Description
The purpose of this paper is to extend the audit pricing literature by examining whether
institutional investors and political connection are associated with higher audit fees.
Accounting Research Journal
Institutional investors, political connection and audit quality in Malaysia
Effiezal Aswadi Abdul Wahab Mazlina Mat Zain Kieran J ames Hasnah Haron
Article information:
To cite this document:
Effiezal Aswadi Abdul Wahab Mazlina Mat Zain Kieran J ames Hasnah Haron, (2009),"Institutional
investors, political connection and audit quality in Malaysia", Accounting Research J ournal, Vol. 22 Iss 2 pp.
167 - 195
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Effiezal Aswadi Abdul Wahab, Mazlina Mat Zain, Kieran J ames, (2011),"Political connections, corporate
governance and audit fees in Malaysia", Managerial Auditing J ournal, Vol. 26 Iss 5 pp. 393-418 http://
dx.doi.org/10.1108/02686901111129562
Rani Hoitash, Ariel Markelevich, Charles A. Barragato, (2007),"Auditor fees and audit quality", Managerial
Auditing J ournal, Vol. 22 Iss 8 pp. 761-786 http://dx.doi.org/10.1108/02686900710819634
Puan Yatim, Pamela Kent, Peter Clarkson, (2006),"Governance structures, ethnicity, and audit
fees of Malaysian listed firms", Managerial Auditing J ournal, Vol. 21 Iss 7 pp. 757-782 http://
dx.doi.org/10.1108/02686900610680530
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Institutional investors, political
connection and audit quality
in Malaysia
Ef?ezal Aswadi Abdul Wahab
Graduate School of Business, Universiti Sains Malaysia, Penang, Malaysia and
Department of Accounting, School of Management,
Universiti Sains Malaysia, Penang, Malaysia
Mazlina Mat Zain
Faculty of Management, Multimedia University, Cyberjaya, Malaysia
Kieran James
School of Accounting, Economics and Finance,
University of Southern Queensland, Toowoomba, Australia, and
Hasnah Haron
Graduate School of Business, Universiti Sains Malaysia, Penang, Malaysia and
Department of Accounting, School of Management,
Universiti Sains Malaysia, Penang, Malaysia
Abstract
Purpose – The purpose of this paper is to extend the audit pricing literature by examining whether
institutional investors and political connection are associated with higher audit fees.
Design/methodology/approach – Both descriptive and multivariate analyses are employed to
address the research objectives. In addition, the authors use panel data to control for both
heterocedasticity and contemporaneous correlations in each cross-section.
Findings – Based on a panel analysis of 390 Malaysian ?rms from 1999 to 2003, a positive
relationship between institutional ownership and audit fees is found, although the economic impact is
minimal. Further, the authors ?nd that audit fees are higher for politically connected ?rms.
Research limitations/implications – A thorough examination on the role of political connection is
much warranted to provide a better understanding on such connection in?uences the audit market.
Originality/value – This paper provides an alternative view on the role of political connection, and
on how they in?uence the audit market.
Keywords Investors, Malaysia, Auditor’s fees, Political systems, Organizations
Paper type Research paper
1. Introduction
In the past, institutional investors were seen as a mechanism to facilitate savings based
on consistent earnings and stable returns (Gomez and Jomo, 1999). We then observed
the growth of savings-based institutional investors in the developed countries (e.g.
California Public Employees’ Retirement System in the USA) and in developing
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1030-9616.htm
The authors are thankful for capable research assistance from Wan Adibah Wan Adnan. The
?rst author would like to thank Universiti Sains Malaysia for ?nancial assistance.
Audit quality
in Malaysia
167
Accounting Research Journal
Vol. 22 No. 2, 2009
pp. 167-195
qEmerald Group Publishing Limited
1030-9616
DOI 10.1108/10309610910987501
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countries (e.g. Employees Provident Fund (EPF) in Malaysia and Central Provident
Fund in Singapore). As institutional investors’ pools of funds grow, so does their
responsibility to the contributors and to the public. Moreover, institutional investors
such as pension funds began to abandon their traditional passive shareholder role and
became more active participants in the governance of their corporate holdings (Monks
and Minow, 1995). Thus, institutional investors play an important role in determining
?rms’ corporate governance.
Their increasing equity share ownership (Cornett et al., 2007) and a ?duciary
obligation (Hawley and William, 1997) to contributors and to the public also makes
them an additional monitor of ?rms. Evidence suggests that institutional investors are
successful in this role. Karpoff (2001) documents numerous event-type studies which
suggest that institutional investors are successful in shareholder activism, and work
and prompt ?rms to act in accordance with investors’ needs. Further, cross-sectional
studies have shown via ?rm performance (Brickley et al., 1988; Cornett et al., 2007),
corporate governance (Abdul Wahab et al., 2007) earnings management (Koh, 2007;
Chung et al., 2002) and director remuneration (Hartzell and Starks, 2002; Almazan et al.,
2005) that institutional investors are effective monitor of the ?rm.
The Asian Financial Crisis of 1997-1998 also initiated an increased awareness
regarding the role of institutional investors, especially in relation to reducing agency
costs[1]. For instance, the Finance Committee on Corporate Governance, a corporate
governance committee set up by the Malaysian government, suggests that a minority
shareholders’ watchdog group led by EPF should play a proactive role in institutional
monitoring of ?rms. Further, Abdul Samad (2004) argues that ownership structure is
one of the most important factors in determining the nature of agency costs in a
governance system. In particular, Asian ?rms’ agency problems are not primarily
between managers and shareholders. Instead they are primarily between minority and
majority shareholders (Claessens and Fan, 2002). The dominant agency problemoutside
the western world is between controlling shareholders and minority shareholders.
We analyse the extent of institutional monitoring in Malaysia and its relationship
with external auditors, since external auditors are likely to play a governance role (Fan
and Wong, 2005). Thus, we aim to examine the relationship between institutional
investors and audit quality. We use audit fee as a proxy of audit quality since higher
audit fees are associated with higher audit quality (Goodwin-Stewart and Kent, 2006;
Francis, 2004). We argue that in the presence of highly concentrated ownership and
family control ?rms (Claessens et al., 2000; Abdul Samad, 2004), which creates an agency
con?ict between majority and minority shareholders, institutional investors demand
better audit effort from external auditors to monitor management and majority
shareholders. Furthermore, institutional investors are expected to monitor since they
have the resources (Shleifer and Vishny, 1997), size (Jennings, 2005) and ?duciary duties
(Hawley and William, 1997) to in?uence the ?rms. We then extend our investigation by
examining institutional investors’ heterogeneity, speci?cally on the basis of whether the
institutional investors have a business relationship with the ?rms. We argue that
institutional investors that hold no business relationship impose less pressure upon the
?rms’ management and are more likely to agree with management’s policies. Relatively,
these investors are more active in monitoring the ?rms in comparison with those
investors that hold a business relationship[2].
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Furthermore, we also include a variable that is important in the Malaysian context.
Since, the Malaysian capital market operates within the context of a racially diverse
society and past evidences suggest that Malaysian has politically connected or
favoured ?rms (Gomez and Jomo, 1999; Gul, 2006; Johnson and Mitton, 2003), we
include one context-speci?c variable namely political connection. Similar to prior
studies, we predict that political connection is important in explaining the variation in
audit fees as political-connected ?rms are generally perceived to entail poor corporate
governance and greater agency problems. Such perceptions in turn are expected to
increase monitoring costs leading to higher audit fees.
Our results, based on 390 non-?nancial ?rms listed on Bursa Malaysia during the
period 1999-2003 indicate a positive relationship between institutional ownership and
audit fees. This appears in line with the notion that institutional investors in Malaysia
play a monitoring role by demanding greater audit effort from the auditors resulting in
increased audit fees. Furthermore, we ?nd investors’ heterogeneity in?uences the
relationship between institutional ownership and audit fees. In particular, our results
document a positive relationship between institutional investors that do not have the
relationship with the ?rm and audit fees. Our analysis of individual institutional
investors indicates that audit fees are positively and signi?cantly related to EPF and
Permodalan Malaysia Berhad, arguably the two most dominant institutional investors
in Malaysia. Interestingly, we also ?nd evidence to suggest that politically connected
?rms pay audit fee premiums due to the greater perceived risk inherent in politically
connected ?rms, leading auditors to exert greater audit effort for these ?rms.
We contribute to the growing body of published literature in this area in a number
of ways. First, most prior studies examining the link between the roles of institutional
investors and audit fees particularly their monitoring roles in mitigating agency costs
tend to study countries with well-developed capital markets such as the USA and
Australia (O’Sullivan, 2000; Kane and Velury, 2004). Our study is conducted in
Malaysia, where the capital market is still at a developing stage and the rules and
regulation with respect to corporate governance are still in their infancy. Further, our
study explores the relationship between institutional investors’ heterogeneity
speci?cally on the basis of their relationship with the ?rms and audit fees. This
allows us to evaluate how the relationship between institutional investors and ?rms
undermines the potential monitoring effectiveness of institutional investors.
Second, although there are similarities in terms of accounting practices and the
regulatory environments in Malaysia with the UK, the USA and Australia (Gul, 2006).
The corporate environment and institutional division in Malaysia are unique because of
the existence of politically-favoured corporations, ethnicity, language and religion
(Haniffa and Cooke, 2002; Yatimet al., 2006; Gul, 2006). Particularly, this is the case of the
Malaysian government’s intervention in the corporate sectors to initiate the
participation of Bumiputera in the Malaysian economy starting from the introduction
of the government’s neweconomic policy (NEP) in 1969. Given this unique environment,
it is worthwhile to further extend the audit pricing literature by examining the
political-related factors and the extent of audit fees paid to the auditors.
To date, a review of literature indicates that several studies have examined the
relationship between political connections (Johnson and Mitton, 2003; Gul, 2006);
ethnicity (Eichenseher, 1995; Yatim et al., 2006). Overall, these studies argue that
politically connected ?rms and Bumiputera-controlled ?rms are favoured and generally
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perceived to be riskier, and have greater agency problems leading to increased
monitoring costs. Johnson and Mitton (2003) utilise two-years data of Malaysian listed
companies (1997 and 1998), Gul (2006) covers three years (1996-1998), where as Yatim
et al. (2006) onlycover one year (2003). Incontrast, the data of our study covers a periodof
?ve years (1999-2003) and our study utilises panel data which allows us to control
heterocedasticity and contemporaneous correlations in each cross-section. Since, the
data for this study covers the period pre- and post-governance reforms in Malaysia, our
study provides an alternative or extended view on the role of auditors, subsequent to
corporate governance reforms in 2001. In addition, we explore an interaction between
political-connected ?rms and audit fees when the institutional investors are present and
?nd evidence to suggest that institutional investors are an effective monitor especially in
relation to politically connected ?rms.
In the next section, we provide background on the Malaysian institutional investors
followed by hypotheses development in Section 3. Research methods and data description
are discussed in Section 4 and Section 5 presents the results. Section 6 concludes.
2. Institutional background
2.1 Institutional investors in Malaysia
Institutional shareholdings in Malaysia are high compared to most other nations in
South-East Asian. As at 2003, the total institutional shareholding in Malaysia was
approximately 13 per cent of the total market capitalisation of Bursa Malaysia. This is
a primary consequence of the 1970 NEP which establishes the Malaysian institutional
investors. Further, the NEP aims to reduce equity ownership imbalance between the
various ethnic groups through increasing Bumiputeras equity ownership in the capital
market (Gomez and Jomo, 1999; Tan, 2004)[3],[4]. To date, there are a few major
institutional shareholders in Malaysia namely EPFs; Permodalan Nasional Berhad
(PNB), Lembaga Tabung Angkatan Tentera (LTAT), Lembaga Tabung Haji (LTH)
and Pertubuhan Keselamatan Sosial.
EPFs is a pension fund for all employees and is the largest institutional investor in
Malaysia. It has total assets in excess of US$50 billion, which is more than half of
Malaysia’s gross domestic product (Thillainathan, 2000). An interesting feature of
EPFs is the presence of strong government control. For example, Malaysian law
requires EPFs to invest 70 per cent of its funds in Malaysian government securities,
while its investment in the domestic stock market cannot exceed 25 per cent. EPFs is
also prohibited from making overseas investments (Thillainathan, 2000).
The next major institutional investor is the ?rst unit trust established in Malaysia.
Established in 1972, Permodalan Malaysia Berhad is Malaysia’s ?rst unit trust
(ownership-in-trust) set up to encourage savings by Bumiputeras. It started with a
single unit trust called Amanah Saham Nasional but now has multiple unit trusts that
cater for all groups of people such as the youth (e.g. Amanah Saham Didik) and the
non-Bumiputeras (e.g. Amanah Saham Malaysia). These unit trusts act as savings
schemes that pay competitive dividends (average of nearly 8 per cent over the past ten
years) (Gomez and Jomo, 1999). As at the end of 2003, PNB managed over Ringgit
Malaysia (RM) 15 billion worth of public and private equity in Malaysia, representing
about two-thirds of its total investment (www.pnb.com.my).
LTAT is the next largest institutional investor which was established in August
1972 by an act of Parliament. LTAT serves as a superannuation fund for the Armed
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Forces of Malaysia[5]. Similar to EPF, its objectives are to provide retirement and other
bene?ts to members of the Armed Forces (compulsory contributors) and to enable
of?cers and mobilised members of the volunteer forces in the services to participate in
a savings scheme.
Another major institutional investors is LTH, which was formed in 1962, aiming to
encourage Malaysian Moslems to save for journeys to Mecca for pilgrimage. Its role
has evolved from a saving depository to providing Malaysian Moslems some returns
on their investments. Like other major institutional investors (EPF, LTAT and
Permodalan Malaysia Berhad), LTH’s investment advisory board includes Islamic
scholars who must make sure that all investments are in accordance with syariah[6].
The ?nal key institutional investor is Pertubuhan Keselamatan Sosial established in
January 1971 by another act of Parliament, through the Social Security Act 1969.
Pertubuhan Keselamatan Sosial serves as an insurance scheme for all Malaysians
working in either the public or the private sector. Pertubuhan Keselamatan Sosial’s
main objective is to ensure and guarantee the timely and adequate provision of bene?ts
in a socially just manner and to promote occupational health and safety. Similar to the
other institutional investors mentioned above, Pertubuhan Keselamatan Sosial has an
investment advisory board consisting of various representatives from the government,
employers and employees.
As the domestic ?nancial systemgrew around commercial banks, other institutional
investors also began to play a part in the domestic ?nancial system. Amongst these are
foreign institutional investors such as California Public Employees’ Retirement System;
Teachers Insurance and Annuity Association – College Retirement Equities Fund; and
United Nation Pension Funds and State of Ohio Retirement Scheme. Collectively, foreign
institutional investors account for about 1 per cent of total institutional ownership in
Malaysia.
2.2 Political connection in Malaysia
Another unique feature in Malaysia is the close links of many large corporations or
conglomerates with the government[7]. Given the close connections to the government,
these politically-linked companies have exclusive business relationships with
state-owned enterprises and have preferential access to major government contracts
(Gomez and Jomo, 1999; EAU, 2002b). For instance, these ?rms are argued to use their
political in?uence in order to have easy access to loans which are usually “soft”, and
which are often obtainable from government-backed banks or state development
bodies and pension funds (EAU, 2002a, b; Yoshihara, 1988).
Many large corporations with substantial loans provided by the state are usually
owned by the state and non-performing as a result of the 1997/1998 ?nancial crisis. For
example, Malaysian resources now owe loans of RM 600-RM 700 million mainly to the
EPF[8]. Likewise, the results of prior studies indicate that political-connected ?rms in
Malaysia are favoured by the government. For instance, Johnson and Mitton (2003)
?nd that politically connected ?rms had a larger drop in share price in comparison to
non-politically connected ?rms. Similarly, Gul (2006) ?nds that politically connected
?rms are being charged higher audit fees by audit ?rms during the onset of the
1997/1998 ?nancial crisis, but declined when the government introduced capital
controls to assist these ?rms.
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2.3 Auditing in Malaysia
Auditors in Malaysia are bound by standard of auditing practices and requirements
similar to other countries[9]. The Companies Act 1965 stresses the need for the auditor
to be independent and gives auditors broad powers to inspect records and to obtain
information for audit, as well as the right to attend and address general meetings of
?rms (Ali et al., 2006). In their documentary analysis, Ali et al. (2006) argue that
auditing practice in Malaysia merely aims to ful?l legal requirements and provide an
image of a modern economy to attract investments from overseas rather than to
address the unique needs of a multi-cultural society[10]. As at the date of this study, the
Big n auditors control nearly 70 per cent of the audit market in Malaysia.
3. Hypotheses development
Two hypotheses are developed in this section: H1 relates to the link between audit fees
and institutional ownership whereas H2 relates to audit fees association with
political-connected ?rms. These hypotheses present arguments on the demand side
(H1) and the supply side (H2) of audit services. From the demand side, it can be argued
that some clients, i.e. institutional investors, may demand a greater level of monitoring
to minimise agency problems and hence results in higher audit fees. From the supply
side, the inherent poor ?rm performance of politically connected ?rms is due to
inef?ciencies and lack of corporate governance. These type of ?rms involve greater
risk corresponding with an increase of audit effort. As a consequence, higher audit fees
will be charged by the auditors (Gul, 2006).
We argue from both the demand and supply sides of audit services because in
Malaysia, the presence of institutional investors is also prevalent in politically connected
?rms since major investors are controlled either directly or indirectly by the government
and thus serve political needs (Norhashim and Abdul Aziz, 2005). This creates an
interesting view on how such relationship could in?uence the pricing of audit services.
We argue that regardless of the risk borne by politically connected ?rms, institutional
investors could still play a monitoring role, and thus demand better audit services.
Further, in order to remove doubts about motives for their shareholdings in politically
connected ?rms and because these ?rms may have a higher probability of ?nancial
misstatement, institutional investors have to demand, at the least the same quality level
of audit services from auditors (if not at a higher level). In other words, it may be less
acceptable to their key stakeholders for institutional shareholders to operate passively
especially when they hold shares in politically connected ?rms.
3.1 Institutional ownership and audit fees
The relationship between institutional investors and audit fees arises out of the agency
problem, which exists between managers and shareholders, or between shareholders
themselves, i.e. majority and minority shareholders. We observe from Claessens et al.
(2000) that East Asian ?rms are highly concentrated and often controlled by a
conglomerate or a particular family. Therefore, the presence of institutional investors,
playing a monitoring role overcomes, or at least minimises the agency problem within
Malaysian ?rms. Knechel and Willekens (2006) and Hay et al. (2008) argue that
variation of audit fees arises from various factors including the cost of audit efforts, the
auditor’s legal liability (Simunic, 1980) and demand from various stakeholders. For
instance, a concentrated shareholding structure in a ?rm controlled by a few
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individuals could yield a demand for better audit effort from minority shareholders.
This scenario may be prevalent in the Malaysian capital market, as observed by
Claessens et al. (2000).
Furthermore, institutional investors are expected to monitor and demand better
audit of the ?rms since they have the resources (Shleifer and Vishny, 1997), expertise in
analysing ?nancial statements (Hand, 1990), ability to apprehend media-pressure (Wu,
2004) and size (Jennings, 2005). The institutional investors, on average, are better
informed than individual investors because of their large-scale development and
analysis of timely and valuable ?rm-speci?c information (Wahal and McConnell, 2000).
Importantly, they have ?duciary duties to serve their contributors and minority
shareholders of their ?rms (Hawley and William, 1997). This is relatively important
since much of the agency problem in Asian ?rms is between majority and minority
shareholders (Claessens and Fan, 2002), thus making institutional investors an ideal
monitor or representative of minority shareholders.
Prior empirical studies support the notion that large institutional shareholdings have
an impact on audit fees. For instance, O’Sullivan (2000) and Kane and Velury (2004)
document a positive relationship between large institutional shareholdings and audit
fees. On the basis of earnings quality, Kane and Velury (2004) argue that a positive
relationship exists between audit and earnings qualities. Assuming that institutional
investors are in?uential and demand high-quality earnings information, the level of
institutional ownership should be positively related with the provision of audit quality
(Kane and Velury, 2004). Interestingly, Velury et al. (2005) also ?nd that ?rms having
greater levels of institutional ownership tend to employ industry specialist audit ?rms.
