An Analysis Of Malaysian Public Listed Companies Accounting Essay

Category: Accounting

In the past decade, audit fee has been one of many concerns for every audited company. Determinants of audit fee are also variable among different audit firms as well. The aim of the research is to examine the relationship of audit fee and audit quality characteristics such as audit tenure, size of audit firm, size of company and frequency of audit committee meetings. In addition, this research takes into account that companies are specifically selected from trading or services sector in Malaysia.

Annual reports of Public Listed Companies (PLC) from Bursa Malaysia are used for data collection, it is also known as Secondary Data analysis. Data analysis is carried out in this research in order to enhance the value of prior studies.

However, the research found that audit tenure and frequency of audit committee meetings are not significant determinants of audit fee whereas there is a relation between size of audit firm and size of company. Limitations and contributions with respect to all independents variables are provided. Overall, the results are expected and consistent with the predictions of prior analytical research.

Keywords: Audit fee; Audit tenure, size of audit firm, size of company and frequency of audit committee meetings; trading or services sector; Secondary Data analysis; Annual reports of Public Listed Companies (PLC) from Bursa Malaysia

CHAPTER 1: INTRODUCTION

Background of the Study

The demand for audit quality has been arising in recent years. Cases for audit failures are still being seen in these few years, such as the most recent case in 2012, Japanese camera and medical equipment manufacturer Olympus was disclosed having involved in the accounting fraud. As a result, expectation for a quality audited financial statement has grown.

The term "audit quality" is defined as an auditor will both detect material misstatements in the client's financial statements and report the material misstatements. (DeAngelo, 1981). However, the probability an auditor will discover a breach in the client's accounting system is dependent upon the competence of the auditor and other variables. (Magee & Tseng, 1990).

Audit fee is a fee that a company pays an external auditor in exchange for performing an audit. According to the rules of ethics of public accountants' compartment, audit fee is "the fee amount may vary depending on the risk assignment, the complexity of services provided, level of expertise required to perform such services, the related cost structure CPA firm and other professional considerations". When the audit quality is defined as membership in Big 6, several studies of private sector have found that audit quality is associated with a fee premium. (Palmrose, 1986; Francis & Simon, 1987). In the past decade, audit fee has been one of many concerns for audited companies. Determinants of audit fee are also variable among different audit firms. However, fees paid to auditors are seemed to affect audit quality in this way: auditors were paid large fees may increase the effort exerted by auditors. (Rani, Ariel & Charles, 2007).

Furthermore, this research focuses on Malaysian trading services industry. In fact, one of the most important international business trends is the growing proportion of trade in services: in the 1990s, over 50% of global FDI was in the service sector (Wirjanto, 1997). According to Malaysia Investment Development Authority (MIDA), the services sector accounted for the largest share of Malaysia's GDP in 2011. The sector contributed 58.6 per cent to GDP for the same period. Therefore, this research will focus on trading services industry in Malaysia because it has significant impact on Malaysia's economy and most listed companies are in this sector.

Problem Statement

An audit failure when an auditor fails to issue a modified or qualified audit report in the appropriate circumstances (audit report failure). In this case, the audited financial statements are potentially misleading to users. (Jere, 2004). Therefore, annual reports which include the audited financial statements of public listed companies will be used to test the degree to which of audit quality. (Jere, 2004). However, this research has strong reliance on Bursa Malaysia published accounts. The credibility of the findings may be affected if management manipulates the financial statements used in this research. As such, many researchers have studied the issues of the relationship of audit fee and audit quality characteristics in other countries by using various methodologies. Therefore, there is lack of a certain methodology for measuring the relationship. Besides, in much of prior literature, the difference between examining audit fee and audit quality characteristics is still ambiguous. (David & Scott, 2004).

Research into the determinants of audit fees is now well established with a diverse literature dealing with the external audit fees of large and small quoted companies in many countries such as USA, UK and Australia. Researchers such as Simunic (1980), Taylor & Baker (1981), Taffler & Ramalinggam (1982), Francis (1984), Firth (1985), Palmrose (1986) and Francis & Strokes (1986) have all proposed and tested models that relate external audit fees to audited firm characteristics. From these prior studies, it showed that there are significant relationships between audit fees and the riskiness of the client (Francis, 1984; Francis and Stokes, 1987) and the size and industry expertise of the auditor (Francis, 1984; Taffler & Ramalinggam, 1982).

Simunic (1980) can be considered as the stimulus for this literature. He provides an economic analysis of competition within the market audit services. To provide the necessary empirical evidence on audit market competition, Simunic analyzes audit fees by developing a model which controls for factors affecting audit quantity and price. Simunic's results generally indicate that measures of auditee complexity and risk are associated with audit fees.

Several studies has expanded upon Simunic's original work by using similar research design and generalized his findings both to different national settings (for example, Francis,1984, to the Australian market; Firth, 1985, to the New Zealand market; Low et al., 1990, to the Singapore market), and to different sizes of firm ( Francis & Stokes, 1986; Francis & Simon, 1987). There remain, however, several gaps in the prior literature. For example, little published work was compared on UK audit fees (for example, Taylor & Baker, 1981; Taffler & Ramalinggam, 1982). Similarly, there are little empirical researches and few studies are conducted on Malaysia's audit fees model, especially for trading or services sector. Furthermore, the past researches to date have been limited to an examination of Big 8, Big 6 and Big 5. (Jere, 1984; Philip, 1993; Simunic, 1980). The information may be outdated. However, this research is conducted on Big 4 now to ensure that the information is up-to-date because Big 4 is dominant audit firms in today's world.

