huang et al., 2017). Previous studies consistently show that, on average,
fraud discovered companies have a higher level of financial distress than that of the
non-fraud companies (Bell et al., 1991; Ravisankar et al., 2011).
A few studies also suggest that companies with high growth rates but facing huge stock
CHAPTER 2 LITERATURE REVIEW 28
price declines have greater incentives to engage in fraudulent financial reporting. For
instance, results from Beneish (1999) suggest that companies with deteriorating
prospects (e.g. decreasing gross margins) are more likely to participate in manipulations
that increase earnings. Johnson et al. (2009) provide similar evidence that fraud
companies usually experience decelerating growth in earning per share before the
misconduct begins.
Meeting the analyst’s forecasts is another performance-related incentive to engage in
fraudulent financial reporting. Kaplane (2003) find that the difference between the
financial analysts’ predicted return and reporting earnings is positively related to the
likelihood of financial reporting fraud. Results from Peng et al. (2011) show that 43%
of financial fraud cases are related to meeting the external analyst forecasts. In addition,
Lou and Wang (2009) indicate that fraudulent reports are positively correlated with
analysts’ forecasting errors which is defined as the difference between the analysts’
forecast versus the company’s actual performance.
Executive compensation structure
CHAPTER 2 LITERATURE REVIEW 29
Equity-based compensation (e.g. stock options) is a common motivation for
misrepresentation of financial reporting. Stock options are associated with the
probability to commit financial reporting fraud because the value of options granted to
CEOs are directly influenced by stock prices (Burns and Kedia, 2006). Consistent with
this view, Goldman and Slezak (2006) show that performance-based compensation can
lead to misreporting behaviour. That is, the higher the correlation between CEO
compensation and reported income, the more likely that CEO will adopt discretionary
accounting policies to boost the reported earnings, increasing the probability of
financial frauds.
Efendi et al. (2007) provide new evidence that, when the CEO holds a large number of
stock options, the likelihood of a restatement increases significantly. Similar results are
also evidenced in Peng and Roell (2008) who find that employee stock options are
positively associated with securities class-action litigations, and in Johnson et al. (2009)
who find that executives with financial reporting misconducts have greater incentives
from their unrestricted stock holdings because unstricken stock holdings are easier to
CHAPTER 2 LITERATURE REVIEW 30
be manipulated. More recently, Call et al. (2016) provide empirical evidence that there
is a positive association between companies involved in class-action securities
litigation and number of stock options granted to employees, suggesting employees are
encouraged by stock options to facilitate misreporting and discourages whistle blowing.
External financing needs
Another motivation for financial reporting fraud is to raise capitals on more favorable
terms. For example, a company may exaggerate earnings to obtain a higher price for a
new equity issuance or a lower interest for a new debt issuance. In extreme cases,
companies may use fraudulent financial reporting to cover up financial distress, because
the disclosure of financial distress may threaten the company’s survival, let alone its
ability to raise new capital. An early study by Dechow et al. (1996) finds that,
companies subject to Accounting and Auditing Enforcement Releases (AAERs), are in
need of external financing during the period of which they commit financial reporting
fraud.3 Burns and Kedia (2006) and Erickson et al. (2000) provide similar results that
3 However, a follow-up study by Beneish (1999) failed to find that companies that needed external financing were involved in more financial reporting fraud. He argued that the difference in results was derived by the use of sample matching method.
CHAPTER 2 LITERATURE REVIEW 31
the need for external financing is positively associated with financial reporting frauds.
2.3.3.2 Institutional features enabling financial reporting fraud
According to the fraud triangle theory, opportunity is a contributing factor to financial
reporting fraud. Many studies have examined institutional characteristics such as
corporate governance that may facilitate and contribute to financial reporting fraud.
Beasley (1996) analyses how the characteristics of external directors affect financial
reporting frauds. He finds that misconduct declines with directors’ shareholdings and
directors’ tenure but increases with the number of outside directorships held, suggesting
that independence of directors plays an important role in reducing financial reporting
misconducts. Subsequent studies by Fich and Shivdasani (2007) and Zhao and Chen
(2008) provide similar evidence that director ownership and stronger corporate
governance help reduce financial reporting misconducts, despite Larcker et al. (2007)
find that the key dimensions of corporate governance have little to do with the sample
of accounting restatement.
CHAPTER 2 LITERATURE REVIEW 32
Some studies further explore the role of internal controls and audit committee
effectiveness on the incidence of financial reporting fraud. Internal control of financial
report has always been considered as an important corporate governance mechanism of
the company (Kirkos et al., 2015). Hazarika et al. (2012) find that companies with
higher monitoring effectiveness are less likely to commit financial fraud. Results from
Beasley et al. (2000) show that the likelihood of financial reporting fraud is lower in
companies with an effective internal audit function. The similar findings are found in
Coram et al. (2008) who study the Australian and New Zealand companies. Farber
(2005) provides evidence that the number of audit committee meetings is negatively
related to financial reporting frauds. Further, he finds that the frequency of audit
committee meetings increases substantially after financial frauds are announced.
2.3.3.3 Executive traits and financial reporting frauds
Prior studies reveal a potential association between executive traits and financial
reporting frauds. Based on a detailed analysis of 49 Accounting and Auditing
Enforcement Releases (AAERs) involving financial reporting fraud, Schrand and
CHAPTER 2 LITERATURE REVIEW 33
Zechman (2012) find that CEO overconfidence and narcissism is positively associated
with financial reporting fraud such as overstating profits. More recently, Davidson et
al. (2015) study how executive behaviour and personal characteristics impact on
financial reporting risks. Results from their study show that CEOs and CFOs with more
previous legal violations are more likely to commit financial reporting fraud.
Furthermore, they find that less frugal CEOs oversee a more relaxed control
environment that helps them participate in financial reporting fraud.
Studies also investigated how CEO power influences the corporate and financial
reporting decisions to prepare for financial reporting fraud. For example, Dechow et al.
(1996) find that when CEO is also the founder of the company, the possibility of
financial fraud is greater. These two results support the view that powerful and
entrenched CEO drives the financial reporting misconduct. Feng et al. (2011) study the
importance of CEOs involvement in financial reporting manipulations and find that
powerful CEOs, measured by CEO pay slice, with higher level of equity incentives are
more likely to manipulate financial reports.
CHAPTER 2 LITERATURE REVIEW 34
2.3.4 Financial reporting fraud in China: an overview of the literature
There is a growing body of studies that investigate the determinants of financial
reporting fraud in the Chinese setting. The findings from recent studies are summarized
in this section.
Consistent with the international evidence, Chinese companies that are subject to
financial pressures are more likely to be associated with financial fraud. Fich et al.
(2007) study the determinants and consequences of falsified financial statements in
China. The results show that companies with high debt and that plan to make equity
issues are more likely inflate their earnings in the current year and restate their financial
reports in subsequent years. They also find that corporate governance plays an
important role in mitigating this association. Further, Fich et al. (2007) provide
evidence that restated companies suffer negative abnormal stock returns, increased cost
of capital, greater information asymmetry, a greater frequency of modified audit
opinions, and greater CEO turnover.
CHAPTER 2 LITERATURE REVIEW 35
Chines companies are subject to a two-tier corporate governance structure that is
different from the Anglo-American corporate governance model. Jia et al. (2009)
provide empirical evidence that Chinese listed companies with larger supervisory
boards are more likely to have more severe sanctions imposed upon them by the CSRC,
and listed companies that face more severe enforcement actions have more supervisory
board meetings.
Further on the role of the board of directors, Chen et al. (2006) find that ownership and
board characteristics are important factors explaining financial reporting fraud in China.
Specifically, they find that the proportion of outside directors, the number of board
meetings, and the tenure of the chairman are associated with the incidence of financial
reporting fraud. Cumming et al. (2015) provide some insights into financial fraud
literature by linking the gender diversity to financial reporting fraud. Based on a large
sample of Chinese companies, they find that board gender diversity moderates the
frequency of fraud. Interestingly, they also find women are more effective in male-
dominated industries in reducing both the frequency and severity of fraud.
CHAPTER 2 LITERATURE REVIEW 36
Regarding the role of executives in financial fraud, Wang et al. (2017) investigate the
associations among managerial ability, political connections and enforcement actions
for financial reporting fraud in China. Using a sample of listed companies in China
during 2007–2012, they find that increased managerial ability leads to less financial
reporting fraud. Further, political connections of companies (SOEs) weaken or limit the
effect of managerial ability on the likelihood of financial statement fraud. Two studies
investigate whether equity compensation is associated with the propensity of financial
fraud. However, the results are mixed. On one hand, Conyon and He (2016) document
a significantly negative correlation between CEO compensation and corporate fraud
based on a sample of Chinese companies between 2005 and 2010. On the other hand,
Hass at al. (2016) show that managers’ equity incentives increase their propensity to
commit corporate fraud and this effect is more pronounced for the SOEs.
As the gatekeeper of the capital market, auditors play important roles in deterring
financial fraud. Firth et al. (2005) suggest that regulators believe auditors are
responsible to detect and report frauds that are egregious, transaction-based, and related
CHAPTER 2 LITERATURE REVIEW 37
to accounting earnings. Their empirical analysis shows that auditors are more likely to
be sanctioned by the regulators for failing to detect and report material misstatement
frauds rather than disclosure frauds. After controlling for other corporate governance
factors, Ding et al. (2007) find that Chinese listed companies audited by large audit
companies are less likely to commit financial statement fraud. This effect is more
pronounced for companies operated in regulated industries and for revenue-related
frauds. This study highlights the role of government sanctions in assuring audit quality
in the Chinese setting where auditors face strong regulatory sanctions, but low litigation
risk associated with audit failures.
Financial analysts can be viewed as an external monitoring mechanism in the broad
corporate governance structure. Based on a sample of Chinese listed companies, Chen
et al. (2016) show a negative association between the propensity of corporate fraud and
analyst coverage, and that this effect is more pronounced among non-state-owned
enterprises. They argued that their results are consistent with the fraud triangle theory
that analysts may reduce the fraud opportunity factor as an external monitoring force.
CHAPTER 2 LITERATURE REVIEW 38
Overall, findings from these Chinese-based studies are generally consistent with
evidence in other jurisdictions. That is, corporate governance (Chen at al., 2006; Jia et
al., 2009), audit quality (Firth et al., 2005; Lin et al., 2010), analyst coverage (Chen et
al., 2016), equity compensation (Conyon and He, 2016; Hass et al., 2016), financial
needs (Firth et al., 2011), political connection (Wang et al., 2017) and board gender
diversity (Cumming et al., 2015) are determinants of financial reporting fraud in China.
This study aims to extend prior studies to investigate whether corporate renaming is a
‘red flag’ for financial fraud in China.
CHAPTER 3 HYPOTHESE DEVELOPMENT 38
CHAPTER 3 HYPOTHESES DEVELOPMENT
This chapter outlines the hypotheses development for this research. Section 3.1
discusses the hypotheses regarding the effect of corporate renaming on the propensity
of financial fraud (H1). Section 3.2 discusses whether the government ownership
moderates the association between the corporate renaming and the likelihood of
financial reporting fraud (H2). Section 3.3 predicts the role of powerful board on the
association between corporate renaming and the incidence of financial reporting fraud
(H3).