This indicates that these ?rms emphasise higher quality audits due to the demand from
their institutional investors which act as monitoring mechanisms. This in turn is
re?ected by the level of audit fees. Mitra et al. (2007) ?nd a positive and signi?cant
relationship between diffused institutional ownership (less than 5 per cent) but a
negative relationship between institutional investors which hold more than 5 per cent
and audit fees. Thus, the above arguments suggest the following hypothesis:
H1. Higher institutional ownership is associated with higher audit fees.
3.2 Political-connected ?rms and audit fees
Unlike other countries, Malaysia has a unique corporate environment which offers clear
identi?able segments of ethnic line. It is also generally accepted that Malaysia has
favoured ?rms (known as politically connected ?rms) (Gomez and Jomo, 1999; Gul, 2006)
as a result of the government’s intervention following the introduction of NEP with the
intention to increase the Malay equity in the country. Johnson and Mitton (2003) provide
evidence that it was politically connected ?rms that suffered the most during the early
stages of the Asian ?nancial crisis. Their share price dropped comparatively more than
their counterparts because it is assumed that the government would be unable to extend
privileges to these ?rms. Likewise, a recent study by Gul (2006) provides empirical
evidence to support the proposition that auditors perceive greater risk inherent in
politically connected ?rms leading to greater audit effort which in turn leads higher fees.
This is because these ?rms have a higher probability of their business failing, and are
more likely to misstate their ?nancial position in their ?nancial statements to avoid
covenant violations. Further, Gul (2006) documents evidence of “crony-capitalism” in
Malaysia by demonstrating that there was a comparatively greater increase in audit fees
Audit quality
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for politically connected ?rms following the Asian Financial Crisis in 1997/1998. The
audit fees for these ?rms declined following the government’s introduction of capital
controls as a way of helping their preferred ?rms. Based on the arguments presented
above, we posit the following hypothesis:
H2. Politically connected ?rms are associated with higher audit fees.
4. Research methods and data description
The panel data set consists of 390 non-?nancial ?rms for ?ve years from 1999 to 2003.
Financial ?rms are eliminated, since prior research shows that determinants of audit
fees are unique for such ?rms (Simunic, 1980). The data used for this study is primarily
collected from Compustat Global and ?rms’ annual reports. We use two alternative
sources, the Stock Performance Guide handbook and DataStream database for missing
data. This study uses period seemingly unrelated regressions to handle both
heterocedasticity and contemporaneous correlations in each cross-section.
We posit the following audit fees model:
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INTERCEPT
it
þa
1
INSTOWN
it
þa
2
POLCON
þa
3
INSTOWN
*
POLCON þa
4
LNASSETS
it
þa
5
CURRENT
it
þa
6
LIQUID
it
þa
7
LNSUBS
it
þa
8
LNFOREIGN
it
þa
9
YE
it
þa
10
DEBT
it
þa
11
ROA
it
þa
12
LOSS
it
þa
13
MANOWN
it
þa
14
BIG_N
it
þa
15
SWITCH þa
16
INDUSTRY
it
þe
it
The experimental variables are in bold, where:
Dependent variable
LAF Natural logarithm of audit fees.
Panel A: experimental variables
INSTOWN – Top ?ve institutional shareholdings in each ?rm.
POLCON – An indicator variable, 1 for politically connected ?rms, 0 otherwise.
Panel B: control variables
LNASSETS – Natural logarithm of total assets.
CURRENT – Current assets to total assets.
LIQIUD – Current assets to current liabilities.
LNSUBS – Natural logarithm of number of subsidiaries.
LNFOREIGN – Natural logarithm of number of foreign subsidiaries.
YE – An indicator variable, 1 for ?scal year ending 31 December, 0
otherwise.
DEBT – Total debt to total equity.
ROA – Net pro?t before tax divided by total assets.
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LOSS – An indicator variable, 1 for loss in the last year, 0 otherwise.
MANOWN – Managerial ownership.
BIG_N – An indicator variable, 1 for Big n audit ?rm, 0 otherwise.
SWITCH – An indicator variable, 1 for ?rms switching auditor, 0 otherwise.
INDUSTRY – Industry dummies that take a value of 1 for ?rms belonging to
(construction), (consumer), high technology and 0 for otherwise.
4.1 Dependent variable
The dependent variable is the audit fee which is measured by the RM value of the audit
fee paid by the ?rm to its auditor. Consistent with previous studies (Francis, 1984;
Francis and Simon, 1987) and following tests of normality, logarithmic transformation
is applied to the audit fee (LAF)[11]. The audit fee data are obtained from Compustat
Global and annual reports.
4.2 Experimental variables
The main experimental variable for this study is institutional ownership (INSTOWN)
which consists of the top ?ve institutional investors’ shareholding in each ?rm. The
institutional ownership data are extracted from annual reports which were obtained
from Bursa Malaysia’s web site and Mergent Online database. We argue that top ?ve
institutional investors represent the level of institutional monitoring in a ?rm as stated
by Hartzell and Starks (2002)[12]. The second experimental variable is political
connection (POLCON) which takes a value of one if the ?rm is considered as politically
connected or zero otherwise. The political connection (POLCON) list is presented in the
Appendix and is derived from Johnson and Mitton (2003), Mohamad et al. (2006) and
Khazanah Nasional Berhad web site[13].
4.3 Control variables
Audit fees model employed in prior research have used a variety of variables to control
for cross-sectional differences associated with auditee size, complexity and the risk of
the client ?rm (Simunic, 1980; Craswell, 1992; Gul and Tsui, 1997). These empirical
models have demonstrated good explanatory power and have been robust across
different samples and different periods of time.
We adopt several standard control variables used in past studies including size,
complexity, risk and audit quality in this paper. The effects of size are controlled for
with the natural log transformation of total assets (LNASSETS). We posit a positive
relationship between ?rm size and audit fees since larger ?rms are more complex
which requires more audit effort, resulting in higher audit fees (Simunic, 1980; Francis,
1984). Equally important, we take into account of the natural log transformation of
total subsidiaries (LNSUBS) and foreign subsidiaries (LNFOREIGN) to control for
audit complexity (Simunic, 1980; Hackenbrack and Knechel, 1997) which implies that
more subsidiaries result in a greater amount of work in consolidation and eliminating
intra-group transactions (Chan et al., 1993; Pong and Whittington, 1994) and subject to
numerous statutory and professional requirements of disclosure (Chan et al., 1993).
We include the ratio of current assets to total assets (CURRENT) to control for
inherent risk. We argue a positive relationship between CURRENT and audit fees
Audit quality
in Malaysia
175
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because certain parts of the audit may have a higher risk of error and require specialised
audit procedures (Simunic, 1980; Francis and Simon, 1987). Liquidity is controlled for by
including the working capital ratio represented by the ratio of current assets to current
liabilities (LIQUID). Furthermore, we include the debt ratio which is total debt to total
equity (DEBT) to control for ?rms’ leverage (Gist, 1992; Craswell and Francis, 1999). We
also include direct managerial ownership (MANOWN) to control for other ownership
structure and we predict a negative relationship between MANOWN and LAF.
The ?scal year-end is controlled for with a dummy variable set as one for those ?rms
with a 31 December ?scal year-end and zero otherwise. Most ?rms in the sample have a
December year-end. Return on assets (ROA) is used as a proxy for pro?tability and we
predict a negative relationship between ROA and audit fees. In addition, we include a
dummy for ?rms which recorded a loss (LOSS), demonstrating ?nancial distress (Pong
and Whittington, 1994) in the previous year in which a positive relationship is predicted.
A dummy variable for Big n auditing ?rms (BIG_N) is also incorporated to control for
differences in audit quality as it is expected that ?rms associated with large auditing
?rms purchase a higher level of audit quality (DeAngelo, 1981; Carcello et al., 2002)[14].
Further, we give the value of one for ?rms that switch (SWITCH) their auditor during
the sample period and we predict a non-directional relationship between SWITCH and
LAF. Fixed effects (PERIOD) is included to control for any unobserved events that
occurred during the sample period that might in?uence the variation of audit fees.
Finally, industry dummies (INDUSTRY) that take a value of one for ?rms belonging to
the construction, consumer, high technology and other sectors and zero otherwise are
included to control for variations in audit fees across industries, since it is conventional
wisdom that these industries have higher complexities and are more dif?cult to audit
(Simunic, 1980; Turpen, 1990; Pearson and Trompeter, 1994) (Table I)[15].
4.4 Descriptive statistics
Table II presents the descriptive statistics for sample ?rms used in this study. The
average (median) audit fees (AF) is RM 282,000 (RM 114,000), and ranging from RM
500 to RM 9.4 million. Panel A of Table II documents descriptive analysis for
experimental variables. INSTOWNaverages 12.069 per cent with a range between 0 and
90.553 per cent. INSENSITIVE, SENSITIVE and INDETERMINATE institutional
investors hold an average of 7.187, 1.029 and 3.852 per cent of institutional
shareholdings. In relation to individual institutional investors, PNB tops the list with an
average of 3.852 per cent while EPF is a second with 2.477 per cent. LTAT, LTH and
Pertubuhan Keselamatan Social (SOCSO) on average hold 0.922, 0.955 and 0.047 per
cent, respectively, from the total institutional shareholdings. Their cumulative
shareholdings constitute nearly 68 per cent of total institutional investors’
shareholdings. Finally, 21.1 per cent of the sample ?rms are politically connected.
Clients attributes’ descriptive are presented in Panel B of Table II. Sample ?rms’
size (ASSETS) averages RM 1.886 billion with a range between RM 1.259 million and
RM 64.41 billion. On average, sample ?rms have 29.321 subsidiaries with 6.604 of them
being domiciled outside Malaysia. Sample ?rms record a mean (median) of 0.367 (0.351)
and 3.584 (1.589) for CURRENT and LIQUID, respectively. Firm are highly levered
(DEBT) at on average of 1.425 and 47.1 per cent of ?rms end their ?scal year at
31 December (year-end). Managerial ownership (MANOWN) has on average of
7.681 per cent and ranges from 0 to 79.773 per cent. ROA averages 5.473 per cent and
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18.3 per cent of sample ?rms’ experience loss (LOSS) during the previous year. Further,
almost 70 per cent of ?rms are being audited by a Big n audit ?rms and 12.5 per cent of
the sample ?rms switched their auditors during this period.
Table III presents the correlations between the test variables. Pearson correlation
records positive and signi?cant correlations at 1 per cent level between INSTOWN and
LAF at 0.236 and 0.210, respectively[16]. The table also documents signi?cant and
positive correlation between LAF and ASSETS, LNSUBS, LNFOREIGN, MANOWN
and POLCON[17].
No. Variables Sign De?nition Sources
1 LAF Natural logarithm of audit fees Compustat Global and Annual
Reports
Panel A: experimental variables
2 INSTOWN þ Top ?ve institutional shareholdings
in each ?rm
Annual Reports
3 POLCON þ An indicator variable, 1 for
politically connected ?rms, 0
otherwise
Johnson and Mitton (2003),
Mohamad et al. (2006) and Khazanah
Berhad web site (www.khazanah.
gov.my)
Panel B: client attributes
LNASSETS þ Natural logarithm of total assets Compustat Global, DataStream and
Stock Performance Guide
CURRENT þ Current assets to total assets Compustat Global, DataStream and
Stock Performance Guide
5 LIQUID þ Current assets to current liabilities Compustat Global, DataStream and
Stock Performance Guide
7 LNSUBS þ Natural logarithm of number of
subsidiaries
Mergent Online and Annual Reports
8 LNFOREIGN þ Natural logarithm of number of
foreign subsidiaries
Mergent Online and Annual Reports
9 YE 2 An indicator variable, 1 for ?scal
year ending 31 December, 0
otherwise
Annual Reports
10 DEBT þ Total debt to total equity Compustat Global, DataStream and
Stock Performance Guide
11 ROA 2 Net pro?t before tax over total assets Compustat Global
12 LOSS þ An indicator variable, 1 for loss in
the last year
Compustat Global
13 MANOWN 2 Managerial ownership Annual Reports
14 BIG_N þ An indicator variable, 1 for Big n
audit ?rms, 0 otherwise
Compustat Global and Annual
Reports
16 SWITCH ? An indicator variable, 1 for ?rms
switching auditor, 0 otherwise
Compustat Global
18 ? Industry dummies that take a value
of 1 for ?rms belonging to the
construction (CONSTRUCTION),
consumer (CONSUMER), high
technology (TECHNOLOGY) and
other (OTHER) sectors and 0
otherwise
Bursa Malaysia’s web site
Table I.
De?nition and expected
direction of variables
Audit quality
in Malaysia
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Mean Median Maximum Minimum SD
Dependent variable
AUDIT FEES (‘000) 282.2 114.0 9400 0.500 656.9
LAF 11.783 11.653 16.056 8.006 1.118
Panel A: experimental variables
INSTOWN 12.069 6.035 90.553 0.000 16.654
INSENSITIVE 7.187 2.272 78.566 0.000 13.414
SENSITIVE 1.029 0.000 23.660 0.000 2.163
INDETERMINATE 3.852 0.000 75.269 0.000 9.468
EPF 2.477 0.357 28.960 0.000 3.927
PNB 3.852 0.000 75.269 0.000 9.468
LTAT 0.922 0.000 74.545 0.000 5.816
LTH 0.955 0.000 25.750 0.000 2.985
SOCSO 0.047 0.000 2.944 0.000 0.221
POLCON 0.211 0.000 1.000 0.000 0.408
Panel B: client attributes
ASSETS (‘000) 1,886,000 587,800 64,410,000 1,259 5,192,000
LNASSETS 20.341 20.197 24.888 14.046 1.311
CURRENT 0.367 0.351 9.068 0.000 0.329
LIQUID 3.584 1.589 195.090 0.000 11.626
SUBS 29.321 15.000 408.000 0.000 43.837
LNSUBS 1.435 2.708 6.011 211.513 4.459
FOREIGN 6.604 1.000 224.000 0.000 17.536
LNFOREIGN 23.329 0.000 5.412 211.513 6.387
YE 0.471 0.000 1.000 0.000 0.499
DEBT 1.425 0.400 37.919 0.000 3.674
ROA 5.473 5.219 140.162 288.504 11.711
LOSS 0.183 0.000 1.000 0.000 0.387
MANOWN 7.681 0.559 79.773 0.000 14.410
BIG_N 0.689 1.000 1.000 0.000 0.463
SWITCH 0.125 0.000 1.000 0.000 0.331
Notes:
@
Observations having a zero for LNSUBS or for LNFOREIGN are re-coded to a small positive
(0.0001) to enable a logarithmic transformation; AF is audit fees while LAF is natural logarithm of
audit fees; INSTOWN is the percentage shareholdings by top ?ve institutional investors;
INSENSITIVE, SENSITIVE and INDETERMINATE are percentage shareholdings held by
pressure insensitive, sensitive and indeterminate investors, respectively; EPF, PNB, LTAT, LTH
and SOCSO are percentage shareholdings held by EPF, PNB, LTAT, LTH and Pertubuhan
Keselamatan Sosial investors, respectively; POLCON takes the value of 1 for politically connected
?rms and 0 otherwise; ASSETS, is total assets while LNASSETS is natural log transformation of
ASSETS; CURRENT is current assets to total assets; LIQUID is current assets to current liabilities;
SUBS is the number of subsidiaries while LNSUBS is the natural log transformation of SUBS;
FOREIGN presents the number of foreign-domicile subsidiaries and LNFOREIGN is the natural log
transformation of FOREIGN; YE takes the value of 1 if the ?scal year-end is 31 December; DEBT is
total debt over total equity; ROA is earnings divided by total assets; LOSS takes the value of 1 if the
?rm recorded a loss in the previous ?scal year; MANOWN is managerial shareholdings; BIG_N takes
the value of 1 for Big n auditors and 0 otherwise; SWITCH takes the value of 1 for ?rm switching
auditor and 0 otherwise
Table II.
Descriptive statistics for
sample ?rms (1999-2003)
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Table III.
Correlations matrix for
sample ?rms (1999-2003)
Audit quality
in Malaysia
179
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A
t
2
1
:
0
8
2
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a
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a
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y
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6
(
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)
5. Results and discussion
5.1 Multivariate analysis
Table IV tabulates panel least squares results for the 390 non-?nancial sample ?rms.
We observe positive and signi?cant intercepts or constant terms across all model
LAF
Model 1 Model 2 Model 3
CONSTANT 3.108 3.924 4.180
4.746
* * *
5.721
* * *
6.051
* * *
INSTOWN 0.007 0.003
3.002
* * *
0.980
POLCON 0.162 0.031
1.652
*
0.275
INSTOWN
*
POLCON 0.010
2.246
* *
LNASSETS 0.438 0.396 0.385
14.342
* * *
12.137
* * *
11.752
* * *
CURRENT 0.343 0.304 0.303
4.455
* * *
3.988
* * *
4.008
* * *
LIQUID 20.015 20.015 20.015
2 5.160
* * *
2 5.176
* * *
2 5.321
* * *
LNSUBS 0.011 0.011 0.012
1.147 1.133 1.235
LNFOREIGN 0.033 0.034 0.033
4.715
* * *
4.848
* * *
4.799
* * *
YE 20.003 0.020 0.020
2 0.042 0.281 0.274
DEBT 20.014 20.013 20.014
2 2.099
* *
2 1.955
*
2 2.098
* *
ROA 20.002 0.000 0.000
2 0.645 2 0.120 2 0.133
LOSS 0.111 0.102 0.114
1.602 1.470 1.653
*
MANOWN 20.005 20.003 20.004
2 1.985
*
2 1.399 2 1.515
BIG_N 0.103 0.061 0.062
1.391 0.820 0.843
SWITCH 0.167 0.142 0.135
2.255
* *
1.899
*
1.826
*
Industry ?xed Yes Yes Yes
Period ?xed Yes Yes Yes
Adjusted R
2
0.426 0.436 0.440
F-statistic 64.939
* * *
60.000
* * *
58.387
* * *
Notes: Signi?cant at:
*
10,
* *
5 and
* * *
1 per cent levels, respectively; t-statistics are italicised; probabilities
are one-tailed when in direction predicted; LAF is natural logarithmof audit fees; INSTOWNis the percentage
shareholdings by top ?ve institutional investors; POLCON takes the value of 1 for politically connected ?rms
and 0 otherwise; LNASSETS is natural log transformation of total assets; CURRENTis current assets to total
assets; LIQUID is current assets to current liabilities; LNSUBS is the natural log transformation of SUBS;
LNFOREIGNis the natural log transformation of FOREIGN; YEtakes the value of 1 if the ?scal year-end is 31
December; DEBTis total debt over total equity; ROAis earnings divided by total assets; LOSS takes the value
of 1 if the ?rmrecorded a loss in the previous ?scal year; MANOWNis managerial shareholdings; BIG_Ntakes
the value of 1 for Big n auditors and 0 otherwise; SWITCHtakes the value of 1 for ?rmswitching auditor and 0
otherwise; n ¼ 390 ?rms
Table IV.
Panel least squares for
sample ?rms (1999-2003)
ARJ
22,2
180
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(
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T
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speci?cations, which indicate ?xed cost in setting up the audit irrespective of the
attributes captured by other variables (Pong and Whittington, 1994). In comparison to
other Malaysian studies in this area (Yatim et al., 2006), our adjusted R
2
is only around
43 per cent across all models whereas a study by Yatim et al. (2006) indicates an
adjusted R
2
of 69 per cent. This may be due to different control variables used in the
study. Our study uses current ratio and current assets to current liabilities to measure
liquidity whereas Yatim et al. (2006) include receivable to total assets and inventories
to total assets.