Moreover, previous research outside the UK indicates that Big 8 audit premiums tend to appear only for relatively small audited firms. (Francis & Stokes, 1986; Francis & Simon, 1987). However, this research presents specific evidence of this for the public listed companies in Malaysia which are normally larger in size. Finally, this research will test the frequency of audit committee meetings, it is less tested in prior researches of audit fee.

Research Objectives and Research Questions

Research Objectives

Research Questions

To examine the association between audit quality characteristics and audit fee.

What is the association between audit fee and audit quality characteristics?

To examine the association between audit tenure and audit fee.

What is the association between audit fee and audit tenure?

To examine the association between audit firm size-Big 4 and non-Big 4 and audit fee.

What is the association between audit fee and audit firm size-Big 4 and non-Big 4?

To examine the association between size of company and audit fee.

What is the association between audit fee and size of company?

To examine the association between frequency of audit committee meetings and audit fee.

What is the association between audit fee and frequency of audit committee meetings?

Significance of Study

This research aims to provide further understanding on association between audit fees and audit quality characteristics, notably Malaysian Public Listed Company (PLC) in trading or services sector. It can also be served as a basic of decision making for public listed company.

Moreover, this research is expected to make the following contributions. First, it specifically estimates and develops a model for the relation of audit fee determinants and audit quality characteristics that is relevant to trading services sector in Malaysia for the first time. The exact and specific results for this relationship still remain unclear and the research will test the result and enhance the value of previous result. Second, it allows a more significant test of whether audit fee is influenced by those characteristics of audit quality. It may possibly enhance the knowledge of stakeholders or company on the design of audit fee. For instance, company may design an audit fee model by using size of company as a reference.

Finally, it may be useful for future researchers in developing countries to identify factors that are specific to their countries. This research is said to provide a deeper insight that some new phenomena may also be responsible for variations in audit fees because there still have some deviations between developed countries and in developing countries.

Outline of Study

The next chapter discusses the theoretical framework for this study and develops the hypothesis for testing, followed by a discussion of our sample and descriptions of our empirical design including the measurement of audit fee by using Yatim audit fee model.

CHAPTER 2: LITERATURE REVIEW

2.1 Theoretical/Conceptual Foundation

The basic paradigm that this research employs is agency theory. Agency theory has provided a general framework in audit pricing internationally (Nikkinen and Sahlström, 2004). In recent years, agency theory has been widely applied to establish the agent and principal relationship between managers and shareholders of companies (Watts and Zimmerman, 1986). According to the agency theory as proposed by Jensen and Meckling (1976), it is suggested that agency costs is monitoring costs incurred by the shareholders to monitor the managers' behavior. Audit fees are an important component of these monitoring costs since auditors have a duty to ensure that the managers are behaving according to the owners' interest. (Nikkinen et al. 2004).

Agency theory was used to study principal-agent relationships between management, owners and auditors. Jensen (1976) proposed that the agency costs of free cash flow are lower for firms with high levels of management ownership. This is because managers' interests are more aligned with shareholders' interests if they own a larger proportion of the shares. Based on the theory of Jensen (1976), higher free cash flow might cause serious agency problem in firms. Firms with agency problems caused by free cash flow are thus likely to pay higher audit fees (Gul et al. 2001; Nikkinen et al. 2004). Moreover, variables affecting the audit fees, i.e. audit firm size, size of company (auditee), audit tenure and frequency of audit committee meetings should be incorporated into a model in order to test the relationship between them.

2.2 Review of the Prior Empirical Studies

Researchers such as Simunic (1980), Palmrose (1986), Rubin (1988) conducted the audit fee models that relate external audit fees to auditee firm characteristics.

Simunic (1980) conducted a research to investigate the impact of the audit firm size variable, after controlling for cross-sectional in auditee characteristics. This research was carried out by using the 397 observations on audit fees and related variables obtained from a sample survey of publicly held corporations in the United States. Simunic found that auditor size was the most important determinants of audit fees and he suggested that a specific Big 8 audit firm may more likely be associated with higher audit fees.

Palmrose (1986) proposed a research about the association between audit firm size and audit fees. Palmrose concluded that there was a positive relation between audit fees and audit firm absolute size.

Rubin (1988) tested the municipal audit fee model which aimed to provide evidence on the determinants of audit fees paid by municipalities to their external auditors. Rubin concluded that there was a significant positive relation of organization size and audit fee.

2.3 Proposed Conceptual Framework/Research Model

2.3.1 Audit Tenure

Prior studies defined audit tenure as the number of years that an "audit firm" has been retained by the audited company. (Johnson, Khurana & Reynolds, 2002). Within the analytical literature, audit tenure has primarily been of interest as it relates to audit pricing and the observed discounting of initial year audits. Prior studies indicate that the relationship between audit fee and audit tenure is that higher audit fee implies higher audit quality, either through audit tenure or through a greater expertise of the auditor. Big 8 audit firms exhibited both higher audit fees and audit hours. (Palmrose, 1986, p.106). Audit hours declined with audit firm tenure while audit fees remained stable. (Palmrose, 1986, p.496). Besides, the initial audits were associated with lower audit fees, higher audit hours, and naturally lower fees per hour. (Giroux et al., 1995, p.74-76). One set of studies examine that the interaction between auditor tenure and audit fees of restatement for firms with short auditor tenure. (Stanley & DeZoort, 2007).

