paper session 3 fraudulent financial reporting in china ...fraudulent financial reporting in china:...

4th Symposium of China Journal of Accounting Research (CJAR) 中国会计学刊研讨会

17 – 18 December 2010

Sponsored by:

Paper Session 3

Fraudulent Financial Reporting in China: Consideration of Timing Traits and

Corporate Governance Mechanisms

By

Dan Yang University of Aberdeen

& Roger Buckland

University of Aberdeen

Fraudulent Financial Reporting in China: Consideration of Timing Traits and Corporate

Governance Mechanisms

Dan Yang1, Roger Buckland2

Department of Accounting, Business School, University of Aberdeen, UK

ABSTRACT: This paper develops an analysis of the prevalence and determinants of fraudulent

financial reporting as identified in the Chinese listed firms over the period 1996 to 2007, and

highlights the relationship of financial fraud and corporate governance mechanisms. 82 cases of fraud

identified by the China Securities Regulatory Commission are selected as the study sample, and 82

control peers are designed to correspond to the study sample as closely as possible, regarding the

assets size and industries, in order to exclude the influence of these factors towards the dependent

variable. The findings of this paper challenge the conventional arguments which have been testified

based on the data from the western countries, mostly from the U.S.. Conventional arguments show

financial fraud is associated with weakness of governance. However, the finding in this paper reveals

that as for the high discussed corporate governance characteristics (e.g. independent directors, the

supervisory board, and audit committee), the fraud firms and their non-fraud peers are not statistically

distinct. Statistical differences of external auditor traits and regulation from the securities market are

found between the groups. The negative results of this paper contribute by updating our understanding

of the supervision of China’s equity markets, whether it can be considered effective in uncovering

financial fraud; and also the results may contribute that governance protections that work in one

system may fail in the other.

Keywords: fraudulent financial reporting; corporate governance; audit committee; independent

directors; the supervisory board; regulation.

1 Dan Yang: a PhD candidate in the Business School, University of Aberdeen, AB24 3QY, United Kingdom. Email: [email protected] 2 Roger Buckland: full Professor, Chair of Accountancy and Finance, Business School, University of Aberdeen, AB24 3QY, United Kingdom. Email: [email protected]

Fraudulent Financial Reporting in China: Consideration of Timing Traits and Corporate Governance Mechanisms

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1. INTRODUCTION

More and more accounting scandals and fraud are damaging the accounting profession. Unethical

practices by corporations are making financial statements unreliable and can drag the economy into a

recession. Financial statement fraud has received considerable attention from investors, creditors,

regulators and the public, with high profile reported financial fraud at large companies such as Enron,

WorldCom (both U.S.), Parmalat (Italy) and Royal Ahold (the Netherlands). When compared to the

U.S. and Europe, financial statement fraud in the Chinese listed companies has been even worse.

From the establishment of China security market in 1992 to 2005, 45 listed companies had been

punished for fraudulent behaviours in financial reports by the China Security Regulatory Committee

(CSRC) (Hu, 2006). A series of fraudulent financial reports created by so-called blue chip companies,

such as Yin Guangxia, Lan Tian, and Daqing Hongguang, result in unheard-of credit crisis in the

Chinese stock market. The pervasiveness of reported financial frauds and related alleged corporate

governance failures has eroded investor confidence all over the world.

Prior research (e.g. Beasley, 1996; Dechow et al., 1996; 1999 COSO Report; Beasley et al., 2000)

provides insight into financial fraud instances in the U.S. market, and argues that financial fraud is

associated with weakness of governance. In the Chinese market, one of the largest emerging

economies in the world, corporate governance has also been a hot topic in identifying fraudulent

financial reporting in the recent years. The Chinese corporate governance structure has its unique

features, for example, American independent directors system and German supervisory board system,

as the main traits of the Anglo-American and European Continental corporate governance structures

respectively, are both required to establish in the Chinese firms. It inosculates the characteristics of

both U.S. and Europe, and is reasonably assumed to be special comparing to the experience of the U.S.

financial markets and valuable to do research. This research seeks to develop an analysis of the

prevalence and determinants of financial statement fraud as reported in the Chinese listed firms over

the period 1996 to 2007, by matching to a control sample of equities from companies where financial


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fraud has not been detected. This evidence is important because an understanding of the occurrence

of financial fraud and its relationship with corporate governance in the Chinese market are relevant

to investors, creditors and regulators in that system, and also provide more findings in developing

market to supplement the global academic research on this issue, which present research cannot

address.

From data reported by the China Securities Regulatory Commission, 82 cases of fraud, occurred

during the period from 1996 to 2007, are selected as the study sample. While 82 control peers are

also designed to correspond to the assets size and industries of the study sample as closely as possible.

First, in this paper, the nature and evolution of reported fraud during this 12-year period are

investigated and documented, to show how the nature of fraud has evolved over time. Then this paper

examines the argument that companies are more, or less, prone to fraudulent reporting by reason of

their corporate governance characteristics. It is well known (Fama and Jensen, 1983; Loebbecke et al.,

1989; Bell et al., 1991) that governance structures and histories may impact upon the opportunities for,

incentives towards and the control or identification of fraud within organisations.

The findings of this paper challenge the conventional arguments which have been testified based on

the data from the western countries, mostly from the U.S.. Conventional arguments show financial

fraud is associated with weakness of governance in western companies (e.g. Beasley et al., 2000).

However, the finding in this research reveals that as for some high discussed corporate governance

characteristics (e.g. the supervisory board, audit committee, independent directors), the fraud firms

and their non-fraud peers are not statistically distinct, suggesting that some corporate governance

mechanisms that are designed to reduce the probability of financial fraud fail to work in the Chinese

market.

The paper makes contribution to both academic researchers and policy makers. It contributes most

that regulations and governance protections that work in one system may fail in the other, and

different gatekeepers need to be designed into different governance systems to monitor for frauds.


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The results also have the advantage of being able to test the hypotheses about the corporate

governance failures in identifying financial fraud in the developing markets.

The paper is organized as follows. In section 2, a brief review of the relevant literature on financial

statement fraud is provided. Section 3 outlines research design and data issues. Section 4 contains the

description of timing traits of the research sample. Section 5 presents the empirical results. Section 6

draws this paper into a conclusion and provides the limitations.

2. LITERATURE REVIEW

Much of prior research of fraudulent financial reporting develops arguments or provides descriptive

information about financial and nonfinancial characteristics of companies experiencing financial fraud.

“Who” engage in financial statement fraud? Rezaee (2002) states that most of, if not all, financial

statement frauds occur with encouragement, participation, approval, and knowledge of top executives,

including CEOs, CFOs, presidents and treasurers. In the 1999 COSO reports, it states that top

executives are involved in most of the fraud cases, that is, CEO and/or CFO are named in 83 percent

of the cases, while Controller and Chief Operating Officer are engaged in 28 percent.

“What” are used in financial statement fraud? The 1999 COSO report finds that nearly 90 percent of

financial statement fraud involved falsification, alteration and manipulation of reported accounting

information, while only about 10 percent involved misappropriation of assets; and overstating profits

by recording fictitiously or prematurely was used in more than half of the fraud companies. Rezaee

(2002) also considers that misstating revenue is the most common way in financial statement fraud. In

China, some other research also focused on aggressive use of choices of accounting policies and

accounting estimate methods (e.g., Wang and Yang, 2006).