Consistent with prior audit fee studies (Simunic, 1980; Yatim et al., 2006; Gul, 2006;
Ferguson, 2005), we ?rst regress audit fees on the control variables only. Results for
basic audit fees model are shown in Columns 1 (hereafter Model 1) of Table IV. The
adjusted R
2
for Model 1 is 42.6 per cent[18]. The signs for client attributes variables are
all in the predicted direction. All other variables remain signi?cant with the exception
of LNSUBS, YE, ROA and LOSS. LNASSETS coef?cient is positive and signi?cant at
1 per cent level (0.438, t ¼ 14.342, p , 0.001), CURRENTalso positive and signi?cant at
1 per cent level (0.343, t ¼ 4.445, p , 0.001). LNFOREIGN coef?cient is ?nd to be
positive at 1 per cent level (0.033, t ¼ 4.715, p , 0.001). Our results indicate that LIQIUD
and DEBT to be negatively associated with audit fees at 1 per cent level (20.015,
t ¼ 5.160, p , 0.001; 20.014, t ¼ 22.099, p , 0.001, respectively). We ?nd the
MANOWN coef?cient to be negative and statistically signi?cant at the 10 per cent
level[19]. The results showthe SWITCHcoef?cient to be positive and signi?cant at 5 per
cent level (0.167, t ¼ 2.255, p , 0.05), BIG_N is in the right direction but insigni?cant.
The main panel least squares results are reported in Column 2 of Table IV (hereafter
refer to Model 2). H1 predicts a positive relationship between institutional ownership
and audit fees. We ?nd the coef?cient for INSTOWN to be positive and signi?cant at 1
per cent level (0.007, t ¼ 3.002, p , 0.001) (as reported in Model 2 of Table IV), thus
providing support for H1. This fully supports the notion that institutional investors do
mitigate agency costs as a monitor of ?rms by demanding a higher quality audit from
auditors, prompting higher audit fees. This also suggests that institutional investors’
roles are not only to monitor management and major shareholders (Knechel and
Willekens, 2006; Hay et al., 2008) but also to play a representative role for minority
shareholders in demanding a higher quality audit. Nevertheless, the parameter of 0.007
represents audit fee premium of only 0.702 per cent, acknowledging that although a
positive relationship is observed between institutional ownership and audit fees, the
economic impact is minimal[20]. Nevertheless, the outcome should be considered as
promising and suggests a potential role for institutional investors. Results for all
control variables generally remain similar, with the exception of MANOWN, which
remains in the same direction but is now not signi?cant.
H2 predicts a positive relationship between political connectedness and audit fees.
The coef?cient for POLCON is positive and signi?cant (0.162, t ¼ 1.652, p , 0.10) thus
providing support for the arguments forwarded by Gul (2006). The parameter of 0.162
suggests that the audit fee premium for politically connected ?rms is 17.58 per cent.
Findings also suggest that auditor do perceive politically connected ?rms to have
greater inherent risk than non-politically connected ?rms leading to their demand for
more audit effort which in turn leads to these ?rms being charged higher audit fees.
We further explore political-connected ?rms and audit fees when institutional
investors are present in these ?rms (as reported in Model 3, Column 3 of Table IV).
Audit quality
in Malaysia
181
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2
1
:
0
8
2
4
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a
n
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a
r
y
2
0
1
6
(
P
T
)
The coef?cient for the interaction in terms of political connectedness with the presence
of institutional investors, INSTOWN
*
POLCON, is positive and signi?cant (0.010,
t ¼ 2.246, p , 0.05). The parameter of 0.010 suggests politically connected ?rms pay
1.005 per cent more audit fees than non-politically connected ?rms when the
institutional investors are present. This indicates that institutional investors act as
monitors and demand more audit effort and work to be undertaken especially in
political ?rms than non-political ?rms. Findings are consistent with prior studies
which suggest that institutional investors are an effective monitor of ?rms especially in
relation to reducing agency costs.
5.2 Further extensions
Several other tests are conducted to extend the basic ?ndings of the paper.
5.2.1 Institutional investors heterogeneity. H1 assumes that institutional investors
are homogenous in relation to objectives, nature of business or relationship with their
investees. In reality, institutional investors differ in various respects. Institutional
investors differ in size, in which some institutional investors are large, mainly due to
the amount of contributors and the nature of the institutions itself. In this sense,
pension funds around the world are large in size. Furthermore, their size can be a factor
in determining their ability to in?uence the ?rms’ managements.
Institutional investors differ in terms of the rules and regulation governing them. As
highlighted by Thillainathan (2000), EPF investments’ heavily emphasise government
bonds and regulation restrictions on overseas investments. Institutional investors such
as insurance ?rms, banks and other ?nancial institutions need to keep high levels of
cash in their funds. Therefore, they are usually required to make short-term returns as
opposed to long-term investment which often yield low returns in the short run. These
mitigating factors thus in?uence how the institutional investors form a relationship
with their investees.
An effectiveness of institutional investors as the monitoring for the ?rm can also be
determined through their business relationship with the ?rms. This relationship may
yield pressure for investors to abide by the position taken by the ?rms’ management to
monitor the ?rms. We argue that any form of relationship between the institutional
investors and the ?rms undermines the potential monitoring effectiveness of the
institutional investors. Furthermore, these institutional investors are not subject to
short-term returns by their contributors. Consistent with the extant literature (Brickley
et al., 1988; Chaganti and Damanpour, 1991; Cornett et al., 2007), we devise variables
that separate the investors according to their business relationship with the ?rms. We
classify institutional investors that do not have any business relationship with the
?rms as pressure-insensitive investors (INSENSITIVE), while investors which have
business relationships are classi?ed as pressure-sensitive (SENSITIVE) investors.
Institutional investors that do not fall in either group are classi?ed as
pressure-indeterminate (INDETERMINATE) investors[21].
Columns 1-6 of Table V present the regressions results which include the various
classi?cations of institutional investors. Model 1 (Column 1 of Table V) regresses
INSENSITIVE investors and POLCON with other control variables. Model 2 (Column 2
of Table V) regresses SENSITIVE investors and POLCON with other control variables.
Model 3 includes INDETERMINATE and POLCON and regresses this other control
variables. For Model 1, we ?nd a positive but statistically insigni?cant coef?cient for
ARJ
22,2
182
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(
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.
0
8
8
0
.
0
3
7
0
.
1
1
9
0
.
0
7
0
0
.
0
2
8
0
.
1
7
2
D
E
B
T
2
0
.
0
1
4
2
0
.
0
1
4
2
0
.
0
1
3
2
0
.
0
1
5
2
0
.
0
1
4
2
0
.
0
1
3
2
2
.
0
8
3
*
*
2
2
.
0
5
2
*
*
2
1
.
9
6
4
*
2
2
.
1
9
9
*
*
2
2
.
0
4
9
*
*
2
1
.
9
6
6
*
R
O
A
0
.
0
0
0
2
0
.
0
0
1
0
.
0
0
0
0
.
0
0
0
2
0
.
0
0
1
2
0
.
0
0
1
(
c
o
n
t
i
n
u
e
d
)
Table V.
Panel least squares
of sample ?rms for types
of institutional investors
(1999-2003)
Audit quality
in Malaysia
183
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
0
8
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
A
F
M
o
d
e
l
1
M
o
d
e
l
2
M
o
d
e
l
3
M
o
d
e
l
4
M
o
d
e
l
5
M
o
d
e
l
6
2
0
.
1
7
0
2
0
.
2
8
0
2
0
.
1
8
5
2
0
.
1
7
2
2
0
.
2
8
2
2
0
.
2
1
7
L
O
S
S
0
.
0
9
5
0
.
0
9
9
0
.
1
0
6
0
.
1
0
4
0
.
0
9
9
0
.
1
1
3
1
.
3
5
4
1
.
4
0
5
1
.
5
3
0
1
.
4
9
5
1
.
4
1
1
1
.
6
3
2
M
A
N
O
W
N
2
0
.
0
0
4
2
0
.
0
0
5
2
0
.
0
0
4
2
0
.
0
0
4
2
0
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0
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2
0
.
0
0
4
2
1
.
6
7
0
*
2
1
.
8
4
9
*
2
1
.
7
1
4
*
2
1
.
7
5
1
*
2
1
.
8
6
6
*
2
1
.
7
4
3
*
B
I
G
_
N
0
.
0
7
7
0
.
0
8
4
0
.
0
6
7
0
.
0
7
7
0
.
0
8
6
0
.
0
6
8
1
.
0
3
5
1
.
1
3
5
0
.
9
0
2
1
.
0
3
8
1
.
1
6
2
0
.
9
2
5
S
W
I
T
C
H
0
.
1
5
2
0
.
1
5
3
0
.
1
2
9
0
.
1
5
1
0
.
1
5
2
0
.
1
1
7
2
.
0
2
5
*
*
2
.
0
3
5
*
*
1
.
7
2
8
*
2
.
0
2
0
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*
2
.
0
3
0
*
*
1
.
5
8
2
I
n
d
u
s
t
r
y
?
x
e
d
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
P
e
r
i
o
d
?
x
e
d
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
A
d
j
u
s
t
e
d
R
2
0
.
4
2
9
0
.
4
2
7
0
.
4
3
5
0
.
4
3
1
0
.
4
2
7
0
.
4
4
0
F
-
s
t
a
t
i
s
t
i
c
5
8
.
3
6
7
*
*
*
5
8
.
0
4
2
*
*
*
5
9
.
8
5
7
*
*
*
5
6
.
3
4
8
*
*
*
5
5
.
4
6
2
*
*
*
5
8
.
2
4
5
*
*
*
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
t
a
t
:
*
1
0
,
*
*
5
a
n
d
*
*
*
1
p
e
r
c
e
n
t
l
e
v
e
l
s
,
r
e
s
p
e
c
t
i
v
e
l
y
;
t
-
s
t
a
t
i
s
t
i
c
s
a
r
e
i
t
a
l
i
c
i
s
e
d
;
p
r
o
b
a
b
i
l
i
t
i
e
s
a
r
e
o
n
e
-
t
a
i
l
e
d
w
h
e
n
i
n
d
i
r
e
c
t
i
o
n
p
r
e
d
i
c
t
e
d
;
L
A
F
i
s
n
a
t
u
r
a
l
l
o
g
a
r
i
t
h
m
o
f
a
u
d
i
t
f
e
e
s
;
I
N
S
E
N
S
I
T
I
V
E
,
S
E
N
S
I
T
I
V
E
a
n
d
I
N
D
E
T
E
R
M
I
N
A
T
E
a
r
e
p
e
r
c
e
n
t
a
g
e
s
h
a
r
e
h
o
l
d
i
n
g
s
h
e
l
d
b
y
p
r
e
s
s
u
r
e
i
n
s
e
n
s
i
t
i
v
e
,
s
e
n
s
i
t
i
v
e
a
n
d
i
n
d
e
t
e
r
m
i
n
a
t
e
i
n
v
e
s
t
o
r
s
,
r
e
s
p
e
c
t
i
v
e
l
y
;
P
O
L
C
O
N
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
f
o
r
p
o
l
i
t
i
c
a
l
l
y
c
o
n
n
e
c
t
e
d
?
r
m
s
a
n
d
0
o
t
h
e
r
w
i
s
e
;
L
N
A
S
S
E
T
S
i
s
n
a
t
u
r
a
l
l
o
g
t
r
a
n
s
f
o
r
m
a
t
i
o
n
o
f
A
S
S
E
T
S
;
C
U
R
R
E
N
T
i
s
c
u
r
r
e
n
t
a
s
s
e
t
s
t
o
t
o
t
a
l
a
s
s
e
t
s
;
L
I
Q
U
I
D
i
s
c
u
r
r
e
n
t
a
s
s
e
t
s
t
o
c
u
r
r
e
n
t
l
i
a
b
i
l
i
t
i
e
s
;
L
N
S
U
B
S
i
s
t
h
e
n
a
t
u
r
a
l
l
o
g
t
r
a
n
s
f
o
r
m
a
t
i
o
n
o
f
S
U
B
S
;
F
O
R
E
I
G
N
p
r
e
s
e
n
t
s
t
h
e
n
u
m
b
e
r
o
f
f
o
r
e
i
g
n
-
d
o
m
i
c
i
l
e
s
u
b
s
i
d
i
a
r
i
e
s
a
n
d
L
N
F
O
R
E
I
G
N
i
s
t
h
e
n
a
t
u
r
a
l
l
o
g
t
r
a
n
s
f
o
r
m
a
t
i
o
n
o
f
F
O
R
E
I
G
N
;
Y
E
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
i
f
t
h
e
?
s
c
a
l
y
e
a
r
-
e
n
d
i
s
3
1
D
e
c
e
m
b
e
r
;
D
E
B
T
i
s
t
o
t
a
l
d
e
b
t
o
v
e
r
t
o
t
a
l
e
q
u
i
t
y
;
R
O
A
i
s
e
a
r
n
i
n
g
s
d
i
v
i
d
e
d
b
y
t
o
t
a
l
a
s
s
e
t
s
;
L
O
S
S
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
i
f
t
h
e
?
r
m
r
e
c
o
r
d
e
d
a
l
o
s
s
i
n
t
h
e
p
r
e
v
i
o
u
s
?
s
c
a
l
y
e
a
r
;
M
A
N
O
W
N
i
s
m
a
n
a
g
e
r
i
a
l
s
h
a
r
e
h
o
l
d
i
n
g
s
;
B
I
G
_
N
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
f
o
r
B
i
g
n
a
u
d
i
t
o
r
s
a
n
d
0
o
t
h
e
r
w
i
s
e
;
S
W
I
T
C
H
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
f
o
r
?
r
m
s
w
i
t
c
h
i
n
g
a
u
d
i
t
o
r
a
n
d
0
o
t
h
e
r
w
i
s
e
;
n
¼
3
9
0
?
r
m
s
Table V.
ARJ
22,2
184
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
0
8
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
INSENSITIVEinvestors (0.004, t ¼ 1.412, p . 0.10) indicating that pressure-insensitive
investors are not reliable monitors and do not lead to better audit quality. Since
pressure-sensitive (SENSITIVE) investors do hold business interests with the ?rms, we
do not expect them to play a monitoring role and thus do not contribute to better audit.
As predicted, we ?nd no evidence of a relationship between SENSITIVE and LAF as
shown in Model 2. In Model 3, we ?nd investors that do not fall in either group
(INDETERMINATE) positively affects audit fees (0.011, t ¼ 2.884, p , 0.001). Further,
the parameter 0.011 of INDETERMINATE presents 1.106 per cent of audit fees
premium. Our ?ndings suggest investors’ heterogeneity does play a signi?cant part in
determining the relationship between institutional ownership and audit fees.
Models 4-6 extend our analysis by looking at interactions of
INSENSITIVE
*
POLCON, SENSITIVE
*
POLCON and INDETERMINATE
*
POLCON.
Interestingly, we ?nd that the coef?cient for the interactions INSENSITIVE
*
POLCON,
and INDETERMINATE
*
POLCON are both positive and signi?cant at (0.010,
t ¼ 1.714, p , 0.01) and (0.018, t ¼ 2.213, p , 0.05). These results suggest that groups
which do not hold any interests in ?rms (INSENSITIVE and INDETERMINATE) play
a more stringent monitoring role and insist on a high-quality audit particularly in the
additional presence of political connectedness.
5.2.2 Individual investors. Since Malaysian institutional investors form the highest
ownership of institutional investors’ equity in the capital market, we examine their role
in in?uencing the variation of audit fees. Speci?cally, we analyse the relationship
between EPF, PNB, LTAT, LTH and PERKESO with audit fees. Since their cumulative
institutional investment represents 68 per cent of total institutional investment, it is
imperative to empirically examine their role in the audit market.
Columns 1-10 of Table VI present the regressions results for individual large
investors in Malaysia. Refer to Column 1-4 of Table VI, we ?nd positive and signi?cant
coef?cients for EPF (0.026, t ¼ 2.707, p , 0.001) and PNB (0.011, t ¼ 2.884, p , 0.001)
providing support that EPF and PNB are positively related to audit effort leading to
higher audit fees. Our results suggest that these institutional investors do demand
higher audit fees. Columns 6-9 of Table VI represent interactions between POLCON
and individual institutional investors. Only the interactions of EPF
*
POLCON and
LTAT
*
POLCON are positive and signi?cant with audit fees at 5 and 1 per cent,
respectively. We view this result as promising which suggest that we should view
seriously the proposition that local institutional investors play a key role in demanding
a better quality audit.
6. Conclusion
This study examines the relationship between institutional ownership and audit fees a
proxy for audit quality in Malaysia. In particular, we examine whether institutional
ownership and political-connected ?rms are associated with higher audit fees. Our
panel analysis of 390 ?rms for the period 1999-2003 ?nds a positive association
between institutional ownership, measured by top ?ve shareholdings of institutional
investors and audit fees. Our ?nding suggests institutional investors demand a higher
quality audit, ultimately increasing audit fees. Furthermore, we ?nd evidence that the
positive relationship does depend on investors’ heterogeneity. Our results also suggest
that political-connected ?rms are associated with higher audit fees, suggesting that
these ?rms are perceived by auditors to be more risky. Consequently, auditors tend to
Audit quality
in Malaysia
185
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
0
8
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
A
F
1
2
3
4
5
6
7
8
9
1
0
C
O
N
S
T
A
N
T
3
.
9
6
4
3
.
7
2
3
3
.
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4
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3
.
5
2
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3
.
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4
.
0
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.
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3
3
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3
.
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3
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*
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0
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0
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3
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4
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0
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0
4
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5
4
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2
3
5
P
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C
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N
0
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1
5
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1
8
6
0
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1
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1
7
2
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6
7
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1
2
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1
2
4
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1
5
4
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1
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1
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5
2
1
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.
8
8
5
*
1
.
7
0
4
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1
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7
3
1
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1
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6
7
8
*
0
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5
0
3
1
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2
3
2
1
.
2
4
6
1
.
5
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8
1
.
5
8
6
E
P
F
*
P
O
L
C
O
N
0
.
0
2
9
1
.
5
3
8
P
N
B
2
*
P
O
L
C
O
N
0
.
0
1
8
2
.
2
1
3
*
*
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T
A
T
*
P
O
L
C
O
N
0
.
0
3
5
2
.
7
3
8
*
*
*
L
T
H
*
P
O
L
C
O
N
0
.
0
3
5
0
.
6
9
9
S
O
C
S
O
*
P
O
L
C
O
N
0
.
0
8
0
0
.
2
6
5
L
N
A
S
S
E
T
S
0
.
3
9
4
0
.
4
0
6
0
.
4
1
5
0
.
4
1
6
0
.
4
1
4
0
.
3
9
1
0
.
4
0
0
0
.
4
1
6
0
.
4
1
5
0
.
4
1
5
1
1
.
9
6
1
*
*
*
1
2
.
6
4
6
*
*
*
1
2
.
8
6
6
*
*
*
1
2
.
8
7
2
*
*
*
1
2
.
8
1
7
*
*
*
1
1
.
8
9
5
*
*
*
1
2
.
4
6
6
*
*
*
1
3
.
0
0
8
*
*
*
1
2
.
8
3
1
*
*
*
1
2
.
8
1
4
*
*
*
C
U
R
R
E
N
T
0
.
2
9
6
0
.
3
0
8
0
.
3
1
4
0
.
3
1
6
0
.
3
1
4
0
.
2
9
4
0
.
3
1
4
0
.
3
2
0
0
.
3
1
6
0
.
3
1
4
3
.
8
8
2
*
*
*
4
.
0
5
3
*
*
*
4
.
0
9
5
*
*
*
4
.
1
2
5
*
*
*
4
.
0
9
4
*
*
*
3
.
8
8
0
*
*
*
4
.
1
5
1
*
*
*
4
.
2
0
8
*
*
*
4
.
1
2
6
*
*
*
4
.
0
9
5
*
*
*
L
I
Q
U
I
D
2
0
.
0
1
4
2
0
.
0
1
5
2
0
.
0
1
5
2
0
.
0
1
5
2
0
.
0
1
5
2
0
.
0
1
4
2
0
.
0
1
5
2
0
.
0
1
5
2
0
.
0
1
5
2
0
.
0
1
5
2
5
.
1
0
2
*
*
*
2
5
.
1
9
5
*
*
*
2
5
.
1
6
4
*
*
*
2
5
.
1
5
7
*
*
*
2
5
.
1
5
5
*
*
*
2
5
.
1
1
2
*
*
*
2
5
.
2
4
7
*
*
*
2
5
.
3
6
8
*
*
*
2
5
.
1
5
1
*
*
*
2
5
.
1
5
4
*
*
*
L
N
S
U
B
S
0
.
0
1
2
0
.
0
1
1
0
.
0
1
2
0
.
0
1
2
0
.
0
1
2
0
.
0
1
2
0
.
0
1
2
0
.