2.3.2 Size of Audit Firm

In this research, the indicator variables for audit firm size are Big 4 and non-Big 4. The relationship of audit fees and audit firm size depends on market competition (Jere. R, 1984). A fee differential between audit firms represents a return to higher quality in a competitive audit market. Therefore, it is important to have a test on examining the fee charged by large audit firms in order to assess the quality differential between large and small auditors. (Ireland & Lennox, 2000). Paradoxically, prior theory suggests that high quality companies are more likely to hire large audit firms and are more likely to pay low fees because they require less audit work. (Titman & Trueman, 1986; Thornton & Moore, 1993).

2.3.3 Size of Company (Auditee)

Size of Company (Auditee) is the most significant explanatory variable in determining audit fees. (Philip, Ezzamel & Gwilliam, 1993) . There is evidence that audit fee model parameters are sensitive to client size. (Craswell et al., 1995). As a result, size should be associated with higher audit fees. (Rubin, 1988). The market for audit services is at least partially competitive and economies of scale will be passed back to the auditee as a non-linear increase in audit fees. (Gerrard, Houghton & Woodliff, 1994). This research has been expected that larger companies would have to pay a higher fee than smaller size companies to audit firms as auditors would have to perform more work to ensure compliance.

2.3.4 Frequency of Audit Committee Meeting

This research is based on meeting frequency which is one of audit committee characteristics and is defined as an audit committee that meets at least four times annually. (Lawrence, Susan, Gary & Raghunandan, 2003). Most recent studies have examined the association between audit fees and audit committee characteristics (Carcello et al., 2002; Abbott et al., 2003; Sharma, 2003). Audit committee meeting frequency is a signal about audit committee diligence (Menon & Williams, 1994). If audit committees are effective, there is likely to be an audit fee reduction to reflect the lower risk. (Lawrence, Susan, Gary & Raghunandan, 2003, p.17-32).

2.3.5 Conceptual Framework

H1 Audit Quality Characteristics

H2Audit Tenure

Audit Fee

Audit Fees

H3Size of Audit Firm

H4Size of Company (Auditee)

Frequency of Audit Committee Meeting

Figure 1: Conceptual Framework of Audit Quality Characteristics and Audit Fees

Adapted from Jere (1984).

Adapted from Abbott, Parker, Peters, & Raghunandan (2003).

2.4 Hypothesis Development

Regarding to the several previous researchers' findings, the long tenure results indicate no significant relation between non-audit fees and likelihood of restatement, using 382 companies in United States as data. (Stanley & DeZoort, 2007). The prior studies' results also suggested that the joint effect of soliciting bids and auditor tenure is an important interaction affecting audit fees. (Rubin, 1988). In light of Enron case, the Chairman of the Malaysian Accounting Standard Board (MASB) announced the intention of the board to make it mandatory to rotate the audit firm once every five years. (The Edge, 2002).

Hence, the hypothesis to be tested is:

H10: There is no association between audit tenure and audit fees.

H11: There is an association between audit tenure and audit fees.

Prior research has developed a hypothesis which is the Big 8 firms function as a cartel and charge higher audit fees. (Simunic, 1980). However, there's a positive relationship indicating audit prices for Big 8 firms according to prior study. (Jere, 1984) Some prior studies support the positive relation between audit fees and auditors that are recognized to be of superior quality. (Hay, Knechel & Wong, 2008). Nevertheless, this study extends Simunic's (1980) tests to examine whether there is a systematic relation between audit firm size and audit fees.

Hence, the hypothesis to be tested is:

H20: There is no association between size of audit firm and audit fees.

H21: There is an association between size of audit firm and audit fees.

Some previous researches indicate that size of company is the most significant explanatory variable in determining audit fee. (Philip, Ezzamel, & Gwilliam, 1993). If audit firms adopt an audit approach that is essentially balance sheet based then total assets may be the most suitable measure. However, the likelihood that larger company will have more sophisticated internal control procedures suggest that the relationship between size of company and audit fee is unlikely to be linear. (David, Mahmoude & Philip, 1993). Some researchers have suggested that Big 8 prices were higher than non-Big 8 prices for small auditees although no price differences were observed for large auditees. (Palmrose, 1986, Francis & Stokes, 1986 & Francis & Simon, 1987). Some researchers have suggested that Big 8 prices were higher than Non-Big 8 prices for small auditees. This research extends prior studies' (Simunic, 1980) tests to examine whether there is an association between size of company and audit fees.

Hence, the hypothesis to be tested is:

H30: There is no association between size of company (auditee) and audit fees.

H31: There is an association between size of company (auditee) and audit fees.

The results of prior research demonstrate that the association between audit committees meeting frequency and audit fees are in various. Audit fees are positively and significantly associated with the audit committee meeting frequency. (Yatim, Kent & Clarkson, 2006). However, a research data indicate that there is no significant relation between audit fees and audit committee meeting frequency. (Abbott et al., 2003). In addition, researchers found that stronger boards are associated with increased audit fees. (Carcello, Hermanson, Neal & Riley, 2002a). Therefore, this research hypothesizes that specific audit committee characteristics, such as audit committee meeting frequency is associated with higher audit fees despite of the previous researchers' results are coming with discrepancy, it aims to explore the possibility of interaction effects without predicting a direction and generate the forth hypothesis.

Hence, the hypothesis to be tested is:

H40: There is no association between audit committee meeting and audit fees.

H41: There is an association between audit committee meeting and audit fees.