3.1 Corporate renaming and fraud
The phenomenon of corporate renaming in China’s A-share market has intensified in
recent years. From 2010 to 2017, there are 1,306 listed companies that have changed
their corporate name. Among these companies, there are 371 companies committed
financial reporting fraud as disclosed by the CSRC, accounting for 28.41% of the
CHAPTER 3 HYPOTHESE DEVELOPMENT 39
observations.4 The major types of frauds include: false statement, a major failure to
disclosure information, illegal share buybacks, delay disclosure and inflated earnings.
Prior literature identifies various contributing factors to financial reporting frauds.5 As
discussed in Chapter 2, some studies focus on the motivations of engaging in financial
reporting misconducts (Bell et al., 1991; Karpoff, 1994; Hooper et al., 2010; Dechow
et al., 2011) while others focus on how institutional characteristics (e.g. weak corporate
governance and ownership structure) facilitate financial reporting fraud (Shleifer and
Vishent, 1994; Beasley, 1996; Chen et al., 2006; Richard, 2013). Moreover, there is a
line of studies that investigate the relation between traits of executives and financial
frauds (Schrand and Zechman, 2012; Feng et al., 2011). This study extends the financial
reporting fraud literature by investigating whether the corporate renaming is associated
(‘a red flag’) with financial reporting fraud.
4 See Chapter 4 for detailed descriptive statistics. 5 See Chapter 2 for a review of the literature on financial reporting fraud.
CHAPTER 3 HYPOTHESE DEVELOPMENT 40
Agency theory (Jensen and Meckling, 1976) suggests that the company is a nexus of
contracts, which is essentially a large network of principal-agent relationships.
Corporate information disclosure reflects the process and result of the multilateral game
of stakeholders and provides the basic information disclosed to stakeholders for their
decision-making. However, during the process, there might be adverse selection and
moral hazard problems arising due to incomplete contract and information asymmetry.
Among many disclosures announced by the company, corporate renaming is the most
eye-catching information for investors. Changes in the corporate’s name will give
investors the most intuitive understanding of the area in which the company is
developing, as well as the company’s operations and future developments. It can be
argued that if a corporate name change is a result of mergers and acquisitions, then
consistent with the signaling theory, the new corporate name is to better reflect the
ownership and changes in business operations. Therefore, the corporate name changes
deliver ‘decision-useful’ information to the investors (Howe, 1982; Horskey and
Swyngedouw, 1987; Muzellec and Lambkin, 2005; Mayo, 2013).
CHAPTER 3 HYPOTHESE DEVELOPMENT 41
However, corporate renaming can also be used by management for manipulating
purposes or even to commit fraud, especially in China where corporate renaming is not
costly (Firth et al., 2005) and the governance and legal schemes are still insufficient in
investor protection (Jiao et al., 2015). Previous research indicates that when a company
changes its corporate name to a word that follows the current economic trend, the
company can obtain excess returns in the short term, regardless of its real operating
performance (Kashmiri and Mahajan, 2015; Morris and Reyes, 1992). Therefore,
renaming becomes the ‘opportunity’ to boost the stock price. On the other hand, stock
price indicates a company’s market performance (Huang, 2012; Tao, 2017).
Management does have incentives to boost the company’s stock price in various means
(Chen, 2006; Dechow et al., 2011). The fraud triangle theory suggests that opportunities
can facilitate the financial reporting frauds. Because corporate renaming can be used
easily, and the governance scheme is not effective enough to deter the misuse of
corporate renaming, management might take this ‘opportunity’ (country-level
governance and regulation weakness) to misuse the means of corporate renaming to
manipulate the company’s capital market price. This is evident in the case of ‘P2P
CHAPTER 3 HYPOTHESE DEVELOPMENT 42
Financial Information Services’ where the company used renaming effect to obtain
excess returns in a short period of time, followed by a large sell of company’s stocks to
achieve illegal cash out when the stock price peaked. Moreover, prior studies provide
mixed results regarding the impact of corporate name changes on stock price reaction.
However, there are still many companies that are keen to change the company name.
One potential reason may be that changing the company name can divert the attention
of regulators and investors and provide a favorable opportunity and times to commit
financial fraud. Renaming behavior may indicate the beginning of the financial fraud.
Accordingly, the first hypothesis is developed as follows:
: Renaming companies are more likely to commit financial fraud than those non-
renaming companies.
3.2 Ownership structure, corporate renaming, and financial reporting fraud
Chinese companies feature highly concentrated ownership (Chen et al., 2016). It is
documented that more than half of Chinese listed companies are state-owned
enterprises (SOEs), directly or indirectly owned by local or central government. State
CHAPTER 3 HYPOTHESE DEVELOPMENT 43
ownership in turn affects the information environment of listed companies, as well as
the monitoring functions of the board and external investors (Gul et al., 2013).
Literature suggests that, compared to non-SOEs, SOEs are less incentivised to commit
financial fraud for a few reasons. Firstly, Chinese SOEs are governed by the State-
owned Assets Supervision and Administration Commission (SASAC). To present the
state ownership and public interests, SASAC appoints their representative directors in
SOEs and evaluates their performance not only based on the economic performance of
the company but also considering its social and public influence (Gul et al., 2013; Hass
et al., 2016). Therefore, the balanced performance measurement scheme in SOEs has
strengthened the awareness of social and public interests and has mitigated the overall
corporate incentive to only pursue financial targets. Hence, SOEs are less incentivised
to engage in financial reporting fraud to achieve financial targets.
Secondly, the disclosure of SOEs tends to be of higher quality and more transparent
(Shleifer and Vishney, 1994). Gul et al. (2013) suggest that in the context of China, a
CHAPTER 3 HYPOTHESE DEVELOPMENT 44
company often enjoys better information environment when its largest shareholder is
affiliated to the government. A more transparent information environment may result
in a situation where management has little opportunities to commit financial fraud.
Thirdly, SOEs in China are subject to strict regulations and are expected to provide
stronger investor protections. Hence the consequences of detected fraud are often much
severe in SOEs than that in the non-SOEs. Hou and Moore (2010) argue that due to the
political connections with the government, SOEs face monitoring and scrutiny not only
from market regulators, but also from local governments and even central government.
Chen et al. (2006) indicate that the consequences of committing fraud in SOEs could
be more serious and sustained. For example, a disclosed financial fraud in a SOE could
make the affected management severely punished and ruin their political career.
Fourthly, SOEs are less likely to be subject to extreme financial distress compared to
CHAPTER 3 HYPOTHESE DEVELOPMENT 45
non-SOEs. According to the fraud triangle theory (Cressey, 1973), financial distress6
is one contributing factor for management to commit fraud (Burns and Kedia, 2006;
Erickson et al., 2000; Huang et al., 2016). SOEs often receive financial support (known
as ‘invisible hands’) from the government when they are financially distressed and are
well supported by favorable regulatory polices (e.g. Tax breaks on certain products;
lower interest rates on loans from state-owned banks). However, these financial
resources and supports are not generally available for non-SOEs. Thus, non-SOEs can
be more sensitive to the company’s financial goals and pressure.
Overall, this study argues that, without interests and pressure heavily aligned with the
company’s financial target, SOEs have less incentives to employ corporate renaming
as an opportunistic means of achieving financial targets and engaging in financial
fraudulent activities. Instead, because of the benefits from a more transparent and
regulated information environment in SOEs, SOEs may be more likely to use corporate
renaming as a mechanism to communicate inside information about future aspect and
In China, if the listed companies reported a loss for two consecutive years, the companies will be marked ‘ST” in front of the company abbreviation to be differentiated from other stocks. The stock exchanges take “special treatment’ to warn the investors about risks of being delisted from the Chinese security exchange.
CHAPTER 3 HYPOTHESE DEVELOPMENT 46
operations of the company (e.g. mergers and acquisitions), reducing information
asymmetry. On the other hand, renaming behaviour provides non-SOEs a possible
channel to solve the long-term financial distress and to engage financial fraud for
compensation and contracting (e.g. debt covenant) purposes. Based on the above
arguments, the second hypothesis is presented as follows:
The association between corporate renaming and the likelihood of financial
reporting fraud is not as strong in SOEs as that in non-SOEs.
3.3 Board power and risk of financial fraud from corporate renaming
The board of directors play an important role in corporate governance. The main
responsibility of the board of directors is to develop the company’s overall strategy,
monitor the management performance and ensure that appropriate corporate
governance structure, including environmental control, adequate disclosure and
protections for the minority shareholders (Yermark, 1996; Bennedsen, 2008). The board
is part of the highest corporate hierarchy in the company’s organisational structure
CHAPTER 3 HYPOTHESE DEVELOPMENT 47
(Kim and Nofsinger, 2007) and is an important ingredient in solving agency problems
within an organisation (Chen et al., 2006). The board of directors is a group of people
who bear certain legal obligations to shareholders (Hermalin and Weisbach, 1991).
They are expected to abide by the rules of business judgement and act with integrity for
the best interests of the company and shareholders (Kim and Nofsinger, 2007).
Corporate renaming is a strategic decision made from the top of the organisation. For
example, Chinese corporate law requires that the corporate name change must be voted
at a general meeting (AGM) by board of directors (Zhang et al., 2016) where the
decision making might be discretionarily influenced by the board’s power in dealing
with corporate agency issues. The number of shares held by the board of directors often
reflects the power of their rights. The higher the shareholding ratio of the board, the
greater the decision-making power it has. Recent empirical studies suggest that the
power of board of directors is associated with several of agency problems. For example,
some studies find that, due to the abuse of power as a sign of corporate governance
failure, powerful board of directors reduce managerial compensation efficiency
CHAPTER 3 HYPOTHESE DEVELOPMENT 48
(Faulkender and Yang, 2010; Bebchuck et al., 2011; Morse et al., 2011). Bebchuch et
al. (2011) and Gabaix and Landier (2008) find that companies with powerful board are
associated with lower profitability and corporate value. Moreover, some boards started
to commit financial fraud to improve their values through accountants (Jensen and
Meckling, 1976). In addition, studies indicate that a powerful board may gain a degree
of autonomy due to lax internal governance mechanisms that leads to monitoring
deficiencies in disciplining the board in case of management misconduct behaviour
(Fogel, Ma and Morck, 2014). As a result, Khanna et al. (2015) conclude that board
power arising from appointment decisions increases the likelihood of financial fraud
scandals and reduces the detection of fraud.
Based on the above arguments, this study predicts that, within the corporate renaming
context, companies with powerful board are more likely to utilise their power to lax the
governance and monitoring schemes and participate in fraudulent activities through the
corporate name changes, leading to the third hypotheses:
: The association between corporate renaming and the likelihood of financial
CHAPTER 3 HYPOTHESE DEVELOPMENT 49
reporting fraud is stronger in a company with a powerful board than that in a company
with a less powerful board.
CHAPTER 4 RESEARCH DESIGN 49
CHAPTER 4 RESEARCH DESIGN
This chapter describes the research design that is used to test the hypotheses developed
in the preceding chapter. Section 4.1 discusses the sample selection and the test period.
The research design is outlined in Section 4.2 where the models and variables are
developed and defined.