0
1
1
0
.
0
1
2
0
.
0
1
2
(
c
o
n
t
i
n
u
e
d
)
Table VI.
Panel least squares for
sample ?rms for
individual ?rms
(1999-2003)
ARJ
22,2
186
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
0
8
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
A
F
1
2
3
4
5
6
7
8
9
1
0
1
.
2
5
3
1
.
2
0
9
1
.
2
4
0
1
.
2
4
4
1
.
2
5
7
1
.
2
1
8
1
.
2
6
8
1
.
1
8
1
1
.
2
3
8
1
.
2
4
8
L
N
F
O
R
E
I
G
N
0
.
0
3
2
0
.
0
3
2
0
.
0
3
2
0
.
0
3
2
0
.
0
3
2
0
.
0
3
2
0
.
0
3
1
0
.
0
3
2
0
.
0
3
2
0
.
0
3
2
4
.
5
6
5
*
*
*
4
.
6
9
8
*
*
*
4
.
6
1
7
*
*
*
4
.
5
7
2
*
*
*
4
.
6
1
4
*
*
*
4
.
6
7
7
*
*
*
4
.
5
5
5
*
*
*
4
.
5
7
6
*
*
*
4
.
5
7
3
*
*
*
4
.
6
2
4
*
*
*
Y
E
0
.
0
2
6
0
.
0
0
9
2
0
.
0
0
2
2
0
.
0
0
1
2
0
.
0
0
1
0
.
0
2
5
0
.
0
1
2
2
0
.
0
1
0
0
.
0
0
1
0
.
0
0
0
0
.
3
6
0
0
.
1
1
9
2
0
.
0
2
3
2
0
.
0
0
9
2
0
.
0
1
5
0
.
3
5
0
0
.
1
7
2
2
0
.
1
3
8
0
.
0
0
8
0
.
0
0
2
D
E
B
T
2
0
.
0
1
3
2
0
.
0
1
3
2
0
.
0
1
4
2
0
.
0
1
4
2
0
.
0
1
4
2
0
.
0
1
3
2
0
.
0
1
3
2
0
.
0
1
4
2
0
.
0
1
4
2
0
.
0
1
4
2
1
.
9
3
8
*
2
1
.
9
6
4
*
2
2
.
1
0
3
*
*
2
2
.
1
0
2
*
*
2
2
.
1
0
3
*
*
2
1
.
9
8
7
*
2
1
.
9
6
6
*
2
2
.
1
2
0
*
*
2
2
.
0
7
7
*
*
2
2
.
1
1
8
*
*
R
O
A
2
0
.
0
0
1
0
.
0
0
0
2
0
.
0
0
1
2
0
.
0
0
1
2
0
.
0
0
1
2
0
.
0
0
1
2
0
.
0
0
1
2
0
.
0
0
1
0
.
0
0
0
2
0
.
0
0
1
2
0
.
3
9
4
2
0
.
1
8
5
2
0
.
2
3
2
2
0
.
2
0
9
2
0
.
2
1
6
2
0
.
3
5
7
2
0
.
2
1
7
2
0
.
3
3
1
2
0
.
2
0
4
2
0
.
2
1
8
L
O
S
S
0
.
1
0
1
0
.
1
0
6
0
.
0
9
6
0
.
0
9
5
0
.
0
9
7
0
.
1
0
3
0
.
1
1
3
0
.
1
1
6
0
.
0
9
5
0
.
0
9
8
1
.
4
5
4
1
.
5
3
0
1
.
3
6
4
1
.
3
6
4
1
.
3
9
1
1
.
4
7
8
1
.
6
3
2
1
.
6
6
9
1
.
3
6
1
1
.
3
9
7
M
A
N
O
W
N
2
0
.
0
0
4
2
0
.
0
0
4
2
0
.
0
0
5
2
0
.
0
0
5
2
0
.
0
0
5
2
0
.
0
0
4
2
0
.
0
0
4
2
0
.
0
0
5
2
0
.
0
0
5
2
0
.
0
0
5
2
1
.
6
0
2
2
1
.
7
1
4
*
2
1
.
8
8
5
*
2
1
.
8
8
3
*
2
1
.
8
5
8
*
2
1
.
5
8
1
2
1
.
7
4
3
*
2
1
.
9
8
2
*
2
1
.
8
6
7
*
2
1
.
8
5
6
*
B
I
G
_
N
0
.
0
6
4
0
.
0
6
7
0
.
0
8
4
0
.
0
8
4
0
.
0
8
4
0
.
0
6
5
0
.
0
6
8
0
.
0
8
5
0
.
0
8
1
0
.
0
8
5
0
.
8
5
8
0
.
9
0
2
1
.
1
3
6
1
.
1
3
5
1
.
1
3
1
0
.
8
8
6
0
.
9
2
5
1
.
1
4
9
1
.
0
9
6
1
.
1
4
2
S
W
I
T
C
H
0
.
1
5
6
0
.
1
2
9
0
.
1
5
0
0
.
1
5
0
0
.
1
5
1
0
.
1
5
3
0
.
1
1
7
0
.
1
4
6
0
.
1
4
9
0
.
1
5
2
2
.
0
9
5
*
*
1
.
7
2
8
*
1
.
9
9
8
*
1
.
9
9
3
*
2
.
0
1
2
*
*
2
.
0
5
9
*
*
1
.
5
8
2
1
.
9
5
3
*
1
.
9
8
3
*
2
.
0
1
9
*
*
I
n
d
u
s
t
r
y
?
x
e
d
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
P
e
r
i
o
d
?
x
e
d
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
A
d
j
u
s
t
e
d
R
2
0
.
4
3
3
0
.
4
3
5
0
.
4
2
7
0
.
4
2
7
0
.
4
2
7
0
.
4
3
5
0
.
4
4
0
0
.
4
3
4
0
.
4
2
7
0
.
4
2
7
F
-
s
t
a
t
i
s
t
i
c
5
9
.
3
9
1
*
*
*
5
9
.
8
5
7
*
*
*
5
7
.
8
9
2
*
*
*
5
7
.
9
3
1
*
*
*
5
7
.
9
4
9
*
*
*
5
7
.
1
5
4
*
*
*
5
8
.
2
4
5
*
*
*
5
6
.
9
7
8
*
*
*
5
5
.
3
7
6
*
*
*
5
5
.
2
9
3
*
*
*
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
t
a
t
:
*
1
0
,
*
*
5
a
n
d
*
*
*
1
p
e
r
c
e
n
t
l
e
v
e
l
s
,
r
e
s
p
e
c
t
i
v
e
l
y
;
t
-
s
t
a
t
i
s
t
i
c
s
a
r
e
i
t
a
l
i
c
i
s
e
d
;
L
A
F
i
s
n
a
t
u
r
a
l
l
o
g
a
r
i
t
h
m
o
f
a
u
d
i
t
f
e
e
s
;
E
P
F
,
P
N
B
,
L
T
A
T
,
L
T
H
a
n
d
P
E
R
K
E
S
O
a
r
e
p
e
r
c
e
n
t
a
g
e
s
h
a
r
e
h
o
l
d
i
n
g
s
h
e
l
d
b
y
E
P
F
,
P
N
B
,
L
T
A
T
,
L
T
H
a
n
d
P
e
r
t
u
b
u
h
a
n
K
e
s
e
l
a
m
a
t
a
n
S
o
s
i
a
l
i
n
v
e
s
t
o
r
s
,
r
e
s
p
e
c
t
i
v
e
l
y
;
P
O
L
C
O
N
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
f
o
r
p
o
l
i
t
i
c
a
l
l
y
c
o
n
n
e
c
t
e
d
?
r
m
s
a
n
d
0
o
t
h
e
r
w
i
s
e
;
L
N
A
S
S
E
T
S
i
s
n
a
t
u
r
a
l
l
o
g
t
r
a
n
s
f
o
r
m
a
t
i
o
n
o
f
t
o
t
a
l
a
s
s
e
t
s
;
C
U
R
R
E
N
T
i
s
c
u
r
r
e
n
t
a
s
s
e
t
s
t
o
t
o
t
a
l
a
s
s
e
t
s
;
L
I
Q
U
I
D
i
s
c
u
r
r
e
n
t
a
s
s
e
t
s
t
o
c
u
r
r
e
n
t
l
i
a
b
i
l
i
t
i
e
s
;
L
N
S
U
B
S
i
s
t
h
e
n
a
t
u
r
a
l
l
o
g
t
r
a
n
s
f
o
r
m
a
t
i
o
n
o
f
S
U
B
S
;
F
O
R
E
I
G
N
p
r
e
s
e
n
t
s
t
h
e
n
u
m
b
e
r
o
f
f
o
r
e
i
g
n
-
d
o
m
i
c
i
l
e
s
u
b
s
i
d
i
a
r
i
e
s
a
n
d
L
N
F
O
R
E
I
G
N
i
s
t
h
e
n
a
t
u
r
a
l
l
o
g
t
r
a
n
s
f
o
r
m
a
t
i
o
n
o
f
F
O
R
E
I
G
N
;
Y
E
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
i
f
t
h
e
?
s
c
a
l
y
e
a
r
-
e
n
d
i
s
3
1
D
e
c
e
m
b
e
r
;
D
E
B
T
i
s
t
o
t
a
l
d
e
b
t
o
v
e
r
t
o
t
a
l
e
q
u
i
t
y
;
R
O
A
i
s
e
a
r
n
i
n
g
s
d
i
v
i
d
e
d
b
y
t
o
t
a
l
a
s
s
e
t
s
;
L
O
S
S
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
i
f
t
h
e
?
r
m
r
e
c
o
r
d
e
d
a
l
o
s
s
i
n
t
h
e
p
r
e
v
i
o
u
s
?
s
c
a
l
y
e
a
r
;
M
A
N
O
W
N
i
s
m
a
n
a
g
e
r
i
a
l
s
h
a
r
e
h
o
l
d
i
n
g
s
;
B
I
G
_
N
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
f
o
r
B
i
g
n
a
u
d
i
t
o
r
s
a
n
d
0
o
t
h
e
r
w
i
s
e
;
S
W
I
T
C
H
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
f
o
r
?
r
m
s
w
i
t
c
h
i
n
g
a
u
d
i
t
o
r
a
n
d
0
o
t
h
e
r
w
i
s
e
;
n
¼
3
9
0
?
r
m
s
Table VI.
Audit quality
in Malaysia
187
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
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charge these ?rms fees premiums. The two way interaction between institutional
investors and political-connected ?rms and audit fee suggests that political-connected
?rm pay higher audit fees than non-political connected ?rms when institutional
investors are present in their ?rms. The exploration of this effect suggests that
institutional investors do play a monitoring role in order to reduce agency costs by
demanding for a higher quality audit particularly for politically connected ?rms.
Our study is not without any limitations. We based our politically connected ?rms
list on the Johnson and Mitton (2003) publication. Future research should further
explore this relationship by using a new list of politically connected ?rms. Since Tun
Mahathir Mohamed handed the Prime Minister position over to Dato’ Seri Abdullah
Ahmad Badawi in 2003, companies in favour of Dato’ Seri Abdullah Ahmad Badawi
should also be included. Besides, this, an extension of further research on the exact
nature of the political relationship could yield a more robust ?nding, and better
understanding of this relationship. Furthermore, we acknowledge the weakness of our
investors’ heterogeneity speci?cations which are based on the extant literature
(Brickley et al., 1988, Cornett et al., 2007). A thorough investigation as to whether
individual business relationships exist could be bene?cial.
Notes
1. Agency costs include: the monitoring expenditures incurred by the principal; the bonding
expenditures incurred by the agent; and the residual loss (Jensen and Meckling, 1976, p. 308).
The residual loss is the ultimate loss in ?rm value that the agency relationship creates and
which is not optimally reduced any further by either the incurrence of additional monitoring
or additional bonding expenditures.
2. We argue that the form of relationship between the institutional investors affects the
potential monitoring effectiveness of institutional investors. We predict that institutional
investors that have a business relationship with the ?rms are not reliable monitors. In
contrast, institutional investors with less interest in the ?rm are expected to play a more
active role in ensuring higher quality audit.
3. Malaysia has about 22.79 million people, of whom 65 per cent are Bumiputera, 26 per cent
Chinese, 8 per cent Indians and 1 per cent others. Of the 65 per cent Bumiputera, 82 per cent
are Malays and 18 per cent are other indigenous people (Department of Statistics Malaysia,
2004).
4. The NEP has been very successful in that is has led to a signi?cant increase in Bumiputeras’
corporate ownership from 2.4 per cent in 1970 to 20.3 per cent in 1990 (Rasiah and Shari,
2001). However, such a ?gure still falls short of the NEP’s 30 per cent target. Since the
country’s economy surged by an average of more than 7 per cent a year for most of the
period, the Malays’ advance did not occur at the expense of other races. Within 20 years
(1970-1990), Chinese equity ownership rose signi?cantly from27.2 per cent in 1970 to 45.5 per
cent in 1990. In addition, the NEP had successfully reduced the dominance of foreign
ownership and control of the economy from 63.3 per cent in 1970 to 25.4 per cent in 1990.
However, the NEP’s 30 per cent of the Bumiputera ownership target has yet to be met after
replacing the NEP with the National Development Policy in 1991.
5. Under the superannuation scheme, serving members of the other ranks in the Armed Forces are
required to contribute 10 per cent of their monthly salary to LTAT with the government as
employer contributing 15 percent. For of?cers, participation is voluntary and the contributions
are a minimum of RM 25 with a maximum of RM 200 monthly (www.ltat.org.my).
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6. Syariah refers to the body of Islamic law. It is the legal framework within which public and
some private aspects of life are regulated for those living in a legal system based on Moslem
principles of jurisprudence. For example, Moslems are not permitted to be involved in
gambling or any contracts involving future predictions or uncertainty.
7. The rise of these politically linked companies is the result of the NEP Plan introduced in 1970
with the objective of achieving economic parity for the Bumiputra
8. The other forms of political favouritism may be due to ?rms run by those from diverse
ethnicity namely Bumiputra, Chinese and Indian including those with close relationships
with prominent politicians (Gul, 2006, p. 936).
9. See Favere-Marchesi (2001) for a thorough review on audit requirements in Malaysia.
10. Ali et al. (2006) summarise the trend of auditing practices after Malaysia gained
independence in 1957. They divide the documentary analysis into three periods: Pre-NEP,
during NEP and after NEP and Asian Financial Crisis.
11. In Malaysia, the duty to disclose audit fees is mandated by the Companies Act 1965 (Che
Ahmad and Houghton, 2001).
12. The top ?ve institutional investors constitute 99 per cent of total institutional investors’
shareholdings.
13. Khazanah Nasional Berhad is the investment holding arm of the government of Malaysia to
manage its commercial assets. It was incorporated in September 1993 and began operations
in 1994. It is structured into a holding company that is a wholly owned entity of the Ministry
of Finance which is part of the Malaysian government.
14. The Big n audit ?rms are Arthur Andersen, Deloitte, KPMG, Ernst and Young and
PricewaterhouseCoopers. For the sake of consistency, well-known partner ?rms (e.g. Kassim
Chan and Hana?ah Raslan) to the Big n are considered as a big auditor if they are mentioned
explicitly.
15. Regression results are reported without the period and industry dummies. The results can be
obtained from the corresponding author.
16. Pearson and Spearman Rank are included for robustness purposes.
17. Standard diagnostic tests reveal no multicollinearity problem.
18. We checked our data properly to avoid errors, univariate and multivariate outliers were
taken out. This study uses period seemingly unrelated regressions to handle both
heterocedasticity and contemporaneous correlations in each cross-section. We also repeat
our analysis by including ?nancial ?rms and we ?nd that adjusted R
2
remains also the same
across all models.
19. Extant literature suggests a piecewise relationship could exist between managerial
ownership and audit quality (Lennox, 2005). Using threshold ?gures of 5, 5-20 and 20 per cent
suggested by Lins (2003) for emerging markets, we ?nd no evidence to suggest such
relationship exists. Alternative analysis using quadratic function of MANOWN yields
insigni?cant results too. Regressions results can be obtained from the corresponding author.
20. The audit fee premium or discount is obtained by calculating the effect of the percentage
shift on natural log of audit fees and is de?ned as e
z
2 1, where z is the parameter for the
testable variable. See Craswell et al. (1995) for thorough explanation.
21. Ideally, we want to know the explicit relationship between the institutional investors and
their investees. However, such information is not available.
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(The Appendix follows overleaf.)
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Appendix
Name
1 Advance Synergy
2 Af?n Holdings
3 Antah
4 Arab Malaysia Development
5 Bandar Raya Development
6 Bank Islam Malaysia Bhd Holdings
7 BCB
8 Berjaya Group
9 Berjaya Land
10 Berjaya Sports Toto
11 Best World Land (MultiVest)
12 Boustead Holdings
13 Cahaya Mata Sarawak
14 Camerlin Group
15 Cement Industries of Malaysia
16 Commerce Assets
17 Cosway Corporation (Singer)
18 Cycle and Carriage
19 Daibochi
20 Damansara Realty
21 DRB-Hicom
22 Edaran Otomobil Nasional
23 Faber Group
24 FCW Holdings (Bata)
25 Fima Corporation
26 Georgetown Holdings
27 Goh Ban Huat
28 Golden Hope Plantation
29 Golden Plus (Dayapi)
30 Granite Industries
31 Ho Hup
32 Hong Leong Bank
33 Hong Leong Credit
34 Hong Leong Industries
35 Hong Leong Properties
36 Hume Industries
37 Jaya Tiasa (Berjaya Textile)
38 Kedah Cement Holdings
39 Kretam
40 Kumpulan Guthrie
41 Land and General
42 Landmarks
43 Leisure Management (Magnum 4D)
44 Lion Corporation
45 Magnum Corporation
46 Malakoff
47 Malayan Banking
48 Malaysian Paci?c Industries
(continued)
Table AI.
List of politically
connected ?rms in
Malaysia (1999-2003)
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Corresponding author
Ef?ezal Aswadi Abdul Wahab can be contacted at: [email protected]
Name
49 Malaysia Airports Holdings
50 Malaysia International Shipping Corporation
51 Malaysian Airlines System
52 Metacorp
53 Metroplex
54 MRCB
55 Mulpha International
56 Multi-Purpose Holdings
57 Mycom
58 Naluri (MHS)
59 Nanyang Press
60 New Straits Times
61 OYL Industries
62 Pantai Hospital
63 Park May
64 Pharmaniaga
65 Philleo Allied Bhd
66 Prime Utilities
67 Proton Holdings
68 PSC Industries
69 Rashid Hussain
70 RHB Capital
71 Sapura Telecommunications
72 Setron
73 Sime Darby
74 Star Publications
75 Taiping Consolidated
76 Tanjong
77 Tasek Corporation
78 Telekom Malaysia
79 Tenaga Nasional
80 Time Engineering
81 UDA Holdings
82 Union Paper (TH Group)
83 Uniphone Telecommunication
84 United Plantations
85 Utusan Melayu
86 Wembley Industries Holdings
87 Wijaya Baru (Paci?c Chemicals)
88 YTL Cement
89 YTL Corporation
90 YTL Power
Sources: Johnson and Mitton (2003); Mohamad et al. (2006); Khazanah Berhad web site (www.khaza
nah.com.my) Table AI.
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Indicators: Utilizing Generalized Least Square Estimation Technique. Procedia - Social and Behavioral
Sciences 164, 477-485. [CrossRef]
5. Effiezal Aswadi Abdul Wahab, Willie.E. Gist, Wan Zurina Nik Abdul Majid. 2014. Characteristics of non-
audit services and financial restatements in Malaysia. Journal of Contemporary Accounting & Economics .
[CrossRef]
6. Rusmin Rusmin, Emita W. Astami, Bambang Hartadi. 2014. The impact of surplus free cash flow and
audit quality on earnings management. Asian Review of Accounting 22:3, 217-232. [Abstract] [Full Text]
[PDF]
7. Mazrah Malek, Saidatunur Fauzi Saidin. 2013. Audit Services Fee, Non-Audit Services and the Reliability
of Earnings. International Journal of Trade, Economics and Finance 259-264. [CrossRef]
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doc_890208012.pdf
The purpose of this paper is to extend the audit pricing literature by examining whether
institutional investors and political connection are associated with higher audit fees.