CHAPTER 3: METHODOLOGY

3.1 Research Design

The research design used in this research is descriptive research. It is to describe data or characteristics of the samples being studied. Besides, this research is cross-sectional studies, a phenomenon at a particular time and collect data at a single point of time. The unit of analysis for this study is the public listed companies in trading services industry.

3.2 Data Collection Methods

Documentary secondary data will be used to conduct this research. The secondary data such as annual reports and audit reports of public listed companies in trading services industry are downloadable from the official website of Bursa Malaysia (http://www.bursamalaysia.com/market/). Companies' annual reports, audit reports and journal articles will be served as major sources for this research.

3.3 Sampling Design

3.3.1 Target Population

Target population focuses on the firms listed in Bursa Malaysia, now known as Kuala Lumpur stock exchange (KLSE). It consists of two markets for securities offering - Main Market and Ace Market. There were 841 companies listed in Main Market and 217 companies listed in Ace Market based on their announcement of annual report in year 2011.

3.3.2 Sampling Frame and Sampling Location

The sampling frames are either listed on the Main Market or the Ace Market of the Bursa Malaysia. Firms are categorized into various sectors in Main Market and Ace Market such as technology, trading services, finance, industrial products, construction, plantation, consumer products and property. The total number of firms listed on the Bursa Malaysia at the end of 2011 is 1058 firms (irrespective of sectors). From wide range of these sectors, trading services sector is chosen as sampling frame which included 316 firms in both Main Market and Ace Markets.

3.3.3 Sampling Elements

Firms in trading services sector which are listed on KLSE will be selected to conduct the research. According to Sekaran & Bougie (2010), the proportion of sample size should be 175 out of 316. Therefore, this research will select 175 out of 316 trading service companies' annual reports in year 2011 from KLSE.

3.3.4 Sampling Technique

Sampling is the process of selecting sample from population. There are two types of sampling procedures - probability sampling and non-probability sampling. Probability sampling can identify a suitable sampling frame based on research questions or objectives and quantitative research is the most suitable method in order to reach research objectives. In this research, probability sampling will be used as sampling method because populations are more than 50. (Henry, 1990)

3.3.5 Sampling Size

A total 175 out of 361 sets of annual reports of public listed companies in trading services sector listed on Bursa Malaysia will be selected for testing. The sample size is proposed by Sekaran et al. (2010).

3.4 Research Instrument

Secondary data such as annual reports are chosen as the research instrument. This research will select 175 trading services firms in Malaysia as sample. (Sekaran et al., 2010). The procedures include reading the annual report, the auditor report and audit committee report to collect information of the independent variables.

3.5 Constructs Measurement

The independent variables are audit tenure, size of audit firm, size of company and frequency of audit committee's meeting and dependant variable is audit fee. Companies are required to disclose their audit fees and non-audit fees in notes to financial statements by Companies Act 1965 Malaysia. The figure was collected from annual reports of those related companies. The sources of data will be collected from annual report of 175 firms (Sekaran et al., 2010). All data are non-parametric and nominal scale while audit fees and size of company are parametric data and ratio scale.

3.6 Data Processing

Few data preparation processes will be used in this research report. Firstly, 175 firms' annual reports which are posted on the website of Bursa Malaysia will be collected. Data will be coded and categorized to facilitate analysis after the data collecting process is completed. Next, the data will be examined in order to minimize errors or omissions. Lastly, collected data will be analyzed through the Statistical Analysis System (SAS) software.

3.7 Data Analysis

Data analysis begins after the data would have been collected and processed. Statistical Analysis System (SAS) will be used to test the input of secondary data such as annual report and auditor's report with completeness, consistency and reliability. Such test will be carried out by SAS and the results will be analyzed by Descriptive Test, Normality Test, Pearson Correlation Analysis and Multiple Linear Regression.

3.7.1 Descriptive Analysis

Descriptive statistic describes the characteristics of the sample by summarizing the reaction from large figures of respondents in some simple statistics. Descriptive Analysis refer to conversion of raw data into a form that simple to know and then interpret, rearranging, ordering and manipulating date to present the descriptive information. (Groenewald, 2010).

3.7.2 Scale Measurement

Normality test is used to test whether the data is well modeled by a normal distribution. Normality test will not be applied in this research since secondary data does not have to be tested for normality.

3.7.3 Inferential Analysis

Inferential analysis examines the cause and effect relationship of the independent variable and dependent variable. According to Hair et al. (2007), there are several inferential statistic techniques which permit the researcher to examine the hypothesis. Thus, inferential analysis technique such as Multiple Linear Regression Analysis and Pearson Correlation Coefficient will be used in this research. The fees and total assets are transformed into natural logarithm. The natural log is used to control for the skewed nature of audit fees. (Yatim et al., 2006).

Pearson Correlation Coefficient measures the strength and direction of the linear relationship between the two variables and describes the direction and degree that the variable is linked to others. (Hair et al., 2007). It is also used to examine the existence of multicollinearity and it ranges from -1 to +1 (Zikmund et al., 2010). Pearson correlation coefficient will be used to test the significance of relationship between each of four independent variables (audit tenure, size of audit firm, size of company, frequency of audit committee meetings) and the dependent variable (audit fee).

Multiple regression analysis is a statistical technique to predict the variance in the dependent variable. (Sekaran & Bougie, 2010). It is applied whereby all the independent variables are tested collectively against the audit fees. In this research, the equation below shows the relationship between independent variables that affecting the audit fees.