4.1 Data and Sample
The China Stock Market and Accounting Research (CSMAR) database is employed to
provide unique data on fraudulent cases and enforcement actions. CSMAR contains
detailed information on corporate fraud enforcement actions against listed companies
in China, as well as data on corporate governance mechanisms, analyst forecasts,
financial data and transaction information for listed companies on Shanghai and
Shenzhen stock exchange. These data are coded directly from the annual financial
reports of listed companies and major announcements of the CSRC. This database is
commonly used in previous research on corporate fraud (e.g., Wang et al., 2017; Chen
CHAPTER 4 RESEARCH DESIGN 50
et al., 2006; Firth et al., 2005). In this study, the data on financial fraud, financial
information and corporate governance are all downloaded from CSMAR. In addition,
corporate renaming data come from the Wind database.
The sample includes all listed companies in China’s A-share market in an eight-year
period from 2010 to 2017. The sample period commences from 2010 because this study
attempts to reduce the impact of the 2008 global financial crisis on the research results.
Constraint to data availability, the sample period ends at 2017 when this study started.
Table 4.1 shows the sample selection process. After merging all listed companies in
Chinese A-share market as selected from CSMAR database with required financial and
corporate governance data, and the renaming information from the Wind database, the
sample starts with 21,990 company-years that have A-shares traded on the Shanghai
and Shenzhen stock exchanges. There are 1,465 observations deleted because of
insufficient data on test variables. In addition, this research further drops the education
industry because there are less than 10 observations (N=9) in the education industry
with perfect multicollinearity presented in the sample. The final sample consists of
CHAPTER 4 RESEARCH DESIGN 51
20,516 company-year observations. The sample selection procedure is outlined in Table
4.1.
4.2 Research Method and Model
Hypotheses 1 (H1) predicts that the likelihood of financial fraud is positively associated
with the incidence of corporate renaming behaviour. In order to test H1, this study
estimates a logistic regression (Model 1 presented below) of fraudulent financial
reporting on corporate renaming behaviour with a set of control variables documented
to be related to the likelihood of fraud in prior literature (Cressey, 1950; Beasley, 1996;
Chen et al., 2006; Wang et al., 2017). The purpose of this research is not to create a
predictive model of fraud, so bias in the constant term has no effect on the analysis.
Company-year observations that have A-shares trade on the stock
exchanges in Shanghai and Shenzhen from 2010 to 2017 21,990
Less: the following observations Missing financial statement data -1,465
The number of observations in the education industry -9
Number of company-years in the full sample 20,516
Table 4.1 Sample selection
CHAPTER 4 RESEARCH DESIGN 52
= + RENAMING + DUAL + OUTSIDE +
ROE + LEV + AUDITINGOPINION + LISTINGPLACE + AGE +
LARGESTSHARE + BIG4 + SIZE + ST+ δ INDUSTRY + Φ
YEAR …………………………………………………………………Model (1)
The dependent variable FRAUD is a dummy variable to measure financial reporting
fraud, defined as 1 when the listed company is alleged to have experienced the financial
fraud and 0 otherwise. It is argued that the impact of renaming on financial fraud can
be concurrent in the same year or led to the subsequent year; therefore, the model is
estimated with the dependent variable FRAUDt and FRAUDt+1 respectively in the tests.
RENAMING is the main variable of interest, coded as 1 if the company renames its
corporate name during the year and 0 otherwise.
This study includes a series of control variables that are identified as determinants of
financial reporting fraud. The first set of variables control for the corporate governance
quality. Jenson (1976) argues that the CEO cannot duly perform the chairperson’s
monitoring role apart from his or her personal interests. He believes that it is important
CHAPTER 4 RESEARCH DESIGN 53
to separate the chairperson and CEO positions if the board is to be an effective
monitoring device. Carcello and Nagy (2004) find a positive relationship between the
financial fraud and CEO duality. Therefore, this study includes an indicator variable,
DUAL, which equals 1 if the same person holds a dual position as the board chair and
CEO of the company, and 0 otherwise. Prior research also finds that the likelihood of
committing to financial fraud is positively related to the board size (Carcello and Nagy,
2004); thus BOARDSIZE, measured as the number of directors on the board, is
controlled in the model. The frequency and severity of corporate frauds are affected by
the supervisory efficiency of outside directors. Hu et al. (2010) find that independent
directors play an effective role in the corporate governance of listed companies in China.
Thus, OUTSIDE is included, representing the percentage of independent directors on
the board. The percentage of shares held by the largest shareholder is also included
(LARSHARE) in the regression because largest shareholder can effectively monitor a
company and thus reduce the likelihood of fraud. Chen et al. (2006) contend that the
characteristics of the board are related to financial fraud. On the one hand, the
concentrated ownership structure may cause the interests of minority shareholders to
CHAPTER 4 RESEARCH DESIGN 54
be encroached. On the other hand, the supervision of major shareholders will help
improve the company’s performance.
The second set of variables control for company characteristics. Basley et al. (1999)
and Carcello and Nagy (2004) state that the likelihood of financial fraud is negatively
associated with the company size, as fraud is more prevalent among smaller companies.
The company size (SIZE) is measured as the natural log of total assets. Previous studies
find that companies with poor financial performances are more likely to commit
financial fraud (Chen et al., 2006, Beasley, 1996). This study considers three financial
indicators related to financial health and company performance: leverage (LEV), return
on equity (ROE) and special treatment (ST). LEV is the financial leverage of the
company measured as the total liabilities divided by total assets. ROE is the return on
equity and indicates the company performance. ST is a dummy variable that equals to
1 if the listed companies is a special treatment7 company and 0 otherwise. Further, this
study includes AGE in the regression model, and it equals to the number of years a
ST stands for special treatment. In the event of financial issues or other abnormal conditions of listed companies that make investors unable to judge the future of the companies and may endanger the interest of investors, the Stock Exchanges shall take special treatment on these stocks.
CHAPTER 4 RESEARCH DESIGN 55
company’s stock has been traded on the stock exchange. The listing place of the listed
companies, LISTINGPLACE, is also controlled in Model (1). LISTINGPLACE is a
dummy variable that equals to 1 if the company is listed on the shanghai stock exchange,
and 0 otherwise.
The last two control variables are related to audit quality as audit quality is found to be
associated with financial reporting fraud (Carcello and Nagy, 2004). Audit opinion
(AUDITOPINION) is an indicator variable that equals 1 when an unmodified opinion
is issued, and 0 otherwise. BIG4 controls for the type of auditors used by the listed
companies. Carcello and Nagy (2004) state that companies audited by the high-quality
audit companies are less likely to commit financial reporting fraud. As such, this study
uses the BIG4 audit companies as a proxy for high-quality auditors. BIG4 is an indicator
variable that equals 1 while the auditor is from one of the big 4 auditors in China, and
0 otherwise.
CHAPTER 4 RESEARCH DESIGN 56
Hypotheses 2 (H2) predicts that the positive association between financial fraud and
corporate renaming is more pronounced in non-SOEs. To test H2, Model (2) is estimated
by including SOE and SOE*RENAMING into Model (1).
= + RENAMING + SOE + SOE*RENAMING + DUAL +
OUTSIDE + ROE + LEV + AUDITINGOPINION +
LISTINGPLACE + AGE + LARGESTSHARE + BIG4 + SIZE
+ ST + δ INDUSTRY + Φ YEAR………………………………………..Model (2)
SOE is a dummy variable that equals 1 if the company is a state-owned enterprise, and
0 otherwise. Prior studies find that SOEs are less like to commit financial fraud (e.g.
Hou and Moore, 2010). As a result, this study predicts that the sign of SOE is negative.
All other variables are previously defined in Model (1). As predicted in H2, the
coefficient on the variable of interest, SOE*RENAMING, is expected to be negative.
Hypotheses 3 (H3) predicts that the positive association between financial fraud and
corporate renaming is more pronounced for companies with a more powerful board of
directors. Model (3) is used to test H3 by including BOARDPOWER and
CHAPTER 4 RESEARCH DESIGN 57
BOARDPOWER*RENAMING in Model (1).
= + RENAMING + BOARDPOWER + BOARDPOWER*RENAMING
+ DUAL + OUTSIDE + ROE+ LEV +
AUDITINGOPINION + LISTINGPLACE + AGE + LARGESTSHARE
+ BIG4 + SIZE + ST + δ INDUSTRY + Φ
YEAR…………………………………………………………………..Model (3)
BOARDPOWER is measured as the number of shares held by the board of directors.
Previous studies find that powerful board increases the likelihood of financial fraud
scandals and reduces the detection of fraud (Khanna et al., 2015). Therefore, this study
predicts that the coefficient on the interaction variable BOARDPOWER*RENAMING
is positive.
Year and industry fixed effects are controlled in Models (1) to (3). The standard errors
are clustered by company in order to deal with potential heteroscedasticity or serial
correlation. The definitions of variables are summarised in Table 4.2 below.
CHAPTER 4 RESEARCH DESIGN 58
Table 4.2 Variable definition and measurement
Variables Measures
FRAUD A dummy variable that equals to 1 when the listed company is alleged to
have experienced financial fraud, and 0 otherwise.
RENAMING A dummy variable that equals to 1 if the company renames its corporate
name during the year, and 0 otherwise.
BOARDPOWER The number of shares held by the board of directors.
SOE A dummy variable that takes the value of 1 if a company is state-owned,
and 0 otherwise.
DUAL A dummy variable that takes the value of 1 if the CEO also serves as the
board chairperson and 0 otherwise.
BOARDSIZE The number of directors on the board.
OUTSIDE The percentage of independent directors on the board.
ROE Return on equity.
LEV Financial leverage ratio measured as total liabilities over total assets.
AUDITINGOPINION A dummy variable that equals to 1 when an unmodified opinion is issued,
and 0 otherwise.
LISTINGPLACE A dummy variable that equals to 1 if the company is listed on the Shanghai
stock exchange, and 0 otherwise.
AGE The number of years a company’s stock has been traded on the stock
exchange.
LARGESTSHARE The percentage of shares held by the largest shareholder.
BIG4 A dummy variable that equals to 1 when the company is audited by a Big4
audit company, and 0 otherwise.
SIZE The log of total assets.
ST A dummy variable that equals to 1 if the listed companies is a special
treatment company, and 0 otherwise.
CHAPTER 5 RESULTS 60
CHAPTER 5 RESULTS
Chapter 5 summarises the set of empirical results. Section 5.1 summarises descriptive
statistics and Section 5.2 presents the correlation matrix. Section 5.3 provides a
summary of the empirical results relating to Hypotheses 1 to 3. Section 5.4 summarises
the results from several robustness and sensitivity tests.
5.1 Descriptive statistics
Panel A of Table 5.1 shows the sample distribution of companies with financial fraud
and corporate renaming in each year. Among the 20,516 company-year observations in
the sample, there is an increasing number of companies listed on Shanghai or Shenzhen
Stock Exchange across the years, from 1,967 companies (9.59 percent) in 2010 to 3,327
companies (16.22 percent) in 2017. It is noted that the percentage of sample companies
that committed to financial fraud increased from16.07 percent (N=316) in 2010 to 22.62
percent (N=550) in 2012, followed by a downward trend from 2013 to 2016. The lowest
percentage of fraud (8.00 percent, N=266) is observed in 2017. The number of
CHAPTER 5 RESULTS 61
companies with renaming increases from 2010 to 2016. In 2010, there are 129 listed
companies (6.56 percent) changed their corporate names, increasing to 218 companies
(7.50 percent) with name changes in 2016. The number of corporate name changes
decreases in 2017 to 189 companies (5.68 percent). This may be a result of the
implementation of “Index of Listed Companies Changing Security Name” in 2016 that
has put strict renaming requirements on listed companies in order to prevent companies
using discretional renaming practice to mislead investors.