Accounting Research Journal
Institutional investors, political connection and audit quality in Malaysia
Effiezal Aswadi Abdul Wahab Mazlina Mat Zain Kieran J ames Hasnah Haron
Article information:
To cite this document:
Effiezal Aswadi Abdul Wahab Mazlina Mat Zain Kieran J ames Hasnah Haron, (2009),"Institutional
investors, political connection and audit quality in Malaysia", Accounting Research J ournal, Vol. 22 Iss 2 pp.
167 - 195
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Effiezal Aswadi Abdul Wahab, Mazlina Mat Zain, Kieran J ames, (2011),"Political connections, corporate
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dx.doi.org/10.1108/02686901111129562
Rani Hoitash, Ariel Markelevich, Charles A. Barragato, (2007),"Auditor fees and audit quality", Managerial
Auditing J ournal, Vol. 22 Iss 8 pp. 761-786 http://dx.doi.org/10.1108/02686900710819634
Puan Yatim, Pamela Kent, Peter Clarkson, (2006),"Governance structures, ethnicity, and audit
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Institutional investors, political
connection and audit quality
in Malaysia
Ef?ezal Aswadi Abdul Wahab
Graduate School of Business, Universiti Sains Malaysia, Penang, Malaysia and
Department of Accounting, School of Management,
Universiti Sains Malaysia, Penang, Malaysia
Mazlina Mat Zain
Faculty of Management, Multimedia University, Cyberjaya, Malaysia
Kieran James
School of Accounting, Economics and Finance,
University of Southern Queensland, Toowoomba, Australia, and
Hasnah Haron
Graduate School of Business, Universiti Sains Malaysia, Penang, Malaysia and
Department of Accounting, School of Management,
Universiti Sains Malaysia, Penang, Malaysia
Abstract
Purpose – The purpose of this paper is to extend the audit pricing literature by examining whether
institutional investors and political connection are associated with higher audit fees.
Design/methodology/approach – Both descriptive and multivariate analyses are employed to
address the research objectives. In addition, the authors use panel data to control for both
heterocedasticity and contemporaneous correlations in each cross-section.
Findings – Based on a panel analysis of 390 Malaysian ?rms from 1999 to 2003, a positive
relationship between institutional ownership and audit fees is found, although the economic impact is
minimal. Further, the authors ?nd that audit fees are higher for politically connected ?rms.
Research limitations/implications – A thorough examination on the role of political connection is
much warranted to provide a better understanding on such connection in?uences the audit market.
Originality/value – This paper provides an alternative view on the role of political connection, and
on how they in?uence the audit market.
Keywords Investors, Malaysia, Auditor’s fees, Political systems, Organizations
Paper type Research paper
1. Introduction
In the past, institutional investors were seen as a mechanism to facilitate savings based
on consistent earnings and stable returns (Gomez and Jomo, 1999). We then observed
the growth of savings-based institutional investors in the developed countries (e.g.
California Public Employees’ Retirement System in the USA) and in developing
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1030-9616.htm
The authors are thankful for capable research assistance from Wan Adibah Wan Adnan. The
?rst author would like to thank Universiti Sains Malaysia for ?nancial assistance.
Audit quality
in Malaysia
167
Accounting Research Journal
Vol. 22 No. 2, 2009
pp. 167-195
qEmerald Group Publishing Limited
1030-9616
DOI 10.1108/10309610910987501
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countries (e.g. Employees Provident Fund (EPF) in Malaysia and Central Provident
Fund in Singapore). As institutional investors’ pools of funds grow, so does their
responsibility to the contributors and to the public. Moreover, institutional investors
such as pension funds began to abandon their traditional passive shareholder role and
became more active participants in the governance of their corporate holdings (Monks
and Minow, 1995). Thus, institutional investors play an important role in determining
?rms’ corporate governance.
Their increasing equity share ownership (Cornett et al., 2007) and a ?duciary
obligation (Hawley and William, 1997) to contributors and to the public also makes
them an additional monitor of ?rms. Evidence suggests that institutional investors are
successful in this role. Karpoff (2001) documents numerous event-type studies which
suggest that institutional investors are successful in shareholder activism, and work
and prompt ?rms to act in accordance with investors’ needs. Further, cross-sectional
studies have shown via ?rm performance (Brickley et al., 1988; Cornett et al., 2007),
corporate governance (Abdul Wahab et al., 2007) earnings management (Koh, 2007;
Chung et al., 2002) and director remuneration (Hartzell and Starks, 2002; Almazan et al.,
2005) that institutional investors are effective monitor of the ?rm.
The Asian Financial Crisis of 1997-1998 also initiated an increased awareness
regarding the role of institutional investors, especially in relation to reducing agency
costs[1]. For instance, the Finance Committee on Corporate Governance, a corporate
governance committee set up by the Malaysian government, suggests that a minority
shareholders’ watchdog group led by EPF should play a proactive role in institutional
monitoring of ?rms. Further, Abdul Samad (2004) argues that ownership structure is
one of the most important factors in determining the nature of agency costs in a
governance system. In particular, Asian ?rms’ agency problems are not primarily
between managers and shareholders. Instead they are primarily between minority and
majority shareholders (Claessens and Fan, 2002). The dominant agency problemoutside
the western world is between controlling shareholders and minority shareholders.
We analyse the extent of institutional monitoring in Malaysia and its relationship
with external auditors, since external auditors are likely to play a governance role (Fan
and Wong, 2005). Thus, we aim to examine the relationship between institutional
investors and audit quality. We use audit fee as a proxy of audit quality since higher
audit fees are associated with higher audit quality (Goodwin-Stewart and Kent, 2006;
Francis, 2004). We argue that in the presence of highly concentrated ownership and
family control ?rms (Claessens et al., 2000; Abdul Samad, 2004), which creates an agency
con?ict between majority and minority shareholders, institutional investors demand
better audit effort from external auditors to monitor management and majority
shareholders. Furthermore, institutional investors are expected to monitor since they
have the resources (Shleifer and Vishny, 1997), size (Jennings, 2005) and ?duciary duties
(Hawley and William, 1997) to in?uence the ?rms. We then extend our investigation by
examining institutional investors’ heterogeneity, speci?cally on the basis of whether the
institutional investors have a business relationship with the ?rms. We argue that
institutional investors that hold no business relationship impose less pressure upon the
?rms’ management and are more likely to agree with management’s policies. Relatively,
these investors are more active in monitoring the ?rms in comparison with those
investors that hold a business relationship[2].
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Furthermore, we also include a variable that is important in the Malaysian context.
Since, the Malaysian capital market operates within the context of a racially diverse
society and past evidences suggest that Malaysian has politically connected or
favoured ?rms (Gomez and Jomo, 1999; Gul, 2006; Johnson and Mitton, 2003), we
include one context-speci?c variable namely political connection. Similar to prior
studies, we predict that political connection is important in explaining the variation in
audit fees as political-connected ?rms are generally perceived to entail poor corporate
governance and greater agency problems. Such perceptions in turn are expected to
increase monitoring costs leading to higher audit fees.
Our results, based on 390 non-?nancial ?rms listed on Bursa Malaysia during the
period 1999-2003 indicate a positive relationship between institutional ownership and
audit fees. This appears in line with the notion that institutional investors in Malaysia
play a monitoring role by demanding greater audit effort from the auditors resulting in
increased audit fees. Furthermore, we ?nd investors’ heterogeneity in?uences the
relationship between institutional ownership and audit fees. In particular, our results
document a positive relationship between institutional investors that do not have the
relationship with the ?rm and audit fees. Our analysis of individual institutional
investors indicates that audit fees are positively and signi?cantly related to EPF and
Permodalan Malaysia Berhad, arguably the two most dominant institutional investors
in Malaysia. Interestingly, we also ?nd evidence to suggest that politically connected
?rms pay audit fee premiums due to the greater perceived risk inherent in politically
connected ?rms, leading auditors to exert greater audit effort for these ?rms.
We contribute to the growing body of published literature in this area in a number
of ways. First, most prior studies examining the link between the roles of institutional
investors and audit fees particularly their monitoring roles in mitigating agency costs
tend to study countries with well-developed capital markets such as the USA and
Australia (O’Sullivan, 2000; Kane and Velury, 2004). Our study is conducted in
Malaysia, where the capital market is still at a developing stage and the rules and
regulation with respect to corporate governance are still in their infancy. Further, our
study explores the relationship between institutional investors’ heterogeneity
speci?cally on the basis of their relationship with the ?rms and audit fees. This
allows us to evaluate how the relationship between institutional investors and ?rms
undermines the potential monitoring effectiveness of institutional investors.
Second, although there are similarities in terms of accounting practices and the
regulatory environments in Malaysia with the UK, the USA and Australia (Gul, 2006).
The corporate environment and institutional division in Malaysia are unique because of
the existence of politically-favoured corporations, ethnicity, language and religion
(Haniffa and Cooke, 2002; Yatimet al., 2006; Gul, 2006). Particularly, this is the case of the
Malaysian government’s intervention in the corporate sectors to initiate the
participation of Bumiputera in the Malaysian economy starting from the introduction
of the government’s neweconomic policy (NEP) in 1969. Given this unique environment,
it is worthwhile to further extend the audit pricing literature by examining the
political-related factors and the extent of audit fees paid to the auditors.
To date, a review of literature indicates that several studies have examined the
relationship between political connections (Johnson and Mitton, 2003; Gul, 2006);
ethnicity (Eichenseher, 1995; Yatim et al., 2006). Overall, these studies argue that
politically connected ?rms and Bumiputera-controlled ?rms are favoured and generally
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perceived to be riskier, and have greater agency problems leading to increased
monitoring costs. Johnson and Mitton (2003) utilise two-years data of Malaysian listed
companies (1997 and 1998), Gul (2006) covers three years (1996-1998), where as Yatim
et al. (2006) onlycover one year (2003). Incontrast, the data of our study covers a periodof
?ve years (1999-2003) and our study utilises panel data which allows us to control
heterocedasticity and contemporaneous correlations in each cross-section. Since, the
data for this study covers the period pre- and post-governance reforms in Malaysia, our
study provides an alternative or extended view on the role of auditors, subsequent to
corporate governance reforms in 2001. In addition, we explore an interaction between
political-connected ?rms and audit fees when the institutional investors are present and
?nd evidence to suggest that institutional investors are an effective monitor especially in
relation to politically connected ?rms.
In the next section, we provide background on the Malaysian institutional investors
followed by hypotheses development in Section 3. Research methods and data description
are discussed in Section 4 and Section 5 presents the results. Section 6 concludes.
2. Institutional background
2.1 Institutional investors in Malaysia
Institutional shareholdings in Malaysia are high compared to most other nations in
South-East Asian. As at 2003, the total institutional shareholding in Malaysia was
approximately 13 per cent of the total market capitalisation of Bursa Malaysia. This is
a primary consequence of the 1970 NEP which establishes the Malaysian institutional
investors. Further, the NEP aims to reduce equity ownership imbalance between the
various ethnic groups through increasing Bumiputeras equity ownership in the capital
market (Gomez and Jomo, 1999; Tan, 2004)[3],[4]. To date, there are a few major
institutional shareholders in Malaysia namely EPFs; Permodalan Nasional Berhad
(PNB), Lembaga Tabung Angkatan Tentera (LTAT), Lembaga Tabung Haji (LTH)
and Pertubuhan Keselamatan Sosial.
EPFs is a pension fund for all employees and is the largest institutional investor in
Malaysia. It has total assets in excess of US$50 billion, which is more than half of
Malaysia’s gross domestic product (Thillainathan, 2000). An interesting feature of
EPFs is the presence of strong government control. For example, Malaysian law
requires EPFs to invest 70 per cent of its funds in Malaysian government securities,
while its investment in the domestic stock market cannot exceed 25 per cent. EPFs is
also prohibited from making overseas investments (Thillainathan, 2000).
The next major institutional investor is the ?rst unit trust established in Malaysia.
Established in 1972, Permodalan Malaysia Berhad is Malaysia’s ?rst unit trust
(ownership-in-trust) set up to encourage savings by Bumiputeras. It started with a
single unit trust called Amanah Saham Nasional but now has multiple unit trusts that
cater for all groups of people such as the youth (e.g. Amanah Saham Didik) and the
non-Bumiputeras (e.g. Amanah Saham Malaysia). These unit trusts act as savings
schemes that pay competitive dividends (average of nearly 8 per cent over the past ten
years) (Gomez and Jomo, 1999). As at the end of 2003, PNB managed over Ringgit
Malaysia (RM) 15 billion worth of public and private equity in Malaysia, representing
about two-thirds of its total investment (www.pnb.com.my).
LTAT is the next largest institutional investor which was established in August
1972 by an act of Parliament. LTAT serves as a superannuation fund for the Armed
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Forces of Malaysia[5]. Similar to EPF, its objectives are to provide retirement and other
bene?ts to members of the Armed Forces (compulsory contributors) and to enable
of?cers and mobilised members of the volunteer forces in the services to participate in
a savings scheme.
Another major institutional investors is LTH, which was formed in 1962, aiming to
encourage Malaysian Moslems to save for journeys to Mecca for pilgrimage. Its role
has evolved from a saving depository to providing Malaysian Moslems some returns
on their investments. Like other major institutional investors (EPF, LTAT and
Permodalan Malaysia Berhad), LTH’s investment advisory board includes Islamic
scholars who must make sure that all investments are in accordance with syariah[6].
The ?nal key institutional investor is Pertubuhan Keselamatan Sosial established in
January 1971 by another act of Parliament, through the Social Security Act 1969.
Pertubuhan Keselamatan Sosial serves as an insurance scheme for all Malaysians
working in either the public or the private sector. Pertubuhan Keselamatan Sosial’s
main objective is to ensure and guarantee the timely and adequate provision of bene?ts
in a socially just manner and to promote occupational health and safety. Similar to the
other institutional investors mentioned above, Pertubuhan Keselamatan Sosial has an
investment advisory board consisting of various representatives from the government,
employers and employees.
As the domestic ?nancial systemgrew around commercial banks, other institutional
investors also began to play a part in the domestic ?nancial system. Amongst these are
foreign institutional investors such as California Public Employees’ Retirement System;
Teachers Insurance and Annuity Association – College Retirement Equities Fund; and
United Nation Pension Funds and State of Ohio Retirement Scheme. Collectively, foreign
institutional investors account for about 1 per cent of total institutional ownership in
Malaysia.
2.2 Political connection in Malaysia
Another unique feature in Malaysia is the close links of many large corporations or
conglomerates with the government[7]. Given the close connections to the government,
these politically-linked companies have exclusive business relationships with
state-owned enterprises and have preferential access to major government contracts
(Gomez and Jomo, 1999; EAU, 2002b). For instance, these ?rms are argued to use their
political in?uence in order to have easy access to loans which are usually “soft”, and
which are often obtainable from government-backed banks or state development
bodies and pension funds (EAU, 2002a, b; Yoshihara, 1988).
Many large corporations with substantial loans provided by the state are usually
owned by the state and non-performing as a result of the 1997/1998 ?nancial crisis. For
example, Malaysian resources now owe loans of RM 600-RM 700 million mainly to the
EPF[8]. Likewise, the results of prior studies indicate that political-connected ?rms in
Malaysia are favoured by the government. For instance, Johnson and Mitton (2003)
?nd that politically connected ?rms had a larger drop in share price in comparison to
non-politically connected ?rms. Similarly, Gul (2006) ?nds that politically connected
?rms are being charged higher audit fees by audit ?rms during the onset of the
1997/1998 ?nancial crisis, but declined when the government introduced capital
controls to assist these ?rms.
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2.3 Auditing in Malaysia
Auditors in Malaysia are bound by standard of auditing practices and requirements
similar to other countries[9]. The Companies Act 1965 stresses the need for the auditor
to be independent and gives auditors broad powers to inspect records and to obtain
information for audit, as well as the right to attend and address general meetings of
?rms (Ali et al., 2006). In their documentary analysis, Ali et al. (2006) argue that
auditing practice in Malaysia merely aims to ful?l legal requirements and provide an
image of a modern economy to attract investments from overseas rather than to
address the unique needs of a multi-cultural society[10]. As at the date of this study, the
Big n auditors control nearly 70 per cent of the audit market in Malaysia.
3. Hypotheses development
Two hypotheses are developed in this section: H1 relates to the link between audit fees
and institutional ownership whereas H2 relates to audit fees association with
political-connected ?rms. These hypotheses present arguments on the demand side
(H1) and the supply side (H2) of audit services. From the demand side, it can be argued
that some clients, i.e. institutional investors, may demand a greater level of monitoring
to minimise agency problems and hence results in higher audit fees. From the supply
side, the inherent poor ?rm performance of politically connected ?rms is due to
inef?ciencies and lack of corporate governance. These type of ?rms involve greater
risk corresponding with an increase of audit effort. As a consequence, higher audit fees
will be charged by the auditors (Gul, 2006).
We argue from both the demand and supply sides of audit services because in
Malaysia, the presence of institutional investors is also prevalent in politically connected
?rms since major investors are controlled either directly or indirectly by the government
and thus serve political needs (Norhashim and Abdul Aziz, 2005). This creates an
interesting view on how such relationship could in?uence the pricing of audit services.
We argue that regardless of the risk borne by politically connected ?rms, institutional
investors could still play a monitoring role, and thus demand better audit services.
Further, in order to remove doubts about motives for their shareholdings in politically
connected ?rms and because these ?rms may have a higher probability of ?nancial
misstatement, institutional investors have to demand, at the least the same quality level
of audit services from auditors (if not at a higher level). In other words, it may be less
acceptable to their key stakeholders for institutional shareholders to operate passively
especially when they hold shares in politically connected ?rms.
3.1 Institutional ownership and audit fees
The relationship between institutional investors and audit fees arises out of the agency
problem, which exists between managers and shareholders, or between shareholders
themselves, i.e. majority and minority shareholders. We observe from Claessens et al.
(2000) that East Asian ?rms are highly concentrated and often controlled by a
conglomerate or a particular family. Therefore, the presence of institutional investors,
playing a monitoring role overcomes, or at least minimises the agency problem within
Malaysian ?rms. Knechel and Willekens (2006) and Hay et al. (2008) argue that
variation of audit fees arises from various factors including the cost of audit efforts, the
auditor’s legal liability (Simunic, 1980) and demand from various stakeholders. For
instance, a concentrated shareholding structure in a ?rm controlled by a few
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individuals could yield a demand for better audit effort from minority shareholders.
This scenario may be prevalent in the Malaysian capital market, as observed by
Claessens et al. (2000).
Furthermore, institutional investors are expected to monitor and demand better
audit of the ?rms since they have the resources (Shleifer and Vishny, 1997), expertise in
analysing ?nancial statements (Hand, 1990), ability to apprehend media-pressure (Wu,
2004) and size (Jennings, 2005). The institutional investors, on average, are better
informed than individual investors because of their large-scale development and
analysis of timely and valuable ?rm-speci?c information (Wahal and McConnell, 2000).
Importantly, they have ?duciary duties to serve their contributors and minority
shareholders of their ?rms (Hawley and William, 1997). This is relatively important
since much of the agency problem in Asian ?rms is between majority and minority
shareholders (Claessens and Fan, 2002), thus making institutional investors an ideal
monitor or representative of minority shareholders.
Prior empirical studies support the notion that large institutional shareholdings have
an impact on audit fees. For instance, O’Sullivan (2000) and Kane and Velury (2004)
document a positive relationship between large institutional shareholdings and audit
fees. On the basis of earnings quality, Kane and Velury (2004) argue that a positive
relationship exists between audit and earnings qualities. Assuming that institutional
investors are in?uential and demand high-quality earnings information, the level of
institutional ownership should be positively related with the provision of audit quality
(Kane and Velury, 2004). Interestingly, Velury et al. (2005) also ?nd that ?rms having
greater levels of institutional ownership tend to employ industry specialist audit ?rms.
This indicates that these ?rms emphasise higher quality audits due to the demand from
their institutional investors which act as monitoring mechanisms. This in turn is
re?ected by the level of audit fees. Mitra et al. (2007) ?nd a positive and signi?cant
relationship between diffused institutional ownership (less than 5 per cent) but a
negative relationship between institutional investors which hold more than 5 per cent
and audit fees. Thus, the above arguments suggest the following hypothesis:
H1. Higher institutional ownership is associated with higher audit fees.
