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The purpose of this study is to investigate the relationship between the audit committee characteristics and firm performance. In order to discover the relationship, some methodologies have been applied to undertake the research. This chapter deals mainly with research methodology applied in this study. The methodology chosen are outlined in detail to help the user's understand what statistical tools are used in this research.
This chapter is divided into several subsections. The organization of this chapter is allocated into some subsections. For Section 3.2, it enlightens on the conceptual framework. Section 3.3 describes on development on hypothesis and followed by Section 3.4 that explains on measurement of the variables. The regression model is developed in Section 3.5. Next, Section 3.6 enlightens on the measurement of variables that explains in details on the choice of dependent, independent and control variables that are selected based on the objective of study and finally Section 3.7 presents the regression model used for this study. Section 3.8 describes the methods that are used in this study to gather the relationship.
3.1 Conceptual Framework
The theoretical framework for this study derived from the previous research by Anthony Kyereboah_Coleman (2007). In his research on the practices of the 103 listed companies on Ghana, Nigeria, Kenya and Johannesburg stock exchange, in their study it have combined the corporate governance structure that are board characteristics and audit committee characteristics towards the firm performance. For this research the researcher is only using the characteristics of audit committee that are size, independence and activity in audit committee that affect the performance of the company. The researcher also added another one variable that is financial knowledge among audit committee. This variable has been used by the previous researchers in their research. As explained, this study investigates the relationship between audit committee characteristics with the performance of the company that measured by Return on Asset. The independent variables are size, independence, activity and financial knowledge of audit committee.
Return on Asset (ROA)
Figure 3.1 : conceptual framework
Figure 3.1 above is the framework, showing independent variable for this research, which are size, independence, activity and financial literate.
3.2 Development of Hypothesis
3.2.1 Company performance (Dependent Variable)
Gain on assets in this study used as performance indicators, Return on assets is also used by Barber and Lyon (1996); the calculation for the ROA as operating profit before depreciation divided by total assets. Gain on assets (ROA) is a financial ratio that shows the percentage of profits that a company produces in relation to overall resources. It is typically defined as net income (or profit before tax) / total assets. ROA is known as the ratio of profits or productivity, for providing information on performance management in the use of small business assets to generate income. ROA and other financial ratios can provide small business owners and managers with a valuable tool to measure their progress against predetermined internal goals, a specific competitor, or industry as a whole. ROA is also used by bankers, investors, and business analysts to rate companies use the resources and strengths the financial
O. Gill.J (1996) noted in his book Financial Basics of Small Business Success, most entrepreneurs decide to own business to make better decisions on their money than is available through a bank or a low risk investment. If the ROA and other profitability ratios showed that this did not happen, especially on small businesses, it has moved beyond the start up phase, the entrepreneur should consider selling the business and invest his money back or elsewhere. ROA measurements include all the assets of a business including those arising from the obligations to creditors or that which arises from contributions by the investors. For this reason, the ROA is usually less attractive to shareholders of several other financial ratios. However, the inclusion of the obligation is to make ROA even more valuable as a tool to measure the performance, particularly in assessing the performance of various departments or sections companies.
ROA is a superior internal management ratio because it measures profit against all of the assets a separation uses to make those earnings. Hence, it is a way to assess the division's performance and efficiency. It's also more suitable because division managers rarely get caught up in raising money or make a decision when using the mix between debt and equity. As written by. Kristy.A.J and. Diamond.Z.S (1984) in their bookÂ Finance without Fear,Â "One of the cardinal rules in managing business professionals is to hold them accountable for only those activities they control. ROA comes close to doing just that."
3.2.2 Audit Committee Characteristics ( Independent variables)
Formation of audit committee can enhance the company performance. As a subcommittee in the cooperation, an audit committee aims to supply an assurance on financial and compliance issues through increased analysis, accountability, and the capable use of resources. An audit committee may also supply an advisory task focusing on performance improvement within the organization. Unfortunately, for audit committees as well, the empirical findings of their influence on performance are mixed. Audit Committee, if it is formed by independent individuals in particular, it can have benefits necessary to increase the reliability of the system of internal controls. This can cause a positive impact on market perception of the company ability to signal to its operations in a manner that is transparent, correct and effective. (Fratini and Tettamanzi, 2006).
