Audit Committee and CEO Ethnicity and Audit fees: Some Malaysian evidence

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The International Journal of Accounting 47 (2012) 302 – 332

Audit Committee and CEO Ethnicity and Audit fees: Some Malaysian evidence Shireenjit Johl a,⁎, Nava Subramaniam a , Mazlina Mat Zain b b

a Deakin University, Australia Multimedia University, Malaysia

Received 28 September 2009

Abstract This study extends the literature on audit pricing by examining the relationship between ethnicity (bumiputra vs non-bumiputra), corporate governance attributes, and audit fees using data from 559 publicly-listed companies in Malaysia in 2005. Drawing from theories of ethnicity and political economy, we discuss our two hypotheses that predict positive associations between audit fees and (1) the proportion of bumiputra members on audit committees, and (2) the presence of a bumiputra CEO. The results support the hypothesis that firms with bumiputra CEOs incur higher audit fees, but we do not find an association for firms with bumiputra-dominant audit committees. In additional analysis, we find that the audit premium paid by firms with a bumiputra CEO is higher for the smaller client firms. Further, we find that firms managed by a bumiputra CEO with a fully bumiputra-composed audit committee tend to pay higher audit fees than the other firms, indicating that there is a combined ethnicity effect on audit fees. © 2012 University of Illinois. All rights reserved. JEL classification: M42 Keywords: Audit pricing; Audit committee; Corporate governance; Malaysian ethnicity; Bumiputra CEO

1. Introduction Ethnicity is part of a society's social fabric, and researchers have rarely considered its impact on economic transactions. 1 Some contend that ethnicity is a central organising principle in social relations and thus has the ability to affect the perceptions, interactions, and activities of ⁎ Corresponding author at: School of Accounting Economics and Finance, Deakin University, Victoria, Australia. Tel.: +61 3 9251 7360. E-mail address: [email protected] (S. Johl). 1 Ethnicity, in general, refers to a societal group whose members are connected with one another based on a common heritage including a common ancestry, language, culture, and often religion (Zagefka, 2009). 0020-7063/$ - see front matter © 2012 University of Illinois. All rights reserved. doi:10.1016/j.intacc.2012.07.002

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business communities (Anthias, 1990; Haniffa & Cooke, 2002). Further, empirical evidence from a number of countries suggests that ethnicity has the potential to shape organisational management and commercial exchanges. For example, Efferin and Hopper (2007) found ethnicity to be a key factor in shaping management control processes in Indonesian firms; Davie (2005) contends that pre-existing patterns of Chiefly power through ethnicity impact the use of accounting reports in Fiji; and Biggs, Raturi, and Srivastava (2002) identified ethnic networks as a critical factor in accessing informal sources of finance (e.g., supplier credit) in Kenya. More recently, we have seen a growing interest in the impact of ethnicity when it is institutionalised through government interventions and policies. In Malaysia, a steady stream of research has developed about the corporate setting, where the political economy has a strong effect on how firms are run both externally (generally based on political intervention) and internally (based on ethnicity) (Abdul Wahab, How, & Verhoeven, 2007; Faccio, Masulis, & McConnell, 2006; Gul, 2006; Haniffa & Cooke, 2002). Much of this research has also focused on the level of bumiputra (i.e., the dominant ethnic group in Malaysia) firm ownership or control, and its impact on various organisational outcomes. More specifically, the emerging empirical evidence indicates significant associations between ethnic firm ownership and organisational factors such as: audit pricing (Gul, 2006; Yatim, Kent, & Clarkson, 2006), audit services (Che Ahmad, Shafie, & Mohamad Yusof, 2006), disclosure practices (Haniffa & Cooke, 2002), and firm performance (Abdul Wahab et al., 2007). The present study contributes to this growing body of research by providing a closer examination of the relationship between the ethnicity of two major governance stakeholders (members of the audit committee and the CEO), and audit pricing behaviour in Malaysian publicly-listed firms. Both the audit committee members and CEOs are the focal stakeholders in this study because they tend to work actively and closely with external auditors. Consequently, the auditors' perceptions of such stakeholders have potential implications for their evaluation of the overall audit risk and, subsequently, the audit effort and audit pricing (Carcello, Hermanson, Neal, & Riley, 2002). Auditors are increasingly expected to consider the quality of their clients' corporate governance, and the audit committee members and the CEOs often act as important conduits of information proprietary to the firm and have substantial roles in the auditor–client interactions and communication processes. Prior studies in this area have largely focused on the effects of ethnicity dominance in terms of firm ownership and board membership (Abdul Wahab et al., 2007; Che Ahmad et al., 2006; Gul, 2006; Yatim et al., 2006). These studies have given little regard to the ethnicity implications at the individual level (namely, those in corporate governance-related functional roles). This void in the literature motivates for the present study. A key justification for choosing Malaysia as the context for this study is that it presents an ideal setting for studying the relationship between ethnicity and economic outcomes because of its unique corporate environment. The Malaysian economy offers clearly identifiable capital segments divided along ethnic lines, and ethnicity privileges are constitutionally secured (Cheong, 1990; Jesudason, 1990). In fact, Salim (2006) states that: “More than anything else, racial composition in Malaysia is the key to understanding the big picture. It has helped shape the constitution, influenced the democratic processes and dictated the pattern of the economy.” (p. 18) Malaysia is a multi-ethnic society, where Malays (otherwise referred to as bumiputras) are the dominant group, followed by Chinese and Indians and a variety of indigenous groups in

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East Malaysia. The first two ethnic groups in particular play a major role in the socio-economic fabric of the country, with the Malays controlling the political administration and the Chinese having significant influence over the economic environment. In order to minimise the so-called economic gap or disparity in economic status between the Malays and Chinese (with the latter seen as being more affluent), the New Economic Policy (NEP) was established in 1971, providing many new initiatives and funding privileges to support bumiputra business and to increase bumiputra participation in the capital market. Government policies favouring bumiputra firms acted as a form of institutionalised positive discrimination based on ethnicity and led to the propagation of many bumiputra business ventures. For instance, the NEP-based reforms saw bumiputra corporate ownership grow from 1.5% in 1970 to 20.3% in 1990 (Tam & Tan, 2007). However, it continues to remain less than the initial target of 30% set by the NEP (Ahmad & Chow, 2006). One less desirable outcome of the NEP, as Suto (2003) argues, is that it may have encouraged the free-rider problem which created an invisible protection umbrella for bumiputra, especially through the establishment of large trust funds. Consequently, as Tam and Tan (2007) argue, the development of the market for professional managers has been undermined. The bumiputra manager is a more recent phenomenon compared with his or her counterpart in local Chinese or multinational firms, and people perceive the bumiputra manager as having less business acumen. For instance, Salim (2006) notes that bumiputra-managed or controlled companies are relatively young and many of the executives and managers lack business experience. Additionally, the perceived independence of the bumiputra directors and senior executives is more likely to be influenced by the close political connections among bumiputra-owned or managed firms (Gul, 2006). Past studies by Ball, Robin, and Wu (2003) and Bushman, Piotroski, and Smith (2004) show that politically connected firms are negatively associated with good corporate governance practice, signalling the higher agency costs inherent in such firms and associated with the key personnel of the firm. 2 Furthermore, bumiputra firms commonly outsource projects to other local contracts after winning government contracts and tenders. Bumiputra directors and CEOs tend to be more open to cronyism and thus rent-seeking behaviours, including deriving financial and personal gains due to their privileged status. Many of the high profile bumiputra directors and CEOs display their political connections (Hamid, 2008). On the other hand, the non-bumiputra firms, particularly local Chinese-owned firms, seem to be run more efficiently and supported by a rich network of family and business affiliations. Yeung (1999) analyses Chinese business in Southeast Asia in the face of increasing globalization and contends that Chinese firms tend to adopt more Western management practices, and operate through effective personal and business networks with other Chinese firms across borders and nations. Consequently, the public perceives Chinese business managers to have strong competitive and managerial skills, particularly in adapting to changing economic conditions.