Audit Fees = a + β1 Audit tenure + β2 Audit firm size + β3 Size of company + β4 Audit committee meeting frequency

Or

LAF = a + β1 AUDTEN + β2 BIG4 + β3 SIZE + β4ACMEET

LAF = Natural log of audit fees.

AUDTEN = A dummy variable of 1 if audit tenure is ≥3 years, 0 otherwise.

BIG4 = A dummy variable of 1 if financial statements audited by Big 4 audit firms, 0 otherwise.

SIZE = Natural log of total assets.

ACMEET = A dummy variable of 1 if the audit committee met four or more times in the sample year; 0 otherwise

CHAPTER 4: DATA ANALYSIS

Introduction

The following result of secondary data in this chapter is carried out by Statistical Analysis System. SAS software using collected data to conduct the analysis for normality test, Pearson correlation, multiple linear regression. Results are shown in next section with table form.

Descriptive Analysis

Demographic Profile

The table below indicates the descriptive analysis of audit firm size which is big 4 or non-big 4, audit tenure more or less than 3 years, audit committee meeting more or less than 4 times, and company size (total assets) which converted to log10. A total of 175 samples are taken from public listed companies in trading sector listed on Bursa Malaysia for each item.

Table 4.1: Summary of demographic profile

Items

Valid

Frequency

Percentage (%)

Audit Tenure

Total

< 3 years

> 3 years

35

140

175

20.0

80.0

Size of Audit Firm

Total

Big 4

Non-Big 4

82

93

175

46.9

53.1

Size of Company

( total asset)

Total

x log 10

1 - 5

5 - 10

10 - 15

2

168

5

175

1.1

96.0

2.9

Frequency of Audit Committee Meeting

Total

< 4 times

> 4 times

40

135

175

22.9

77.1

Source: Developed for research

Based on Table 4.1, shows that 46.93 % which is 82 companies is audited by Big 4 (KPMG, Pricewaterhousecoopers, Ernst & Young, and Deloitte) while 53.1% indicates that 93 companies under trading sector is audited by Non- Big 4. The outcomes shown for audit tenure which is less than 3 years is 20.0%, out of 175 companies, 35 companies indicates that there are changes in auditor and 80.0% of companies persist with same auditors for more than 3 years.

Audit committee meetings are directs to meeting that attended by all the members during the financial year. Thus, 22.9% point out those 40 companies had meeting less than 4 times and 77.1% shows companies had meeting more than 4 times during financial year. Total assets of companies under trading sector shows that 1.1% which is 2 companies has assets in range of RM 100,000 to RM 300,000 while, 96.0% indicates 168 companies has an assets within log 5 to log 10 which is more than RM 300,000 and 2.9%, that is 5 companies has a total assets from log 10 to log 15 falls under range of more than 40 million.

Central Tendencies measurement of Constructs

In this research mean and standard deviation are chosen as a measurement of central tendencies. According to Sauders et al., (2009), standard deviation is a statistic used to describe the extent of spread of numerical values of data around the mean. If the standard deviation is low, then the data point tends to be very close to mean and if the standard deviation is high, the data point are spread out of large range. While, mean is defined as the average calculated by adding all the values and divide it by total number of cases.

Table 4. 2: Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

LAF

175

4.00

7.45

5.37

0.49

AUDTEN

175

0

1.00

0.80

0.40

BIG4

175

0

1.00

0.47

0.50

SIZE

175

5.35

10.74

8.30

0.97

ACMEET

175

0

1.00

0.77

0.42

Source: Developed for research

The table above illustrates the results of descriptive statistics of the variables. It shows the sample, mean, minimum, maximum and standard deviation for the following independent variables which are audit tenure, company size (total asset), audit committee meeting, audit firm size and for dependent variable, audit fees. The LAF represent audit fees and company size (total asset) is in log10. For a better understanding, the entire amount is transformed into log 10 because of giant amount of audit fees and total assets which held under listed companies.

According to Aksu (2003), Centre of the scale is considered acceptable if the value is more than 3.00 as a minimum for cut point. Thus the mean values of audit fees and size of company (total asset) is µ=5.37 and µ=8.30 which the variables are more towards neutral and agreed. However, for the audit tenure, audit committee meeting and size of audit firm mean values are less than 3, which is µ=0.80, µ=0.77 and µ=0.47. These items are more to disagree. In addition to it, all the variables have a standard deviation of less than 1.

Scale Measurement

Normality Test

Table 4.3: Normality Analysis

Kolmogorov-Smirnov a

Statistic

Standardized Residual

.090109

Table 4.3 illustrates the result of normality test. Normality test is to conclude whether the data is normally distributed. Hence, an audit fee (dependent variable) is studied by using this test. The most common test carry out for normality is Kolmogorov- Smirnov test and Shapiro- Wilk test. Kolmogorov-Smirnov is the appropriate test of normality for samples of more than 100 (Coakes, Steed & Dzidic, 2009). While, for data to be assumed normally distributed, the rule of significant is p value > 0.05 (Chong, Lin, Ooi, Raman, 2009).

For this research, 175 samples are obtained from trading sector under Public Listed Companies, thus group decide to use Kolmogorov-Smirnov test and the result for this test shows that the data is not normally distributed which p-value is 0.0100 (requires P<0.05). This is because audit fee figures were adapted from companies' annual reports. It is hard for the distribution to be normal because secondary data method is less of control to data collected and normality test is more focus on survey data. However, bias will not be produced in the coefficient estimates. (Robert, 2012).