The industry distribution8 is reported in Panel B of Table 5.1. Companies from the
Manufacturing industry make up about 64 percent of the sample, and companies in
Wholesale and Retail Trade, IT as well as Real Estate account for another 15 percent
of observations. The remaining observations are evenly distributed across the other
industries with exceptions of Public Administration and Defense (0.09 percent) and
Human Health and Social Work (0.17 percent). It is also noted from Table 5.1 Panel B
that Agriculture industry reports the highest percentage (35.49 percent) to commit
The industry classification is based on the industry codes issued by the CSRC. As a result, the sample companies are classified into 18 industries.
CHAPTER 5 RESULTS 62
financial fraud. In addition, Accommodation industry reports the highest percentage
(18.18 percent) to change corporate name between 2010 and 2017.
Table 5.1 Sample distributions
Panel A: by year
Year Freq. Percent Number of
observations
with fraud
Percent Number of
observations
with
renaming
Percent
2010 1,967 9.59% 316 16.07% 129 6.56%
2011 2,265 11.04% 465 20.53% 139 6.14%
2012 2,431 11.85% 550 22.62% 139 5.72%
2013 2,403 11.71% 501 20.85% 143 5.95%
2014 2,508 12.22% 445 17.74% 153 6.10%
2015 2,709 13.20% 527 19.45% 196 7.24%
2016 2,906 14.16% 401 13.80% 218 7.50%
2017 3,327 16.22% 266 8.00% 189 5.68%
Total 20,516 100% 3,471 16.92% 1,306 6.37%
CH
APT
ER 5
RES
ULT
S 63
Pane
l B: b
y in
dust
ry
Indu
stry
Fr
eq.
Perc
ent
Num
ber
of o
bser
vatio
ns
with
frau
d
Perc
ent
Num
ber
of o
bser
vatio
ns w
ith
rena
min
g
Perc
ent
Agri
cultu
re
324
1.58
%
115
35.4
9%
41
12.6
5%
Min
ing
523
2.55
%
127
24.2
8%
53
10.1
3%
Man
ufac
turi
ng
13,1
01
63.8
3%
3,54
3 27
.04%
1,
118
8.53
%
Powe
r, ga
s and
wat
er
646
3.15
%
89
13.7
8%
41
6.35
%
Con
stru
ctio
n 52
4 2.
55%
13
3 25
.38%
35
6.
68%
W
hole
sale
and
reta
il tr
ade
1,12
8 5.
50%
24
5 21
.72%
81
7.
18%
Tr
ansp
orta
tion
633
3.09
%
65
10.2
7%
24
3.79
%
Acco
mm
odat
ion
88
0.43
%
29
32.9
5%
16
18.1
8%
IT
1,15
6 5.
63%
30
6 26
.47%
75
6.
49%
Fi
nanc
ial a
nd in
sura
nce
305
1.49
%
60
19.6
7%
14
4.59
%
Real
est
ate
991
4.83
%
223
22.5
0%
107
10.8
0%
Leas
ing
225
1.10
%
47
20.8
9%
14
6.22
%
Prof
essi
onal
, sci
entif
ic a
nd te
chni
cal
144
0.70
%
14
9.72
%
8 5.
56%
Ad
min
istr
ativ
e an
d su
ppor
t ser
vice
19
8 0.
97%
46
23
.23%
15
7.
58%
Pu
blic
adm
inis
trat
ion
and
defe
nse
19
0.09
%
2 10
.53%
1
5.26
%
Hum
an h
ealth
and
soci
al w
ork
35
0.17
%
3 8.
57%
2
5.71
%
Arts
, ent
erta
inm
ent a
nd re
crea
tion
233
1.14
%
33
14.1
6%
33
14.1
6%
Oth
ers
243
1.18
%
69
28.4
0%
40
16.4
6%
Tota
l 20
,516
10
0%
CHAPTER 5 RESULTS 64
Table 5.2 displays the descriptive statistics for all variables used in the regressions. The
full sample comprises 20,516 9 company-year observations for Chinese listed
companies from 2010 to 2017. The mean FRAUDt is 0.1691, indicating that about 16.91
percent of listed companies during 2010 to 2017 are detected as fraud by the regulatory
agencies. Similarly, the mean FRAUD t+1 is 0.1776, indicating that about 17.76 percent
of listed companies during 2011 to 2017 are detected as fraud. There are, on average,
6.37 (6.74) percent of total listed companies changed their corporate name
(RENAMING) during the sample period 2010-2017 (2011-2017). The other two
variables of interest are SOE and BOARDPOWER. The summary statistics shows that
the average shareholding ratio by the board is 12.41 percent (BOARDPOWER). In
addition, on average, there are 41.97 percent of total listed companies are state-owned
enterprises (SOE).
In terms of corporate governance variables, the mean DUAL is 0.7373, suggesting that
73.73 percent companies’ CEO and board chair are the same person. In addition, the
The full sample size for the T+0 period (from 2010 to 2017) is 20,516 and the sample size for the T+1 period (from 2011 to 2017) is 17,011.
CHAPTER 5 RESULTS 65
average number of directors on the board is 8.7349 (BOARDSIZE). The descriptive
statistics also show that on average, 37.29 percent of directors on the board are
independent directors (OUTSIDE). Furthermore, the average percentage of shares held
by the largest shareholder is 35.33 percent (LARGESHARE). Regarding the company
characteristics, the average size (natural log of total assets) of the listed companies is
22.0321, ranging from a minimum of 13.0760 to a maximum of 30.8148. The average
mean ROE and LEV are 0.0667 and 0.4360 respectively, suggesting that most sample
companies have a good financial performance during the sample period and these
companies are not highly leveraged. Further, the mean ST is only 3.67 percent,
suggesting that majority of companies perform well. The average number of years a
company’s stock has been traded on the Chinese securities exchange is 9.3494 years
(AGE) and 61.09 percent of sample companies are listed on the Shanghai Stock
Exchange. Finally, two variables are included in models to measure the audit quality of
listed companies. During the sample period, only about 6 percent of listed companies
used Big 4 auditors. The mean AUDITOPINION is 0.9614, showing that 96.14 percent
of listed companies obtained an unmodified opinion during the sample period.
CHAPTER 5 RESULTS 66
All the variables are defined in Table 4.2.
Table 5.2 Summary statistics Variable Obs Mean Median 25% 75% Std. Dev. Min Max
FRAUDt 20,516 0.1691 0 0 0 0.3749 0 1
RENAMINGt 20,516 0.0637 0 0 0 0.2442 0 1
FRAUD t+1 17,011 0.1776 0 0 0 0.3822 0 1
RENAMING t+1 17,011 0.0674 0 0 0 0.2507 0 1
BOARDPOWER 20,516 0.1241 0.0005 0 0.2197 0.1962 0 0.6753
SOE 20,516 0.4197 0 0 1 0.4935 0 1
DUAL 20,516 0.7373 1 0 1 0.4401 0 1
BOARDSIZE 20,516 8.7349 9 7 9 1.8196 3 22
OUTSIDE 20,516 0.3729 0.3333 0.333 0.4286 0.0549 0.1250 0.8000
ROE 20,516 0.0667 0.0720 0.031 0.1133 0.1181 -0.8496 0.6421
LEV 20,516 0.4360 0.4210 0.250 0.6024 0.2351 0.0262 2.2581
AUDITOPINION 20,516 0.9614 1 1 1 0.1926 0 1
AGE 20,516 9.3494 8 3 15 6.9446 0 27
LARGESTSHARE 20,525 0.3533 0.3332 0.234 0.4533 0.1516 0.0220 0.8999
BIG4 20,516 0.0592 0 0 0 0.2360 0 1
SIZE 20,516 22.032 21.830 21.05 22.764 1.4538 13.076 30.814
ST 20,516 0.0367 0 0 0 0.1881 0 1
LISTINGPLACE 20,516 0.6109 1 0 1 0.4876 0 1
CHAPTER 5 RESULTS 67
5.2 Results of Correlations
Table 5.3 shows the Pearson correlations for the variables used in the regressions. The
dependent variable FRAUD is positively correlated with RENAMING (r=0.080,
p<0.01), providing preliminary evidence that corporate renaming behaviour can
increase the likelihood of a company committing financial fraud. It is shown that
FRAUD is also positively correlated to the leverage ratio (r=0.087, p<0.01), the
numbers of years a company’s stock has been traded on a national securities exchange
(r=0.035, p<0.01) and ‘special treatment’ (r=0.076, p<0.01) suggesting that companies
under pressure (e.g. special treatment companies because of consecutive losses for two
years) are more likely to commit frauds.
However, FRAUD is found to be negatively correlated with BIG 4 (r=-0.052, p<0.01)
and audit opinion (r=-0.128, p<0.01), which indicates that high quality auditors can
reduce the likelihood of a company committing financial fraud. In addition, FRAUD is
negatively correlated to the ROE (r=-0.104, p<0.01) and SIZE (r=-0.062, p<0.01),
which may suggest that fraud is more prevalent among smaller companies and
CHAPTER 5 RESULTS 68
companies with good performance are less incentivized to engage in financial frauds.
Further, the independent variable RENAMING is positively correlated with DUAL
(r=0.014, p<0.05), LEV (r=0.126, p<0.01), ST (r=0.749, p<0.01), and AGE (r=0.153,
p<0.01). However, RENAMING is negatively correlated with the BOARDSIZE (r=-
0.025, p<0.01), ROE (r=-0.040, p<0.01), AUDITOPINION (r=-0.143, p<0.01),
LARGESTSHARE (r=-0.056, p<0.01), BIG4 (r=-0.033, p<0.01) and SIZE (r=-0.062,
p<0.01).
CH
APT
ER 5
RES
ULT
S 69
Tabl
e 5.
3 C
orre
latio
n m
atri
x
Vari
able
s (1
) (2
) (3
) (4
) (5
) (6
) (7
) (8
) (9
) (1
0)
(11)
(1
2)
(13)
(1
4)
(15)
(1
6)
(1) F
RAU
D
1.00
0
(2) F
RAU
D T
+1
0.39
9***
1.00
0
(3) R
ENAM
ING
0.
080**
* 0.
060**
* 1.
000
(4) R
ENAM
ING
T+1
0.
073**
* 0.
085**
* 0.
240**
* 1.
000
(5) D
UAL
-0
.016
**
-0.0
26**
* 0.
014**
0.
019**
1.
000
(6) B
OAR
DSI
ZE
-0.0
13**
-0
.013
* -0
.025
***
-0.0
38**
* 0.
178**
* 1.
000
(7) O
UTS
IDE
-0.0
06
-0.0
19
-0.0
01
0.00
3
-0.1
03**
* -0
.435
***
1.00
0
(8) R
OE
-0.1
04**
* -0
.087
***
-0.0
40**
* -0
.116
***
-0.0
16**
0.
033**
* -0
.014
**
1.00
0
(9) L
EV
0.08
7***
0.07
6***
0.12
6***
0.13
7***
0.15
7***
0.19
1***
-0.0
14**
-0
.107
***
1.00
0
(10)
AU
DIT
OPI
NIO
N
-0.1
28**
* -0
.143
***
-0.1
43**
* -0
.150
***
-0.0
08
-0.0
05
0.01
0
0.13
7***
-0.1
73**
* 1.
000
(11)
AG
E 0.
035**
* 0.