Relative to the size of its capital market, the number of politically connected firms in Malaysia is seen to be very high (Abdul Wahab et al., 2007). For instance, Faccio et al. (2006) based on data from 1997 to 2002 report that the number of politically-connected firms in Malaysia was 81, which is second to the United Kingdom with 118 politically-connected firms. 2

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Based on the factors discussed above, this study argues that bumiputra directors and CEOs are perceived to have higher levels of reputational risk for poor business management than non-bumiputra directors. As such, auditors are likely to view the decisions of bumiputra directors and managers with greater scepticism and scrutiny. In other words, auditors may perceive the quality of the corporate governance and business nuance exercised by bumiputra directors and managers differently than they view non-bumiputra directors and managers. This difference has the potential to be reflected in audit pricing. However, we have no empirical evidence on the effect of the ethnicity of audit committee members and CEOs on audit pricing in Malaysia. Prior studies have largely focused on firm level characteristics such as ownership and political connections, but have ignored the individual level characteristics of key stakeholders of corporate governance. Our results, based on the analysis of 559 publicly-listed Malaysian firms in 2005, identify that audit fees are positively associated with bumiputra CEO managed firms, but not bumiputra-dominant audit committees. Further, this positive link between firms with a bumiputra CEO and audit fees is more prevalent in smaller client firms. In addition, we find that audit fees are higher for firms that are managed by a bumiputra CEO with a fully bumiputra-composed audit committee than they are for other firms. This difference indicates that there are combined ethnicity effects on audit fees. These results extend previous studies on the effects of ethnicity on audit fees within the Malaysian context by identifying the ethnicity of the CEO as a significant factor in audit pricing (Gul, 2006; Yatim et al., 2006). The results indicate the need for better, more open management of auditor and client communications and relationships in firms that have bumiputra CEOs. The remainder of this paper is organised as follows. The next section (Section 2) provides an overview of the research on audit fees, particularly the supply and demand theoretical perspectives for audit and the Malaysian corporate environment, including the recent changes in corporate governance guidelines in Malaysia. In Section 3, we discuss the development of research hypotheses and delineate the research method and data analysis in Section 4. The final two sections (i.e., Sections 5 and 6) are composed of discussions of the results and conclusions of the study, including its limitations and suggestions for future research. 2. Background 2.1. Audit fee—supply versus demand perspectives Audit pricing can be understood from both a supply and demand perspective. From a supply-side perspective, audit fees can be seen as a function of an auditor's assessment of the overall risk of an audit. In other words, auditors are assumed to “minimize total cost by balancing their resource costs (costs of performing more audit work) and their expected future losses from legal liability” (Carcello et al., 2002, p. 369). Any additional audit effort (including the associated costs) is balanced with additional benefits accrued from such audit efforts. The existence of alternate monitoring mechanisms should play a substitute role, where auditors are less compelled to undertake additional audit efforts in the presence of other strong governance mechanisms. For example, based on a supply-side perspective, Tsui, Jaggi, and Gul (2001) contend that auditors tend to consider corporate governance as an important internal control mechanism that affects the nature and extent of audit testing.

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Strong corporate governance mechanisms are likely to lead to better quality accounting information, which reduces auditors' assessments of audit risk and subsequently leads to lower audit testing, and lower audit fees. These arguments are supported by Tsui et al.'s (2001) empirical findings in which more independent corporate boards generally have lower audit fees. In contrast, the demand-side perspective of audit pricing proposes that the existence of better corporate governance leads to higher audit fees. The argument here is that firms with strong corporate governance mechanisms such as better quality boards and internal controls, are likely to demand a higher quality external audit from their auditor, resulting in a higher audit fee (Goodwin-Stewart & Kent, 2006). Empirical evidence from Abbott, Parker, Peters, and Raghunandan (2003) and Carcello et al. (2002) supports this perspective. These studies find a positive association between better corporate governance features and audit fees. They argue that more independent, diligent, and expert boards will seek to preserve their reputation, avoid potential litigation, and purchase higher quality audit services. Over the years, these perspectives have shaped a line of research that identifies the key determinants of audit pricing (Gul & Goodwin, 2010; Hay, Knechel, & Ling, 2008). 2.2. Audit fee research Numerous empirical studies suggest that client firm size, complexity, riskiness, and other characteristics of the audited entity tend to vary based on audit fees (Hay, Knechel, & Wong, 2006). The effects of such factors on audit fees are also evident in a number of developing economies such as Bangladesh (Karim & Moizer, 1996), Hong Kong (Gul, 1999; Ho & Ng, 1996; Simon, Teo, & Trompeter, 1992), India (Simon, Ramanan, & Dugar, 1986), and South Africa (Simon, 1995). However, evidence of nation-specific idiosyncrasies has also been reported by Chen, Su, and Wu (2007), where data from the Chinese binary audit market (i.e., supplementary versus statutory market) reveal that the Big 5 earn a significant fee premium in the less competitive supplementary market compared to those in the statutory market. 3 Similarly, in Korea, where regulators are able to assign auditors to firms, Jeong, Jung, and Lee (2005) found that assigned auditors charge significantly higher audit fees than freely-selected auditors. We have scant evidence from developing countries on the impact of ethnicity-related factors on economic transactions, although multiculturalism and strong political interventions are often characteristic of such nations (Efferin & Hopper, 2007; Haniffa & Cooke, 2002). The impact of ethnicity differences is akin to affecting perceptions and expectations of a given social group, which has implications for interpersonal interactions and communication processes within and across groups (Haniffa & Cooke, 2002; Salim, 2006). Given that auditing is a socio-technical process, we need to understand better the effects of ethnicity on auditor perceptions and judgements in relation to key governance stakeholders in client firms. Potentially, this plays a vital role in the audit pricing process (O'Keefe, Simunic, & Stein, 1994). For example, the extent to which personnel involved in the audit process are perceived to provide reliable information on issues that arise during an audit engagement can affect the 3

Besides a statutory audit, Chinese companies with foreign investments are required to undergo a supplementary audit.

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auditor's assessment of inherent risks and subsequently can affect the time and effort spent on an engagement, which ultimately affects audit fees. 2.3. Malaysia—corporate governance background In comparison to most other East Asian economies, the Malaysian equity market is considered well-developed (EAU, 2002). Malaysia continues to be ranked as one of the largest stock markets by both market capitalisation and number of listed companies in the developing/emerging market in the post-Asian Financial Crisis period from 2000 onwards (EAU, 2002). For example, in 2000, a total of 757 companies were listed with a market capitalisation of RM552 billion. Nevertheless, the 1997 Asian Financial Crisis precipitated several corporate governance reforms over the last decade. For instance, the Malaysian Code of Corporate Governance (MCCG) was first issued in March 2000. It is a non-statutory, self-regulatory voluntary guide. The recommendations set out in MCCG are divided into four main parts: Part (1) Principles of Corporate Governance; Part (2) Best Practice in Corporate Governance; Part (3) Principles and Best Practices for Other Corporate Participants; and Part (4) Explanatory Notes. (For a more detailed discussion of the development of corporate governance in Malaysia, see Liew, 2007; Subramaniam, Mat Zain, & Johl, 2009.) In 2004, the Kuala Lumpur Stock Exchange became demutualised, and was re-named Bursa Malaysia. Considerable efforts were subsequently undertaken to enhance corporate governance practices by integrating the MCCG into the listing requirements. 4 3. Hypotheses development 3.1. Audit committee, ethnicity and audit fees Audit committees are viewed as a major mechanism through which management and auditors are able to communicate and negotiate the terms and conduct of the audit. A major responsibility of an audit committee is to provide oversight of the financial reporting process, which includes assessing the overall adequacy and appropriateness of the internal controls and reporting mechanisms. An audit committee's composition and expertise are therefore critical for the client–auditor management process. Audit committees should be composed of a majority of independent members with at least one with financial expertise (ASX Corporate Governance Council, 2003; BRC, 1999; SC, 2007). More independent and diligent audit committees are associated with activities that enhance the audit function (Abbott et al., 2003; Carcello et al., 2002). DeZoort and Salterio (2001) found that audit committees with independent members and audit knowledge are more likely to support the independent auditor in a substance-over-form dispute with management. Subsequently, from an audit supply-side perspective, a better (poorer) quality audit committee is likely to decrease 4 More recently, the MCCG was revised and published on 1 October, 2007, with the amendments largely focusing on enhancing the roles of boards by spelling out more clearly the eligibility criteria for the appointment of directors, and the roles of internal auditors and audit committees. In tandem, Bursa Malaysia also announced key amendments to its corporate governance guidelines under its listing requirements, mirroring the MCCG's changes.