Inferential Analysis

Pearson Correlation Efficient

Pearson Correlation Coefficient measures the strength and direction of the linear relationship between the two variables and describes the direction and degree that the variable is linked to others. The numbers that represent the Pearson correlation if refer as a correlation coefficient. The Correlation of (+1) means that there is a perfect relationship between two variables and vice versa.

Table of 4.4 : Rule of Thumb about Correlation Coefficient Size

Coefficient Range

Strength of Associates

± 0.91- ± 1.00

Very Strong

± 0.71- ± 0.90

High

± 0.41- ± 0.70

Moderate

± 0.21- ± 0.40

Small but definite relationship

± 0.01- ± 0.20

Slight, almost negligible

Table of 4.5 : Table of Correlations

Pearson Correlation Coefficients, N=175

Prob>|r| under H0:Rho=0

LAF

AUDTEN

BIG4

ACMEET

LAF

1.00000

0.21637

AUDTEN

0.0040

1.00000

0.39235

0.21185

BIG4

<0.001

0.0049

1.0000

0.47801

0.06366

0.18213

SIZE

<0.0001

0.4026

0.0159

1.0000

0.00435

0.06804

-0.14336

-0.00428

ACMEET

0.9544

0.3710

0.0584

0.9552

N = 175

Abbreviation:

AUDTEN : Audit Tenure

SIZE : Size of Company (Auditee)

ACMEET : Audit Committee Frequency

BIG4 : Size of Audit Firm

Multicollinearity refers to associations between the explanatory variables. Table 4.5 above clearly shows that the correlation relationship between all the independent variables (AUDTEN, SIZE, ACMEET and BIG4) and dependent variables, audit fee (LAF) was analyzed. Based on the table 4.4 and 4.5, dependent variable of audit fee and independent variable of meeting frequency have the multicollinearity problem because the value is 0.9552 which is more than the 0.9000. The problem also goes to the independent variable of audit committee meeting frequency and size of company, the value is 0.9544. Therefore, there have similar characteristics between the variables. The remaining variables do not have multicollinearity problem and have different characteristics since the value is below than 0.9000. If many correlations are greater in absolute value than 0.8 or 0.9, multicollinearity problem may exist. (George, 2010). In brief, frequency of audit committee meeting variable should be reconsidered for future research.

Multiple Linear Regressions

Multiple linear regression analysis examines associative relationships between a metric dependent variable and one or more independent variable. In this study, multiple linear regressions is used to analysis how much of the percentage for all independent variable which including audit tenure, size of company, audit committee meeting frequency and auditor's firm size contribute to explain the dependent variable - audit fee.

The equation is: Y=a + b1X1 + b2X2 + b3X3 +………bnXn

Y = Prediction relationship of types of variables towards quality of internal control

a = Constant Value

bn = Unstandardised coefficients

Xn = Dimension of independents variables

Table of 4.6 : Model Summary b

Model

R

R Square

Adjusted R Square

1

0.5849

0.3422 a

0.3267

Predictors : (Constant), AUDTEN, SIZE, ACMEET, BIG4

Dependant Variable : LAF

R2 measures the percentage of variation explained by the model. Based on the table of 4.3.3, the R2 value is 0.3422. It has explained that 34.2% of dependent variable (audit fee) is able to be explained by these four independent variables. Meanwhile, the adjusted R square value is 0.3267 (32.6%), it has showed that there exists small but definite relationship for all independent variables towards dependent variable. This result is said not to be satisfactory if R2 value is more than 0.50. However, it is acceptable because its R2 is more than 0.30 (30%). The strength may be not strong because it may have affected by other factors and further investigation is required.

Table 4.7: The Coefficient of Multiple Linear Regressions Analysis

Coefficients a

Model

Beta (β)

Standard Error

t Value

Significance b

(Constant)

3.34512

0.27097

12.35

<.0001

AUDITEN

0.15139

0.07785

1.94

0.0535

BIG4

0.28854

0.06387

4.52

<0.0001

SIZE

0.20919

0.03180

6.58

<0.0001

ACMEET

0.04646

0.07323

0.63

0.5267

Dependant Variable: LAF

P-value. If P > 0.05, it is not significant; if P < 0.05, it is significant.

Source: Developed for the research

Table 4.7 presents the multiple regressions for KLSE Public Listed Companies (PLC) in trading or services sector. The multiple regressions can be expressed as follows:

LAF = 3.34512 + 0.15139AUDTEN + 0.28854BIG4 + 0.20919SIZE + 0.04646ACMEET

From the regression equation above, it reports that the audit tenure (AUDTEN, β=0.15139) is positive which would indicate that longer audit tenure is not related to lower audit fees and it is not significant (p=0.0535). This result is somewhat unexpected as many previous researches have proved the significant positive relationship between audit tenure and audit fees. However, this result is in contradicting with some prior studies at last.

The frequency of audit committee meetings (ACMEET, β=0.04646) is positive and it is not significant (p=0.5267). Its coefficient is positive which would indicate that the frequency of audit committee meetings is not related to audit fees. This would seem to indicate that the audit tenure and the frequency of audit committee meetings are not important determinants in testing the relationship with audit fees.

The effect of company size (p<0.0001) is significant. The size variable is related to audit fees and functions more as a proxy for audit fees. Finally, the audit firm size (BIG4, p<0.0001) seems to be related to audit fees. However, their coefficients are positive.