“Why” does financial statement fraud occur? Financial statement fraud are motivated by many

aspects and committed for a variety of reasons. Robertson (2000) identifies some reasons as primary


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motives of financial statement fraud, including meeting company goals and objectives, obtaining new

financing or more favourable terms on existing financing. Lys and Watts (1994), and Carcello et al.

(2000) also investigate financial pressures according to poor financial performance and weak financial

condition as an incentive mechanism.

“Where” and “when” is financial statement fraud likely to happen? O’Brien (1988) finds a

significant positive relationship between analyst following, firm size, and institutional ownership.

Latham and Jacobs (2000) conclude that the extent of monitoring, either direct (corporate governance)

or indirect (analysts), can create an environment that permits no error, irregularities, and fraud. In

China, Huang (2005) and Chen (2007) find that avoiding regulation (e.g., ST and PT) is the primary

pressure, and fraud opportunities mainly come from the higher top 10 shareholders’ ownership

concentration, fewer times of directorate meetings, fewer percentage of shares owned by directorate

members.

That research of financial fraud provides much of the foundation for the inclusion of many of the

fraud risk factors in regulation. Then several studies (e.g. Beasley, 1996; Dechow et al., 1996;

McMullen, 1996; Beasley et al., 2000) move research forward to “Does corporate governance

matter?” An association between weaknesses in certain corporate governance mechanisms and

fraudulent financial reporting have been documented. For example, Beasley et al. (2000) provides

insight into financial statement fraud instances investigated during the late 1980s through the 1990s

within three volatile industries, and highlights important corporate governance differences between

fraud companies and no-fraud benchmarks. However those studies focus on only one or a few internal

corporate governance mechanisms. Also many studies in this area in China (e.g., Huang, 2005; Hu,

2006) lie in investigating the influence of ownership structure and board governance mechanisms on

financial fraud. Most of other relevant research (e.g., Liu and Du, 2003; Wang and Li, 2004) in fraud

in China has attributed financial fraud to auditing failures and theoretically argues that external

auditors act the first role in deterring financial statement fraud. The empirical research of financial

fraud and its relationship with corporate governance mechanisms, especially some high discussed

mechanisms, is rare. Thus, this paper is motivated and warranted.


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3. RESEARCH DESIGN AND DATA ISSUES

The Chinese corporate governance structure has unique features, for example, American independent

directors system and German supervisory board system, are both required to establish in the Chinese

firms. In this paper, we focus on some high discussed corporate governance mechanisms, including

independent directors, the supervisory board, audit committee, external auditors and regulation rules

in the securities market. It aims to examine whether these mechanisms work as well in identifying

financial fraud in the Chinese market.

3.1 Research Hypotheses

3.1.1 The Relationship of Board of Directors and Financial Statement Fraud

The situation that the board is controlled by top management team is the combination of chairman of

the board and CEO. When the chairman also serves as CEO, the board may be absolutely dominated

by insiders. It leads to weakness of the board’s supervisory independence, and increases the

probability for managers to engage in earnings manipulation and misappropriation of external

investors’ benefits (Jensen 1993). Thereby, it can be expected that the firms with the combination of

chairman of the board and CEO are more likely to perpetrate financial fraud or financial statements

prettification, and may be more inclined to conceal bad accounting information.

H1.1: The situation that the board is controlled by top management team and the occurrence of

financial statement fraud are positively related

Independent director is a member of the board of directors who is differentiated from inside director,

related director and gray director (Daniel, 2002), and they do not form part of the executive

management team or are not involved in the day-to-day running of business. In 23rd August 2001, the

Chinese Securities Regulatory Commission issued Introduction on Development of Independent

Director Mechanism in the Chinese Listed Companies, stating that until 30th June 2002, the board of

directors in the listed companies should include at least two independent directors; until 30th June


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2003, one third of the directorate members should be independent directors, and one of them should

be accounting professionals. Prior research (e.g. Leftwich et al. 1981, Fama and Jesen 1983) argue

that high proportion of independent directors in the board could availably monitor the opportunism

existing in top management. Many Chinese scholars, such as Lu and Wang (2004), also argue that the

independence of the board is improved through independent director mechanism in preventing the

majority shareholders and managers illimitably expand their self-awareness. And we expect that the

listed companies with greater independent directors are less likely to engage in financial statement

fraud.

H1.2: The percentage of independent directors in the board is lower in fraud firms compared to

matched non-fraud firms

3.1.2 The Relationship of the Supervisory Board and Financial Statement Fraud

As for the members of the supervisory board, an effective shareholding contract is one important way

to harmonize their interest with that of shareholders, which can inspirit them to behave towards the

shareholders’ profit maximization at low cost. The greater shares they hold, the stronger motivations

they are given to monitor the actions of top management and also the higher efficiency the board

operates. Therefore, according to the general governance theory, we can expect that high proportion

of shares held by the supervisors improves the disclosure of accounting information and its quality in

the listed companies.

H2: The firms committing financial statement fraud are more likely to have a smaller proportion of

shares owned by supervisors

3.1.3 The Relationship of Audit Committee and Financial Statement Fraud

The western accounting literature, especially empirical studies, cites evidences proving the potential

for a vigilant audit committee as one important mechanism of corporate governance. Previous

research (Beasley 1996, Dechow et al. 1996, McMullen 1996) indicates that firms engaging in


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financial statement fraud are more apt to have ineffective audit committees which meet infrequently

or have no audit committee. DeFond and Jiambalvo (1994) find that non-fraud firms have more active

and effective audit committee than fraud firms. Several reports, such as the Treadway Commission,

the NYSE and NASD, have addressed the role of audit committee in the areas of corporate

governance and Blue Ribbon Committee (BRC) issued ten recommendations and five guiding

principles aimed at enhancing audit committee members’ independence and qualification to ensure a

reliable financial reporting process. The role and function of audit committee have evolved over the

years in the western countries and now its future is expected to be the ultimate guardians of investors’

interest and accountability. While in China, audit committee is still a new concept both in literature

and in the practical operations of firms. Although the Chinese Securities Regulatory Commission

(CSRC) announced that the Chinese listed companies should set up audit committee and issued its

functions in 2002, not all the Chinese listed companies have established audit committee until now.

Most of the Chinese research (e.g. Zhang 2007, Wen 2007, Ye and Ban 2008) focus on theoretically

arguing the functions, significance and problems of audit committee. Based on analysis of the role and

function of audit committee, we expect that in the Chinese stock market, firms with audit committee

are less likely to perpetrate financial statement fraud.

