FRAUDULENT FINANCIAL REPORTING IN CHINA ...Fraudulent Financial Reporting in China: Evidence from Renaming Behaviour ii Abstract Using a sample of listed companies in China during

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


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,


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


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


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


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,


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


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


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


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.


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


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


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.


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


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


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


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


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


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


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


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)


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


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.


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


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


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


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


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


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.


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.


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


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.


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.


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.


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


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.


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


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.


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).


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


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


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


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


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.


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


(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


(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


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


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


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


= + 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


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


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.


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.


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


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.


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


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.


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%


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.


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.


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


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


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.


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


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.


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


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.


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%


Panel B


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


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


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.


Table 5.6 Corporate renaming and financial reporting fraud: the moderation role

of board power


variables are defined in Table 4.2. *Significant at the 10% level, using two-tailed tests. **Significant


Variable Dependent Variable: FRAUD

FRAUDt

FRAUDt+1


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


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.


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.


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.


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

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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


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.

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gnifi

cant

at t

he 5

% le

vel,

usin

g tw

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s. **

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nific

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t the

1%

leve

l, us

ing

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taile

d te

sts.

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ble

D

epen

dent

Var

iabl

e:

FRAU

Dt

2010

2011

2012

2013

2014

2015

2016

2017

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ef.

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t. Co

ef.

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t. Co

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t. Co

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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.

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at.

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NA

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05

0.

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0.

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n ro

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dard

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or c

lust

ered

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pany

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n, 2

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bles

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able

4.2

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gnifi

cant

at

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10%

leve

l, us

ing

two-

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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.


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.


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.


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

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NIO

N

-0.5

16**

* -2

.70

-0

.249

* -1

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-0

.810

***

-5.2

7

-1.2

28**

* -8

.08

ST

2.

090*

* 19

.27

0.

713*

**

4.77

0.65

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17

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01

0.

055*

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0.04

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54

0.

034*

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LA

RGES

TSH

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1

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07

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2

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59

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4

-0.2

74

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2 BI

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49

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1 SI

ZE

0.17

2***

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69

-0

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***

-8.2

1

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30**

* -8

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-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

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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

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cor

pora

te re

nam

ing

beha

viou

r

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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.

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at.

FRAU

D d

ecla

re y

ear

0.13

3 1.

10

0.

212*

* 2.

41

0.

178*

* 1.

78

-0

.018

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.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**

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.06

-0

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* -1

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TSID

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1.

84

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***

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9

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* -1

1.60

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* -8

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LEV

-0.2

28

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1

1.28

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7.

82

1.

204*

**

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80

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ies

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13

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2 0.

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0.

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0.

1194


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




10 Because of collinearity, STATA dropped 248 observations during the regression.


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


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.


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



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-


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,


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


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


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.

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FRAUDULENT FINANCIAL REPORTING IN CHINA ...Fraudulent Financial Reporting in China: Evidence from Renaming Behaviour ii Abstract Using a sample of listed companies in China during