3.2 Political-connected ?rms and audit fees
Unlike other countries, Malaysia has a unique corporate environment which offers clear
identi?able segments of ethnic line. It is also generally accepted that Malaysia has
favoured ?rms (known as politically connected ?rms) (Gomez and Jomo, 1999; Gul, 2006)
as a result of the government’s intervention following the introduction of NEP with the
intention to increase the Malay equity in the country. Johnson and Mitton (2003) provide
evidence that it was politically connected ?rms that suffered the most during the early
stages of the Asian ?nancial crisis. Their share price dropped comparatively more than
their counterparts because it is assumed that the government would be unable to extend
privileges to these ?rms. Likewise, a recent study by Gul (2006) provides empirical
evidence to support the proposition that auditors perceive greater risk inherent in
politically connected ?rms leading to greater audit effort which in turn leads higher fees.
This is because these ?rms have a higher probability of their business failing, and are
more likely to misstate their ?nancial position in their ?nancial statements to avoid
covenant violations. Further, Gul (2006) documents evidence of “crony-capitalism” in
Malaysia by demonstrating that there was a comparatively greater increase in audit fees
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for politically connected ?rms following the Asian Financial Crisis in 1997/1998. The
audit fees for these ?rms declined following the government’s introduction of capital
controls as a way of helping their preferred ?rms. Based on the arguments presented
above, we posit the following hypothesis:
H2. Politically connected ?rms are associated with higher audit fees.
4. Research methods and data description
The panel data set consists of 390 non-?nancial ?rms for ?ve years from 1999 to 2003.
Financial ?rms are eliminated, since prior research shows that determinants of audit
fees are unique for such ?rms (Simunic, 1980). The data used for this study is primarily
collected from Compustat Global and ?rms’ annual reports. We use two alternative
sources, the Stock Performance Guide handbook and DataStream database for missing
data. This study uses period seemingly unrelated regressions to handle both
heterocedasticity and contemporaneous correlations in each cross-section.
We posit the following audit fees model:
LAF
it
¼ a
0
INTERCEPT
it
þa
1
INSTOWN
it
þa
2
POLCON
þa
3
INSTOWN
*
POLCON þa
4
LNASSETS
it
þa
5
CURRENT
it
þa
6
LIQUID
it
þa
7
LNSUBS
it
þa
8
LNFOREIGN
it
þa
9
YE
it
þa
10
DEBT
it
þa
11
ROA
it
þa
12
LOSS
it
þa
13
MANOWN
it
þa
14
BIG_N
it
þa
15
SWITCH þa
16
INDUSTRY
it
þe
it
The experimental variables are in bold, where:
Dependent variable
LAF Natural logarithm of audit fees.
Panel A: experimental variables
INSTOWN – Top ?ve institutional shareholdings in each ?rm.
POLCON – An indicator variable, 1 for politically connected ?rms, 0 otherwise.
Panel B: control variables
LNASSETS – Natural logarithm of total assets.
CURRENT – Current assets to total assets.
LIQIUD – Current assets to current liabilities.
LNSUBS – Natural logarithm of number of subsidiaries.
LNFOREIGN – Natural logarithm of number of foreign subsidiaries.
YE – An indicator variable, 1 for ?scal year ending 31 December, 0
otherwise.
DEBT – Total debt to total equity.
ROA – Net pro?t before tax divided by total assets.
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LOSS – An indicator variable, 1 for loss in the last year, 0 otherwise.
MANOWN – Managerial ownership.
BIG_N – An indicator variable, 1 for Big n audit ?rm, 0 otherwise.
SWITCH – An indicator variable, 1 for ?rms switching auditor, 0 otherwise.
INDUSTRY – Industry dummies that take a value of 1 for ?rms belonging to
(construction), (consumer), high technology and 0 for otherwise.
4.1 Dependent variable
The dependent variable is the audit fee which is measured by the RM value of the audit
fee paid by the ?rm to its auditor. Consistent with previous studies (Francis, 1984;
Francis and Simon, 1987) and following tests of normality, logarithmic transformation
is applied to the audit fee (LAF)[11]. The audit fee data are obtained from Compustat
Global and annual reports.
4.2 Experimental variables
The main experimental variable for this study is institutional ownership (INSTOWN)
which consists of the top ?ve institutional investors’ shareholding in each ?rm. The
institutional ownership data are extracted from annual reports which were obtained
from Bursa Malaysia’s web site and Mergent Online database. We argue that top ?ve
institutional investors represent the level of institutional monitoring in a ?rm as stated
by Hartzell and Starks (2002)[12]. The second experimental variable is political
connection (POLCON) which takes a value of one if the ?rm is considered as politically
connected or zero otherwise. The political connection (POLCON) list is presented in the
Appendix and is derived from Johnson and Mitton (2003), Mohamad et al. (2006) and
Khazanah Nasional Berhad web site[13].
4.3 Control variables
Audit fees model employed in prior research have used a variety of variables to control
for cross-sectional differences associated with auditee size, complexity and the risk of
the client ?rm (Simunic, 1980; Craswell, 1992; Gul and Tsui, 1997). These empirical
models have demonstrated good explanatory power and have been robust across
different samples and different periods of time.
We adopt several standard control variables used in past studies including size,
complexity, risk and audit quality in this paper. The effects of size are controlled for
with the natural log transformation of total assets (LNASSETS). We posit a positive
relationship between ?rm size and audit fees since larger ?rms are more complex
which requires more audit effort, resulting in higher audit fees (Simunic, 1980; Francis,
1984). Equally important, we take into account of the natural log transformation of
total subsidiaries (LNSUBS) and foreign subsidiaries (LNFOREIGN) to control for
audit complexity (Simunic, 1980; Hackenbrack and Knechel, 1997) which implies that
more subsidiaries result in a greater amount of work in consolidation and eliminating
intra-group transactions (Chan et al., 1993; Pong and Whittington, 1994) and subject to
numerous statutory and professional requirements of disclosure (Chan et al., 1993).
We include the ratio of current assets to total assets (CURRENT) to control for
inherent risk. We argue a positive relationship between CURRENT and audit fees
Audit quality
in Malaysia
175
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because certain parts of the audit may have a higher risk of error and require specialised
audit procedures (Simunic, 1980; Francis and Simon, 1987). Liquidity is controlled for by
including the working capital ratio represented by the ratio of current assets to current
liabilities (LIQUID). Furthermore, we include the debt ratio which is total debt to total
equity (DEBT) to control for ?rms’ leverage (Gist, 1992; Craswell and Francis, 1999). We
also include direct managerial ownership (MANOWN) to control for other ownership
structure and we predict a negative relationship between MANOWN and LAF.
The ?scal year-end is controlled for with a dummy variable set as one for those ?rms
with a 31 December ?scal year-end and zero otherwise. Most ?rms in the sample have a
December year-end. Return on assets (ROA) is used as a proxy for pro?tability and we
predict a negative relationship between ROA and audit fees. In addition, we include a
dummy for ?rms which recorded a loss (LOSS), demonstrating ?nancial distress (Pong
and Whittington, 1994) in the previous year in which a positive relationship is predicted.
A dummy variable for Big n auditing ?rms (BIG_N) is also incorporated to control for
differences in audit quality as it is expected that ?rms associated with large auditing
?rms purchase a higher level of audit quality (DeAngelo, 1981; Carcello et al., 2002)[14].
Further, we give the value of one for ?rms that switch (SWITCH) their auditor during
the sample period and we predict a non-directional relationship between SWITCH and
LAF. Fixed effects (PERIOD) is included to control for any unobserved events that
occurred during the sample period that might in?uence the variation of audit fees.
Finally, industry dummies (INDUSTRY) that take a value of one for ?rms belonging to
the construction, consumer, high technology and other sectors and zero otherwise are
included to control for variations in audit fees across industries, since it is conventional
wisdom that these industries have higher complexities and are more dif?cult to audit
(Simunic, 1980; Turpen, 1990; Pearson and Trompeter, 1994) (Table I)[15].
4.4 Descriptive statistics
Table II presents the descriptive statistics for sample ?rms used in this study. The
average (median) audit fees (AF) is RM 282,000 (RM 114,000), and ranging from RM
500 to RM 9.4 million. Panel A of Table II documents descriptive analysis for
experimental variables. INSTOWNaverages 12.069 per cent with a range between 0 and
90.553 per cent. INSENSITIVE, SENSITIVE and INDETERMINATE institutional
investors hold an average of 7.187, 1.029 and 3.852 per cent of institutional
shareholdings. In relation to individual institutional investors, PNB tops the list with an
average of 3.852 per cent while EPF is a second with 2.477 per cent. LTAT, LTH and
Pertubuhan Keselamatan Social (SOCSO) on average hold 0.922, 0.955 and 0.047 per
cent, respectively, from the total institutional shareholdings. Their cumulative
shareholdings constitute nearly 68 per cent of total institutional investors’
shareholdings. Finally, 21.1 per cent of the sample ?rms are politically connected.
Clients attributes’ descriptive are presented in Panel B of Table II. Sample ?rms’
size (ASSETS) averages RM 1.886 billion with a range between RM 1.259 million and
RM 64.41 billion. On average, sample ?rms have 29.321 subsidiaries with 6.604 of them
being domiciled outside Malaysia. Sample ?rms record a mean (median) of 0.367 (0.351)
and 3.584 (1.589) for CURRENT and LIQUID, respectively. Firm are highly levered
(DEBT) at on average of 1.425 and 47.1 per cent of ?rms end their ?scal year at
31 December (year-end). Managerial ownership (MANOWN) has on average of
7.681 per cent and ranges from 0 to 79.773 per cent. ROA averages 5.473 per cent and
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18.3 per cent of sample ?rms’ experience loss (LOSS) during the previous year. Further,
almost 70 per cent of ?rms are being audited by a Big n audit ?rms and 12.5 per cent of
the sample ?rms switched their auditors during this period.
Table III presents the correlations between the test variables. Pearson correlation
records positive and signi?cant correlations at 1 per cent level between INSTOWN and
LAF at 0.236 and 0.210, respectively[16]. The table also documents signi?cant and
positive correlation between LAF and ASSETS, LNSUBS, LNFOREIGN, MANOWN
and POLCON[17].
No. Variables Sign De?nition Sources
1 LAF Natural logarithm of audit fees Compustat Global and Annual
Reports
Panel A: experimental variables
2 INSTOWN þ Top ?ve institutional shareholdings
in each ?rm
Annual Reports
3 POLCON þ An indicator variable, 1 for
politically connected ?rms, 0
otherwise
Johnson and Mitton (2003),
Mohamad et al. (2006) and Khazanah
Berhad web site (www.khazanah.
gov.my)
Panel B: client attributes
LNASSETS þ Natural logarithm of total assets Compustat Global, DataStream and
Stock Performance Guide
CURRENT þ Current assets to total assets Compustat Global, DataStream and
Stock Performance Guide
5 LIQUID þ Current assets to current liabilities Compustat Global, DataStream and
Stock Performance Guide
7 LNSUBS þ Natural logarithm of number of
subsidiaries
Mergent Online and Annual Reports
8 LNFOREIGN þ Natural logarithm of number of
foreign subsidiaries
Mergent Online and Annual Reports
9 YE 2 An indicator variable, 1 for ?scal
year ending 31 December, 0
otherwise
Annual Reports
10 DEBT þ Total debt to total equity Compustat Global, DataStream and
Stock Performance Guide
11 ROA 2 Net pro?t before tax over total assets Compustat Global
12 LOSS þ An indicator variable, 1 for loss in
the last year
Compustat Global
13 MANOWN 2 Managerial ownership Annual Reports
14 BIG_N þ An indicator variable, 1 for Big n
audit ?rms, 0 otherwise
Compustat Global and Annual
Reports
16 SWITCH ? An indicator variable, 1 for ?rms
switching auditor, 0 otherwise
Compustat Global
18 ? Industry dummies that take a value
of 1 for ?rms belonging to the
construction (CONSTRUCTION),
consumer (CONSUMER), high
technology (TECHNOLOGY) and
other (OTHER) sectors and 0
otherwise
Bursa Malaysia’s web site
Table I.
De?nition and expected
direction of variables
Audit quality
in Malaysia
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Mean Median Maximum Minimum SD
Dependent variable
AUDIT FEES (‘000) 282.2 114.0 9400 0.500 656.9
LAF 11.783 11.653 16.056 8.006 1.118
Panel A: experimental variables
INSTOWN 12.069 6.035 90.553 0.000 16.654
INSENSITIVE 7.187 2.272 78.566 0.000 13.414
SENSITIVE 1.029 0.000 23.660 0.000 2.163
INDETERMINATE 3.852 0.000 75.269 0.000 9.468
EPF 2.477 0.357 28.960 0.000 3.927
PNB 3.852 0.000 75.269 0.000 9.468
LTAT 0.922 0.000 74.545 0.000 5.816
LTH 0.955 0.000 25.750 0.000 2.985
SOCSO 0.047 0.000 2.944 0.000 0.221
POLCON 0.211 0.000 1.000 0.000 0.408
Panel B: client attributes
ASSETS (‘000) 1,886,000 587,800 64,410,000 1,259 5,192,000
LNASSETS 20.341 20.197 24.888 14.046 1.311
CURRENT 0.367 0.351 9.068 0.000 0.329
LIQUID 3.584 1.589 195.090 0.000 11.626
SUBS 29.321 15.000 408.000 0.000 43.837
LNSUBS 1.435 2.708 6.011 211.513 4.459
FOREIGN 6.604 1.000 224.000 0.000 17.536
LNFOREIGN 23.329 0.000 5.412 211.513 6.387
YE 0.471 0.000 1.000 0.000 0.499
DEBT 1.425 0.400 37.919 0.000 3.674
ROA 5.473 5.219 140.162 288.504 11.711
LOSS 0.183 0.000 1.000 0.000 0.387
MANOWN 7.681 0.559 79.773 0.000 14.410
BIG_N 0.689 1.000 1.000 0.000 0.463
SWITCH 0.125 0.000 1.000 0.000 0.331
Notes:
@
Observations having a zero for LNSUBS or for LNFOREIGN are re-coded to a small positive
(0.0001) to enable a logarithmic transformation; AF is audit fees while LAF is natural logarithm of
audit fees; INSTOWN is the percentage shareholdings by top ?ve institutional investors;
INSENSITIVE, SENSITIVE and INDETERMINATE are percentage shareholdings held by
pressure insensitive, sensitive and indeterminate investors, respectively; EPF, PNB, LTAT, LTH
and SOCSO are percentage shareholdings held by EPF, PNB, LTAT, LTH and Pertubuhan
Keselamatan Sosial investors, respectively; POLCON takes the value of 1 for politically connected
?rms and 0 otherwise; ASSETS, is total assets while LNASSETS is natural log transformation of
ASSETS; CURRENT is current assets to total assets; LIQUID is current assets to current liabilities;
SUBS is the number of subsidiaries while LNSUBS is the natural log transformation of SUBS;
FOREIGN presents the number of foreign-domicile subsidiaries and LNFOREIGN is the natural log
transformation of FOREIGN; YE takes the value of 1 if the ?scal year-end is 31 December; DEBT is
total debt over total equity; ROA is earnings divided by total assets; LOSS takes the value of 1 if the
?rm recorded a loss in the previous ?scal year; MANOWN is managerial shareholdings; BIG_N takes
the value of 1 for Big n auditors and 0 otherwise; SWITCH takes the value of 1 for ?rm switching
auditor and 0 otherwise
Table II.
Descriptive statistics for
sample ?rms (1999-2003)
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Table III.
Correlations matrix for
sample ?rms (1999-2003)
Audit quality
in Malaysia
179
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R
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A
t
2
1
:
0
8
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
5. Results and discussion
5.1 Multivariate analysis
Table IV tabulates panel least squares results for the 390 non-?nancial sample ?rms.
We observe positive and signi?cant intercepts or constant terms across all model
LAF
Model 1 Model 2 Model 3
CONSTANT 3.108 3.924 4.180
4.746
* * *
5.721
* * *
6.051
* * *
INSTOWN 0.007 0.003
3.002
* * *
0.980
POLCON 0.162 0.031
1.652
*
0.275
INSTOWN
*
POLCON 0.010
2.246
* *
LNASSETS 0.438 0.396 0.385
14.342
* * *
12.137
* * *
11.752
* * *
CURRENT 0.343 0.304 0.303
4.455
* * *
3.988
* * *
4.008
* * *
LIQUID 20.015 20.015 20.015
2 5.160
* * *
2 5.176
* * *
2 5.321
* * *
LNSUBS 0.011 0.011 0.012
1.147 1.133 1.235
LNFOREIGN 0.033 0.034 0.033
4.715
* * *
4.848
* * *
4.799
* * *
YE 20.003 0.020 0.020
2 0.042 0.281 0.274
DEBT 20.014 20.013 20.014
2 2.099
* *
2 1.955
*
2 2.098
* *
ROA 20.002 0.000 0.000
2 0.645 2 0.120 2 0.133
LOSS 0.111 0.102 0.114
1.602 1.470 1.653
*
MANOWN 20.005 20.003 20.004
2 1.985
*
2 1.399 2 1.515
BIG_N 0.103 0.061 0.062
1.391 0.820 0.843
SWITCH 0.167 0.142 0.135
2.255
* *
1.899
*
1.826
*
Industry ?xed Yes Yes Yes
Period ?xed Yes Yes Yes
Adjusted R
2
0.426 0.436 0.440
F-statistic 64.939
* * *
60.000
* * *
58.387
* * *
Notes: Signi?cant at:
*
10,
* *
5 and
* * *
1 per cent levels, respectively; t-statistics are italicised; probabilities
are one-tailed when in direction predicted; LAF is natural logarithmof audit fees; INSTOWNis the percentage
shareholdings by top ?ve institutional investors; POLCON takes the value of 1 for politically connected ?rms
and 0 otherwise; LNASSETS is natural log transformation of total assets; CURRENTis current assets to total
assets; LIQUID is current assets to current liabilities; LNSUBS is the natural log transformation of SUBS;
LNFOREIGNis the natural log transformation of FOREIGN; YEtakes the value of 1 if the ?scal year-end is 31
December; DEBTis total debt over total equity; ROAis earnings divided by total assets; LOSS takes the value
of 1 if the ?rmrecorded a loss in the previous ?scal year; MANOWNis managerial shareholdings; BIG_Ntakes
the value of 1 for Big n auditors and 0 otherwise; SWITCHtakes the value of 1 for ?rmswitching auditor and 0
otherwise; n ¼ 390 ?rms
Table IV.
Panel least squares for
sample ?rms (1999-2003)
ARJ
22,2
180
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A
t
2
1
:
0
8
2
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a
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a
r
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2
0
1
6
(
P
T
)
speci?cations, which indicate ?xed cost in setting up the audit irrespective of the
attributes captured by other variables (Pong and Whittington, 1994). In comparison to
other Malaysian studies in this area (Yatim et al., 2006), our adjusted R
2
is only around
43 per cent across all models whereas a study by Yatim et al. (2006) indicates an
adjusted R
2
of 69 per cent. This may be due to different control variables used in the
study. Our study uses current ratio and current assets to current liabilities to measure
liquidity whereas Yatim et al. (2006) include receivable to total assets and inventories
to total assets.
Consistent with prior audit fee studies (Simunic, 1980; Yatim et al., 2006; Gul, 2006;
Ferguson, 2005), we ?rst regress audit fees on the control variables only. Results for
basic audit fees model are shown in Columns 1 (hereafter Model 1) of Table IV. The
adjusted R
2
for Model 1 is 42.6 per cent[18]. The signs for client attributes variables are
all in the predicted direction. All other variables remain signi?cant with the exception
of LNSUBS, YE, ROA and LOSS. LNASSETS coef?cient is positive and signi?cant at
1 per cent level (0.438, t ¼ 14.342, p , 0.001), CURRENTalso positive and signi?cant at
1 per cent level (0.343, t ¼ 4.445, p , 0.001). LNFOREIGN coef?cient is ?nd to be
positive at 1 per cent level (0.033, t ¼ 4.715, p , 0.001). Our results indicate that LIQIUD
and DEBT to be negatively associated with audit fees at 1 per cent level (20.015,
t ¼ 5.160, p , 0.001; 20.014, t ¼ 22.099, p , 0.001, respectively). We ?nd the
MANOWN coef?cient to be negative and statistically signi?cant at the 10 per cent
level[19]. The results showthe SWITCHcoef?cient to be positive and signi?cant at 5 per
cent level (0.167, t ¼ 2.255, p , 0.05), BIG_N is in the right direction but insigni?cant.