H3: The firms experiencing financial statement fraud are less likely to have an audit committee

than non-fraud firms

3.1.4 The Relationship of External Auditors and Financial Statement Fraud

Users of disclosed accounting information have held external auditors responsible for assuring

financial reports free of material misstatements caused by error or fraud and detecting financial

statement fraud. Auditor’s independence is the cornerstone of auditing quality. The literature has long

been concerned that change and tenure of accounting firms potentially affect audit quality, but

contains conflicting arguments. DeAngelo (1981) and Watts and Zimmerman (1990) consider that as

the auditor-client relationship lengthens, auditors may easily develop personal friendships and

economic dependency on audit clients which impairs audit independence and auditing quality (Mautz


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and Sharaf, 1961; AICPA, 1997; SEC, 2002); and Davis et al. (2003) find a positive relationship

between audit firm tenure and discretionary accruals. While other researchers hold that information

asymmetry between auditors and clients reduces over time as client-specific knowledge is needed in

auditing. For the reason that client-specific knowledge can help detecting material misstatements in

financial statements, the lack of the knowledge in the beginning of audit engagement may lead to

lower auditing quality (Beck et al. 1988; Knapp, 1991; Solomon et al. 1999; Geiger and

Raghunandan, 2002). In China, few scholars study if the duration of the relationship between auditors

and clients is related with the occurrence of financial statement fraud, and most of them focus on

emphasizing the importance of auditor’s independence (e.g. Yu and Li, 2003). In this paper, we expect

a positive relationship between change of accounting firms and the occurrence of financial statement

fraud, and a negative relation between tenure of accounting firms and the likelihood of financial

statement fraud.

H4.1: Change of accounting firms and the occurrence of financial statement fraud are positively

related

H4.2: Tenure of accounting firms and the occurrence of financial statement fraud are negatively

related

As for the influence of accounting firm size on auditing quality, no conclusive and supportive

evidence indicates that the larger accounting firms (e.g., Big Four now, previous Big Eight, Big Six,

or Big Five) can provide more effective audit service and do better in detecting financial statement

fraud. For example, Dechow et al. (1996) find no significant relationship between a non-Big Four

audit firm and financial fraud reporting firms, whereas McMullen (1996) indicates a positive

relationship. In China, research on this issue contains different arguments as well. Hu (2002) shows

that Big Four accounting firms have reputation premium in the Chinese capital market from the aspect

of IPO. While Liu et al. (2003) and Chen and Xia (2006) do not get those supportive conclusions but

even opposite results. As expected the Big Four accounting firms have more professional personnel


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and circumstance, we assume here that larger accounting firms can result in higher auditing quality

and lower possibility of financial statement fraud.

H4.3: Auditing quality and the occurrence of financial statement fraud are negatively related

3.1.5 The Relationship of Regulation Rules and Financial Statement Fraud

One motivation for perpetration of financial statement fraud is associated with the need to hide loss to

prevent ST (Special treatment) or PT (Particular transfer) in the capital market. In terms of Company

Law and Qualifications of Stock being Listed, it can be found that a corporation is much apt to be

treated specially, including ST, suspending being listed or being de-listed, by the Securities

Regulation Sector when it reports continuous loss. When the company is specially treated, on one

hand, the creditors may deem its solvency decreasing, and in order to protect their own benefits, they

may press on with dunning the debt or requiring the company to pay back in advance. On the other

hand, it may increase difficulty for the company in getting loans from banks. Therefore, both debt

financing and equity financing are influenced or even become impossible, and the company may get

into serious financial difficulties. We expect that the listed companies may attempt to utilize

diversified earnings management ways, even fraudulent methods, to make up deficits or prevent

reporting loss.

H5.1: Avoiding regulation in securities market (e.g. ST) and the occurrence of financial statement

fraud are positively related

H5.2: Time length of being listed and the occurrence of financial statement fraud are negatively

related

3.2 Research Variables

The explained variable is whether the listed company engages in financial statement fraud, and the

value can be set to 1 for the fraud firms, while 0 for the non-fraud firms. The explanatory variables are


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as indicated in Table 1. Eight control variables are also involved which relate to motivational and

conditional factors identified in Loebbecke et al. (1989) and Beasley (1996), and most of them are

known to affect the possibility of the occurrence of financial statement fraud in the literature (Simpson,

1986; Baucus and Near, 1991; Bell et al., 1991). The control variables are indicated in Table 2.

Table 1 The explanatory variables of corporate governance

Item Variables Description and measurement of variables

BD1 A dummy variable with a value of one when the chairman of the board

serves as CEO or president and a value of zero otherwise Board of

directors BD2 The proportion of independent directors in the board

SB1 Size of the supervisory board Supervisory

board SB2 The percentage of shares owned by the supervisory board members

Audit

committee AC

A dummy variable with a value of one if the firm has an audit committee

in the year of financial statement fraud and a value of zero otherwise

EA1 A dummy variable with a value of one when accounting firms are

changed in the fraud year and a value of zero otherwise

EA2 The tenure of accounting firms External

auditors

EA3 The authority of accounting firms with a value of one when the

accounting firm is the Big Four and a value of zero otherwise

RG1 Special treated in fraud-occurring year, with a value of one when a firm

is signed ST and a value of zero otherwise

RG2 Special treated in fraud-reporting year, with a value of one when a firm

is signed ST and a value of zero otherwise

Regulators

RG3 Time length of a firm being listed in public markets


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Table 2 The control variables

Variables Description and measurement of variables

IC Industry culture, with a value of one for industry with high competition and

scare resources, such as manufacturing, and a value of zero otherwise

CS Corporate size which is the natural logarithm of total assets of a firm

H Fraud history of a firm, with a value of one when financial statement fraud

occurs in the previous year and a value of zero otherwise

AO Auditing opinion, with a value of one when it is perfect opinion and a value of

zero otherwise

LEVER Financial leverage ratio which is the ratio of liabilities and assets

ROE Return on equity of a firm

ST Special treated, with a value of one when a firm is signed ST and a value of zero

otherwise

RSG Rate of sales growth

3.3 Research Methods

3.3.1 Variance Analysis

Variance analysis is a collection of statistical sample and their associated procedures, in which the

observed variance is partitioned into components due to different explanatory variables. Variance

analysis is employed in this study to provide insight into corporate governance differences between

study sample and control sample benchmarks on an industry basis, and the formula can be seen as

followed:

CGij=ui+eij (F 1)

Where


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CGij= the corporate governance variable of firm j in group i;

ui= the average value of corporate governance variable in group i;

eij= the residual of firm j in group i.

The eij above describes the differences between the corporate governance variable of individual firms

and the average level of that group, and it is assumed normally distributed. Further, Formula 4.2 is

usually transformed to Formula 4.3 for statistical purpose:

CGij=u+ai+eij (F 2)

Where

u= the general average value of corporate governance variable without considering fraud or not;

ai= additional effects when the sample are fraud firms or non-fraud firms.

When corporate governance mechanisms has no relationship with financial statement fraud, there are

no additional effects of the two samples, and a1=a2=0. Therefore, in order to test the role of corporate

governance mechanisms in the commission of fraud, the following assumptions should be tested:

H0: a1=a2=0; H1: at least a1 or a2 is not 0

3.3.2 Factor Analysis

Factor analysis is a statistical method used to describe variability among the observed variables in

terms of a potentially lower number of unobserved variables called factors. One advantage of Factor

Analysis is reduction of number of variables, by combining two or more variables into a single factor.

Factor Analysis is performed in this study to avoid the probable multicollinearity phenomenon

resulting from highly correlated relationship among the research variables.