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(increase) audit risk assessment, which can be expected to lower (increase) audit effort and audit fees. From the supply-side perspective, we argue that the ethnicity of audit committee members is likely to have a bearing on auditors' risk assessment of a client, which will be reflected in the audit fees. Specifically, we contend that auditors are likely to assess a higher level of audit risk when a bumiputra-dominant audit committee is present because they may have a poorer reputation with respect to business management. In general, the reputation for business management of bumiputra directors and senior managers is poor because of the following factors. First, the bumiputra director is a more recent phenomenon compared to his/her Chinese counterparts. In fact, bumiputra-owned firms are generally perceived to be poorly run and lacking in accountability and good corporate governance (Salim, 2006). The situation is often exacerbated because these firms are the beneficiaries of government projects and other state-funded initiatives (Salim, 2006). Thus, both the lack of business experience and the lack of incentives to adopt more competitive and accountable governance practices can easily lead to perceptions of complacency and laxity in bumiputra leadership (Cheong, 1990; Jesudason, 1990). Further, bumiputras tend to be more politically connected and, thus, open to cronyism (Salim, 2006). The general argument Johnson and Mitton (2003) as well as Gomez and Jomo (1997) present is that bumiputra-controlled firms are ethnically-favoured firms that are also often politically connected. Local researchers such as Gomez (2009) have increasingly criticized the failure of government initiatives to create large competitive enterprises in the industrial sector (http://malaysiaeconomy.blogspot.com/). The situation has worsened with the failure of small to medium industrial enterprises, often owned by bumiputras. While these criticisms are thwarted at the national level policies, the underlying arguments tend to suggest a general lack of bumiputra leadership in business. Based on the above discussion, we predict that the auditors are likely to assess inherent risk as being higher with increasing bumiputra dominance of audit committees, ultimately resulting in additional monitoring efforts and higher audit fees. Therefore, the first hypothesis for this study is: H1. There is a positive relationship between the proportion of bumiputra members on the audit committee and audit fees. 3.2. CEO, ethnicity and audit fees Leadership is a critical aspect of management, with senior management such as CEOs and managing directors playing an important role not only in managing the day-to-day internal affairs of their organisations, but also acting as liaisons between the firm and external parties. Furthermore, when it comes to external audit matters, senior management often has to deal with issues like queries relating directly to the audit. Management may also have to attend interviews, update the external auditor on corporate strategic developments, post-audit reviews and updates, and negotiate on accounting policies and estimates. This requires considerable self-confidence, business nuance, and governance experience. As discussed in the previous sub-section, we argue that given the potential lack of business nuance and the higher probability that bumiputra senior executives are politically well-

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Table 1 Summary of the sample selection process. Number of firms listed on the Main Board of Bursa Malaysia as of 31 December 2005

646

Less: Finance firms Annual reports not available Firms with missing values for some control variables Final sample

(45) (35) (7) 559

connected, auditors are likely to perceive such CEOs to have greater reputational risks. Hall, Blass, and Massengale (2004) argue that a leader who has a higher or more positive reputation will be regarded with a higher degree of trust, will be monitored less, and will be held to lower accountability standards than a leader with a lesser reputation. Therefore, in an external audit, a bumiputra CEO's decisions could come under greater scrutiny and external auditors may take a longer time over their interactions with a bumiputra CEO. Further, the auditors may resort to alternative information sources to attain a full understanding of how the company is being led and managed. Consequently, the effort spent on an audit involving bumiputra CEOs is likely to be higher and thus have higher audit fees. The second hypothesis for this study is: H2. Audit fees will be significantly higher for firms with a bumiputra CEO than for firms with a non-bumiputra CEO.

4. Research method 4.1. Sample The data were primarily hand-collected from the 2005 annual reports of companies listed on the Main Board of the Bursa Malaysia. 5 Both financial and non-financial data were extracted from the annual reports, which we obtained online from the Bursa Malaysia's website. The initial data, which consist of 646 firms, were screened for financial firms, missing annual reports, and missing data on both the dependent and independent variables. After eliminating finance firms and firms with no annual reports, the sample was reduced to 568 firms. Next, we further reduced the sample to 559 after deleting those with missing values on the variables. Table 1 summarises the selection process.

4.2. Audit fee model specification and variables description Based on prior literature on audit fees (Carcello et al., 2002; Ferguson, Francis, & Stokes, 2003; Francis, 1984; Gul, 1999, 2006; Yatim et al., 2006), the following ordinary least squares

5

As of 31 December 2005 there were 646 companies listed on the Main Board.

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regression model is used to test the hypotheses: LAF ¼ α 0 þ β 1 LASSET þ β2 LEV þ β3 RECTA þ β4 INVTA þ β 5 CACL þ β6 ROE þβ7 YE þ β8 LSUB þ β9 LFORSUB þ β 10 LOSS þ β 11 LAGE þ β12 BIG4 þβ13 OPINION þ β14 ATENURE þ β15 POL þ β 16 BODIND þ β17 BODMEET þβ18 ACIND þ β19 ACMEET þ β20 ACFE þ β21 BUMIAC þ β22 BUMICEO þ þε where: Dependent variable LAF natural logarithm of audit fees

Control variables LASSET natural logarithm of total assets LEV book-value of long-term debt to total equity RECTA book-value of receivables to total assets INVTA book-value of inventories to total assets CACL current assets to current liabilities ROE net income to total equity YE 1 for financial year ending 31/12, 0 otherwise LSUB natural logarithm of the number of subsidiaries LFORSUB natural logarithm of the number of foreign subsidiaries LOSS 1 for firms with a loss in the prior year, 0 otherwise LAGE natural logarithm of the number of years since date of incorporation BIG4 1 for big audit firms, 0 otherwise OPINION 1 if the audit report is qualified, and 0 otherwise ATENURE 1 if the incumbent auditor is the auditor for more than three years, and 0 otherwise POL 1 if the firm is politically connected to the ruling party—Barisan Nasional, 6 and 0 otherwise BODIND proportion of independent directors on the board BODMEET number of board meetings held in the year ACIND percentage of independent non-executive audit committee members ACMEET number of audit committee meetings held in the year ACFE number of audit committee members with accounting and financial backgrounds to total number of audit committee members

Hypotheses variables BUMIAC percentage of bumiputra members on the audit committee BUMICEO 1 if the firm's CEO is a bumiputra, and 0 otherwise.

6

Politically-connected firms are defined and identified based on Johnson and Mitton (2003) and Gul (2006).

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In the model above, the natural logarithm of audit fees (LAF) is the dependent variable. From the descriptive statistics reported in Table 2, the average audit fee is RM$260,540 and ranges from RM$6000 to RM$9,100,000. 7 The audit fee model used in this study includes several control variables that were used in prior studies (e.g., Carcello et al., 2002; Hay et al., 2006; Simunic, 1980) and those that are unique to the Malaysian setting (e.g., Gul, 2006; Yatim et al., 2006). These variables include firm size (LASSET), client risk (LEV, CACL, ROE, LOSS, OPINION), audit complexity (RECTA, INVTA, LSUB, LFORSUB, and YE), firm age (LAGE), auditor quality (BIG4, ATENURE), and politically-connected firms (POL). As shown in Table 2, the mean total asset for our sample is RM1,410,000,000 and ranges from RM$465,000 to RM$63,500,000,000. The sample firms have an average leverage of 0.701 and the mean ROE is − 0.018. About 28.2% of the sample firms reported a loss in the prior year. The Big 4 auditors appear to dominate the Malaysian audit market with a market share of about 68.5%. In terms of auditor–client relationships, about 61.3% of the sample firms have been with their incumbent auditor for more than 3 years. One institutional factor that is unique to Malaysia is the existence of politically-favoured companies, and 12.7% of the sample firms are politically connected to the ruling political party (Barisan Nasional). 8 In addition to the typical audit fees model variables, recent studies have also included corporate governance variables such as board independence (BODIND), board activity (BODMEET), audit committee independence (ACIND), audit committee diligence (measured in terms of audit committee meetings—ACMEET) and audit committee financial expertise (ACFE). As shown in the table 40% of the directors of sample firms are independent on average. The number of board meetings held ranges between 3 and 15, with most firms having a mean of 7 meetings in the year. Moving to audit committee characteristics, the mean percentage of audit committee members who are independent is 76% and ranges from 33% to 100%. In terms of audit committee diligence, the number of meetings held in the year ranges from 1 to 13 with a mean of 4.8 meetings in the year. The mean percentage of firms with accounting and finance expertise is 59% and ranges between zero and 100%. In the model specified above, bumiputra audit committee (BUMIAC), and bumiputra CEO (BUMICEO) are the hypothesised ethnicity variables relating to H1 and H2, respectively. In relation to the audit committee, the mean and median proportions of bumiputra members on the audit committee (BUMIAC) are 0.434 and 0.333, respectively. About 30% of the sample firms are managed by a bumiputra CEO. Bumiputra influence on the board is similar to its influence on the audit committee, in that the mean proportion of bumiputra on the board is about 41%. Using 60% as a cut-off to denote dominant influence, 23% of the sample firms were bumiputra-controlled firms. Further analysis on bumiputra CEOs shows that 85% of the bumiputra-controlled firms and 15% of non-bumiputra-controlled firms are managed by a bumiputra CEO. The Pearson correlations presented in Table 3 generally suggest that audit fees are positively correlated with the two hypothesised variables—bumiputra audit committee 7 8

As at 31 December 2005, the exchange rate per US$ is RM$3.80. About 15% of the sample firms in Gul (2006) were politically-connected.

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Panel A: descriptive statistics for continuous variables Variable

Mean

Std. dev.