015**
0.
153**
* 0.
134**
* 0.
236**
* 0.
102**
* -0
.033
***
-0.0
86**
* 0.
395**
* -0
.136
***
1.00
0
(12)
LAR
GES
TSH
ARE
-0
.084
***
-0.0
78**
* -0
.056
***
-0.0
74**
* 0.
045**
* 0.
020**
* 0.
050**
* 0.
100**
* 0.
025**
* 0.
096**
* -0
.086
***
1.00
0
(13)
BIG
4
-0.0
52**
* -0
.059
***
-0.0
33**
* -0
.036
***
0.07
8***
0.18
5***
0.03
1***
0.06
9***
0.14
5***
0.03
3***
0.06
0***
0.13
5***
1.00
0
(14)
SIZ
E -0
.062
***
-0.0
72**
* -0
.062
***
-0.1
02**
* 0.
183**
* 0.
351**
* -0
.010
0.
100**
* 0.
427**
* 0.
098**
* 0.
269**
* 0.
228**
* 0.
429**
* 1.
000
(15)
ST
0.07
6***
0.06
4***
0.74
9***
0.31
5***
0.02
1***
-0.0
23**
-0
.004
-0
.058
***
0.15
7***
-0.1
66**
* 0.
151**
* -0
.052
***
-0.0
32**
* -0
.105
***
1.00
0
(16)
LIS
TIN
GPL
ACE
0.
003
-0.0
07
-0.0
25**
* -0
.026
***
-0.1
80**
* -0
.157
***
0.02
7***
0.00
1 -0
.261
***
0.03
7***
-0.3
20**
* -0
.117
***
-0.1
64**
* -0
.284
***
-0.0
49**
* 1.
00
All
the
cont
inuo
us v
aria
bles
are
win
soriz
ed a
t 1%
and
99%
to m
itiga
te th
e ef
fect
of o
utlie
rs. A
ll th
e va
riabl
es a
re d
efin
ed in
Tab
le 4
.2.
*Si
gnifi
cant
at t
he 1
0% le
vel,
usin
g tw
o-ta
iled
tests
.
**S
igni
fican
t at t
he 5
% le
vel,
usin
g tw
o-ta
iled
tests
.
***S
igni
fican
t at t
he 1
% le
vel,
usin
g tw
o-ta
iled
test.
CHAPTER 5 RESULTS 70
5.3 Regression Results
5.3.1 Corporate renaming and financial reporting fraud
Table 5.4 reports the regression results from testing H1 regarding the association
between corporate renaming and financial reporting fraud. The results show that the
coefficient on RENAMING is positive and significant at the 1 percent level, indicating
that companies with renaming experience are more likely to commit financial fraud in
the year of name change (Column 2 and 3: coefficient 0.520, z-stat=5.05) and the
following year (Column 4 and 5: coefficient 0.363, z-stat=3.00). To interpret the
economic importance of this result, this study estimates the change in the odds of a
company having fraudulent financial reporting in response to a one-unit increase in the
corresponding independent variable, RENAMING. Economically, when RENAMING
increases by one standard deviation, the probability of fraudulent financial reporting
increases about 12.58% (0.520*0.2419). This result is consistent with the prediction
that corporate renaming can be used by management for manipulating purposes or even
to committed fraud, especially in China where corporate renaming is not costly and the
governance and legal schemes are still insufficient in investor protection. Thus, H1 is
CHAPTER 5 RESULTS 71
supported.
Regarding the control variables, it can be seen that the coefficient for LEV is positive
and significant, indicating that highly leveraged companies are more likely to create
fraudulent financial reports. The coefficient for ROE is negative and statistically
significant, consistent with the argument that companies with good financial
performance are less like to commit financial fraud. These results are consistent with
the prior studies (e.g. Chen et al., 2006; Zhang et al., 2017). In addition, the negative
coefficient for LARGESTSHARE suggests that the likelihood of financial reporting
fraud decreases with a greater number of shares held by the largest shareholders. The
coefficient for BIG4 is significantly negative, suggesting that clients of the top four
audit companies are less likely to commit fraud. In addition, the coefficient for SIZE,
AGE, BOARDSIZE, OUTSIDE, ST and LISTINGPLACE are statistically insignificant.
CHAPTER 5 RESULTS 72
Table 5.4 Corporate renaming and financial reporting fraud
The z-statistics are based on robust standard error clustered by company (Petersen, 2009). All the
variables are defined in Table 4.2. *Significant at the 10% level, using two-tailed tests. **Significant at
the 5% level, using two-tailed tests. ***Significant at the 1% level, using two-tailed tests.
Variable Dependent Variable: FRAUD FRAUDt
FRAUDt+1
Coef. z-stat. Coef. z-stat.
RENAMING 0.520*** 5.05
0.363*** 3.00
DUAL -0.145** -2.44
-0.178*** -2.83
BOARDSIZE -0.027 -1.44
-0.031 -1.56
OUTSIDE -0.470 -0.86
-1.082* -1.89
ROE -1.182*** -7.04
-1.029*** -5.52
LEV 0.782*** 5.46
0.631*** 4.22
AUDITOPINION -0.835*** -7.72
-1.030*** -8.68
AGE 0.001 0.23
-0.007 -1.17
LARGESTSHARE -1.199*** -6.05
-1.078*** -5.34
BIG4 -0.550** -3.40
-0.666*** -3.93
SIZE -0.046 -1.70
-0.038 -1.33
ST -0.149 -1.00
-0.139 -0.84
LISTINGPLACE 0.003 0.05
-0.083 -1.18
Industry and year dummies YES
YES
N 20,516
17,011
Pseudo R2 0.0594 0.0562
CHAPTER 5 RESULTS 73
5.3.2 Corporate renaming and financial fraud: the role of government ownership
(SOE vs non-SOE)
Table 5.5 presents the regression results of estimating H2. Results show that the
coefficient for RENAMING continues to be positive and significantly significant at 1%
level, as predicated. Notably, the coefficient for SOE is negative and significant,
indicating that SOEs are less likely to commit financial fraud. More importantly, the
coefficient for the variable of interest SOE*RENAMING is negative and significant
(P<0.05), suggesting that the probability of corporate renaming behaviour in increasing
financial reporting fraud is lower for SOE than for non-SOE. Collectively, these
analyses indicate that renaming behaviour provides non-SOEs possible channels to
solve the long-term financial distress and to engage financial fraud for compensation
and contracting (e.g. debt covenant) purposes because non-SOEs do not have the same
financial support and resources as SOEs do when they are financial distressed.
Therefore, H2 is supported.
CHAPTER 5 RESULTS 74
Table 5.5 Corporate renaming and financial reporting fraud: the moderation role of government ownership
Panel A Variable Obs Proportion
SOE 8,615 41.99%
Non-SOE 11,901 58.01%
Total 20,516 100.00%
CHAPTER 5 RESULTS 75
Panel B
The z-statistics are based on robust standard error clustered by company (Petersen, 2009). All the
variables are defined in Table 4.2 *Significant at the 10% level, using two-tailed tests. **Significant
at the 5% level, using two-tailed tests. ***Significant at the 1% level, using two-tailed tests.
Variable Dependent Variable: FRAUD
FRAUDt
FRAUDt+1
Coef. z-stat. Coef. z-stat.
RENAMING
0.481*** 4.35
0.291** 2.29
SOE
-0.291*** -3.94
-0.297*** -3.92
SOE * RENAMING
-0.443** -1.97
-0.246*** -1.02
DUAL
-0.106* -1.79
-0.141** -2.23
BOARDSIZE -0.016 -0.86 -0.020 -1.02
OUTSIDE
-0.436 -0.79
-1.058* -1.85
ROE
-1.268*** -7.50
-1.102*** -5.89
LEV
0.792*** 5.47
0.644*** 4.25
AUDITOPINION
-0.818*** -7.58
-1.012*** -8.53
AGE
0.009 1.58
0.001 0.23
LARGESTSHARE
-1.059*** -5.26
-0.951*** -4.65
BIG4 -0.528*** -3.29 -0.646*** -3.78
SIZE
-0.030 -1.12
-0.022 -0.77
ST
-0.099 -0.64
-0.099 -0.58
LISTINGPLACE
-0.022 -0.33
-0.108 -1.55
Industry and year dummies YES YES
N
20,516
17,011
Pseudo R2 0.0619 0.0584
CHAPTER 5 RESULTS 76
5.3.3 Corporate renaming and financial fraud: the moderating role of powerful
directors
Table 5.6 presents the results of estimating H3. Regression results continue to show that
the coefficient for RENAMING is positive and significant, as predicted. More
importantly, consistent with H3, it is shown that the coefficient for
BOARDPOWER*RENAMING is significantly positive, suggesting that the impact of
renaming behaviour on increasing financial reporting fraud is higher for a company
with higher board power than that with lower board power. These results are consistent
with the prior literature that board power increases the likelihood of financial fraud
scandals and reduces the detection of fraud (e.g. Morse et al., 2011; Khanna et al., 2015).
Therefore, H3 is supported.
CHAPTER 5 RESULTS 77
Table 5.6 Corporate renaming and financial reporting fraud: the moderation role
of board power
The z-statistics are based on robust standard error clustered by company (Petersen, 2009). All the
variables are defined in Table 4.2. *Significant at the 10% level, using two-tailed tests. **Significant
at the 5% level, using two-tailed tests. ***Significant at the 1% level, using two-tailed tests.
Variable Dependent Variable: FRAUD
FRAUDt
FRAUDt+1
Coef. z-stat. Coef. z-stat.
RENAMING
0.301*** 2.39
0.243* 1.73
BOARDPOWER
-0.094 -0.57
0.089 0.56
BOARDPOWER * RENAMING
1.879*** 3.45
1.082* 1.91
DUAL
-0.142** -2.35
-0.171*** -2.69
BOARDSIZE
-0.027 -1.47
-0.029 -1.53
OUTSIDE
-0.462 -0.84
-1.091* -1.91
ROE
-1.195*** -7.10
-1.039*** -5.58
LEV
0.776*** 5.41
0.636*** 4.24
AUDITOPINION
-0.841*** -7.78
-1.033*** -8.69
AGE 0.000 0.16 -0.005 -0.79
LARGESTSHARE
-1.189*** -5.97
-1.057*** -5.22
BIG4
-0.547*** -3.44
-0.662*** -3.90
SIZE
-0.048* -1.79
-0.039 -1.36
ST
0.009 0.05
-0.052 -0.30
LISTINGPLACE
0.004 0.07
-0.889 -1.26
Industry and year dummies YES YES
N
20,516
17,011
Pseudo R2 0.0602 0.0565
CHAPTER 5 RESULTS 78
5.4 Additional and robustness tests
5.4.1 The association between corporate renaming and different types of fraud
The CSRC is entrusted with the supervision and investigation of companies that commit
financial fraud. Examples of financial fraud include embezzlement by company official
or securities companies, the expropriation of assets, falsified financial statements,
inadequate financial disclosures, and stock market manipulation. The CSRC regularly
monitors fraudulent activities of companies through regular reviews, random
inspections and surveys that look for “red flags”. They also conduct investigations
based on information received from a variety of sources, including current and former
employees, newspaper, insiders, legal proceedings, information about complaints,
police investigations and stock exchange. Panel A of Table 5.7 describes different types
of financial fraud based on the CSRC enforcement actions. The enforcement actions by
the CSRC are classified into six types: false statement, major failure to disclose
information, illegal share buyback, delay in disclosure, inflated earnings, and others.