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3.3.3 Logistic Regression

Logistic regression is involved in the research design of this paper, because financial statement fraud,

as the dependent variable, is dichotomous. The study sample and one-to-one matched control sample

are analyzed in the estimation, although we cannot assume that the rate of companies that are alleged

to have experienced financial statement fraud within the total population of the listed companies is 50

percent, and this approach in the study is different from a pure random sampling approach. Logistic

regression is employed in empirical analysis of each corporate governance factors to test the

hypothesized relationship between the occurrence of financial statement fraud and corporate

governance mechanisms. The logistic regression model is developed as followed:

FSFi= α+ β1CGi + β2ICi+ β3CSi+ β4Hi+ β5AOi+ β6LEVERi+ β7ROEi+ β8STi+ β9RSGi+ εi

(F 3)

Where

FSF- a dummy variable with a value of one when the firm is disclosed to have engaged in

financial statement fraud and a value of zero otherwise;

CG- governance characteristics of corporate governance parties;

IC- industry culture, with a value of one for industry with high competition and scare

resources, such as manufacturing, and a value of zero otherwise;

CS- corporate size which is the natural logarithm of total assets of a firm;

H- fraud history of a firm, with a value of one when financial statement fraud occurs in the

previous year and a value of zero otherwise;

AO- auditing opinion, with a value of one when it is perfect opinion and a value of zero

otherwise;

LEVER- financial leverage ratio which is the ratio of liabilities and assets;

ROE- return on equity of a firm;

ST- special treated, with a value of one when a firm is signed ST and a value of zero

otherwise, which is used to measure if the firm is experiencing financial trouble;


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RSG- rate of sales growth;

i- firm 1 through 164;

ε- the residual.

3.4 Data Collection

Study sample and control sample are mainly chosen from the China Securities Regulatory

Commission (http://www.csrc.gov.cn), Shanghai Stock Exchange website (http://www.sse.com.cn)

and Shenzhen Stock Exchange website (http://www.szse.cn), and other helpful websites that can

provide relevant financial information of the listed companies are http://www.homeway.com.cn,

http://www.cnlist.com and http://www.cninfo.com.cn.

Through carefully reading the punitive notices disclosed by the China Securities Regulatory

Commission from 2002 to 2009, 82 instances of financial statement fraud alleged by the CSRC and

occurred during the 12-year period between 1996 and 2007 are chosen as the study sample1. The

fraudulent financial reports without influence on profits and assets are not involved for lack of fraud

signals on financial data. The periodic punitive notices by the CSRC, which contain summaries of

violation actions of the listed companies, represent one of the most important sources of alleged cases

of fraudulent financial reporting in China and provide recent relevant information. The financial

statement fraud involves violations of Article 177 of Securities Law which is “disobeying the relevant

rules to disclose financial information, or disclosing sham, misguided or highly incomplete

information”; violations of Article 74(2) of Provisional Regulations on the Administration of Share

Issuance and Trading that is “providing fallacious or misleading statements, or omitting momentous

financial information during the process of share issuance and trading”; and violations of Article 12 of

Provisional Regulations on Prohibiting Securities Fraud.

1 The listed companies in Financials industry are not included in the study sample because of different accounting policy and regulation.


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The control sample is also chosen those are designed to correspond to the assets size and industries of

the study sample as closely as possible. Each fraud firm is matched with a non-fraud firm according to

four requirements, which are Stock Exchange, industry, firm size and time period. (Beasley, 1996)

The benchmark industry category is according to industry regulations of Shanghai Stock Exchange

and Shenzhen Stock Exchange. Prior studies on financial fraud consider the absence of non-fraud

control sample as a limitation and have provided empirical evidence of differences in governance

characteristics between fraud firms and non-fraud firms (Beasley, 1996; McMullen, 1996; Beasley et

al., 2000). However, potential possibility of bias exists in choosing the control sample, which is

potential cases of financial statement fraud might be included in the control sample. This represents a

limitation of this paper and we expect that the listed companies that are not in the punitive notices of

the CSRC are less likely to engage in fraudulent activities. In addition, in order to minimize the

likelihood of some misclassification when a company identified as control sample has an occurrence

of financial statement fraud that has not yet been detected, its financial indices are checked. Those

with abnormal indices (such as unusually high level of cash, abnormal assets/debt ratio) are not

involved.

4. TIMING TRAITS OF THE RESEARCH SAMPLES

Table 3 shows that financial statement fraud occurs in each year during the 12-year period between

1996 and 2007, therein, most of the fraudulent financial reports are produced from 2000 to 2004,

which represents 68.13% of the total. The engagements of companies in financial statement fraud are

mostly between 2000 and 2004 as well, which represents 80% of the total. With the development of

the Chinese capital market, since 2000, the securities market has come into an active period. Many

companies consider stock market as “capital resource without cost” and the listing qualification as a

rare resource. Rapid development of internet makes the listed companies pay more attention to their

financial information disclosure (Wang, 2001). Thus, because of the existence of agency problem and

information asymmetry, and imperfect regulation system of the Chinese securities market, many listed

companies are inclined to meet their needs through financial statement fraud. From Figure 1, it can be


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found that before 2004, the occurrence of financial statement fraud has a steady increasing trend, but

decreases suddenly after 2004. One probable reason is that, with increasing disclosure of fraudulent

financial reporting, more pressure from the stakeholders of the listed companies, such as shareholders,

investors and creditors, have been put on the companies and external auditors to get transparent and

accurate accounting information. The other probable reason is, it takes a long time from investigating

financial fraud to disclosing the punitive notices, not all financial statement frauds in the recent three

years have been detected by the China Securities Regulatory Commission yet, and many listed

companies have been put on record to investigate fraudulent activities by the commission but haven’t

got the results.

Based on above analysis, we have a position that we argue that: 1) financial statement fraud occurs

and varies according to pressure and opportunities for misrepresentation, fuelled by return to

successful fraud, and this proportion varies over time; 2) some proportion of fraud has been

uncovered, reported and penalised, and this proportion varies over time as well; 3) the expectation of

detection changes the opportunities and the expected return to fraud, then affecting (1) recursively.

As indicated in Table 4, from the occurrence of financial statement fraud to that the fraud has been

detected and disclosed in the punitive notices by the China Securities Regulatory Commission, time

delay is usually between 2 and 6 years, with 3 years and 4 years in the majority. This indicates that

time delay is one of the main reasons that instances of financial statement fraud suddenly decrease

after 2004, and not all cases of financial statement fraud in recent years have been identified and

reported. Figure 2 describes the relationship line of occurring year and reporting year of financial

statement fraud, and we focus on the fraud cases that occur between 1999 and 2004, because the

delayed reporting years of the fraud cases in this period are mainly from 2002 to 2009. Figure 2

clearly shows that in reporting year t+1, the instances of financial statement fraud identified in a

certain occurring year are more than that in reporting year t, then we can reasonably expect that, a

kind of function relation exists between time delay of the fraud occurring year and reporting year Δt

and the increased instances of financial statement fraud indentified over time ΔFSF, which is assumed


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as ΔFSF= f (Δt). Based on Table 4, we can find out the increased instances of financial statement

fraud indentified in each occurring year when Δt is from 2 to 6 years, as shown in Table 5. Therefore,

it can be reasonably estimated that although in the study sample, the cases of financial statement fraud

identified in 2005, 2006 and 2007 are respectively 2, 1 and 1, some proportion of fraud has not been

detected yet, and the estimated cases of financial statement fraud in these three years are probably

around 14, 13 and 13.