Min

Max

Median

LAF AF (RM'000) LASSET ASSET (RM'000) LEV RECTA INVTA CACL ROE LSUB SUB (numbers) LFORSUB FORSUB (numbers) AGE LAGE ATENURE BODIND BODMEET ACIND ACMEET ACFE BUMIAC BUMICONTROL1

11.787 240.956 19.968 1,420,000 0.701 0.169 0.090 0.446 − 0.018 2.261 15.569 0.475 2.569 24.687 2.879 3.311 0.397 7.685 0.762 4.791 0.591 0.435 0.412

0.951 529.019 1.394 4,630,000 3.194 0.136 0.105 .222 1.049 0.993 20.508 0.867 8.683 18.471 0.905 1.003 0.110 2.056 0.144 1.280 0.225 0.313 0.261

8.700 6 13.050 465 − 0.09 0 0 0 − 13.89 0 0 0 0 1 0 1 0 3 0.333 1 0 0 0

16.024 9100 24.874 63,500,000 53.39 0.65 0.71 1.27 7.45 5.656 286 5.069 159 100 4.605 4 0.83 17 1 13 1 1 1

11.657 115.5 19.902 440,000 0.190 0.140 0.050 0.440 0.070 2.303 10 0 0 22 3.091 4 0.380 7 0.750 5 0.667 0.333 0.333

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Table 2 Descriptive statistics for sample companies (N = 559).

Panel A: descriptive statistics for continuous variables Variable

Mean

Std. dev.

Min

Max

Median

Panel B: Frequencies for dichotomous variables Firms coded 1

%

Firms coded 0

%

YE LOSS BIG4 OPINION ATENURE BUMICEO POL

308 158 383 538 343 168 71

55.10 28.26 68.52 96.24 61.36 30.05 12.70

251 401 176 21 216 391 488

44.90 71.74 31.48 3.76 38.64 69.95 87.30

LAF = natural logarithm of total audit fees; AF = total audit fees (RM'000); LASSET = natural logarithm of total assets; ASSET = total assets (RM'000); LEV = book value of long-term debt to total equity; RECTA = book value of receivables to total assets; INVTA = book value of inventories to total assets; CACL = current assets to current liabilities; ROE = net income to total equity; LSUB = natural logarithm of the number of subsidiaries; SUB = total number of subsidiaries; LFORSUB = natural logarithm of the number of foreign subsidiaries; FORSUB = total number of foreign subsidiaries; AGE = the number of years since date of incorporation; LAGE = natural logarithm of the number of years since date of incorporation; BODIND = proportion of independent directors on the board; BODMEET = number of board meetings held in the year; ACIND = percentage of independent non-executive audit committee members with accounting and financial background to total number of audit committee members; ACMEET = number of audit committee meetings held in the year; ACFE = proportion of accounting and financial expertise on the audit committee; BUMIAC = proportion of bumiputra members on the audit committee; BUMICONTROL1 = proportion of bumiputra members on the board of directors; YE = 1 for financial year ending 31/12, 0 otherwise; LOSS = 1 for firms with loss in the prior year, 0 otherwise; BIG4 = 1 for big audit firms, 0 otherwise; OPINION = 1 if the audit report is qualified, 0 otherwise; ATENURE = 1 if the incumbent auditor has been the auditor for more than three years; POL = 1 if the firm is politically connected to the ruling party—Barisan Nasional, 0 otherwise; BUMICEO = 1 for firms with bumiputra CEO, and 0 otherwise.

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Variable

313

314

Table 3 Pearson correlations.

LAF LASSET LEV RECTA INVTA CACL ROE YE LSUB LFORSUB LOSS AGE BIG4 OPINION ATENURE POL BODIND BODMEET ACIND ACMEET ACFE BUMIAC BUMICEO

1

2

3

1 .631 ⁎⁎ .082 .059 − .035 − .032 .027 − .006 .604 ⁎⁎ .493 ⁎⁎ .023 .159 ⁎⁎ .114 ⁎⁎ .021 .127 ⁎⁎ .248 ⁎⁎ .084 ⁎ .214 ⁎⁎ .106 ⁎ .206 ⁎⁎ .008 .197 ⁎⁎ .167 ⁎⁎

1 .053 − .170 ⁎⁎ − .124 ⁎⁎ − .246 ⁎⁎ .033 − .059 .372 ⁎⁎ .382 ⁎⁎ − .063 .131 ⁎⁎ .104 ⁎ .125 ⁎⁎ .108 ⁎ .222 ⁎⁎ .015 .255 ⁎⁎ .088 ⁎ .202 ⁎⁎ .052 .130 ⁎⁎ .084 ⁎

1 .001 − .085 ⁎ − .038 − .231 ⁎⁎ − .023 .103 ⁎ .064 .135 ⁎⁎ .008 − .091 ⁎ − .207 ⁎⁎ .039 .035 .060 − .120 ⁎⁎ .033 .058 − .019 .048 .047

4

5

6

7

8

9

10

11

12

1 .367 ⁎⁎ .041 .068 − .135 ⁎⁎ .003 − .109 ⁎⁎ − .102 ⁎ .020 .074 .085 ⁎ − .096 ⁎ − .073 .062 − .020 − .066 − .056 − .148 ⁎⁎ − .170 ⁎⁎

1 .029 .053 − .086 ⁎ − .016 − .022 − .114 ⁎⁎ − .005 .032 .022 − .098 ⁎ .001 − .006 − .029 − .028 − .092 ⁎ − .110 ⁎⁎ − .051

1 − .015 − .056 .035 − .191 ⁎⁎ .066 .075 .109 ⁎⁎ .099 ⁎ .063 − .111 ⁎⁎ .067 − .055 − .145 ⁎⁎ .024 − .028 − .019

1 − .041 − .046 − .024 − .047 .071 − .008 .022 − .034 − .045 − .005 .003 − .046 − .022 .038 .043

1 .561 ⁎⁎ .037 .130 ⁎⁎ − .004 − .091 ⁎ .052 .182 ⁎⁎ .160 ⁎⁎ .081 − .010 .248 ⁎⁎ .068 .177 ⁎⁎ .080

1 − .036 .118 ⁎⁎ .070 − .095 ⁎ .077 .150 ⁎⁎ .141 ⁎⁎ .078 − .036 .148 ⁎⁎ .064 .080 .008

1 .148 ⁎⁎ − .090 ⁎ − .148 ⁎⁎ − .073 .059 .016 − .091 ⁎ .039 .013 − .067 .055 .082

1 .086 ⁎ − .059 .153 ⁎⁎ .207 ⁎⁎ .047 .044 .080 .082 .050 .156 ⁎⁎ .084 ⁎

1

.171 ⁎⁎ .518 ⁎⁎ .036 − .011 − .037 − .004 − .006 − .156 ⁎⁎ − .018 .054 .011 − .066 − .037 .014 − .036 .007 − .018 − .035 − .020

*Correlation is significant at the 0.05 level (2-tailed).**Correlation is significant at the 0.01 level (2-tailed). All variables are defined in Table 2.

S. Johl et al. / The International Journal of Accounting 47 (2012) 302–332

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Table 3 Pearson correlations.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

LAF LASSET LEV RECTA INVTA CACL ROE YE LSUB LFORSUB LOSS AGE BIG4 OPINION ATENURE POL BODIND BODMEET ACIND ACMEET ACFE BUMIAC BUMICEO