3.2.3 Audit committee size
Abbott et al. (2004) expressed the opinion to show that the audit committee with at least three directors has a better quality in monitoring and associated with a lower incidence of restatement. However, after the satisfaction of individual members may not exert enough effort in the work of the committee. Conversely, the smaller teams can often pursue their tasks more effectively. Yermack (1996), for example, found that smaller boards are associated with higher quality monitoring. He shows that companies with smaller boards could shape the CEO for a better more disciplined in the case of poor performance, to give executives a lower level of total compensation, and is also associated with higher market valuation. Similarly, the expectation that the problem cannot be prevented; increased the effective function of the large audit committee to spot potential problems in financial reporting. In addition, if the size of a team is large, individual members may be more vulnerable to the pressures and more subject to follow the others' opinion without giving another argument. In this case, the audit committee members are not likely willing to question the potential errors in the accounting reports of the internal review process, which in turn can lead to a greater chance of presenting again later. Conversely, a small team will facilitate the exchange of information and a better discussion between members, to assist management to identify potential errors in financial reporting and reduce the incidence of restatement of the minimum size requirements, a large committee may suffer from the problem of free riders, In previous studies, the size of the audit committee determined by the amount of the number of audit committee. These variables have been tested in previous studies conducted by Xie et al., (2003). The results showed that the size of the audit committee to devote more resources is more likely to oversee financial reporting and internal control systems (Anderson et al, 2004.) High and facilitate discussions between the audit committee members (DeZoort and Salterio, 2001). Empirical evidence shows that companies with greater audit committee prefer to suspicious auditor switches (Archambeault and DeZoort, 2001) and more likely to have lower costs of debt (Anderson et. Al, 2004.). Since the exchange, the effect now requires their registrants to have at least three directors on the audit committee.
Thus, The first hypothesis is :
H1: There is relationship between audit committee size and firm performance
Independence of audit committee is determined by two definitions; first definition is independence is classified if director is a non executive director, but it a feeble definition because even though they are not involve directly, non executive director may be have another relationship through the previous employment or in business relationship that crack the meaning independence. The second definition is non executive director and does not have any relationship with the company, these definition are similar to Vafeas (2001).
A study done by the Carcello and Neal (1999), found that the likelihood of financial distress company received the going concern opinion from the auditors is lower when the percentage of outside director is bigger in the formation of audit committee, it means that the independence of the audit committee can help the external auditor to maintain their fiduciary duty without influence from the director. Another research by them found that a positive relationship between independence of audit committee and financial reporting quality; suggested that having the independence of director in audit committee can enhance the firm performance.
The success of the audit committee is also influenced by the composition of the committee. Previous literature that stated that if the board or executive committee members tend to form a coalition with the top management, it is likely to be small because they are very cautious in all matters affecting the shareholders as they have a responsibility to protect the interests of shareholders ( Conyon and He, 2004). In addition, if the board or committee members have business relations or other relationship with the company or members of the committee, for example, as a brother, a company lawyer, accountant, or consultant, they may feel a strong sense of duty towards the top management, who they should, depends on obtaining and renewing the contract agreement (Core et al, 1999). Consequently, the associate members may be more reluctant to challenge the top management, and are less likely to look for potential errors in financial reporting. As a result, we expect that the companies have audit committees composed entirely of independent directors that must hold better quality and to identify potential fraud in financial reporting and further reduce the possibility of profit restatement.
Thus, The second hypothesis is :
H2: There is relationship between audit committee independence and firm performance
A more active audit committee is expected to provide a mechanism for effective oversight of the company. Since, the level of activity reflects the audit committee of good government, should improve the reliability of financial reporting. Manual of Corporate Governance states that the provision of an institutionalized forum audit committee encourages external auditors to take a troublesome issue in the early stages. As a best practice, audit committee meetings should be conducted at least once a year without the presence of members of the executive board to avoid interference in the issues arising. However, the number of meetings depends on the requirements of reference and operating complexity. At least three or four meetings should be planned to coincide with the audit cycle and the annual report issued in addition to the other meeting held in response to the incurred during the fiscal year ( Code on Corporate Governance, 2000). Consistent with this argument, a study of Anderson et al. (2004) showed that the cost of debt is reduced while increasing the frequency of audit committee meetings; shown to improve the performance of the company to reduce debt. Xie et. al. (2003) found that the number of negative audit meetings related to discretionary accruals (DAC)
Effective monitors in companies by the audit committee it is not enough if they are independent, they also must be active (Menon and Williams, 1994). This proposes that when examining the independence, the researcher should also examine the level of audit committee activity.