From Table 6, the average of financial statement fraud’s duration in the Chinese listed companies is

2.28 years which is more than a single year. Previous studies (Baucus and Near, 1991; Mulford and

Comiskey, 2002) state that illegal activities usually do not occur in one single accounting period, and

companies disclosed to commit financial fraud often have criminal records before. The 1999 COSO

Report also concludes that most fraudulent activities are not isolated to a single fiscal period.

5. EMPIRICAL ANALYSIS RESULTS

5.1 The Relationship of Board of Directors and Financial Statement Fraud

Based on the statistical description (Table 7) and analysis of variance (Table 8), it is found that the

situation that the board is controlled by the top management team (BD1) is more common in the fraud

firms than that in non-fraud firms, and the chairperson of the boards in more than a half of fraud

companies also serves as CEO or president. The percentage of independent directors in the board

(BD2) for both the fraud group and non-fraud group are on a low level, for the reason that

independent directors system in the Chinese securities market was set up in 2001, and the Chinese

Securities Regulatory Commission required that at the end of 2003, one third of directorate members

in the Chinese listed companies should be independent directors. Young independent directors system,

without actual supervision efficacy, is easily to be pro forma in some of the listed companies, which is

one of the probable reasons for the analysis results.


18

Logistic regression is further deployed to test the hypothesized relationship of the board traits and

financial statement fraud. When univariate differences exist, the logistic regression offers advantages

over the comparison of Variance analysis because some firm specific factors which have been known

to have an effect on occurrences of financial statement fraud can be controlled. The Logistic

regression model here is:

FSFi= α+ β1BD1i+ β2BD2i+ β3ICi+ β4CSi+ β5Hi+ β6AOi+ β7LEVERi+ β8ROEi+ β9STi+ β10RSGi+ εi

(F 4)

Factor Analysis is also employed in advance of Logistic regression, so as to avoid the probable

multicollinearity problem because of highly correlated relationship among the variables. Table 13

reveals the output results of Logistic analysis. As regards variable BD1, its coefficient is positive and

statistically significant, suggesting that firms with a board that is controlled by top executive team are

more likely to engage in fraudulent behaviors. As for the board traits variable BD2, its significant

value is greater than 0.05 that fails in the significance test, suggesting that the proportion of

independent directors in the board does not affect the occurrence of financial statement fraud. The

results are consistent with what we get from Variance analysis. The results thus succeed in supporting

the research hypothesis.

H1.1 The situation that the board is controlled by top management team and the occurrence of

financial statement fraud are positively related: confirmed.

While the results fail to support the research hypothesis,

H1.2 The percentage of independent directors in the board is lower in fraud firms compared to

matched non-fraud firms: not confirmed.


19

5.2 The Relationship of Supervisory Board and Financial Statement Fraud

From Table 7 and Table 8, the sizes of the supervisory board (SB1) for the fraud firms and non-fraud

firms are both on a low level2, with the averages of approximate 4 persons. The proportions of shares

owned by the board members (SB2) for the groups are also relatively low, with the average values of

0.0056 percent and 0.0049 percent respectively. Despite the results of variance analysis indicating that

there are no significant differences of the proportion of shares held by the supervisory board members

between the two groups, based on statistical description, it can be seen that the supervisory board

members of the fraud firms generally hold more shares than that of non-fraud firms. In China, the

board of directors and the supervisory board are parallel and independent, and the members of the

supervisory board are mostly shareholders and employees. In this binary corporate governance

structure, the power of the supervisory board is not like the German style and has no advantages of

Anglo-American Independent Directors. When the efficacy of the supervisory board is weak and

ineffective, and together with the situation that the directorate is controlled by top management, the

likelihood that managers engage in fraudulent financial reporting is enlarged a lot.

In the Logistic analysis, the regression model is developed as follows.

FSFi= α+ β1SB1i+ β2SB2i+ β3ICi+ β4CSi+ β5Hi+ β6AOi+ β7LEVERi+ β8ROEi+ β9STi+ β10RSGi+ εi

(F 5)

Table 13 reveals the output results. The results presented show that the size of the supervisory board

and the percentage of shares owned by the supervisory board members do not influence the likelihood

that top management produce fraudulent financial reports, as evidenced by the insignificant

coefficients on SB1 and SB2 (Sig. value=0.893, 0.840). The result is consistent with what is got from

Variance analysis that the presence of the supervisory board does not play a role in reducing and

2 According to the Chinese Company Law, the size of the supervisory board in the listed companies should be at least three persons. Available: http://www.gov.cn/ziliao/flfg/2005-10/28/content_85478.htm (in Chinese)


20

preventing the occurrence of fraudulent financial reporting in practice. The empirical results fail to

support the research hypothesis.

H2 The firms committing financial statement fraud are more likely to have a smaller proportion of

shares owned by supervisors: not confirmed.

5.3 The Relationship of Audit Committee and Financial Statement Fraud

As indicated in Table 7 and Table 8, audit committees in the fraud group and non-fraud group are

both not common. The results of Variance analysis reveal that the fraud firms have significantly more

audit committees than non-fraud firms, suggesting probably 1) that although the oversight functions

of audit committee have been recognized in theory, it does not play a role in the practical operations;

2) that with reverse causation: firms with Audit committees may be more likely to have fraudulent

behaviours uncovered. For the two probable explanations, this paper prefers the latter one. Audit

committee system is still not universal in the Chinese corporate governance structure. It can be

expected that some fraud firms set up audit committee only in form but not in substance, in order to

show a good corporate governance structure, or to hide unfavourable performance.

In Logistic analysis, the regression model is developed as follows. Beasley (1996) argues that because

of many the board composition reform proposals, e.g., AICPA National Commission on Fraudulent

Financial Reporting 1987; AICPA Public Oversight Board 1993, 1994, the presence of an audit

committee indirectly influences board composition when outside directors are involved in the board to

serve on the audit committee. Therefore, some board traits variables that are relevant to the audit

committee are added to the Logistic model.

FSFi= α+ β1ACi+ β2OUTi+ β3INDi+β4ICi+ β5CSi+ β6Hi+ β7AOi+ β8LEVERi+ β9ROEi+ β10STi+

β11RSGi+ εi

(F 6)


21

Where

AC- a dummy variable with a value of one if the firm has an audit committee in the year of

financial statement fraud and a value of zero otherwise;

OUT- the percentage of outside directors in the board;

IND- the proportion of independent directors in the board;

Table 13 reveals the output results of Logistic analysis. The results presented indicate that the

presence of an audit committee has no significant effect on the occurrence of financial statement fraud,

as evidenced by the insignificant coefficient on AC (Sig. value=0.093). Young audit committee

system in the Chinese capital market is still one of the main reasons that the presence of an audit

committee is less likely to reduce the possibility of financial statement fraud. However, this finding is

consistent with many western scholars’ reports (Sommer 1991, Beasley 1996) noting that considerable

anecdotal evidence is found that many, if not most, audit committees fall short of doing what they are

expected to do as their duties. The results gained fail to support the research hypothesis.

H3 The firms experiencing financial statement fraud are less likely to have an audit committee than

non-fraud firms: not confirmed.