CHAPTER 5 RESULTS 79
Panel B of Table 5.7 presents the results from the additional test that investigates the
association between corporate renaming behaviour and the different types of financial
fraud. Columns labelled as Type (1) -(6) represent the regression results on each type
of financial fraud respectively as the independent variables. RENAMING is positive and
statistically significant at 1 percent level on (1) False statements, (2) Failure to disclose
information, (4) Delay in disclosure and (6) Others. However, RENAMING is
insignificantly associated with (3) Illegal share buybacks and (5) Inflated earnings.
These results provide additional evidence that renaming companies are more likely to
commit information-disclosure related frauds. Frauds including illegal buyback and
inflating earnings require high level of professional knowledge and the cost to commit
these types of fraud are relatively high. Comparatively, concealing or disclosing
misleading information costs less. Thus, companies use less costly tool such as
renaming to distract the public’s attentions in order to hide information regarding their
fraudulent activities.
CHAPTER 5 RESULTS 80
Table 5.7 Corporate renaming and different types of fraud
Panel A: Description of fraud types
False
statement
A false statement refers to an act of misleading statements of
important events and improper disclosure of information during
the issue or trading of securities.
Major failure
to disclose
information
A major failure disclosure is that the information disclosure obligor
does not fully record the matters in the information disclosure
document, or only partly disclose information.
Illegal share
buybacks
Illegal share buybacks refer to the illegal repurchasing of share of
stock by the company that issued them.
Delay in
disclosure
A delay in disclosure means failure to disclose important
information that should be disclosed to the public within the
prescribed time, and the violation of the principle of timeliness.
Inflated
earnings
Inflated earnings refer to exaggerate current period earnings on the
income statement by artificially inflating revenue and gains, or by
deflating current period expenses. This approach makes the
financial condition of the company look better than it actually is in
order to meet established expectations.
Others Other acts that violate the provisions of the Security Act, such as
the fabrication of assets, the unauthorized change of fund usages.
CHAPTER 5 RESULTS 81
Panel B
Fraud Type Obs
(1) False Statement 271
(2) Failure of Disclosure 482
(3) Illegal Share Buybacks 205
(4) Delay in Disclosure 520
(5) Inflated Earnings 58
(6) Others 910
CH
APT
ER 5
RES
ULT
S 82
The
z-st
atis
tics
are
base
d on
robu
st s
tand
ard
erro
r clu
ster
ed b
y co
mpa
ny (P
eter
sen,
200
9).A
ll th
e va
riabl
es a
re d
efin
ed in
Tab
le 4
.2. *
Sign
ifica
nt a
t the
10%
leve
l, us
ing
two-
taile
d te
sts.
**Si
gnifi
cant
at t
he 5
% le
vel,
usin
g tw
o-ta
iled
test
s. **
*Sig
nific
ant a
t the
1%
leve
l, us
ing
two-
taile
d te
st.
Pane
l C: c
orpo
rate
rena
min
g an
d di
ffere
nt ty
pes
of fr
aud
Va
riabl
es
Dep
ende
nt v
aria
ble:
Typ
es o
f fin
anci
al re
porti
ng fr
aud
(1)
Fal
se S
tate
men
t
(2)
Fai
lure
of
Dis
clos
ure
(3) I
llega
l Sha
re
Buyb
acks
(4) D
elay
in
Dis
clos
ure
(5) I
nfla
ted
Earn
ings
(6
) Oth
ers
co
ef.
z-st
at
co
ef.
z-st
at
coef
. z-
stat
coef
. z-
stat
co
ef.
z-st
at
coef
. z-
stat
R
EN
AMIN
G
0.44
7***
2.
35
0.
608*
* 4.
02
0.
101
0.46
0.45
1***
3.
13
-0
.020
-0
.04
0.
494*
**
4.16
D
UAL
-0
.215
* -1
.70
-0
.191
* -1
.94
0.
038
0.37
-0.2
31**
* -2
.65
-0
.162
-0
.63
-0
.141
**
-1.9
6 BO
ARD
SIZE
-0
.049
-1
.27
-0
.059
**
-2.0
5
0.03
5 1.
12
-0
.088
***
-2.7
1
0.00
0 -0
.01
-0
.034
-1
.58
OU
TSID
E -1
.747
-1
.56
-0
.415
-0
.49
0.
771
0.78
-0.9
67
-1.1
4
-1.8
14
-0.6
5
0.17
5 0.
27
ROE
-1.3
39**
* -5
.35
-0
.998
***
-4.6
5
-0.1
81
-0.5
5
-1.0
36**
* -5
.21
-1
.899
***
-5.0
7
-1.1
67**
* -6
.10
LEV
0.42
1**
2.01
0.58
7***
3.
27
0.
379*
1.
80
0.
999*
**
5.60
-0.0
94
-0.2
4
0.62
4***
4.
08
AUD
ITO
PIN
ION
-1
.326
***
-7.8
3
-1.0
90**
* -7
.71
-0
.005
-0
.02
-1
.014
***
-7.9
0
-2.3
89**
* -9
.52
-0
.757
***
-6.2
8 AG
E -0
.004
-0
.40
0.
012
1.41
-0.0
16
-1.7
3
0.01
9**
2.51
-0.0
08
-0.3
6
0.00
2 0.
33
LARG
ESTS
HAR
E -1
.549
***
-3.7
1
-1.3
16**
* -4
.15
-1
.764
-5
.31
-0
.840
***
-2.7
9
-0.4
19
-0.4
1
-1.0
72**
* -4
.41
BIG
4 -0
.219
-0
.63
-0
.952
***
-2.7
1
-0.5
93**
-2
.26
-0
.664
**
-2.4
8
-0.4
08
-0.5
1
-0.6
07**
* -3
.05
SIZE
-0
.047
-0
.95
0.
197
0.51
-0.0
75*
-1.6
5
-0.0
24
-0.6
8
-0.0
05
-0.0
5
-0.0
03
-0.1
1 ST
0.
125
0.50
-0.3
87*
-1.8
2
-0.5
03
-1.5
1
-0.1
07
-0.5
3
0.12
3 0.
22
-0
.185
-1
.13
LIST
ING
PLAC
E 0.
182
1.40
-0.0
036
-0.3
5
0.41
0***
3.
44
-0
.150
-1
.55
-0
.331
-1
.28
-0
.044
-0
.55
Indu
str y
and
yea
r dum
mie
s Y
ES
YES
Y
ES
YES
Y
ES
YES
N
20,4
81
20,5
16
20,4
97
20,4
81
18,0
82
20,4
97
Ps
eudo
R2
0.07
98
0.07
14
0.
0388
0.
0688
0.13
57
0.
0584
CHAPTER 5 RESULTS 83
5.4.2 The association between corporate renaming and fraud by year
Table 5.8 shows the results of the yearly logistic regression of FRAUD on RENAMING.
FRAUD is positively associated with RENAMING between 2010 and 2016, consistent
with the main results reported in the Table 5.4. However, for 2017, results show that
RENAMING is not statistically significant, and the coefficient is comparatively smaller.
It can be possible attributable to the recent regulatory intervention on corporate
renaming practices that may have had a significant effect in deterring discretionary
renaming behaviour for fraudulent purposes. On September 30, 2016, the Shanghai
Stock Exchange issued the “Index of Listed Companies Changing Securities Name”
that required clear and business-relevant names in listed companies and prohibited
listed companies from misleading investors by corporate name changes. In other words,
company’s renaming behaviour should be derived from the actual needs of the business
development, and should not be used for speculation, improper market value
management and other illegal purposes. It is further required that if a company changes
its name, it shall disclose the compliance and prompt risk. According to an official
statistic released by Chinese Stock Exchanges, the occurrence of a surge in stock price
CHAPTER 5 RESULTS 84
due to corporate name change has decreased since the release of the regulation guidance.
Among the companies that have been renamed since 2017, the average increase in share
price between the first day and the last 10 days is negative (Chinese Securities Daily,
2017). Overall, results reported in this section suggest that the implementation of the
new policy has constrained the opportunities for using corporate renaming as a tool to
engage in financial frauds. The new policy released in 2016 aims to regulate and control
the artificial manipulation of stock prices by enterprises, and also improves the quality
of accounting information disclosure (e.g. transparency of information).
CH
APT
ER 5
RES
ULT
S 85
Tabl
e 5.
8 C
orpo
rate
ren
amin
g an
d fin
anci
al r
epor
ting
frau
d by
yea
r
The
z-st
atis
tics
are
base
d on
rob
ust s
tand
ard
erro
r cl
uste
red
by c
ompa
ny (
Pete
rsen
, 200
9).A
ll th
e va
riabl
es a
re d
efin
ed in
Tab
le 4
.2 *
Sign
ifica
nt a
t the
10%
leve
l, us
ing
two-
taile
d te
sts.
**Si
gnifi
cant
at t
he 5
% le
vel,
usin
g tw
o-ta
iled
test
s. **
*Sig
nific
ant a
t the
1%
leve
l, us
ing
two-
taile
d te
sts.
Varia
ble
D
epen
dent
Var
iabl
e:
FRAU
Dt
2010
2011
2012
2013
2014
2015
2016
2017
Co
ef.
z-sta
t. Co
ef.
z-sta
t. Co
ef.
z-sta
t. Co
ef.
z-sta
t. Co
ef.
z-sta
t. Co
ef.
z-sta
t. Co
ef.
z-sta
t. Co
ef.
z-sta
t.
REN
AM
ING
0.
422*
0.
68
0.60
9***
1.
65
0.74
0**
1.83
0.49
2*
1.33
0.75
6***
2.
80
0.44
4**
2.09
0.79
2***
3.
47
0.15
2 0.
40
DU
AL
0.14
8 0.
90
-0.0
92
-0.7
2
-0.2
39**
-2
.03
-0.0
76
-0.6
1
-0.1
68
-1.3
0
-0.1
22
-1.0
4
-0.3
45**
* -2
.67
0.07
2 0.
46
BOAR
DSI
ZE
-0.0
12
-0.2
9
-0.0
15
-0.4
0
-0.0
69
-1.9
8
-0.0
37
-0.9
8
-0.0
48
-1.2
1
-0.0
37
-0.9
9
0.00
2 0.
04
-0.0
13
-0.2
5
OU
TSID
E -0
.390
-0
.29
1.13
4 1.
06
-0.6
72
-0.6
7
-0.8
75
-0.7
7
-0.0
53
-0.0
4
0.88
2 0.
81
-3.3
74**
-2
.51
-1.2
45
-0.7
7
ROE
-0.5
31
-0.9
5
-0.9
55**
* -2
.64
-2.0
83**
* -4
.18
-0.7
50
-1.7
5
-0.8
00*
-1.9
2
-0.7
82**
-2
.32
-1.9
18**
* -3
.96
-1.7
15**
* -2
.84
LEV
0.62
4***
2.
85
0.76
3***
2.
93
1.30
2***
4.
39
1.35
6***
4.
26
1.17
5***
3.
74
1.34
9***
4.
38
0.84
9**
2.50
1.53
3***
3.