14

15

16

17

18

19

20

21

22

23

1 − .249 ⁎⁎ .118 ⁎⁎ .029 − .019 .098 ⁎ .175 ⁎⁎

1 .050 .052 − .014 .014 − .070

1 − .016 − .048 .143 ⁎⁎ .176 ⁎⁎

1 .038 .116 ⁎⁎ .077

1 .001 − .013

1 .504 ⁎⁎

1

1 .048 .019 .064 − .050 .058 .088 ⁎ − .018 .017 .038 .076

1 .017 .047 − .019 .154 ⁎⁎ .008 − .054 .071 − .019 − .014

1 − .006 .009 .039 .039 − .024 − .019 .023 − .001

1 .057 .135 ⁎⁎ .033 .092 ⁎ − .004 .133 ⁎⁎ .043

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(BUMIAC), and bumiputra CEO (BUMICEO). The correlations amongst the independent variables are comparatively low. All values are well below 0.50, except for the correlation between LSUB and LFORSUB (r = 0.561), CACL and RECTA (r = 0.518), and BUMIAC and BUMICEO (r = 0.504). To test for multicollinearity, the VIF was calculated for each independent variable. Myers (1990) suggests that a VIF value of 10 and above is cause for concern. Our results indicate that for all estimations, the independent variables had VIF values of less than 10, with the highest value recorded by variable LSUB (VIF value = 1.67). 9 5. Empirical findings A total of four estimations were carried out, as reported in Table 4. The first estimation was carried out to test the validity of the audit fee model without incorporating any of the test variables, followed by the second and third estimations to test the two hypotheses (H1 and H2). Finally, the fourth estimation tests both H1 and H2 jointly. As shown in Table 4, the F-statistic for each of the OLS models is statistically significant at 1% level and the adjusted R 2 is about 62%. Although the adjusted R 2 of each of the models is slightly lower than it is in some of the prior studies in the US, the UK, and Australia, they are comparable to other studies in Malaysia (Gul, 2006; Yatim et al., 2006). Consistent with prior studies, with the exception of OPINION, CACL and LAGE, the traditional variables used in the audit fees model, LASSET, LEV, RECTA, INVTA, ROE, YE, LSUB, LFORSUB, LOSS, BIG4 and ATENURE, are all positive and significant (p b 0.10, p b 0.05 and p b 0.01). The POL variable measuring firms that are politically-connected is also significant and positively associated with audit fees in all estimations, which is consistent with Gul's (2006) findings. Moving to the governance control variables, BODMEET (board meeting) is significant (p b 0.05) and positively associated with audit fees. Likewise, in terms of audit committee characteristics, ACIND (audit committee independence) is positive and significant (at 1% and 5% levels of significance). Interestingly, this is contrary to previous studies where Yatim et al. (2006) and Bliss, Muniandy, and Majid (2007) did not find any such direct relationship using Malaysian data. However, it is consistent with other studies such as Abbott et al. (2003) and Carcello et al. (2002). Given that Bursa Malaysia's listing requirements continue to provide organisations with the flexibility of having a fully-independent audit committee composition (as opposed to a majority independent committee), this result suggests that the former has a stronger impact on audit pricing. In relation to ACFE (audit committee financial expertise), the relationship is only marginally significant (at 10% level of significance) but is negatively associated with audit fees. 10 The other two governance control variables, BODIND and ACMEET, are not significant in all four estimations. 9

Note: In our further testing on the influence of bumiputra control on audit fees, we included the variables BUMICONTROL1 (BUMICONTROL2/BUMICONTROL3) and BUMIAC in our estimation and our VIFs for these two variables were beyond 2.0 (i.e., 3.63 and 2.60, respectively). Because of the high VIFs in these two variables, in our analyses, as shown in Table 5, we excluded BUMIAC in our estimation. 10 This result is in contrast to Abbott et al. (2003) and Yatim et al. (2006) which report a positive relationship between audit expertise and audit fees. The finding is also contrary to the findings of Goodwin-Stewart and Kent (2006) and Carcello et al. (2002), who find that audit committee characteristics are not significant when boardrelated variables are included. In summary, the results suggest that audit committee expertise reduces auditor risk assessments associated with the audit of the financial reporting process, thus reducing the extent of the audit and, in turn, lowering audit fees.

S. Johl et al. / The International Journal of Accounting 47 (2012) 302–332

317

Table 4 OLS regression results. Expected sign

Constant LASSET

+

LEV

+

RECTA

+

INVTA

+

CACL

+

ROE

?

YE

+

LSUB

+

LFORSUB

+

LOSS

+

LAGE

?

BIG4

+

OPINION

+

ATENURE

−

POL

+

BODIND

+

BODMEET

+

ACIND

+

ACMEET

+

Estimation 1 Audit fee model (without test variables) Coefficient (t-statistic)

Estimation 2 Bumi audit committee Coefficient (t-statistic)

Estimation 3 Bumi CEO Coefficient (t-statistic)

Estimation 4 Bumi audit committee and Bumi CEO Coefficient (t-statistic)

3.692 5.21*** .310 7.57*** .006 1.41† .951 4.39*** .377 1.63** .149 1.13 .0250 1.89† .0736 1.39† .359 9.85*** .0980 2.37** .102 1.61** .352 1.12 .110 1.74** − .0210 − 0.15 .679 1.27† .164 1.73** .143 0.50 .023 1.83** .413 2.22** .005 0.29

3.724 5.28*** .309 7.61*** .006 1.42† .932 4.35*** .418 1.79** .164 1.27 .025 1.99** .067 1.27† .354 9.75*** .100 2.41** .100 1.58† .298 0.94 .107 1.71** − .022 − 0.16 .674 1.26 .155 1.62 .118 0.42 .023 1.84** .372 2.02** .003 0.15

3.86 5.52*** .306 7.71*** .006 1.42† .934 4.26*** .495 2.14** .145 1.11 .022 1.90** .063 1.20 .356 9.80*** .104 2.59*** .090 1.45† .032 1.02 .095 1.53† − .024 − 0.18 .0688 1.31† .166 1.78** .029 0.11 .025 2.01** .326 1.76** .001 0.06

3.86 5.51*** .306 7.70*** .006 1.41† .931 4.28*** .497 2.14** .148 1.14 .022 1.91** .062 1.18 .355 9.79*** .104 2.59*** .090 1.46† .031 0.99 .954 1.53† − .025 − 0.18 .069 1.30† .164 1.74** .030 0.11 .025 2.00** .322 1.75** .001 0.05 (continued on next page)

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Table 4 (continued) Expected sign

Estimation 1 Audit fee model (without test variables) Coefficient (t-statistic)

Estimation 2 Bumi audit committee Coefficient (t-statistic)

Estimation 3 Bumi CEO Coefficient (t-statistic)

Estimation 4 Bumi audit committee and Bumi CEO Coefficient (t-statistic)

ACFE

+

− .140 − 1.34†

− .134 − 1.29†

BUMIAC (H1)

+

− .136 − 1.32† .157 1.94**

BUMICEO(H2)

+

− .133 − 1.29† .032 0.34 .181 2.40*** 0.623 41.81

Adjusted R2 F-Stat

0.615 43.27

0.618 41.29

.192 3.04*** 0.623 43.91

†, **, *** = statistically significant at less than the 0.10, 0.05, and 0.01 levels, based on one-tailed (two-tailed) tests for variables where direction of relationship with dependent variable is (is not) specified. All variables are defined in Table 2.

Hypotheses 1 and 2 predict a positive association between audit fees and the two ethnicityrelated independent variables, that is, the proportion of bumiputra audit committee members and CEO ethnicity, respectively. As shown in Table 4 under Estimation 2, the variable, bumiputra audit committees (BUMIAC), is positive and is significantly associated with audit fees (0.157; p b 0.05, 1-tailed). The variable bumiputra CEO (BUMICEO) in Estimation 3 of Table 4, is positive and is strongly associated with audit fees (Estimation 3, 0.192; p b 0.01; 1-tailed). However, when both variables BUMIAC and BUMICEO are included in the estimation (Estimation 4), the significance of BUMIAC diminishes, while BUMICEO still remains significant (Estimation 4, 0.181; p b 0.01; 1-tailed). This suggests that H1 is not supported but H2 is, and that the presence of a bumiputra CEO has a much stronger effect on audit fees. A possible explanation for the support of H2 and not H1 is that the nature of interactions between the auditor and the audit committee, and interactions between the auditor and the CEO, may differ. First, audit committees generally meet less frequently with the auditor and have a specific agenda in relation to reviewing financial statements and related audit issues. It is also important to note that, in these interactions, non-bumiputra members are also present. Next, the interactions between CEO and the auditor are more often on a one-to-one basis because the CEO has overall responsibility for corporate strategic developments and the overall management of the firm. The auditor will often need to discuss and gain confirmation on a variety of issues including the firm's strategic risk management, post-audit reviews and updates on recommendations. The auditor may also have to undertake negotiations on accounting policies and estimates— which, in total, affect overall audit risk. Thus, given the nature of these interactions, it is possible that the bumiputra CEO's effect on audit fees is stronger than the audit committee's effect.