5.4 The Relationship of External Auditor and Financial Statement Fraud

Based on the statistical description and analysis of variance (Table 7 and Table 8), it is found that both

the fraud firms and non-fraud firms have some instances of accounting firms changes (EA1), and

comparing to non-fraud firms, more changes of accounting firms occur in the fraud firms. The tenures

of accounting firms (EA2) for the matched control sample are longer, with the average of 4.48 years,

while for the study sample, the average tenure of accounting firms is 3.70 years. The probable reasons

for relatively more accounting firm changes in the fraud companies are as followed. First, because of

the lack of the knowledge in the beginning of audit engagement, it is impossible for external auditors

to fully get hold of the client’s financial situation and the probability that fraudulent financial


22

activities cannot be detected is high; as the auditor-client relationship lengthens, information

asymmetry between auditors and clients reduces over time, and the fraud companies, in order to make

their illegal acts not be uncovered, may choose to change the accounting firms to hide their financial

fraud engagement. Second, during the audit engagement, when auditors find out some clients’

fraudulent activities and require relevant revisions which are inconsistent with the clients’ interests,

the clients may not be willing to accept the revision requirements, and as a result, poor coordination

between auditors and the clients leads to termination of the cooperative contract and accounting firm

changes. Therefore, frequent changes of accounting firms can be deemed as one of indicators of

financial abnormality in the listed companies. As regards the tenure of accounting firms, the analysis

results indicate that the average for the fraud group is relatively smaller and the tenure is shorter,

suggesting again that more accounting firm changes happen in the fraud group. Comparing to the

western highly concentrative auditing market 3 , much dispersive auditing market in China and

numerous small-sized accounting firms in the market that engage in financial audits for the listed

companies, result in extremely serious low-cost competition in auditing sector. In such operating

environment, when independent auditors have irresolvable contradiction with the clients, they are

more likely to be fired. As to the effect of authority of accounting firms on financial statement fraud

(EA3), we find that the cases that employ the Big Four accounting firms as their external auditing

body are quite few in both the study sample and control sample, therein, 4 percent of fraud firms

employ the Big Four for financial audits while only 1 percent of non-fraud firms surveyed hire the Big

Four as external auditors, which reflects again the operating environment in the Chinese auditing

market. Thereby, there is no conclusive and supportive evidence to show that the larger accounting

firms provide more effective audit service and do better in detecting financial statement fraud.

Logistic regression is then involved to test the hypothesized relationship of external auditor traits and

financial statement fraud. The Logistic regression model is developed as followed, and eight control

3 The U.S. Government Accountability Office (GAO) study found the Big Four audit firms collected 94 percent of all audit fees paid by public companies in 2006 (96 percent in 2002); 82 percent of the large public companies surveyed see their auditor choice as limited to the Big Four in 2008.


23

variables that have also been discussed to influence fraudulent financial reporting in the literature (e.g.,

Loebbecke et al., 1989; Beasley, 1996) are included.

FSFi= α+ β1EA1i+ β2EA2i+ β3EA3i+β4ICi+ β5CSi+ β6Hi+ β7AOi+ β8LEVERi+ β9ROEi+ β10STi+

β11RSGi+ εi

(F 7)

In advance of Logistic regression, Factor Analysis of the external auditor variables is performed in

order to avert the probable multicollinearity problem resulting from highly correlated relationship

among the variables. In the situation that research variables contain highly similar information, the

coefficient estimates may change erratically in response to small changes in the model. The

correlation matrix of Factor analysis can be seen in Table 9.

The variable EA1 (whether accounting firms are changed in the fraud year) and EA2 (the tenure of

accounting firms) indicate highly correlated relations, with the correlation coefficient of -0.459 and

the significant value of 0.000. According to Table 10, in matrix terms, we have

F1= 0.862*EA1- 0.844*EA2+ 0.049*EA3

F2= -0.034*EA1- 0.123*EA2+ 0.995*EA3 (F 8)

Factor F1 corresponds to the turnover of accounting firms that engage in financial audits for the listed

companies, while factor F2 corresponds to the authority of accounting firms. We substitute the two

factors F1 and F2 for the three external auditor variables EA1, EA2 and EA3 into original Logistic

regression model and new Logistic model can be seen as followed.

FSFi= α’+ β’1F1i+ β’2F2i+ β’3ICi+ β’4CSi+ β’5Hi+ β’6AOi+ β’7LEVERi+ β’8ROEi+ β’9STi+ β’10RSGi+

εi

(F 9)


24

In Table 13, as regards the turnover of accounting firms factor F1, the results exhibited show that

financial fraud is more likely to be reported in the Chinese firms with more turnovers of accounting

firms, as evidenced by its significant coefficient (Sig. value= 0.039); while in the light of factor F2

representing the authority of accounting firms, no supportive evidence shows that accounting firms

with high authority (e.g. the Big Four) provide more effective audit service and perform better in

detecting financial statement fraud, as indicated by its insignificant coefficient (Sig. value=0.403).

The result is consistent with that of Variance analysis that fraud firms have significantly more

instances of accounting firms changes and shorter tenures of audit service, and no significant

variability regarding the authority of accounting firms is found between the fraud sample and the

matched control sample. The results gained succeed in supporting the research hypotheses.

H4.1 Change of accounting firms and the occurrence of financial statement fraud are positively

related: confirmed;

H4.2 Tenure of accounting firms and the occurrence of financial statement fraud are negatively

related: confirmed.

But the results are inconsistent with the research hypothesis,

H4.3 Auditing quality and the occurrence of financial statement fraud are negatively related: not

confirmed.

5.5 The Relationship of Regulation and Financial Statement Fraud

As indicated in the statistical description and analysis of variance (Table 7 and Table 8), in the fraud-

occurring years, quite a few companies that engage in financial statement fraud are signed ST, and

most of the fraud companies indicate profitable operating performance; while in the matched non-

fraud group, the companies that have been signed ST are much more than that in fraud group.


25

Seemingly, the occurrence of financial statement fraud has no significant association with regulation

pressure, and companies that are not signed ST and not pressured by regulation requirements commit

more fraudulent financial activities. However, with consideration of variable RG2, the true story is

presented. Variable RG2 measures in fraud-reporting year when financial fraud is disclosed by the

China Securities Regulatory Commission, if the firm is signed ST or not. As regards variable RG2, no

significant difference is found between fraud companies and non-fraud companies, with respectively

30 percent and 21 percent of the companies that are special treated because of poor financial

performance. Based on the Timing description of the fraud sample in Part 4, it is known that from the

occurrence of financial statement fraud to that the fraud has been detected and disclosed in punitive

notices by the China Securities Regulatory Commission, time delay is usually between 2 and 6 years,

with 3 years and 4 years in the majority. According to variable RG1 and RG2, it is reasonably

interpreted that when the listed companies are running into financial difficulties, for fear that both

debt financing and equity financing are influenced resulting from being ST, they may perpetrate

fraudulent behaviours to falsely present good and stable operating performance. However, financial

fraud only works to temporarily cover the financial difficulties of the companies, and if no effective

solutions are performed, the financial difficulties will finally be disclosed over a period to come,

which leads that the companies are signed ST with a few years delayed. Thereby, when the companies

are possible and pressured to be signed ST by regulation commission, they have greater motivations

to engage in financial statement fraud. As for time length of a firm being listed in public markets, we

find that non-fraud group’s listing time length is significantly longer than that of fraud group, which is

consistent with the results of The National Commission on Fraudulent Financial Reporting (AICPA,

1987) studies, and companies that are newly listed in public markets have a proportionately greater

risk of financial statement fraud for the probable purpose of meeting earnings expectations and

increase financing degree in the stock market.