94
AUD
ITO
PINI
ON
-0
.236
-0
.74
-0.2
29
-0.7
3
-1.3
49**
* -5
.54
-1.2
72**
* -5
.40
-1.2
12
-4.9
3
-0.9
38
-4.0
7
-0.9
08**
* -4
.11
-0.3
17
-1.0
5
AGE
-0.0
07
-0.5
4
-0.0
08
-0.7
2
-0.0
42**
* -3
.97
-0.0
17
-1.5
9
0.00
3 0.
33
0.01
5*
1.74
0.02
4***
2.
60
0.00
5 0.
42
LARG
ESTS
HAR
E -1
.920
***
-4.1
7
-0.4
78
-1.2
6
-1.2
98**
* -3
.61
-1.0
41
-2.7
1
-1.8
18**
* -4
.50
-0.9
48**
-2
.49
-1.6
40**
* -3
.59
-1.7
55**
* -3
.25
BIG
4 -0
.100
-0
.27
-0.4
88
-1.5
0 -0
.474
-1
.61
-0.6
89*
-1.9
3 -0
.714
**
-2.1
9 -0
.402
-1
.44
-0.4
65
-1.4
8 -1
.000
* -2
.18
SIZE
-0
.122
**
-2.1
0
-0.0
61
-1.1
0
-0.0
48
-0.8
7
-0.1
41**
-2
.40
-0.0
38
-0.7
2
-0.1
13**
-2
.16
-0.0
50
-0.9
2
-0.0
18
-0.2
8
ST
0.09
8 0.
14
-0.3
07
-0.7
0
-0.4
22
-0.8
8
-0.5
90
-1.2
9
-0.4
23
-1.0
5
0.09
1 0.
26
0.24
0 0.
74
0.92
0**
2.03
LIST
ING
PLAC
E 0.
415*
**
2.77
0.58
4***
4.
48
0.13
3 1.
06
0.12
3***
0.
99
-0.1
85
-1.4
8
-0.2
39**
-2
.09
-0.4
76**
* -3
.77
-0.4
90**
* -3
.53
Indu
stry
and
year
dum
mie
s Y
ES
YES
Y
ES
YES
Y
ES
YES
Y
ES
YES
N
1,94
9 2,
262
2,42
8 2,
400
2,48
8 2,
689
2,90
6 3,
327
Pseu
do R
2 0.
0455
0.03
67
0.
0636
0.05
43
0.
0672
0.05
99
0.
0891
0.06
46
CHAPTER 5 RESULTS 86
5.4.3 Extend testing windows
This additional test extends the testing window from t+0 to t+3 (three years after the
change of the company name). Table 5.9 indicates that RENAMING is positively and
significantly associated with FRADUt+0 and FRAUDt+1, which supports H1, but
insignificantly associated with FRAUD t+2 and FRAUD t+3. It seems that companies are
easier to commit financial reporting fraud in the year of changing the company name
and the following year, but not in the second and third year after the company’s name
has changed. These results provide interesting evidence that the likelihood of fraud
commitment associated with corporate name change holds in the first two years when
renaming occurs, but this effect fades afterwards.
CH
APT
ER 5
RES
ULT
S 87
Ta
ble
5.9
Cor
pora
te r
enam
ing
and
finan
cial
rep
ortin
g fr
aud:
ext
ende
d te
stin
g w
indo
ws
Varia
ble
Dep
ende
nt V
aria
ble:
FRA
UD
FR
AUD
t FR
AUD
t+1
FRAU
Dt+
2 FR
AUD
t+3
C
oef.
z-sta
t. Co
ef.
z-sta
t.
Coef
. z-
stat.
Co
ef.
z-st
at.
RE
NA
MIN
G
0.52
0***
5.
05
0.
363*
**
3.00
0.02
0 0.
12
0.
248
1.38
D
UAL
-0
.145
**
-2.4
4
-0.1
78**
* -2
.83
-0
.143
**
-2.0
4
-0.1
27
-1.5
8 BO
ARD
SIZE
-0
.027
-1
.44
-0
.031
-1
.56
-0
.028
-1
.28
-0
.021
-0
.90
OU
TSID
E -0
.470
-0
.86
-1
.082
* -1
.89
-1
.183
* -1
.90
-0
.760
-1
.06
ROE
-1.1
88**
* -7
.04
-1
.030
***
-5.5
2
-1.0
02**
* -5
.24
-0
.685
***
-3.2
6 LE
V 0.
782*
**
5.46
0.63
1***
4.
22
0.
569*
**
3.67
0.63
6***
3.
71
AUD
ITO
PIN
ION
-0
.835
***
-7.7
2
-1.0
30**
* -8
.68
-0
.759
***
-5.4
9
-0.4
52**
* -2
.86
ST
-0.1
49
-1.0
0
-0.1
39
-0.8
4
0.22
8 1.
13
-0
.112
-0
.52
AGE
0.00
1 0.
23
-0
.007
-1
.17
-0
.006
-0
.87
0.
000
0.04
LA
RGES
TSH
ARE
-1.2
00**
* -6
.05
-1
.078
***
-5.3
4
-1.0
33**
* -4
.73
-1
.059
***
-4.3
1 BI
G4
-0.5
50**
* -3
.46
-0
.666
***
-3.9
3
-0.7
34**
* -3
.74
-0
.673
***
-3.1
3 SI
ZE
-0.0
46*
-1.7
0*
-0
.038
-1
.33
-0
.061
**
-2.0
0
-0.1
10**
* -3
.31
LIST
ING
PLAC
E 0.
003
0.05
-0.0
83
-1.1
8
-0.1
98**
* -2
.57
-0
.245
***
-2.8
5
In
dust
ry a
nd y
ear d
umm
ies
YES
Y
ES
YES
Y
ES
N
20,5
16
17,0
11
13,8
52
11,0
37
Ps
eudo
R2
0.05
94
0.05
62
0.05
02
0.04
93
Th
e z-
stat
istic
s are
bas
ed o
n ro
bust
stan
dard
err
or c
lust
ered
by
com
pany
(Pet
erse
n, 2
009)
. All
the
varia
bles
are
def
ined
in T
able
4.2
*Si
gnifi
cant
at
the
10%
leve
l, us
ing
two-
taile
d te
sts.
**Si
gnifi
cant
at t
he 5
% le
vel,
usin
g tw
o-ta
iled
test
s. **
*Sig
nific
ant a
t the
1%
leve
l, us
ing
two-
taile
d te
sts.
CHAPTER 5 RESULTS 88
5.4.4 The financial fraud and subsequent renaming behaviour
This additional test examines whether the company will change their corporate name
after they commit financial fraud. Results reported in Panel A of Table 5.10 show that
FRAUD is positively and significantly associated with RENAMINGt, RENAMINGt+1,
RENAMINGt+2, RENAMINGt+3, suggesting that the company may change the corporate
name in the next three years after the company conducts financial fraud, consistent with
impression management. That is, companies are more likely to change the company
name to manipulate public perceptions to rebuild its market reputation. However, the
results also rise an econometric issue that the relation between FRAUD and
RENAMING may be confounded by the endogenous nature. The potential endogeneity
issue is hence discussed in section 5.4.5.
CHAPTER 5 RESULTS 89
Panel B of Table 5.10 introduces a new independent variable, FRAUD declare year,
which equals to 1 if CSRC discloses company’s financial fraud scandals in the year,
and 0 otherwise. Renaming is a method to erase negative brand equity and image
problems. At the same time, renaming can influence stakeholder’s perception by a
radical revitalisation of the market aesthetics (Muzellec and Lambkin, 2006). When the
company’s financial fraud scandals were disclosed and announced by the CSRC, this
could be a huge negative signal for stakeholders and the market. Companies may
eliminate the negative effects by changing the corporate name. Results in Panel B of
Table 5.10 show that FRAUD disclosure year is insignificantly associated with
RENAMINGt and RENAMINGt+3 However, FRAUD declare year is positively and
significantly associated with RENAMINGt+1 and RENAMINGt+2. It suggests that
although the company will not change its name in the year when the company’s
financial fraud is disclosed by the CSRC, the company will change its name in the near
future.
CHAPTER 5 RESULTS 90
Based on a subsample with all fraudulent companies that were disclosed by CSRC
(N=3,223), Panel C of Table 5.10 further tests, after company’s fraud behaviour is
disclosed, whether the penalties imposed by the CSRC would affect the corporate
renaming behaviour. A new independent variable PUNISHMENT is introduced to
measure the CSRC’s punishment. PUNISHMENT equals to 1 when CSRC announces
certain punishments to the fraud companies, including fine, denounce, and confiscation
of illegal gains; PUNISHMENT equals to 0 when CSRC only discloses company’s
fraudulent behaviour, but no actual punishment was given. Results in Panel C of Table
5.10 indicate that PUNISHMENT is positively and significantly associated with
RENAMING. Companies subject to CSRC penalties are more likely to change their
corporate name. This is because the punishment is often related to the severity of the
company’s fraudulent behaviour, giving a negative impression on stakeholders and the
security market. Therefore, these companies prefer to use the renaming behaviour
subsequently to erase company’s negative image after the punishments were taken.
CH
APT
ER 5
RES
ULT
S 91
Tabl
e 5.
10 F
inan
cial
rep
ortin
g fr
aud
and
subs
eque
nt c
orpo
rate
ren
amin
g be
havi
our
Pane
l A: F
inan
cial
repo
rting
frau
d an
d su
bseq
uent
cor
pora
te re
nam
ing
beha
viou
r
Varia
ble
Dep
ende
nt V
aria
ble:
REN
AMIN
G
RE
NAM
ING
t
RENA
MIN
Gt+
1
RENA
MIN
Gt+
2
RENA
MIN
Gt+
3
Coef
. z-
stat.
Coef
. z-
stat
. Co
ef.
z-st
at.
Coef
. z-
stat.
FRAU
D
0.53
3***
5.
03
0.
264*
**
3.39
0.20
8**
2.40
0.25
7***
2.
74
DU
AL
-0.1
13
-1.1
1 0.
130
1.57
0.
067
0.74
0.
084
0.86
BO
ARD
SIZE
-0
.064
**
-2.0
0
-0.0
44*
-1.7
5
-0.0
22
-0.8
0
-0.0
33
-1.0
3 O
UTS
IDE
-1.5
20
-1.6
1
-0.2
93
-0.4
0
-0.0
33
-0.0
4
0.30
0 0.
35
ROE
0.98
5**
2.05
-1.0
73**
* -4
.22
-3
.485
***
-11.
58
-2
.084
***
-8.2
4 LE
V -0
.307
-1
.07
1.
298*
**
7.90
1.20
7***
5.
82
0.
888*
**
4.79
AU
DIT
OPI
NIO
N
-0.5
16**
* -2
.70
-0
.249
* -1
.70
-0
.810
***
-5.2
7
-1.2
28**
* -8
.08
ST
2.
090*
* 19
.27
0.
713*
**
4.77
0.65
3***
4.
17
AGE
0.05
0***
7.
01
0.
055*
**
8.70
0.04
3***
5.
54
0.
034*
**
4.06
LA
RGES
TSH
ARE
-0.5
99*
-1.8
1
-0.4
07
-1.6
2
-0.3
59
-1.2
4
-0.2
74
-0.9
2 BI
G4
-0.4
85**
-2
.06
-0
.067
-0
.32
0.
026
0.11
-0.2
49
-0.9
1 SI
ZE
0.17
2***
3.
69
-0
.271
***
-8.2
1
-0.3
30**
* -8
.25
-0
.225
***
-5.4
4 LI
STIN
GPL
ACE
0.43
2***
4.