Conclusion

Based on the statistical analysis, the four independent variables that composed which are audit committee meeting frequency, audit tenure, size of client's company and auditor's firm size have shown in different relationship with dependant variable - audit fee. However, audit committee meeting frequency and audit tenure do not have significant relationship with dependant variable according to the test. Size of company and auditor's firm size have significant relationship with audit fee. Therefore, discussion, implications and conclusion will be presented in chapter 5.

CHAPTER 5: DISCUSSION, CONCLUSION AND IMPLICATIONS

Introduction

This chapter provides further discussion on the results generated in previous chapter. Furthermore, limitations of the study encountered during the progress of the research will be discussed. However, recommendations will be provided for future researchers to assist future researchers in doing their research. Lastly, there is a brief conclusion for the entire research study.

Discussion of Major Findings

Table 5.1 Summary of the Results of Hypothesis Testing

Hypothesis 1

H1: There is an association between audit tenure and audit fees.

Reject

Hypothesis 2

H1: There is an association between size of audit firm and audit fees.

Accept

Hypothesis 3

H1: There is an association between size of company and audit fees.

Accept

Hypothesis 4

H1: There is an association between audit committee meeting and audit fees.

Reject

Source: Developed for the research

Based on the Table 5.1 above, it presents Hypothesis 2 and Hypothesis 3 are supported while Hypothesis 1 and Hypothesis 4 are not supported because there is no significant relationship (both p-value are more than 0.05) from the regression analysis results which were processed by the SAS.

The relationship between audit tenure and audit fees

H0: There is no association between audit tenure and audit fees.

According to the Table 4.7, the AUDTEN's significant value is 0.0535 which is more than the standard p-value of 0.05. Therefore, the null hypothesis is not rejected, stating that there is no significant relationship between audit tenure and audit fees. In short, audit tenure does not have an effect on audit fees.

This result supports the findings stating that audit tenure itself is not found to explain significant variance in audit fees whereas the prior findings suggest that the joint effect of soliciting bids and auditor tenure is an important interaction affecting audit fees but not the audit tenure itself affecting audit fees. Based on the past study, it also states that cities which change auditors do not pay significantly different audit fees in the year after the change than cities which do not change auditors. (Rubin, 1988). Although some of prior audit fee studies have showed that there is no significant relationship between audit tenure and audit fees, this research tends to enhance the prior results because Simunic (1980) and DeAngelo (1981) support the hypothesis that the audit tenure variable has the expected sign and it is significantly related with audit fees. Thus, this independent variable can be taken into consideration based on the previous statistical findings.

The relationship between audit firm size and audit fees

H1: There is an association between audit firm size and audit fees.

According to the Table 4.7, the BIG4's significant value is less than 0.05 (p< 0.0001). Therefore, the researchers reject the null hypothesis, stating that there is significant relationship between size of audit firm and audit fees. In other words, size of audit firm has positive significant relationship with audit fees and it is consistent with prior studies's results. (Simunic, 1980). The prior findings stating that there is a statistically association between auditor size and audit fees based on Big Eight and non- Big Eight dichotomy regardless of industry specialist categorizations. (Palmrose, 1986). Numerous studies in many countries have found that the largest, international and reputational audit firms will earn more fee premiums due to their perceived higher quality. (Lasse, 2004). However, result is in contradicting with Simunic (1980) and Firth (1985) studies. They found that no significant influence of auditor size in other countries (i.e US and New Zealand).

The relationship between size of company and audit fees

H1: There is an association between size of company and audit fees.

According to Table 4.7, the SIZE's significant value is less than 0.05 (p< 0.0001). Therefore, the researchers reject the null hypothesis, stating that there is significant relationship between audit firm size and audit fees. In other words, audit firm size has positively effect on audit fees.

This result is supported by the findings (A. K M Waresul Karim and Peter Moizer, 1996) stating that audit fees are positively associated with the size of the company measured by assets. It is because more assets need more verification and thus a higher volume of audit work is required. Besides, Tony, Michael and Roydon (1994) also indicated that larger companies with more subsidiaries were charged higher audit fees. Further, the past study (Chan et al, 1993) also stated that auditee size is by far remained the most significant explanatory variable in determining audit fees.

The relationship between frequency of audit committee meeting and audit fees

H0: There is no association between frequency of audit committee meeting and audit fees.

According to the Table 4.7, the ACMEET's significant value is 0.5267 which is more than the standard p-value of 0.05. Therefore, the researchers do not reject the null hypothesis, stating that there is no significant relationship between audit committee meeting and audit fees. The prior studies hypothesized that firm with more diligent audit committees (higher frequency of audit committee meetings) are likely to pay lower external audit fees. (Yatim et al., 2006). In other words, this research would expect frequency of audit committee meeting to be a variable on testing the relationship with audit fees but the result has showed that it did not have significant effect or association on audit fees.

According to the previous study, findings of Abbott et.al (2003) support this research's result where the regression analysis did not reveal there is significant association between audit committee meeting and audit fees. However, this independent variable still can be taken into consideration since the previous study (Yatim et al., 2006) provides supporting evidence. Compared to Yatim et al. (2006) model, one reason that the result fails to prove a significant relationship between these two variables is this research has used a dummy variable of 1 for firms that held 4 (required by the Main Market Listing Requirements) or above audit committee meetings in the financial year whilst Yatim et al. (2006) directly used the number of meetings as a measurement. If this research uses the number of meetings as measurement but not a dummy variable, the hypothesis may be supported. Besides, the frequency of audit committees meetings is mandatory to be held for at least 4 times as required by Main Market Listing Requirements, most companies will have meetings for at least 4 times per year, therefore, the result is expected to be insignificant because this research found that the range of audit meetings frequency is between 4 to 7 times for the sample selected. In other words, audit committee frequency has not much influence or difference on audit fees among companies.