In Logistic analysis, the regression model is:

FSFi= α+ β1RG1i+ β2RG2i+ β3RG3i+β4ICi+ β5CSi+ β6Hi+ β7AOi+ β8LEVERi+ β9ROEi+ β10RSGi+ εi

(F 10)


26

Factor Analysis is also performed in advance of Logistic regression. The correlation matrix of factor

analysis is shown in Table 11. The variable RG1 (whether the firm is signed ST in the fraud-occurring

year) and RG2 (whether the firm is signed ST in the fraud-reporting year) indicate highly correlated

relations, with the correlation coefficient of 0.457 and the significant value of 0.000. On the basis of

Table 12, in matrix terms, we have

F1’= 0.850*RG1+ 0.848*RG2+ 0.108*RG3

F2’= 0.088*RG1+ 0.096*RG2+ 0.994*RG3 (F 11)

Factor F1’ corresponds to the consistency of financial performance of the listed companies, while

factor F2’ corresponds to time length of the listed companies being listed in public markets. We

substitute F1’ and F2’ for the regulation variables RG1, RG2 and RG3 into original Logistic

regression model. The new Logistic model is seen as followed.

FSFi= α’+ β’1F1’i+ β’2F2’i+ β’3ICi+ β’4CSi+ β’5Hi+ β’6AOi+ β’7LEVERi+ β’8ROEi+ β’9RSGi+ εi

(F 12)

Table 13 reveals that as to the consistency of financial performance factor F1’, the results exhibited

demonstrate that financial fraud is more likely to be reported in the Chinese firms with inconsistent

financial performance in fraud-occurring years and fraud-reporting years, as evidenced by its

significant coefficient (Sig. value= 0.040); while in the light of factor F2’ representing time length of

the listed companies being listed in public markets, supportive evidence is found that companies that

are newly listed in public markets have proportionately greater likelihood of financial statement fraud,

as indicated by its significant coefficient (Sig. value=0.034). The results are consistent with that of

Variance analysis that when the listed companies are running into financial difficulties, for fear of the

negative influences resulted from being ST, they may perpetrate fraudulent behaviours to temporarily


27

hide poor finance performance, and regarding time length of the companies being listed in capital

market, non-fraud group’s listing time length is significantly longer than that of fraud group. The

results gained succeed in supporting the research hypotheses.

H5.1 Avoiding regulation in securities market (e.g. ST) and the occurrence of financial statement

fraud are positively related: confirmed;

H5.2 Time length of being listed and the occurrence of financial statement fraud are negatively

related: confirmed.

6. CONCLUSIONS

The findings of this research challenge the conventional arguments which have been testified based

on the data from the western countries. Conventional arguments show financial fraud is associated

with weakness of governance in western companies (e.g. Beasley et al., 2000). However, the finding

in this research reveals that as for some high discussed corporate governance characteristics (e.g. the

supervisory board, audit committee, independent directors), the fraud firms and their non-fraud peers

are not statistically distinct, suggesting that corporate governance mechanisms that are designed to

reduce the probability of financial fraud fail to work in the Chinese market. Statistical differences of

external auditor traits and regulation from the securities market are found between the groups.

The negative results bring deep thinking to both academic researchers and policymakers. Why are

contradictions gained in the Chinese market? It is difficult to answer the question at the moment.

One probable explanation provided here relates to the system of share ownership. Two basic

ownership systems are: disperse ownership system (e.g., the U.S. market) and concentrated ownership

system (e.g., the Continental European, and the Chinese markets) (Wang, 2003; Coffee, 2005; Zhang,

2007). In the dispersed ownership system, corporate performance is mostly controlled by managers

and governance issues arise from agency relationship between shareholders and managers (Jensen

and Meckling, 1976; Jensen, 1986); while in the concentrated ownership system, there is usually a


28

controlling shareholder or shareholder group in the corporations who has absolute control on

managers and corporate performance, and governance issues refer to if the controlling shareholders

overreach minority shareholders (Gordon, 1999; Kirchmaier and Grant, 2004). The closest argument

is supported by Coffee (2005), who argues that gatekeepers, that is professional agents serving

shareholders but selected by the corporation, are not believed to work as well in concentrated

ownership regimes as in dispersed ownership regimes. Whether different ownership system accounts

for the inconsistent findings in different economies, further research is warranted. However, it is

worth noting that this research develops the analysis based on the data from the concentrated

ownership system, and all the research findings are valid only in the concentrated ownership system.

The research contributes most that regulations and governance protections that work in one system

may fail in the other, and different gatekeepers need to be designed into different governance systems

to monitor for different frauds.

In appraising the findings of this paper, it is important to consider the following limitations. The

studied cases in this paper are mainly chosen from the punitive notices disclosed by the Chinese

Securities Regulatory Commission. For the reason that the CSRC is most inclined to take formal

investigations with strong evidences and high probability of success, focusing on the punitive notices

of the CSRC might offer the possibility of bias. There are likely to be potential instances of fraudulent

financial reporting not included in the study sample. Also, potential possibility of bias may exist in

choosing the control sample. Potential cases of financial statement fraud might be included in the

control group. Although due to this limitation, the matched non-fraudulent sample is carefully chosen

and also checked if they have some abnormal financial indices that may suggest a greater possibility

of engaging in fraudulent activities. The bias of choosing control sample is only minimized but cannot

be eliminated. Furthermore, because of the timing traits of the research sample, the fraud sample

would have over-representation of past fraud, and again, there would also be probability of recent

fraudulent cases involved in the control sample.


29

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33

Table 3 Time distribution of the studied sample

Occurring

year Fraudulent financial

statements (occurred) Fraud in this year/

the total (%) Companies with FSF

finished Companies in this year/ the total (%)

1996 2 2.20 0 0

1997 5 5.49 1 2.50

1998 9 9.89 2 5.00

1999 9 9.89 2 5.00

2000 14 15.38 6 15.00

2001 13 14.29 8 20.00

2002 11 12.09 3 7.50

2003 14 15.38 7 17.50

2004 10 10.99 8 20.00

2005 2 2.20 2 5.00

2006 1 1.10 0 0

2007 1 1.10 1 2.50

Total 914 100 40 100

Table 4 The relation of financial statement fraud (FSF) occurring year and reporting year

Number of fraudulent financial statements identified in the reporting year Occurring year 2002 2003 2004 2005 2006 2007 2008 2009

1996 1 0 0 0 1 0 0 0

1997 2 1 1 0 1 0 0 0

1998 3 2 3 0 1 0 0 0

1999 2 3 3 0 1 0 0 0

2000 1 5 5 2 1 0 0 0

2001 1 2 7 2 1 0 0 0

2002 ---- 0 2 4 3 2 0 0

2003 ---- ---- 0 4 4 5 0 1

2004 ---- ---- ---- 1 3 3 2 1

2005 ---- ---- ---- ---- 0 1 0 1

2006 ---- ---- ---- ---- ---- 0 1 0

2007 ---- ---- ---- ---- ---- ---- 1 0

Total 10 13 21 13 16 11 4 3

4 The fraud sample here is 91 financial statements in 40 firms. Due to lack of the relevant financial information in 9 cases, the research sample in variance analysis and Logistic regression is 82 fraudulent cases.