45
0.
096
1.31
0.12
6 1.
41
0.
184*
1.
89
Indu
stry
and
yea
r dum
mie
s Y
ES
YES
Y
ES
YES
N
19,7
53
16,9
92
13,8
13
11,0
03
Ps
eudo
R2
0.05
53
0.16
89
0.16
94
0.12
08
CH
APT
ER 5
RES
ULT
S 92
Pane
l B: F
inan
cial
repo
rting
frau
d de
clar
atio
n an
d su
bseq
uent
cor
pora
te re
nam
ing
beha
viou
r
Varia
ble
Dep
ende
nt V
aria
ble:
REN
AMIN
G
RE
NAM
ING
t
RENA
MIN
Gt+
1
RENA
MIN
Gt+
2
RENA
MIN
Gt+
3
Coe
f. z-
stat
. Co
ef.
z-sta
t. Co
ef.
z-sta
t. Co
ef.
z-st
at.
FRAU
D d
ecla
re y
ear
0.13
3 1.
10
0.
212*
* 2.
41
0.
178*
* 1.
78
-0
.018
-0
.15
DU
AL
-0.1
27
-1.2
4
0.12
0 1.
45
0.
059
0.66
0.07
4 0.
76
BOAR
DSI
ZE
-0.0
66**
-2
.06
-0
.045
* -1
.77
-0
.024
-0
.83
-0
.036
-1
.13
OU
TSID
E -1
.557
-1
.63
-0
.307
-0
.42
-0
.045
-0
.06
0.
258
0.30
RO
E 0.
870*
1.
84
-1
.099
***
-4.2
9
-3.5
04**
* -1
1.60
-2.1
19**
* -8
.28
LEV
-0.2
28
-0.8
1
1.28
8***
7.
82
1.
204*
**
5.76
0.91
1***
4.
80
AUD
ITO
PINI
ON
-0
.604
-3
.14
-0
.268
* -1
.83
-0
.829
***
-5.3
7
-1.2
85**
* -8
.39
ST
2.
093*
* 19
.36
0.
715*
**
4.78
0.66
1***
4.
22
AGE
0.05
0***
7.
00
0.
055*
**
8.72
0.04
3***
5.
54
0.
033*
**
3.95
LA
RGES
TSH
ARE
-0.6
83**
-2
.05
-0
.432
* -1
.72
-0
.378
-1
.30
-0
.338
-1
.13
BIG
4 -0
.509
**
-2.1
6
-0.0
74
-0.3
5
0.02
1 0.
09
-0
.271
-0
.98
SIZE
0.
164*
**
3.59
-0.2
71**
* -8
.17
-0
.329
***
-8.1
8
-0.2
23**
* -5
.38
LIST
ING
PLAC
E 0.
419*
**
4.32
0.09
5 1.
30
0.
127
1.41
0.19
4**
1.99
In
dust
ry a
nd y
ear d
umm
ies
YES
Y
ES
YES
Y
ES
N
19
,753
16
,992
13
,813
11
,003
Pseu
do R
2 0.
0509
0.16
82
0.
169
0.
1194
CHAPTER 5 RESULTS 93
Panel C: Financial reporting fraud declaration and subsequent corporate renaming
behaviour
Variable Dependent Variable: RENAMING
Coef. z-stat.
PUNISHMENT 0.459** 1.99
DUAL -0.261 -1.34
BOARDSIZE -0.110 -1.51
OUTSIDE -2.539 -1.40
ROE 1.474 1.43
LEV -1.408*** -3.02
AUDITOPINION -0.613** -2.01
ST
AGE 0.049*** 3.05
LARGESTSHARE -0.974 -1.33
BIG4 -0.876 -1.04
SIZE 0.202*** 2.29
LISTINGPLACE 0.588*** 2.78
Industry and year dummies YES N 3,22310 Pseudo R2 0.0982
The z-statistics are based on robust standard error clustered by company (Petersen, 2009). All the
variables are defined in Table 4.2. *Significant at the 10% level, using two-tailed tests. **Significant
at the 5% level, using two-tailed tests. ***Significant at the 1% level, using two-tailed tests.
10 Because of collinearity, STATA dropped 248 observations during the regression.
CHAPTER 5 RESULTS 94
5.4.5 Addressing potential endogeneity
As mentioned in Section 5.4.4, the association between company renaming behaviour
and the fraud may be confounded by a potential endogenous nature. This study attempts
to address the potential endogeneity issue by using a two-stage Heckman model. In the
first stage, this study models RENAMING as a function of one instrumental variable
(IV), MERGE (a dummy variable equals to 1 is the company have mergers and
acquisitions; and 0 otherwise) and other explanatory variables. This is supported by
Muzellec and Lambkin (2006) who consider that the changing in ownership structure
should be a reason for corporate rebranding. Muzellec and Lambkin (2006) state that
the change in the corporate name is driven by changes that have affected the company’s
structure and organization. As discussed in Chapter 2, the merger and acquisition often
reflect changes of company’s ownership thus a corporate renaming is often the result
of it.
In the second stage regression, Model (1) is re-estimated using the predicted value of
RENAMING from the first stage regression. Ideally the instrument (MERGE) will be
CHAPTER 5 RESULTS 95
correlated with the endogenous variable, RENAMING, and uncorrelated with the error
term. Recognizing potential problems with the use of instruments, this study conducts
a number of tests to evaluate the appropriateness of instrumental variable following
Larcker and Rusticus (2010).
The coefficient of MERGE in the first stage is positive and significant as expected
(untabulated), indicating that instrument variable (MERGE) and independent variable
(RENAMING) are strongly correlated. In Table 5.11, results for the second-stage model
show that RENAMING is positive and significant associated with FRAUD. While it is
impossible to rule out the potential endogeneity issue, the results of the Heckman
analyses is consistent with the main finding as reported in Table 5.4 that companies are
more likely to commit financial fraud after changing the company name. In views of
the main tests and the robust results from a battery of robustness tests, a conclusion can
be reasonably made that in a less regulated environment like China, company’s
renaming behaviour is a ‘red flag’ for the regulators to investigate financial fraud.
CHAPTER 5 RESULTS 96
Table 5.11 Corporate renaming and financial reporting fraud: Heckman Test
Variable
Dependent Variable:
FRAUD Coef. z-stat.
RENAMING 1.564*** 5.78
DUAL -0.008 -1.02
BOARDSIZE 0.004* 1.73
OUTSIDE 0.038 0.59
ROE -0.242*** -8.98
LEV 0.169*** 10.38
AUDITOPINION -0.133*** -7.47
ST -1.442*** -5.50
AGE -0.003*** -4.48
LARGESTSHARE -0.097*** -4.40
BIG4 -0.015 -0.99
SIZE -0.023*** -7.00
LISTINGPLACE -0.019** -2.45
Industry and year dummies YES N 20,525 Inverse Mills Ratio 0.153*** -1.50
Predicted value of Instrument Variable (Merge) in the
first stage 0.307*** 10.88
The z-statistics are based on robust standard error clustered by company (Petersen, 2009). All the
variables are defined in Table 4.2. *Significant at the 10% level, using two-tailed tests. **Significant
at the 5% level, using two-tailed tests. ***Significant at the 1% level, using two-tailed tests
CHAPTER 6 CONCLUSION 96
CHAPTER 6 CONCLUSION
This chapter briefly summarises the findings (section 6.1), contributions and practical
implications (section 6.2), limitations (section 6.3), and provides suggestions on future
research opportunities.
6.1 Summary of findings and discussion
The quality of financial information is a major concern for investors, regulators, and
capital market participants. However, due to the relatively weak legal and institutional
environment, falsified financial information are not uncommon in China. This study
examines the association between corporate renaming behaviour and financial
reporting fraud in China.
Using a sample of listed companies in China during 2010-2017, this study finds that
companies with renaming experience are more prone to commit financial fraud than
companies without renaming experience. The positive association between corporate
renaming and fraudulent financial reporting is less pronounced for SOEs than for non-
CHAPTER 6 CONCLUSION 97
SOEs. Reported results also suggest that the power of the board of directors positively
moderates the association between company renaming behaviour and the likelihood of
fraudulent financial reporting.
A battery of additional tests was undertaken to provide further evidence on the research
question. First, this study classifies the financial fraud into 6 categories (e.g. false
statement, a major failure to disclosure information, illegal share buyback, a delay in
disclosure, inflated earnings, and others) and re-runs the main models. Results show
that renaming companies are more likely to commit fraud related to information
disclosure, such as delay in disclosure or non-disclosure of information. Second, when
observing the association between renaming and fraud in different years, this study
finds that the implementation of the new regulation “Index of Listed Companies
Changing Security Name” in 2016 has weaken the association between the corporate
renaming and financial reporting fraud. Third, when the testing windows were extended,
results show that renaming companies will commit fraud in the short term (e.g. the year
of renaming and the following year) after they changed the corporate name. Fourthly,
CHAPTER 6 CONCLUSION 98
this study examines whether the companies change their name after they committed
fraud. The results indicate that financial reporting fraud is positively associated with
the subsequent corporate renaming behaviour. This result suggests that the association
between financial reporting fraud and corporate renaming may be confounded by the
endogenous nature. In order to address the endogeneity concerns, this study performs a
two-stage Heckman test and the results are consistent with the main results. Finally, this
study investigates whether the penalties imposed by CSRC would affect the corporate
renaming behaviour among fraud companies. The results suggest that companies
subject to CSRC penalties are more likely to change the company name subsequently.
6.2 Contributions and practical implications
This research contributes to the literature by presenting the first evidence that corporate
renaming behaviour is closely associated with corporate fraud. The results from a
battery of empirical tests indicate that corporate renaming might have been used by
management as a less costly tool to manage corporate image and conceal corporate
misconduct behaviour. It also suggests that corporate renaming can be viewed as a ‘red
CHAPTER 6 CONCLUSION 99
flag’ for detecting potential financial fraud in the market. Given the negative impact of
financial fraud on capital market efficiency and the relatively weak institutional
governance on investor protection in China, the findings from this study regarding the
indicative role of renaming behaviour is of the interest to regulators and standard setters
in shaping a better governed capital market and deterring financial frauds in the market.
This study also finds evidence that the implementation of “Index of Listed Companies
Changing Security Name” in 2016 has substantially eliminated the association between
renaming and financial fraud, suggesting the positive effect of enhanced regulation and
market discipline on capital market efficiency.
6.3 limitations and future research avenue
The study is subject to a few research limitations. First, the sample has been restricted
to the period 2010-2017 and the Chinese setting due to data availability. Although
insufficient investor protection might be more prevalent in developing economies like
China, the association between renaming and corporate fraud might be a generalised
issue in all economies. Future research can focus on the evidence in other countries
CHAPTER 6 CONCLUSION 100
regarding the association between corporate renaming and fraud.
Second, due to the time constraints of the Master of Philosophy program, this study has
not excluded the situation of corporate renaming due to generic economic reasons, e.g.,
name changes due to mergers and acquisitions. Corporate name changes due to generic
reasons is a natural reflection of corporate business change and may not necessarily
suggest corporate fraud. Future research can attempt to classify the type of corporate
renaming and investigates how the different types of corporate renaming influence the
financial reporting fraud. Excluding the name changes out of normal business
restructuring from the sample will provide a cleaner setting to examine the association
of corporate renaming and financial fraud.
REFERENCES 101
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