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319

The significance of BUMICEO is much stronger (t-statistic = 3.00) than the variable politically-connected firms (POL) (t-statistic = 1.93), which seems to indicate that auditors may consider leadership ethnicity more critically when assessing the firm's inherent risk. To further investigate whether bumiputra CEOs of politically-linked firms were driving the significance of BUMICEO, we interact the variable BUMICEO with POL. The analysis (not presented in the table) did not find the interaction variable to be significant. In summary, the results support the notion that auditors tend to rate the inherent risks of firms led by bumiputra CEOs as higher than firms without bumiputra CEOs due to the reputational risks attributed to bumiputra CEOs. This assessment of higher inherent risk is then reflected in higher audit fees. 5.1. Additional analyses Three other analyses are conducted to extend the basic findings in this paper. The first test includes a continuous variable (or dummy variable) for bumiputra-controlled boards, which was used in Yatim et al. (2006) and Gul (2006). The second test involves an interaction between a fully dominated bumiputra audit committee (BUMIAC100) and a bumiputra CEO (BUMICEO). This test is undertaken to capture firms that are purely bumiputra managed, and where the internal oversight role is carried out by an audit committee that is entirely dominated by bumiputra members. Finally, the third test includes a dummy variable—auditor ethnicity (measured in three ways: the ethnicity of the signing auditor (AETHNICITY), ethnicity match between CEO and signing auditor (BCEOBA), and ethnicity match between bumiputra-dominant audit committee and signing auditor (BACBA)). The quality of the communication between the auditor and the CEO/audit committee members may also be based on the ethnicity of each party. Tables 5, 6 and 7 summarise the results from these three tests. 5.2. Bumiputra-controlled firms As discussed in the descriptives section (and Table 2), the mean proportion of bumiputra members (BUMICONTROL1) on the board is 41% and ranges from 0 to 100%. In capturing bumiputra dominance, we used a dummy variable = 1 if the board of directors is made up of at least 60% and 0 otherwise. Based on this 60% cut-off, one hundred and twenty-nine (129) firms (23%) are bumiputra-controlled (BUMICONTROL2). 11 We also used a second bumiputra-dominant board variable, with boards that are fully dominated by bumiputra members (BUMICONTROL3). 28 firms (5%) fall into the category of fully-dominated bumiputra boards. As shown in Table 5, the coefficients for the three different bumiputra control variables (BUMICONTROL1/BUMICONTROL2/BUMICONTROL3) in the three estimations are not significant. However, the variable of interest, BUMICEO, remains positive and strongly significant at 1% level of significance. 12 A possible reason for the 11 We have tested using 50% cut-off, and the coefficient of bumiputra board variable is negative but only weakly significant at 10% level. The variable BUMICEO remains positive and significant. We believe that the 50% cutoff does not capture ‘true’ bumiputra dominance and thus utilise a 60% cut-off. 12 In these sets of regressions we find that when BUMIAC is included, the VIFs for bumiputra board control are greater than 2 and thus decided to drop BUMIAC. When BUMIAC is included the results remain consistent, in that, bumiputra control board is insignificant, whilst BUMICEO is positive and significant. The variable BUMIAC is not significant.

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non-significance of all three bumiputra control variables may relate to the use of a more recent set of data (2005) in this study in contrast to Yatim et al. (2006) 13 who used 2003 year-end data. A second reason for the insignificance of the bumiputra control variable is perhaps due to the manner in which we measure the variable. In this study, we use bumiputra dominance on the board of directors as a proxy for control whilst Yatim et al. (2006) and Gul (2006) use bumiputra ownership as a proxy for control. 14 We select bumiputra dominance on the board of directors in this study because prior studies assume that bumiputra-controlled firms have poorer corporate governance. Given that the board has the oversight responsibility for governance design and processes, we focus on board composition. 5.3. Bumiputra audit committee and bumiputra CEO interaction Given that audit committees play an important internal monitoring role in a firm's governance landscape, the composition of an audit committee composed entirely of bumiputra members may reduce the effectiveness of its oversight of the financial reporting process. The effectiveness of the audit committee's role is further exacerbated by the presence of a bumiputra CEO. In other words, auditors are likely to assess the inherent risk of such firms as high, which is reflected in higher audit fees. Sixty-five firms (12%) in the sample have fully bumiputra-dominated audit committees (BUMIAC100), and 168 firms (30%) have a bumiputra CEO (BUMICEO). Fifty-four firms (10%) have both; that is, they have fully bumiputra-dominated audit committees (BUMIAC100) and a bumiputra CEO (BUMICEO). As shown in Table 6, Estimation 1, the variable BUMIAC100 is not significant, while the coefficient of BUMICEO is positive and strongly significant at 1% level. The interaction variable (BUMIAC100 ∗ BUMICEO) in Estimation 2 is also positive and significant at 5% level. The results support the notion that firms that are managed by a bumiputra CEO and have an audit committee made up entirely by bumiputras tend to pay higher audit fees which, from a supply-side perspective, suggests that auditors tend to factor in the higher reputation risk associated with bumiputra leadership and governance structure. Hence, the combined ethnicity effect has a negative implication for the auditors' risk assessment, which is reflected in higher audit effort and audit fees. 5.4. Auditor ethnicity Finally, the third test is intended to rule out the possibility of auditor ethnicity driving our results. From our sample, 14% (78 firms) of the lead audit (signing) partners were bumiputra. About 9% (51 firms) of the sample firms had both a bumiputra CEO and a bumiputra lead auditor (BCEOBA), whilst 11% (61 firms) of the sample firms had both a bumiputra-dominant audit committee and a bumiputra lead auditor (BACBA). Table 7 shows that although the coefficient of AETHNICITY in Estimation 1 is positive and weakly significant (coefficient 0.119; p b 0.10), the coefficients for AETHINICITY, BACBA and BCEOBA in the rest of the 13

The variable CEO duality was also not significant in Yatim et al.'s (2006) study. It is important to note the difference in the findings of both Yatim et al. (2006) and Gul (2006). Yatim et al. (2006) using 2003 data found a weak negative relationship between bumiputra control and audit fees, while Gul (2006) using data from 1996 to 1999 found a positive relationship between those variables. 14

S. Johl et al. / The International Journal of Accounting 47 (2012) 302–332

321

Table 5 Additional analyses—bumiputra control firms. Variables

Expected sign

Constant LASSET

+

LEV

+

RECTA

+

INVTA

+

CACL

+

ROE

?

YE

+

LSUB

+

LFORSUB

+

LOSS

+

LAGE

?

BIG4

+

OPINION

+

ATENURE

−

POL

+

BODIND

+

BODMEET

+

ACIND

+

ACMEET

+

ACFE

+

BUMICEO

+

Estimation 1 Coefficient (t-statistic)

Estimation 2 Coefficient (t-statistic)

Estimation 3 Coefficient (t-statistic)

Estimation 4 Coefficient (t-statistic)

3.698 5.22*** 0.309 7.57*** 0.006 1.46† 0.942 4.35*** 0.416 1.74** 0.154 1.19 0.024 1.85† 0.068 1.27† 0.358 9.84*** 0.098 2.38*** 0.099 1.55† 0.034 1.08 0.107 1.71** − 0.018 − 0.13 0.068 1.28† 0.159 1.69* 0.112 0.40 0.023 1.86** 0.392 2.11** 0.004 0.21 − 0.136 − 1.31†

3.913 5.65*** 0.305 7.72*** 0.006 1.32† 0.948 4.36*** 0.454 1.93** 0.13 1.00 0.023 2.01** 0.071 1.37† 0.358 9.97*** 0.107 2.69*** 0.093 1.49† 0.032 1.05 0.095 1.55† − 0.031 − 0.24 0.068 1.29† 0.179 1.93** 0.051 0.19 0.025 1.98** 0.338 1.84** 0.003 0.14 − 0.139 − 1.34† 0.271 3.00***

3.863 5.55*** 0.305 7.72*** 0.005 1.24 0.934 4.27*** 0.480 2.07** 0.140 1.07 0.022 1.81† 0.068 1.30† 0.356 9.86*** 0.107 2.66*** 0.091 1.46† 0.033 1.06 0.099 1.61** − 0.031 − 0.24 0.065 1.23 0.176 1.88** 0.054 0.20 0.025 1.98** 0.338 1.85** 0.001 0.07 − 0.136 − 1.30† 0.243 2.68***

3.854 5.51*** 0.306 7.76*** 0.006 1.42 0.934 4.25*** 0.496 2.14** 0.145 1.12 0.022 1.90** 0.063 1.20 0.356 9.79*** 0.104 2.58*** 0.090 1.45† 0.032 1.02 0.095 1.53† − 0.025 − 0.19 0.069 1.31† 0.166 1.77** 0.029 0.11 0.025 2.00** 0.326 1.76** 0.001 0.06 − 0.134 − 1.29† 0.190 2.77***

(continued on next page)

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Table 5 (continued) Variables

Expected sign

BUMICONTROL1

+

BUMICONTROL2

+

BUMICONTROL3

+

Adjusted R2 F-Stat

Estimation 1 Coefficient (t-statistic) 0.096 0.92

0.616 41.19

Estimation 2 Coefficient (t-statistic) − 0.218 − 1.44†

0.625 42.21

Estimation 3 Coefficient (t-statistic)

Estimation 4 Coefficient (t-statistic)

− 0.092 − 0.97

0.624 41.50

0.010 0.07 0.623 41.86

†, **, *** = statistically significant at less than the 0.10, 0.05, and 0.01 levels, based on one-tailed (two-tailed) tests for variables where direction of relationship with dependent variable is (is not) significant. BUMICONTROL2 = 1 if the proportion of bumiputra members on the board is 60% and above, and 0 otherwise; BUMICONTROL3 = 1 if the board of directors is made up entirely of bumiputra members. All other variables are defined in Table 2.