The main panel least squares results are reported in Column 2 of Table IV (hereafter
refer to Model 2). H1 predicts a positive relationship between institutional ownership
and audit fees. We ?nd the coef?cient for INSTOWN to be positive and signi?cant at 1
per cent level (0.007, t ¼ 3.002, p , 0.001) (as reported in Model 2 of Table IV), thus
providing support for H1. This fully supports the notion that institutional investors do
mitigate agency costs as a monitor of ?rms by demanding a higher quality audit from
auditors, prompting higher audit fees. This also suggests that institutional investors’
roles are not only to monitor management and major shareholders (Knechel and
Willekens, 2006; Hay et al., 2008) but also to play a representative role for minority
shareholders in demanding a higher quality audit. Nevertheless, the parameter of 0.007
represents audit fee premium of only 0.702 per cent, acknowledging that although a
positive relationship is observed between institutional ownership and audit fees, the
economic impact is minimal[20]. Nevertheless, the outcome should be considered as
promising and suggests a potential role for institutional investors. Results for all
control variables generally remain similar, with the exception of MANOWN, which
remains in the same direction but is now not signi?cant.
H2 predicts a positive relationship between political connectedness and audit fees.
The coef?cient for POLCON is positive and signi?cant (0.162, t ¼ 1.652, p , 0.10) thus
providing support for the arguments forwarded by Gul (2006). The parameter of 0.162
suggests that the audit fee premium for politically connected ?rms is 17.58 per cent.
Findings also suggest that auditor do perceive politically connected ?rms to have
greater inherent risk than non-politically connected ?rms leading to their demand for
more audit effort which in turn leads to these ?rms being charged higher audit fees.
We further explore political-connected ?rms and audit fees when institutional
investors are present in these ?rms (as reported in Model 3, Column 3 of Table IV).
Audit quality
in Malaysia
181
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R
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S
I
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A
t
2
1
:
0
8
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
The coef?cient for the interaction in terms of political connectedness with the presence
of institutional investors, INSTOWN
*
POLCON, is positive and signi?cant (0.010,
t ¼ 2.246, p , 0.05). The parameter of 0.010 suggests politically connected ?rms pay
1.005 per cent more audit fees than non-politically connected ?rms when the
institutional investors are present. This indicates that institutional investors act as
monitors and demand more audit effort and work to be undertaken especially in
political ?rms than non-political ?rms. Findings are consistent with prior studies
which suggest that institutional investors are an effective monitor of ?rms especially in
relation to reducing agency costs.
5.2 Further extensions
Several other tests are conducted to extend the basic ?ndings of the paper.
5.2.1 Institutional investors heterogeneity. H1 assumes that institutional investors
are homogenous in relation to objectives, nature of business or relationship with their
investees. In reality, institutional investors differ in various respects. Institutional
investors differ in size, in which some institutional investors are large, mainly due to
the amount of contributors and the nature of the institutions itself. In this sense,
pension funds around the world are large in size. Furthermore, their size can be a factor
in determining their ability to in?uence the ?rms’ managements.
Institutional investors differ in terms of the rules and regulation governing them. As
highlighted by Thillainathan (2000), EPF investments’ heavily emphasise government
bonds and regulation restrictions on overseas investments. Institutional investors such
as insurance ?rms, banks and other ?nancial institutions need to keep high levels of
cash in their funds. Therefore, they are usually required to make short-term returns as
opposed to long-term investment which often yield low returns in the short run. These
mitigating factors thus in?uence how the institutional investors form a relationship
with their investees.
An effectiveness of institutional investors as the monitoring for the ?rm can also be
determined through their business relationship with the ?rms. This relationship may
yield pressure for investors to abide by the position taken by the ?rms’ management to
monitor the ?rms. We argue that any form of relationship between the institutional
investors and the ?rms undermines the potential monitoring effectiveness of the
institutional investors. Furthermore, these institutional investors are not subject to
short-term returns by their contributors. Consistent with the extant literature (Brickley
et al., 1988; Chaganti and Damanpour, 1991; Cornett et al., 2007), we devise variables
that separate the investors according to their business relationship with the ?rms. We
classify institutional investors that do not have any business relationship with the
?rms as pressure-insensitive investors (INSENSITIVE), while investors which have
business relationships are classi?ed as pressure-sensitive (SENSITIVE) investors.
Institutional investors that do not fall in either group are classi?ed as
pressure-indeterminate (INDETERMINATE) investors[21].
Columns 1-6 of Table V present the regressions results which include the various
classi?cations of institutional investors. Model 1 (Column 1 of Table V) regresses
INSENSITIVE investors and POLCON with other control variables. Model 2 (Column 2
of Table V) regresses SENSITIVE investors and POLCON with other control variables.
Model 3 includes INDETERMINATE and POLCON and regresses this other control
variables. For Model 1, we ?nd a positive but statistically insigni?cant coef?cient for
ARJ
22,2
182
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9
1
.
2
5
6
1
.
2
6
9
1
.
2
6
8
L
N
F
O
R
E
I
G
N
0
.
0
3
3
0
.
0
3
2
0
.
0
3
2
0
.
0
3
3
0
.
0
3
2
0
.
0
3
1
4
.
7
2
6
*
*
*
4
.
5
7
9
*
*
*
4
.
6
9
8
*
*
*
4
.
7
4
8
*
*
*
4
.
5
7
4
*
*
*
4
.
5
5
5
*
*
*
Y
E
0
.
0
0
6
0
.
0
0
3
0
.
0
0
9
0
.
0
0
5
0
.
0
0
2
0
.
0
1
2
0
.
0
8
8
0
.
0
3
7
0
.
1
1
9
0
.
0
7
0
0
.
0
2
8
0
.
1
7
2
D
E
B
T
2
0
.
0
1
4
2
0
.
0
1
4
2
0
.
0
1
3
2
0
.
0
1
5
2
0
.
0
1
4
2
0
.
0
1
3
2
2
.
0
8
3
*
*
2
2
.
0
5
2
*
*
2
1
.
9
6
4
*
2
2
.
1
9
9
*
*
2
2
.
0
4
9
*
*
2
1
.
9
6
6
*
R
O
A
0
.
0
0
0
2
0
.
0
0
1
0
.
0
0
0
0
.
0
0
0
2
0
.
0
0
1
2
0
.
0
0
1
(
c
o
n
t
i
n
u
e
d
)
Table V.
Panel least squares
of sample ?rms for types
of institutional investors
(1999-2003)
Audit quality
in Malaysia
183
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
0
8
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
A
F
M
o
d
e
l
1
M
o
d
e
l
2
M
o
d
e
l
3
M
o
d
e
l
4
M
o
d
e
l
5
M
o
d
e
l
6
2
0
.
1
7
0
2
0
.
2
8
0
2
0
.
1
8
5
2
0
.
1
7
2
2
0
.
2
8
2
2
0
.
2
1
7
L
O
S
S
0
.
0
9
5
0
.
0
9
9
0
.
1
0
6
0
.
1
0
4
0
.
0
9
9
0
.
1
1
3
1
.
3
5
4
1
.
4
0
5
1
.
5
3
0
1
.
4
9
5
1
.
4
1
1
1
.
6
3
2
M
A
N
O
W
N
2
0
.
0
0
4
2
0
.
0
0
5
2
0
.
0
0
4
2
0
.
0
0
4
2
0
.
0
0
5
2
0
.
0
0
4
2
1
.
6
7
0
*
2
1
.
8
4
9
*
2
1
.
7
1
4
*
2
1
.
7
5
1
*
2
1
.
8
6
6
*
2
1
.
7
4
3
*
B
I
G
_
N
0
.
0
7
7
0
.
0
8
4
0
.
0
6
7
0
.
0
7
7
0
.
0
8
6
0
.
0
6
8
1
.
0
3
5
1
.
1
3
5
0
.
9
0
2
1
.
0
3
8
1
.
1
6
2
0
.
9
2
5
S
W
I
T
C
H
0
.
1
5
2
0
.
1
5
3
0
.
1
2
9
0
.
1
5
1
0
.
1
5
2
0
.
1
1
7
2
.
0
2
5
*
*
2
.
0
3
5
*
*
1
.
7
2
8
*
2
.
0
2
0
*
*
2
.
0
3
0
*
*
1
.
5
8
2
I
n
d
u
s
t
r
y
?
x
e
d
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
P
e
r
i
o
d
?
x
e
d
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
A
d
j
u
s
t
e
d
R
2
0
.
4
2
9
0
.
4
2
7
0
.
4
3
5
0
.
4
3
1
0
.
4
2
7
0
.
4
4
0
F
-
s
t
a
t
i
s
t
i
c
5
8
.
3
6
7
*
*
*
5
8
.
0
4
2
*
*
*
5
9
.
8
5
7
*
*
*
5
6
.
3
4
8
*
*
*
5
5
.
4
6
2
*
*
*
5
8
.
2
4
5
*
*
*
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
t
a
t
:
*
1
0
,
*
*
5
a
n
d
*
*
*
1
p
e
r
c
e
n
t
l
e
v
e
l
s
,
r
e
s
p
e
c
t
i
v
e
l
y
;
t
-
s
t
a
t
i
s
t
i
c
s
a
r
e
i
t
a
l
i
c
i
s
e
d
;
p
r
o
b
a
b
i
l
i
t
i
e
s
a
r
e
o
n
e
-
t
a
i
l
e
d
w
h
e
n
i
n
d
i
r
e
c
t
i
o
n
p
r
e
d
i
c
t
e
d
;
L
A
F
i
s
n
a
t
u
r
a
l
l
o
g
a
r
i
t
h
m
o
f
a
u
d
i
t
f
e
e
s
;
I
N
S
E
N
S
I
T
I
V
E
,
S
E
N
S
I
T
I
V
E
a
n
d
I
N
D
E
T
E
R
M
I
N
A
T
E
a
r
e
p
e
r
c
e
n
t
a
g
e
s
h
a
r
e
h
o
l
d
i
n
g
s
h
e
l
d
b
y
p
r
e
s
s
u
r
e
i
n
s
e
n
s
i
t
i
v
e
,
s
e
n
s
i
t
i
v
e
a
n
d
i
n
d
e
t
e
r
m
i
n
a
t
e
i
n
v
e
s
t
o
r
s
,
r
e
s
p
e
c
t
i
v
e
l
y
;
P
O
L
C
O
N
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
f
o
r
p
o
l
i
t
i
c
a
l
l
y
c
o
n
n
e
c
t
e
d
?
r
m
s
a
n
d
0
o
t
h
e
r
w
i
s
e
;
L
N
A
S
S
E
T
S
i
s
n
a
t
u
r
a
l
l
o
g
t
r
a
n
s
f
o
r
m
a
t
i
o
n
o
f
A
S
S
E
T
S
;
C
U
R
R
E
N
T
i
s
c
u
r
r
e
n
t
a
s
s
e
t
s
t
o
t
o
t
a
l
a
s
s
e
t
s
;
L
I
Q
U
I
D
i
s
c
u
r
r
e
n
t
a
s
s
e
t
s
t
o
c
u
r
r
e
n
t
l
i
a
b
i
l
i
t
i
e
s
;
L
N
S
U
B
S
i
s
t
h
e
n
a
t
u
r
a
l
l
o
g
t
r
a
n
s
f
o
r
m
a
t
i
o
n
o
f
S
U
B
S
;
F
O
R
E
I
G
N
p
r
e
s
e
n
t
s
t
h
e
n
u
m
b
e
r
o
f
f
o
r
e
i
g
n
-
d
o
m
i
c
i
l
e
s
u
b
s
i
d
i
a
r
i
e
s
a
n
d
L
N
F
O
R
E
I
G
N
i
s
t
h
e
n
a
t
u
r
a
l
l
o
g
t
r
a
n
s
f
o
r
m
a
t
i
o
n
o
f
F
O
R
E
I
G
N
;
Y
E
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
i
f
t
h
e
?
s
c
a
l
y
e
a
r
-
e
n
d
i
s
3
1
D
e
c
e
m
b
e
r
;
D
E
B
T
i
s
t
o
t
a
l
d
e
b
t
o
v
e
r
t
o
t
a
l
e
q
u
i
t
y
;
R
O
A
i
s
e
a
r
n
i
n
g
s
d
i
v
i
d
e
d
b
y
t
o
t
a
l
a
s
s
e
t
s
;
L
O
S
S
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
i
f
t
h
e
?
r
m
r
e
c
o
r
d
e
d
a
l
o
s
s
i
n
t
h
e
p
r
e
v
i
o
u
s
?
s
c
a
l
y
e
a
r
;
M
A
N
O
W
N
i
s
m
a
n
a
g
e
r
i
a
l
s
h
a
r
e
h
o
l
d
i
n
g
s
;
B
I
G
_
N
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
f
o
r
B
i
g
n
a
u
d
i
t
o
r
s
a
n
d
0
o
t
h
e
r
w
i
s
e
;
S
W
I
T
C
H
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
f
o
r
?
r
m
s
w
i
t
c
h
i
n
g
a
u
d
i
t
o
r
a
n
d
0
o
t
h
e
r
w
i
s
e
;
n
¼
3
9
0
?
r
m
s
Table V.
ARJ
22,2
184
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
0
8
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
INSENSITIVEinvestors (0.004, t ¼ 1.412, p . 0.10) indicating that pressure-insensitive
investors are not reliable monitors and do not lead to better audit quality. Since
pressure-sensitive (SENSITIVE) investors do hold business interests with the ?rms, we
do not expect them to play a monitoring role and thus do not contribute to better audit.
As predicted, we ?nd no evidence of a relationship between SENSITIVE and LAF as
shown in Model 2. In Model 3, we ?nd investors that do not fall in either group
(INDETERMINATE) positively affects audit fees (0.011, t ¼ 2.884, p , 0.001). Further,
the parameter 0.011 of INDETERMINATE presents 1.106 per cent of audit fees
premium. Our ?ndings suggest investors’ heterogeneity does play a signi?cant part in
determining the relationship between institutional ownership and audit fees.
Models 4-6 extend our analysis by looking at interactions of
INSENSITIVE
*
POLCON, SENSITIVE
*
POLCON and INDETERMINATE
*
POLCON.
Interestingly, we ?nd that the coef?cient for the interactions INSENSITIVE
*
POLCON,
and INDETERMINATE
*
POLCON are both positive and signi?cant at (0.010,
t ¼ 1.714, p , 0.01) and (0.018, t ¼ 2.213, p , 0.05). These results suggest that groups
which do not hold any interests in ?rms (INSENSITIVE and INDETERMINATE) play
a more stringent monitoring role and insist on a high-quality audit particularly in the
additional presence of political connectedness.
5.2.2 Individual investors. Since Malaysian institutional investors form the highest
ownership of institutional investors’ equity in the capital market, we examine their role
in in?uencing the variation of audit fees. Speci?cally, we analyse the relationship
between EPF, PNB, LTAT, LTH and PERKESO with audit fees. Since their cumulative
institutional investment represents 68 per cent of total institutional investment, it is
imperative to empirically examine their role in the audit market.
Columns 1-10 of Table VI present the regressions results for individual large
investors in Malaysia. Refer to Column 1-4 of Table VI, we ?nd positive and signi?cant
coef?cients for EPF (0.026, t ¼ 2.707, p , 0.001) and PNB (0.011, t ¼ 2.884, p , 0.001)
providing support that EPF and PNB are positively related to audit effort leading to
higher audit fees. Our results suggest that these institutional investors do demand
higher audit fees. Columns 6-9 of Table VI represent interactions between POLCON
and individual institutional investors. Only the interactions of EPF
*
POLCON and
LTAT
*
POLCON are positive and signi?cant with audit fees at 5 and 1 per cent,
respectively. We view this result as promising which suggest that we should view
seriously the proposition that local institutional investors play a key role in demanding
a better quality audit.
6. Conclusion
This study examines the relationship between institutional ownership and audit fees a
proxy for audit quality in Malaysia. In particular, we examine whether institutional
ownership and political-connected ?rms are associated with higher audit fees. Our
panel analysis of 390 ?rms for the period 1999-2003 ?nds a positive association
between institutional ownership, measured by top ?ve shareholdings of institutional
investors and audit fees. Our ?nding suggests institutional investors demand a higher
quality audit, ultimately increasing audit fees. Furthermore, we ?nd evidence that the
positive relationship does depend on investors’ heterogeneity. Our results also suggest
that political-connected ?rms are associated with higher audit fees, suggesting that
these ?rms are perceived by auditors to be more risky. Consequently, auditors tend to
Audit quality
in Malaysia
185
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
0
8
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
A
F
1
2
3
4
5
6
7
8
9
1
0
C
O
N
S
T
A
N
T
3
.
9
6
4
3
.
7
2
3
3
.
5
4
9
3
.
5
2
8
3
.
5
6
8
4
.
0
4
0
3
.
8
6
3
3
.
5
3
9
3
.
5
5
4
3
.
5
6
3
5
.
7
2
7
*
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*
5
.
4
9
2
*
*
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5
.
2
0
6
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5
.
1
6
5
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5
.
2
2
9
*
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8
3
0
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5
.
7
0
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5
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2
3
6
*
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5
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1
9
6
*
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.
2
1
8
*
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E
P
F
0
.
0
2
6
0
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1
5
2
.
7
0
7
*
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1
.
3
0
9
P
N
B
0
.
0
1
1
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0
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.
8
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4
*
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1
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1
2
9
L
T
A
T
0
.
0
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2
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0
1
9
0
.
0
2
6
2
1
.
9
9
5
*
L
T
H
0
.
0
0
5
0
.
0
0
3
0
.
4
0
2
0
.
2
0
5
S
O
C
S
O
0
.
0
8
1
0
.
0
4
8
0
.
5
4
1
0
.
2
3
5
P
O
L
C
O
N
0
.
1
5
0
0
.
1
8
6
0
.
1
6
9
0
.
1
7
2
0
.
1
6
7
0
.
0
5
8
0
.
1
2
5
0
.
1
2
4
0
.
1
5
4
0
.
1
6
1
1
.
5
2
1
1
.
8
8
5
*
1
.
7
0
4
*
1
.
7
3
1
*
1
.
6
7
8
*
0
.
5
0
3
1
.
2
3
2
1
.
2
4
6
1
.
5
0
8
1
.
5
8
6
E
P
F
*
P
O
L
C
O
N
0
.
0
2
9
1
.
5
3
8
P
N
B
2
*
P
O
L
C
O
N
0
.
0
1
8
2
.
2
1
3
*
*
L
T
A
T
*
P
O
L
C
O
N
0
.
0
3
5
2
.
7
3
8
*
*
*
L
T
H
*
P
O
L
C
O
N
0
.
0
3
5
0
.
6
9
9
S
O
C
S
O
*
P
O
L
C
O
N
0
.
0
8
0
0
.
2
6
5
L
N
A
S
S
E
T
S
0
.
3
9
4
0
.
4
0
6
0
.
4
1
5
0
.
4
1
6
0
.
4
1
4
0
.
3
9
1
0
.
4
0
0
0
.
4
1
6
0
.
4
1
5
0
.
4
1
5
1
1
.
9
6
1
*
*
*
1
2
.
6
4
6
*
*
*
1
2
.
8
6
6
*
*
*
1
2
.
8
7
2
*
*
*
1
2
.
8
1
7
*
*
*
1
1
.
8
9
5
*
*
*
1
2
.
4
6
6
*
*
*
1
3
.
0
0
8
*
*
*
1
2
.
8
3
1
*
*
*
1
2
.
8
1
4
*
*
*
C
U
R
R
E
N
T
0
.
2
9
6
0
.
3
0
8
0
.
3
1
4
0
.
3
1
6
0
.
3
1
4
0
.
2
9
4
0
.
3
1
4
0
.
3
2
0
0
.
3
1
6
0
.
3
1
4
3
.
8
8
2
*
*
*
4
.