Implications of the Study

This research aims to provide further understanding on association between audit fees and audit quality characteristics, notably Malaysian Public Listed Company (PLC) in trading services sector. The findings of our research provide the practical implications for audit/corporate managers, practitioners and policy makers to make a decision on audit fees based on factors which we have proposed.

Managerial Implications

The understanding of audit fee determination is pertinent to suppliers and customers of the audit services industry (Che-Ahmad & Houghton, 1996). However, this research has contributed audit fee model with respect to audit tenure, size of company, audit firm size and the frequency of audit committee meeting to managers or practitioners from small medium entities or public listed companies in the trading or services sector. The pricing of these fees is also important to market regulators as previous studies have shown audit services might not be priced competitively due to high concentration of the number of accounting firms (Che-Ahmad & Houghton, 1996).

Audit tenure and frequency of audit committee meeting variables were tested in this research. These two variables are rarely tested by previous researchers. The relationship of these two variables and audit fees still remain unclear. This research has made a contribution which enhances the relationship between these two variables and audit fees. The results showed that there are not significant relationships between these two variables and audit fees because both are less than 0.05 of P-value. Other than that, the previous results have shown that long tenure indicates no significant relation between non-audit fees and likelihood of restatement. (Stanley and DeZoort, 2007) and a research data indicates that there is no significance relation between audit fees and audit committee meeting frequency. (Abbott et al., 2003). This research's results are consistent with the previous researches' results. This research has provided clearer indication to auditors or companies in determining audit fees. For example, auditors or companies may avoid using audit tenure and frequency of audit committee meetings as their determinants of audit fees.

Most previous researches for modeling of audit fees have been examined without limiting to a single sector. However, this research is limited to a single sector which is trading or services sector. Therefore, the results of this research may have differences with most previous researches. This research has extended the perspective of audit fees model for auditors or companies in trading services sector because there's not much researchers are focus on a single sector.

This research is conducted in developing country - Malaysia. The previous research has shown that on average, companies in developing countries pay lower audit fees than companies in developed countries. (Chung & Narasimhan, 2006). This research has provided a deeper insight to public listed companies in trading services sector in developing country. In this research's results, those listed companies in Malaysia may propose an audit model that is different from developed country.

5.3 Limitations of the Study and Recommendations for Future Research

The overall result is not significant as R square is 0.3422 (34.22%) and adjusted R square is 0.3267 (32.67%). We acknowledge the limitations in our research. Firstly, sample is relatively small which reduces the power of tests. Future researchers are advised to have larger sample size.

Secondly, our results are for Malaysian Public Listed Companies in trading or services sector. This is a serious limitation as public listed companies have the responsibility to be profitable as private firms are subject to the same accounting standards. Our research is limited to a single sector as other firms in different sectors may show different data or information, for example, total assets of firms in construction sector may be higher than firms in trading or services sector. The coverage for our research information becomes small and thus reduces the accuracy because research's results do not cover other industries in Malaysia. For recommendation, future researchers are strongly recommended to cover other industries as much as possible but not restricted to single industry only. In other words, the wider the scope of investigation, the greater coverage of the result.

Thirdly, Log of total assets (LNTA) and total revenue are used as a proxy for auditee size. (Seetharaman, Gul, & Lynn, 2001). Firm size was measured by total assets and by total sales. (Waddock & Graves, 1997). This research has only used natural log of total assets to measure the size of company but total revenue is not used in the research. This would slightly reduce the accuracy of results. The total revenue may also be one of the best proxies in modeling audit fee. To enhance the outcome, future researchers are suggested to use different proxies other than log of total assets in their studies.

In addition, firms whose audit committees meet at least four times annually are less likely to have restated their audited financial statements. (J. Abbott, Parker, & F. Peters, 2004) However, The Bursa Malaysia Corporate Governance Guide (2009) emphasizes that at a minimum, the audit committee should meet at least four times a year (Para 2.6.2). The result has showed that the audit committee frequency was not a significant independent variable. We would like to recommend future researchers to have deeper insight into audit committee characteristics but not only focusing on audit committee meeting frequency as it is ambiguous in audit fee model. For example, audit committee frequency is a signal about audit committee diligence (Menon & Williams, 1994) but audit committee diligence can be defined in different ways. Therefore, future researchers are recommended to test the relationship between the audit committee characteristics and audit fees instead of audit committee meeting frequency as it can be categorized into audit committee characteristics.

There are some limitations on secondary data. First, the researcher may have defined the variables differently. For example, audit fees may be categorized as "audit fee" and "non-audit fee" instead of containing every major category. Second, its answer may not fit research questions. It may not have been collected in the geographic region desired, in the years desired, or the specific population. The researcher has no control over the content in data set. This can limit the analysis or alter the questions the researcher sought to answer. (Boslaugh, 2007). Future researchers are suggested to collect the updated data and specify the population. Moreover, the variables should be clearly defined otherwise data are collected wrongly and biases may be resulted in data.

Conclusion

This research has concluded that the size of audit firm and size of company have associated with audit fees that company paid to auditors in exchange for performing an audit. Thus, future research should be conducted to investigate characteristics of audit quality as it is getting important and essential to audit success.

Summary of Variables and Measurements Variables

Variables

Items

Description