estimations (Estimations 2 to 5) are not significant. The results, therefore, suggest that higher audit fees are due to the auditor's higher assessment of inherent risk given the ethnicity of the leadership (bumiputra CEO). The non-significance in the match variables (BACBA and BCEOBA) could mean that bumiputra CEOs/audit committee members feel more comfortable with a bumiputra auditor as these auditors are able to deal with sensitive questions. In addition, bumiputra auditors may understand the issues surrounding bumiputra-led firms better without incurring a significant increase in audit fees. 5.5. Client size effects Prior literature indicates that the log of total assets varies with client size (Bell, Knechel, & Willingham, 1994; Carson & Fargher, 2007). In order to capture client size effect, we follow Carson and Fargher (2007) and include indicator variables for each quintile by total asset. We interact the indicator variable with the log of total assets (LASSET ∗ EACH QUINTILE). Next, we also partition the BUMICEO by firms into three sizes of categories. Specifically, we interact an indicator variable for the largest, medium, and smallest categories with BUMICEO (BUMICEO ∗ LARGE/MEDIUM/SMALL). Table 8 shows the results of the piecewise regression models that take client size effect into account. Estimation 1 of Table 8 includes the additional variables used in the audit fee model to capture client size effect, which allow the coefficient on log of total assets (LASSET) to vary with client size. The results in Table 9 show that there is a linear pattern (as opposed to the ‘U-shaped’ pattern shown in Carson and Fargher, 2007), where the coefficient is lowest for the smallest clients and highest for the largest clients. Our test variable, BUMICEO, remains positive and significant at 1% level. Estimation 2 of Table 8 shows the results when the variable, BUMICEO, is partitioned by client size (three even-sized categories, small, middle and large). The coefficients for all three variables (BUMICEOsmall, BUMICEOmiddle and BUMICEOlarge) are positive. More interestingly, we find that the premium paid by firms with a bumiputra CEO (BUMICEO) is most significant for the smallest clients (Coefficient = 0.427; significant at

S. Johl et al. / The International Journal of Accounting 47 (2012) 302–332

323

Table 6 Additional analyses—bumiputra audit committee and bumiputra CEO. Variables

Expected sign

Constant LASSET

+

LEV

+

RECTA

+

INVTA

+

CACL

+

ROE

?

YE

+

LSUB

+

LFORSUB

+

LOSS

+

LAGE

?

BIG4

+

OPINION

+

ATENURE

−

POL

+

BODIND

+

BODMEET

+

ACIND

+

ACMEET

+

ACFE

+

BUMIAC100

+

BUMICEO

+

BUMIAC100 ∗ BUMICEO

+

Estimation 1 Coefficient (t-statistic)

Estimation 2 Coefficient (t-statistic)

3.876 5.57*** 0.304 7.70*** 0.006 1.33† 0.936 4.26*** 0.485 2.09** 0.132 1.01 0.021 1.67† 0.063 1.20 0.358 9.87*** 0.104 2.60*** 0.087 1.39† 0.032 1.04 0.096 1.55† − 0.015 − 0.12 0.069 1.30† 0.168 1.80** 0.021 0.08 0.025 2.03** 0.338 1.83** 0.001 0.07 − 0.136 − 1.30† − 0.098 − 1.06 0.220 3.03***

3.888 5.57*** 0.305 7.70*** 0.006 1.39† 0.939 4.28*** 0.459 1.99** 0.135 1.03 0.021 1.79† 0.060 1.16 0.355 9.82*** 0.104 2.62*** 0.083 1.33† 0.033 1.09 0.091 1.48† − 0.016 − 0.12 0.076 1.43† 0.165 1.78** − 0.001 0.00 0.025 1.98** 0.328 1.78** 0.001 0.06 − 0.122 − 1.17 − 0.403 − 2.80*** 0.183 2.38*** 0.176 (continued on next page)

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Table 6 (continued) Variables

Expected sign

Adjusted R2 F-Stat

Estimation 1 Coefficient (t-statistic)

Estimation 2 Coefficient (t-statistic)

0.624 41.83

2.01** 0.626 41.04

†, **, *** = statistically significant at less than the 0.10, 0.05, and 0.01 levels, based on one-tailed (two-tailed) tests for variables where direction of relationship with dependent variable is (is not) significant. BUMIAC100 = 1 if the audit committee is made up entirely of bumiputra members. All other variables are defined in Table 2.

Table 7 Additional analyses—auditor ethnicity. Variables

Expected sign

Constant LASSET

+

LEV

+

RECTA

+

INVTA

+

CACL

+

ROE

−

YE

+

LSUB

+

LFORSUB

+

LOSS

+

LAGE

?

BIG4

+

OPINION

+

ATENURE

−

POL

+

Estimation 1 Coefficient (t-statistic)

Estimation 2 Coefficient (t-statistic)

Estimation 3 Coefficient (t-statistic)

Estimation 4 Coefficient (t-statistic)

Estimation 5 Coefficient (t-statistic)

3.811 5.24*** .307 7.46*** .006 1.33† .959 4.40*** .400 1.73** .145 1.10 .023 1.80** .072 1.36† .361 9.78*** .100 2.41** .099 1.57† .035 1.10 .080 1.35† − .030 − 0.22 .0747 1.38† .165 1.75**

3.893 5.46*** .305 7.60*** .006 1.42† .935 4.28*** .501 2.17** .145 1.11 .022 1.85** .061 1.17 .356 9.74*** .104 2.58*** .091 1.46† .031 0.97 .093 1.51† − 0.024 − 0.19 .071 1.34† .164 1.74**

3.873 5.50*** .306 7.69*** .006 1.42† .932 4.28*** .497 2.15** .146 1.12 .022 1.89** .061 1.18 .355 9.77*** .104 2.58*** .092 1.46† .030 0.96 .093 1.50† − 0.023 − 0.18 .070 1.32† .164 1.75**

3.867 5.50*** .306 7.70*** .006 1.42† .931 4.27*** .497 2.15** .148 1.14 .022 1.89** .062 1.18 .355 9.78*** .104 2.58*** .091 1.46† .030 0.96 .094 1.52† −.024 − 0.18 .070 1.32† .164 1.74**

3.921 5.43*** .304 7.46*** .006 1.35† .941 4.29*** .504 2.16** .142 1.07 .217 1.88** .063 1.20 .356 9.64*** .105 2.60*** .088 1.39† .033 1.03 .074 1.24 − .032 − .024 .072 1.35† .169 1.78**

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325

Table 7 (continued) Variables

Expected sign

Estimation 1 Coefficient (t-statistic)

Estimation 2 Coefficient (t-statistic)

Estimation 3 Coefficient (t-statistic)

Estimation 4 Coefficient (t-statistic)

Estimation 5 Coefficient (t-statistic)

BODIND

+

BODMEET

+

ACIND

+

ACMEET

+

ACFE

+

.093 0.33 .023 1.82** .392 3.10*** .003 0.15 − .152 − 1.46†

BUMIAC

+

BUMICEO

+

.026 0.09 .025 2.00** .315 1.68** − 0.0005 − 0.03 − 0.135 − 1.30† .027 0.27 .173 2.12***

.027 0.10 .025 1.99** .317 1.71** .0004 0.02 − .136 − 1.31† .025 0.26 .177 2.27***

AETHNICITY

+

.019 0.07 .025 1.99** .313 1.69** − 0.0004 0.02 − 0.138 − 1.33† .020 0.20 .176 2.30*** .046 0.55

BCEOBA

+

BACBA

+

.002 0.01 .025 2.00** .324 1.73* .0004 0.02 − .142 − 1.37† .026 0.26 .179 2.17*** .096 0.74 .027 0.13 − .078 − 0.41 0.623 37.54

Adjusted R2 F-Stat

.119 1.46†

.036 0.31

0.616 41.76

0.623 40.75

0.623 40.76

.028 0.28 0.623 40.54

†, **, *** = statistically significant at less than the 0.10, 0.05, and 0.01 levels, based on one-tailed (two-tailed) tests for variables where direction of relationship with dependent variable is (is not) significant. AETHNICITY = 1 if the lead/signing auditor is a bumiputra, and 0 otherwise; BCEOBA = 1 if the firm had both a bumiputra CEO and a bumiputra lead/signing auditor, and 0 otherwise; BACBA = 1 if the firm had a bumiputra-dominant audit committee and a bumiputra lead/signing auditor, and 0 otherwise. All other variables are defined in Table 2.