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Table 5 The relation of ΔFSF identified and time delay Δt

Δt, time delay of FSF occurring year and reporting year Occurring year Δt=2 Δt=3 Δt=4 Δt=5 Δt=6

1999 ---- 2 5 8 9

2000 1 6 11 13 14

2001 3 10 12 13 13

2002 2 6 9 11 11

2003 4 8 13 13 14

2004 4 7 9 10 ----

Average 2.8 6.5 9.8 11.3 12.2

Table 6 Fraud duration of the studied sample

Fraud duration 1 year 2 years 3 years 4 years 5 years 6 years 7 years 8 years Total

Companies 13 15 6 4 0 1 0 1 40

Average 2.28


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Figure 1 Time distribution line of the studied sample

Figure 2 The relation of financial statement fraud occurring year and reporting year


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Table 7 Statistical description of corporate governance characteristics

Fraud firms Non-fraud firms

Variables N Mean Std. D Variance Variables N Mean Std. D Variance

BD1 82 0.51 0.503 0.253 BD1 82 0.20 0.399 0.159

BD2 82 14.856 14.638 214.291 BD2 82 15.696 15.122 228.679

SB1 82 4.02 1.100 1.209 SB1 82 4.11 1.305 1.704

SB2 82 0.0056 0.0077 0.000 SB2 82 0.0049 0.0090 0.000

AC 82 0.29 0.458 0.210 AC 82 0.16 0.367 0.135

EA1 82 0.17 0.379 0.143 EA1 82 0.11 0.315 0.099

EA2 82 3.70 2.147 4.610 EA2 82 4.48 3.159 9.981

EA3 82 0.04 0.189 0.036 EA3 82 0.01 0.110 0.012

RG1 82 0.02 0.155 0.024 RG1 82 0.11 0.315 0.099

RG2 82 0.30 0.463 0.215 RG2 82 0.21 0.408 0.166

RG3 82 5.68 2.238 5.009 RG3 82 6.79 3.332 11.105


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Table 8(a) Summary of output results of test of variance analysis

Variables df Mean Square F Sig.

Between Groups 1 28.963 0.131 0.718BD2

Within Groups 162 221.485

Between Groups 1 0.299 0.205 0.651SB1


Between Groups 1 0.000 0.251 0.617SB2


Between Groups 1 0.115 5.184 0.028LgEA25


Significance level: 0.05

Table 8(b) Summary of output results of test of variance analysis6

Variables Statistic* df1 df2 Sig.

Welch 20.013 1 153.990 0.000BD1

Brown-Forsythe 20.013 1 153.990 0.000

Welch 4.282 1 154.763 0.040AC

Brown-Forsythe 4.282 1 154.763 0.040

Welch 5.259 1 156.731 0.026EA1

Brown-Forsythe 5.259 1 156.731 0.026

Welch 1.019 1 130.576 0.315EA3

Brown-Forsythe 1.019 1 130.576 0.315

Welch 4.858 1 118.243 0.029RG1

Brown-Forsythe 4.858 1 118.243 0.029

Welch 2.049 1 159.449 0.154RG2

Brown-Forsythe 2.049 1 159.449 0.154

Welch 6.267 1 141.722 0.013RG3

Brown-Forsythe 6.267 1 141.722 0.013

*Asymptotically F distributed; Significance level: 0.05 5 In variance analysis, variable EA2 fails in the homogeneity testing. By dealing with original EA2 values logarithmically, variance analysis of LgEA2 passes the homogeneity test. 6 The variables in this form all fail in homogeneity testing of variance analysis. When their original values cannot be dealt with logarithmically, Statistic Brown-Forsythe and Statistic Welch are involved, which are better than Statistic F, when homogeneity of variances for some variables cannot be assumed.


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Table 9 Correlation matrix of Factor analysis for external auditor variables

EA1 EA2 EA3

EA1 1.000 -0.459 0.050

EA2 -0.459 1.000 -0.122Correlation

EA3 0.050 -0.122 1.000

EA1 0.000 0.263

EA2 0.000 0.061Sig.

(1-tailed) EA3 0.263 0.061

KMO and Bartlett’s Test: 40.605 (Sig.: 0.000)

Significance level: 0.05;

Table 10 Rotated component matrix for external auditor variables

Component

1 2

EA1 0.862 -0.034

EA2 -0.844 -0.123

EA3 0.049 0.995

Rotation Method: Varimax with Kaiser Normalization Where EA1- A dummy variable with a value of one when accounting firms are changed in the fraud year and a value of zero otherwise EA2- The tenure of accounting firms EA3- The authority of accounting firms with a value of one when the accounting firm is the Big Four and a value of zero otherwise


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Table 11 Correlation matrix of Factor analysis for regulation variables

RG1 RG2 RG3

RG1 1.000 0.457 0.181

RG2 0.457 1.000 0.185

Correlation

RG3 0.181 0.185 1.000

RG1 0.000 0.010

RG2 0.000 0.009

Sig.

(1-tailed)

RG3 0.010 0.009

KMO and Bartlett’s Test: 45.340 (Sig.: 0.000)

Significance level: 0.05;

Table 12 Rotated component matrix for regulation variables

Component

1 2

RG1 0.850 0.088

RG2 0.848 0.096

RG3 0.108 0.994

Rotation Method: Varimax with Kaiser Normalization Where RG1- Special treated in fraud-occurring year, with a value of one when a firm is signed ST and a value of zero otherwise RG2- Special treated in fraud-reporting year, with a value of one when a firm is signed ST and a value of zero otherwise RG3- Time length of a firm being listed in public markets


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Table 13 Summary of output results of Logistic regression

Independent variable

Predicated relation

Estimated coefficients

Standard Errors Wald value Sig.

The board traits variables:

BD1 + 1.473 0.531 7.682 0.006

BD2 none -0.026 0.020 1.604 0.205

The supervisory board variables:

SB1 none 0.023 0.169 0.018 0.893

SB2 none 4.907 24.372 0.041 0.840

The audit committee variables:

AC none 1.029 0.613 2.820 0.093

The external auditor variables: turnover of accounting firms factor F1

F1 + 0.367 0.222 4.424 0.039

The authority of accounting firms factor F2

F2 none 0.219 0.261 0.700 0.403

The regulation traits variables: the consistency of financial performance factor F1’

F1’ - -0.047 0.245 4.419 0.040

Time length of the companies being listed factor F2’

F2’ - -0.493 0.233 4.475 0.034

Chi-Square Test of Model’s Fit Sig.: 0.000

Total cases: 164

Fraud cases: 82

Non-fraud cases: 82

Significance level: 0.05 Where BD1- A dummy variable with a value of one when the chairman of the board serves as CEO or president and a value of zero otherwise BD2- The proportion of independent directors in the board SB1- Size of the supervisory board SB2- The percentage of shares owned by the supervisory board members AC- A dummy variable with a value of one if the firm has an audit committee in the year of financial statement fraud and a value of zero otherwise F1- The factor corresponding to turnover of accounting firms that engage in financial audits, with a value obtained from Factor analysis F2- The factor corresponding to the authority of accounting firms that engage in financial audits, with a value obtained from Factor analysis

F1’- The factor corresponding to the consistency of financial performance of the listed companies, with a value obtained from Factor analysis F2’- The factor corresponding to time length of the listed companies being listed in public markets, with a value obtained from Factor analysis

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