0
5
3
*
*
*
4
.
0
9
5
*
*
*
4
.
1
2
5
*
*
*
4
.
0
9
4
*
*
*
3
.
8
8
0
*
*
*
4
.
1
5
1
*
*
*
4
.
2
0
8
*
*
*
4
.
1
2
6
*
*
*
4
.
0
9
5
*
*
*
L
I
Q
U
I
D
2
0
.
0
1
4
2
0
.
0
1
5
2
0
.
0
1
5
2
0
.
0
1
5
2
0
.
0
1
5
2
0
.
0
1
4
2
0
.
0
1
5
2
0
.
0
1
5
2
0
.
0
1
5
2
0
.
0
1
5
2
5
.
1
0
2
*
*
*
2
5
.
1
9
5
*
*
*
2
5
.
1
6
4
*
*
*
2
5
.
1
5
7
*
*
*
2
5
.
1
5
5
*
*
*
2
5
.
1
1
2
*
*
*
2
5
.
2
4
7
*
*
*
2
5
.
3
6
8
*
*
*
2
5
.
1
5
1
*
*
*
2
5
.
1
5
4
*
*
*
L
N
S
U
B
S
0
.
0
1
2
0
.
0
1
1
0
.
0
1
2
0
.
0
1
2
0
.
0
1
2
0
.
0
1
2
0
.
0
1
2
0
.
0
1
1
0
.
0
1
2
0
.
0
1
2
(
c
o
n
t
i
n
u
e
d
)
Table VI.
Panel least squares for
sample ?rms for
individual ?rms
(1999-2003)
ARJ
22,2
186
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
0
8
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
L
A
F
1
2
3
4
5
6
7
8
9
1
0
1
.
2
5
3
1
.
2
0
9
1
.
2
4
0
1
.
2
4
4
1
.
2
5
7
1
.
2
1
8
1
.
2
6
8
1
.
1
8
1
1
.
2
3
8
1
.
2
4
8
L
N
F
O
R
E
I
G
N
0
.
0
3
2
0
.
0
3
2
0
.
0
3
2
0
.
0
3
2
0
.
0
3
2
0
.
0
3
2
0
.
0
3
1
0
.
0
3
2
0
.
0
3
2
0
.
0
3
2
4
.
5
6
5
*
*
*
4
.
6
9
8
*
*
*
4
.
6
1
7
*
*
*
4
.
5
7
2
*
*
*
4
.
6
1
4
*
*
*
4
.
6
7
7
*
*
*
4
.
5
5
5
*
*
*
4
.
5
7
6
*
*
*
4
.
5
7
3
*
*
*
4
.
6
2
4
*
*
*
Y
E
0
.
0
2
6
0
.
0
0
9
2
0
.
0
0
2
2
0
.
0
0
1
2
0
.
0
0
1
0
.
0
2
5
0
.
0
1
2
2
0
.
0
1
0
0
.
0
0
1
0
.
0
0
0
0
.
3
6
0
0
.
1
1
9
2
0
.
0
2
3
2
0
.
0
0
9
2
0
.
0
1
5
0
.
3
5
0
0
.
1
7
2
2
0
.
1
3
8
0
.
0
0
8
0
.
0
0
2
D
E
B
T
2
0
.
0
1
3
2
0
.
0
1
3
2
0
.
0
1
4
2
0
.
0
1
4
2
0
.
0
1
4
2
0
.
0
1
3
2
0
.
0
1
3
2
0
.
0
1
4
2
0
.
0
1
4
2
0
.
0
1
4
2
1
.
9
3
8
*
2
1
.
9
6
4
*
2
2
.
1
0
3
*
*
2
2
.
1
0
2
*
*
2
2
.
1
0
3
*
*
2
1
.
9
8
7
*
2
1
.
9
6
6
*
2
2
.
1
2
0
*
*
2
2
.
0
7
7
*
*
2
2
.
1
1
8
*
*
R
O
A
2
0
.
0
0
1
0
.
0
0
0
2
0
.
0
0
1
2
0
.
0
0
1
2
0
.
0
0
1
2
0
.
0
0
1
2
0
.
0
0
1
2
0
.
0
0
1
0
.
0
0
0
2
0
.
0
0
1
2
0
.
3
9
4
2
0
.
1
8
5
2
0
.
2
3
2
2
0
.
2
0
9
2
0
.
2
1
6
2
0
.
3
5
7
2
0
.
2
1
7
2
0
.
3
3
1
2
0
.
2
0
4
2
0
.
2
1
8
L
O
S
S
0
.
1
0
1
0
.
1
0
6
0
.
0
9
6
0
.
0
9
5
0
.
0
9
7
0
.
1
0
3
0
.
1
1
3
0
.
1
1
6
0
.
0
9
5
0
.
0
9
8
1
.
4
5
4
1
.
5
3
0
1
.
3
6
4
1
.
3
6
4
1
.
3
9
1
1
.
4
7
8
1
.
6
3
2
1
.
6
6
9
1
.
3
6
1
1
.
3
9
7
M
A
N
O
W
N
2
0
.
0
0
4
2
0
.
0
0
4
2
0
.
0
0
5
2
0
.
0
0
5
2
0
.
0
0
5
2
0
.
0
0
4
2
0
.
0
0
4
2
0
.
0
0
5
2
0
.
0
0
5
2
0
.
0
0
5
2
1
.
6
0
2
2
1
.
7
1
4
*
2
1
.
8
8
5
*
2
1
.
8
8
3
*
2
1
.
8
5
8
*
2
1
.
5
8
1
2
1
.
7
4
3
*
2
1
.
9
8
2
*
2
1
.
8
6
7
*
2
1
.
8
5
6
*
B
I
G
_
N
0
.
0
6
4
0
.
0
6
7
0
.
0
8
4
0
.
0
8
4
0
.
0
8
4
0
.
0
6
5
0
.
0
6
8
0
.
0
8
5
0
.
0
8
1
0
.
0
8
5
0
.
8
5
8
0
.
9
0
2
1
.
1
3
6
1
.
1
3
5
1
.
1
3
1
0
.
8
8
6
0
.
9
2
5
1
.
1
4
9
1
.
0
9
6
1
.
1
4
2
S
W
I
T
C
H
0
.
1
5
6
0
.
1
2
9
0
.
1
5
0
0
.
1
5
0
0
.
1
5
1
0
.
1
5
3
0
.
1
1
7
0
.
1
4
6
0
.
1
4
9
0
.
1
5
2
2
.
0
9
5
*
*
1
.
7
2
8
*
1
.
9
9
8
*
1
.
9
9
3
*
2
.
0
1
2
*
*
2
.
0
5
9
*
*
1
.
5
8
2
1
.
9
5
3
*
1
.
9
8
3
*
2
.
0
1
9
*
*
I
n
d
u
s
t
r
y
?
x
e
d
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
P
e
r
i
o
d
?
x
e
d
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
Y
e
s
A
d
j
u
s
t
e
d
R
2
0
.
4
3
3
0
.
4
3
5
0
.
4
2
7
0
.
4
2
7
0
.
4
2
7
0
.
4
3
5
0
.
4
4
0
0
.
4
3
4
0
.
4
2
7
0
.
4
2
7
F
-
s
t
a
t
i
s
t
i
c
5
9
.
3
9
1
*
*
*
5
9
.
8
5
7
*
*
*
5
7
.
8
9
2
*
*
*
5
7
.
9
3
1
*
*
*
5
7
.
9
4
9
*
*
*
5
7
.
1
5
4
*
*
*
5
8
.
2
4
5
*
*
*
5
6
.
9
7
8
*
*
*
5
5
.
3
7
6
*
*
*
5
5
.
2
9
3
*
*
*
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
t
a
t
:
*
1
0
,
*
*
5
a
n
d
*
*
*
1
p
e
r
c
e
n
t
l
e
v
e
l
s
,
r
e
s
p
e
c
t
i
v
e
l
y
;
t
-
s
t
a
t
i
s
t
i
c
s
a
r
e
i
t
a
l
i
c
i
s
e
d
;
L
A
F
i
s
n
a
t
u
r
a
l
l
o
g
a
r
i
t
h
m
o
f
a
u
d
i
t
f
e
e
s
;
E
P
F
,
P
N
B
,
L
T
A
T
,
L
T
H
a
n
d
P
E
R
K
E
S
O
a
r
e
p
e
r
c
e
n
t
a
g
e
s
h
a
r
e
h
o
l
d
i
n
g
s
h
e
l
d
b
y
E
P
F
,
P
N
B
,
L
T
A
T
,
L
T
H
a
n
d
P
e
r
t
u
b
u
h
a
n
K
e
s
e
l
a
m
a
t
a
n
S
o
s
i
a
l
i
n
v
e
s
t
o
r
s
,
r
e
s
p
e
c
t
i
v
e
l
y
;
P
O
L
C
O
N
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
f
o
r
p
o
l
i
t
i
c
a
l
l
y
c
o
n
n
e
c
t
e
d
?
r
m
s
a
n
d
0
o
t
h
e
r
w
i
s
e
;
L
N
A
S
S
E
T
S
i
s
n
a
t
u
r
a
l
l
o
g
t
r
a
n
s
f
o
r
m
a
t
i
o
n
o
f
t
o
t
a
l
a
s
s
e
t
s
;
C
U
R
R
E
N
T
i
s
c
u
r
r
e
n
t
a
s
s
e
t
s
t
o
t
o
t
a
l
a
s
s
e
t
s
;
L
I
Q
U
I
D
i
s
c
u
r
r
e
n
t
a
s
s
e
t
s
t
o
c
u
r
r
e
n
t
l
i
a
b
i
l
i
t
i
e
s
;
L
N
S
U
B
S
i
s
t
h
e
n
a
t
u
r
a
l
l
o
g
t
r
a
n
s
f
o
r
m
a
t
i
o
n
o
f
S
U
B
S
;
F
O
R
E
I
G
N
p
r
e
s
e
n
t
s
t
h
e
n
u
m
b
e
r
o
f
f
o
r
e
i
g
n
-
d
o
m
i
c
i
l
e
s
u
b
s
i
d
i
a
r
i
e
s
a
n
d
L
N
F
O
R
E
I
G
N
i
s
t
h
e
n
a
t
u
r
a
l
l
o
g
t
r
a
n
s
f
o
r
m
a
t
i
o
n
o
f
F
O
R
E
I
G
N
;
Y
E
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
i
f
t
h
e
?
s
c
a
l
y
e
a
r
-
e
n
d
i
s
3
1
D
e
c
e
m
b
e
r
;
D
E
B
T
i
s
t
o
t
a
l
d
e
b
t
o
v
e
r
t
o
t
a
l
e
q
u
i
t
y
;
R
O
A
i
s
e
a
r
n
i
n
g
s
d
i
v
i
d
e
d
b
y
t
o
t
a
l
a
s
s
e
t
s
;
L
O
S
S
t
a
k
e
s
t
h
e
v
a
l
u
e
o
f
1
i
f
t
h
e
?
r
m
r
e
c
o
r
d
e
d
a
l
o
s
s
i
n
t
h
e
p
r
e
v
i
o
u
s
?
s
c
a
l
y
e
a
r
;
M
A
N
O
W
N
i
s
m
a
n
a
g
e
r
i
a
l
s
h
a
r
e
h
o
l
d
i
n
g
s
;
B
I
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Table VI.
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charge these ?rms fees premiums. The two way interaction between institutional
investors and political-connected ?rms and audit fee suggests that political-connected
?rm pay higher audit fees than non-political connected ?rms when institutional
investors are present in their ?rms. The exploration of this effect suggests that
institutional investors do play a monitoring role in order to reduce agency costs by
demanding for a higher quality audit particularly for politically connected ?rms.
Our study is not without any limitations. We based our politically connected ?rms
list on the Johnson and Mitton (2003) publication. Future research should further
explore this relationship by using a new list of politically connected ?rms. Since Tun
Mahathir Mohamed handed the Prime Minister position over to Dato’ Seri Abdullah
Ahmad Badawi in 2003, companies in favour of Dato’ Seri Abdullah Ahmad Badawi
should also be included. Besides, this, an extension of further research on the exact
nature of the political relationship could yield a more robust ?nding, and better
understanding of this relationship. Furthermore, we acknowledge the weakness of our
investors’ heterogeneity speci?cations which are based on the extant literature
(Brickley et al., 1988, Cornett et al., 2007). A thorough investigation as to whether
individual business relationships exist could be bene?cial.
Notes
1. Agency costs include: the monitoring expenditures incurred by the principal; the bonding
expenditures incurred by the agent; and the residual loss (Jensen and Meckling, 1976, p. 308).
The residual loss is the ultimate loss in ?rm value that the agency relationship creates and
which is not optimally reduced any further by either the incurrence of additional monitoring
or additional bonding expenditures.
2. We argue that the form of relationship between the institutional investors affects the
potential monitoring effectiveness of institutional investors. We predict that institutional
investors that have a business relationship with the ?rms are not reliable monitors. In
contrast, institutional investors with less interest in the ?rm are expected to play a more
active role in ensuring higher quality audit.
3. Malaysia has about 22.79 million people, of whom 65 per cent are Bumiputera, 26 per cent
Chinese, 8 per cent Indians and 1 per cent others. Of the 65 per cent Bumiputera, 82 per cent
are Malays and 18 per cent are other indigenous people (Department of Statistics Malaysia,
2004).
4. The NEP has been very successful in that is has led to a signi?cant increase in Bumiputeras’
corporate ownership from 2.4 per cent in 1970 to 20.3 per cent in 1990 (Rasiah and Shari,
2001). However, such a ?gure still falls short of the NEP’s 30 per cent target. Since the
country’s economy surged by an average of more than 7 per cent a year for most of the
period, the Malays’ advance did not occur at the expense of other races. Within 20 years
(1970-1990), Chinese equity ownership rose signi?cantly from27.2 per cent in 1970 to 45.5 per
cent in 1990. In addition, the NEP had successfully reduced the dominance of foreign
ownership and control of the economy from 63.3 per cent in 1970 to 25.4 per cent in 1990.
However, the NEP’s 30 per cent of the Bumiputera ownership target has yet to be met after
replacing the NEP with the National Development Policy in 1991.
5. Under the superannuation scheme, serving members of the other ranks in the Armed Forces are
required to contribute 10 per cent of their monthly salary to LTAT with the government as
employer contributing 15 percent. For of?cers, participation is voluntary and the contributions
are a minimum of RM 25 with a maximum of RM 200 monthly (www.ltat.org.my).
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6. Syariah refers to the body of Islamic law. It is the legal framework within which public and
some private aspects of life are regulated for those living in a legal system based on Moslem
principles of jurisprudence. For example, Moslems are not permitted to be involved in
gambling or any contracts involving future predictions or uncertainty.
7. The rise of these politically linked companies is the result of the NEP Plan introduced in 1970
with the objective of achieving economic parity for the Bumiputra
8. The other forms of political favouritism may be due to ?rms run by those from diverse
ethnicity namely Bumiputra, Chinese and Indian including those with close relationships
with prominent politicians (Gul, 2006, p. 936).
9. See Favere-Marchesi (2001) for a thorough review on audit requirements in Malaysia.
10. Ali et al. (2006) summarise the trend of auditing practices after Malaysia gained
independence in 1957. They divide the documentary analysis into three periods: Pre-NEP,
during NEP and after NEP and Asian Financial Crisis.
11. In Malaysia, the duty to disclose audit fees is mandated by the Companies Act 1965 (Che
Ahmad and Houghton, 2001).
12. The top ?ve institutional investors constitute 99 per cent of total institutional investors’
shareholdings.
13. Khazanah Nasional Berhad is the investment holding arm of the government of Malaysia to
manage its commercial assets. It was incorporated in September 1993 and began operations
in 1994. It is structured into a holding company that is a wholly owned entity of the Ministry
of Finance which is part of the Malaysian government.
14. The Big n audit ?rms are Arthur Andersen, Deloitte, KPMG, Ernst and Young and
PricewaterhouseCoopers. For the sake of consistency, well-known partner ?rms (e.g. Kassim
Chan and Hana?ah Raslan) to the Big n are considered as a big auditor if they are mentioned
explicitly.
15. Regression results are reported without the period and industry dummies. The results can be
obtained from the corresponding author.
16. Pearson and Spearman Rank are included for robustness purposes.
17. Standard diagnostic tests reveal no multicollinearity problem.
18. We checked our data properly to avoid errors, univariate and multivariate outliers were
taken out. This study uses period seemingly unrelated regressions to handle both
heterocedasticity and contemporaneous correlations in each cross-section. We also repeat
our analysis by including ?nancial ?rms and we ?nd that adjusted R
2
remains also the same
across all models.
19. Extant literature suggests a piecewise relationship could exist between managerial
ownership and audit quality (Lennox, 2005). Using threshold ?gures of 5, 5-20 and 20 per cent
suggested by Lins (2003) for emerging markets, we ?nd no evidence to suggest such
relationship exists. Alternative analysis using quadratic function of MANOWN yields
insigni?cant results too. Regressions results can be obtained from the corresponding author.
20. The audit fee premium or discount is obtained by calculating the effect of the percentage
shift on natural log of audit fees and is de?ned as e
z
2 1, where z is the parameter for the
testable variable. See Craswell et al. (1995) for thorough explanation.
21. Ideally, we want to know the explicit relationship between the institutional investors and
their investees. However, such information is not available.
Audit quality
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(The Appendix follows overleaf.)
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Appendix
Name
1 Advance Synergy
2 Af?n Holdings
3 Antah
4 Arab Malaysia Development
5 Bandar Raya Development
6 Bank Islam Malaysia Bhd Holdings
7 BCB
8 Berjaya Group
9 Berjaya Land
10 Berjaya Sports Toto
11 Best World Land (MultiVest)
12 Boustead Holdings
13 Cahaya Mata Sarawak
14 Camerlin Group
15 Cement Industries of Malaysia
16 Commerce Assets
17 Cosway Corporation (Singer)
18 Cycle and Carriage
19 Daibochi
20 Damansara Realty
21 DRB-Hicom
22 Edaran Otomobil Nasional
23 Faber Group
24 FCW Holdings (Bata)
25 Fima Corporation
26 Georgetown Holdings
27 Goh Ban Huat
28 Golden Hope Plantation
29 Golden Plus (Dayapi)
30 Granite Industries
31 Ho Hup
32 Hong Leong Bank
33 Hong Leong Credit
34 Hong Leong Industries
35 Hong Leong Properties
36 Hume Industries
37 Jaya Tiasa (Berjaya Textile)
38 Kedah Cement Holdings
39 Kretam
40 Kumpulan Guthrie
41 Land and General
42 Landmarks
43 Leisure Management (Magnum 4D)
44 Lion Corporation
45 Magnum Corporation
46 Malakoff
47 Malayan Banking
48 Malaysian Paci?c Industries
(continued)
Table AI.
List of politically
connected ?rms in
Malaysia (1999-2003)
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Corresponding author
Ef?ezal Aswadi Abdul Wahab can be contacted at: [email protected]
Name
49 Malaysia Airports Holdings
50 Malaysia International Shipping Corporation
51 Malaysian Airlines System
52 Metacorp
53 Metroplex
54 MRCB
55 Mulpha International
56 Multi-Purpose Holdings
57 Mycom
58 Naluri (MHS)
59 Nanyang Press
60 New Straits Times
61 OYL Industries
62 Pantai Hospital
63 Park May
64 Pharmaniaga
65 Philleo Allied Bhd
66 Prime Utilities
67 Proton Holdings
68 PSC Industries
69 Rashid Hussain
70 RHB Capital
71 Sapura Telecommunications
72 Setron
73 Sime Darby
74 Star Publications
75 Taiping Consolidated
76 Tanjong
77 Tasek Corporation
78 Telekom Malaysia
79 Tenaga Nasional
80 Time Engineering
81 UDA Holdings
82 Union Paper (TH Group)
83 Uniphone Telecommunication
84 United Plantations
85 Utusan Melayu
86 Wembley Industries Holdings
87 Wijaya Baru (Paci?c Chemicals)
88 YTL Cement
89 YTL Corporation
90 YTL Power
Sources: Johnson and Mitton (2003); Mohamad et al. (2006); Khazanah Berhad web site (www.khaza
nah.com.my) Table AI.
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doc_890208012.pdf