1% level), followed by the middle clients (Coefficient = 0.102; significant at 10% level), and insignificant for the largest clients (Coefficient = 0.103; insignificant). Overall, the results suggest that the premium paid by BUMICEO firms is most evident in the smallest clients. Finally, we undertook further robustness tests of our results by examining the effects of three potential omitted variables: industry specialist auditor, government linked firms, and US cross-listing. Our findings (untabulated) do not change with the inclusion of these variables in our regression model. Further, of these three variables, only the auditor industry specialist variable was found to be significant. The result is consistent with prior studies (e.g., Carson & Fargher, 2007; Ferguson, Francis, & Stokes, 2006), suggesting that the industry specialist auditors earn audit fee premiums. 6. Conclusions This paper adds to the literature on audit pricing in developing countries by considering the association between audit fees and the ethnicity of the members of audit committees and CEOs within the context of Malaysia. Our results support a significant and positive association between audit fees and firms with bumiputra CEOs, but we find no such

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Table 8 Additional findings—client size effects. Expected sign

Constant LASSET ∗ QUINTILE 1 (smallest)

+

LASSET ∗ QUINTILE 2

+

LASSET ∗ QUINTILE 3

+

LASSET ∗ QUINTILE 4

+

LASSET ∗ QUINTILE 5 (largest)

+

LEV

+

RECTA

+

INVTA

+

CACL

+

ROE

?

YE

+

LSUB

+

LFORSUB

+

LOSS

+

LAGE

?

BIG4

+

OPINION

+

ATENURE

−

POL

+

BODIND

+

BODMEET

+

Estimation 1 Allowing fees to vary with client size (t-statistic)

Estimation 2 Allowing BUMICEO to vary by client size (t-statistic)

6.831 5.47*** 0.142 2.05** 0.149 2.22** 0.152 2.34*** 0.158 2.51*** 0.179 3.00*** 0.008 1.93** 1.087 4.98*** 0.651 2.75*** 0.077 0.60 0.015 1.29* 0.046 0.90 0.341 9.78*** 0.096 2.40*** 0.085 1.36* 0.026 0.84 0.076 1.26 0.037 0.32 0.066 1.26 0.139 1.51* 0.059 0.22 0.024 1.95**

6.368 5.43*** 0.163 2.51*** 0.173 2.78*** 0.175 2.90*** 0.181 3.09*** 0.201 3.60*** 0.009 2.12** 1.104 5.02*** 0.673 2.76*** 0.059 0.46 0.017 1.43* 0.054 1.05 0.339 9.7*** 0.094 2.36*** 0.101 1.63* 0.021 0.7 0 0.086 1.42* 0.071 0.59 0.063 1.21 0.136 1.45* 0.076 0.29 0.025 2.06**

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327

Table 8 (continued) Expected sign

Estimation 1 Allowing fees to vary with client size (t-statistic)

Estimation 2 Allowing BUMICEO to vary by client size (t-statistic)

ACIND

+

ACMEET

+

ACFE

+

BUMIAC

+

0.326 1.84** 0.004 0.25 − .144 − 1.39* − .019 − 0.20

BUMICEO

+

0.360 2.02** 0.002 0.09 − 0.142 − 1.35* − 0.011 − 0.11 0.160 2.21**

BUMICEOsmall

+

BUMICEOmedium

+

BUMICEOlarge

+

Adjusted R2 F-Stat

64.17 37.86

0.427 2.82*** 0.102 1.37* 0.103 0.63 64.50 35.70

†, **, *** = statistically significant at less than the 0.10, 0.05, and 0.01 levels, based on one-tailed (two-tailed) tests for variables where direction of relationship with dependent variable is (is not) significant. All variables are defined in Table 2.

association for bumiputra-dominant audit committees. Further, we also find that the audit premium paid by firms with a bumiputra CEO is higher for smaller client firms. Large firms may be better able to attract bumiputra CEOs with business nuance, which in turn affects the quality of the CEO–auditor interactions and reflected in their lower audit fees when compared with smaller firms. Interestingly, we also find a significant interaction between bumiputra CEOs and bumiputra audit committees, where firms with fully bumiputra-dominant audit committees and managed by a bumiputra CEO are found to pay significantly higher fees than the rest of the sample. These results are consistent with our argument that ethnicity has important implications for audit fees, and that CEO ethnicity, in particular, is likely to affect auditor assessment of the auditee's inherent risk. In practical terms, our study highlights the need for more transparent and accountable internal controls and decision-making processes to be implemented, particularly in firms with bumiputra CEOs. As a critical governance stakeholder group, CEOs will need to be able to voice any concerns to the auditor and faithfully discharge their duties regardless of their ethnicity. If CEOs had additional support through more supportive boards and/or other senior management, businesses would have more transparent and accountable workplaces, which will lower the demand for audit assurance. As bumiputra directors and managers gain greater confidence and business nuance, they will need to find ways to improve their image and reputation as professionals. From a theoretical development perspective, this is the first time a study has adopted differences based on the ethnicity of key governance stakeholders and the associated

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Table 9 OLS regression results. Expected Estimation 1 sign Allowing fees to vary with client size (t-statistic) Constant LASSET ∗ QUINTILE 1 (smallest)

+

LASSET ∗ QUINTILE 2

+

LASSET ∗ QUINTILE 3

+

LASSET ∗ QUINTILE 4

+

LASSET ∗ QUINTILE 5 (largest)

+

LEV

+

RECTA

+

INVTA

+

CACL

+

ROE

?

YE

+

LSUB

+

LFORSUB

+

LOSS

+

LAGE

?

BIG4

+

OPINION

+

ATENURE

−

POL

+

BODIND

+

BODMEET

+

ACIND

+

6.831 5.47*** 0.142 2.05** 0.149 2.22** 0.152 2.34*** 0.158 2.51*** 0.179 3.00*** 0.008 1.93** 1.087 4.98*** 0.651 2.75*** 0.077 0.60 0.015 1.29* 0.046 0.90 0.341 9.78*** 0.096 2.40*** 0.085 1.36* 0.026 0.84 0.076 1.26 0.037 0.32 0.066 1.26 0.139 1.51* 0.059 0.22 0.024 1.95** 0.360

Estimation 2 Allowing BUMICEO to vary by client size (t-statistic) 6.368 5.43*** 0.163 2.51*** 0.173 2.78*** 0.175 2.90*** 0.181 3.09*** 0.201 3.60*** 0.009 2.12** 1.104 5.02*** 0.673 2.76*** 0.059 0.46 0.017 1.43* 0.054 1.05 0.339 9.7*** 0.094 2.36*** 0.101 1.63* 0.021 0.7 0 0.086 1.42* 0.071 0.59 0.063 1.21 0.136 1.45* 0.076 0.29 0.025 2.06** 0.326

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329

Table 9 (continued) Expected Estimation 1 sign Allowing fees to vary with client size (t-statistic) ACMEET

+

ACFE

+

BUMIAC

+

BUMICEO

+

BUMICEO and SMALL SIZE QUINTILE 1

+

2.02** 0.002 0.09 − 0.142 − 1.35* − 0.011 − 0.11 0.160 2.21**

BUMICEO and MEDIUM SIZE QUINTILE 2–4 + BUMICEO and LARGE SIZE QUINTILE 5 Adjusted R2 F-Stat

+ 64.17 37.86

Estimation 2 Allowing BUMICEO to vary by client size (t-statistic) 1.84** 0.004 0.25 − .144 − 1.39* − .019 − 0.20

0.427 2.82*** 0.102 1.37* 0.103 0.63 64.50 35.70

reputational risks to explain audit pricing. The positive association found between bumiputra CEOs and audit fees provides preliminary empirical support for the link between ethnic culture-related theories and audit pricing (Hofstede, 1983; Osman-Gani & Tan, 2002). However, we need further systematic study into how auditors' perceptions and interactions with bumiputra CEOs versus non-bumiputra CEOs differ and thus affect their assessment of the audit client risk. For instance, rather than assuming that the perceived lack of experience of bumiputra CEOs contributes to higher audit risk assessment, we might discover that the communication style between such CEOs and auditors affects such an assessment. Osman-Gani and Tan (2002), for example, argue that bumiputra and non-bumiputra managers tend to display slightly different communication styles. This paper has a number of limitations. First, we did not systematically assess and compare the differences in the perceptions of the business management reputations of bumiputra directors and managers as opposed to their non-bumiputra counterparts. This is an area ripe for further research, where qualitative approaches can be undertaken to gain a more in-depth understanding of the role ethnicity plays in auditor–client interactions and, consequently, its implications for audit pricing. Second, this paper adopts a supply-side perspective for audit fees and does not test the demand-side for audit fees. Bedard and Johnstone (2004) undertake a study using a proprietary database to assess how various corporate governance factors affect auditors' billing behaviour. Third, there may be exogenous factors at the entity level that correlate with audit committee characteristics, CEO appointments, and audit fees. We have controlled for a range of common determinants of audit fees, as used in prior studies, for example, firm size, risk, and other related corporate governance variables such as board size and independence. We have also tested for other omitted variables such as auditor industry specialisation, government-linked companies and cross-listings. We find that our results still hold. Nevertheless, omitted variables remain potential limitations. Finally, the data we used

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