Thus, The third hypothesis is:
H3: There is relationship between audit committee activity and firm performance
3.2.6 Financial Literacy
The definition of financial skills recommended by the Blue Ribbon Committee (1999), is which director holds the certification from the professional bodies or members of professional bodies in accounting and has served as Chief Executive Officer (CEO) or senior executive positions in finance or accounting. The second definition describes the financial expertise of directors who are members of professional accountancy body that proposed by Rainsbury Elizabeth (2004). This proposal shows that audit committee members should be two main types of understanding on how business is presented in financial reports and the ability to analyze reporting (financial reporting knowledge), and the understanding of the nature and purpose of auditing the financial report (audit report knowledge). Audit committee members with financial-reporting will be even more likely to support the auditor in disputes with the will of the management of low levels of knowledge (F. Todd and Salterio, 2001). Members with the knowledge that should be better talented to understand the technical accounting procedures and standards, and thus appreciate the importance of valuation in accounting substance over form, the source of frequent disputes between auditors and management (Shah 1996)
Thus, The fourth hypothesis is :
H4: There is relationship between audit committee financial literacy and firm performance
With the use of debt financing, potential conflicts of interest arise between shareholders and debtholders which give rise to agency costs ( Jensen and Meckling, 1976). Accounting-based covenants are typically written into debt contracts by debtholders to mitigate these conflicts and therefore monitor the actions of management and shareholders. These covenants often require firms to obtain audits of their financial statements and a certificate of compliance with the covenants (Smith and Warner, 1979). However, managers of firms with higher leverage have greater incentives to make accounting policy choices that manipulate their financial statements, consequently avoiding the costs of violating debt covenants. Therefore, in such situations, firms have incentives for improved monitoring of the process of financial reporting (Klein, 2002). As leverage increases, boards are predicted to voluntarily establish independent audit committees with financial expertise as a means of reassuring debtholders that the audit committee is effectively monitoring the financial reporting process (Rainsbury et al., 2008).
This suggests the following hypothesis:
H5: There is relationship between leverage and firm performance
3.3 Measurement of variables
In this study, variables are chosen based on the detailed analysis that has been done from prior researches. In reality, there are no particular accepted rules or guidelines that can be applied for the chosen of variables in carry out the research. Most probably, those three factors are barely that are suitable and can be considered as rationale for the chosen of such variables. Firstly, the researcher can choose the variables that have been used by the prior researchers that provide significant explanatory in the past regression model. Secondly, the selection of variables can be made based on the accessibility of the data. Thirdly, variables should be carefully chosen based on the relevancy with the factors that are going to be tested in line with the of audit committee in listed companies in Malaysia.
3.3.1 Firm performance
As this research to measure the performance of the company, the researcher has used the return on assets (Kyreboah-Coleman, 2007).
3.3.2 Audit committee size
In this study, audit committee size is determined by the number of audit committee in the company. This variable has been tested in the previous study done by the Xie et al., (2003).
Independence audit committee can be explained by the two definitions; the independence of directors is classified if the non executive directors, but the definition is weak for the reason that although they are not directly involved, the executive director could not have had other contacts through previous employment or business relationship that cracks in the meaning of freedom. The second definition is a non executive director and is not related to the company. This definition is consistent with that used by Vafeas (2001) and consistent with the concept of freedom of the BRC (1999). For this study, researcher used the second definition of independence. While the audit committee independence is considered if all members of the audit committee is in full independence of not having any relationship with the company interaction and will be encoded with 1, but if the audit committee is not full independent will be encoded with the number 2
In this study the researcher will be using the number of meeting that is attended by audit committee as a proxy to measure the level of audit committee activity. This method is similar with the previous research done by Menon and Williams (1994). They use the number of audit committee meetings as a proxy for the level of audit committee activity. The reason why they use number of meeting is for the reason that audit committees that do not meet or meet only a little times, are unlikely to be effective monitors. With this fact, audit committee activity as an essential part of audit committee effectiveness.
3.3.5 Financial literate
For this study the researcher will use the definition that is used by the Rainsbury (2004); as the experience of director if they only hold the position as a Chief Financial Officer. The reason why the researcher chose the CFO is if the director has an experience as a CFO, he or she is having the knowledge in financial background such as read and analyze the financial report. In addition in best practice in MCCG it stated that "all its members should be able to read, analyse and interpret financial statements so that they will be able to effectively discharge their functions" (MCCG, 2007. the audit committee financial knowledge will be encoded with 1 if an audit committee has the professional qualifications of the professional accountancy bodies and 2 if it is not.
Leverage have been used in prior study such as Krishnan and Young (2005).. The probability of this variable to influence firm performance is high, since greater borrowings require the lender to play a greater monitoring role of the company and managers may also control the earnings to avoid debt covenant violations. Thus, leverage is measured by total liabilities divided by total assets
3.4 Regression model
The objective of this study is to determine the relationship between audit committee characteristics and firm performance in Malaysia companies. Therefore, regression analysis is applied in order to achieve this objective. It is to identify the existence of the relation between audit committee characteristics and firm performance such as audit committee size, frequency meeting, independence and financial knowledge. The regression model of this study is as follows:
ROAi = Î²0 + Î²1 ACSIZE + Î²2 ACMEET + Î²3 ACIND + Î²4 ACFINLIT + control variable É›i
ROAi = EBIT/TOTAL ASSET
ACSIZE = Total number of directors on the audit committee
ACMEET = Total number of audit committee meeting held within the financial year
ACIND = Full independent of audit committee
ACMEET = Total number of audit committee meeting
FINLIT = Having the profesional certificate
Control variable (Leverage)= Total Liability/Total Assets
Î² = Parameters
É›i = Error
3.5 Data collection
This study involves both quantitative and qualitative approach. This is a cross sectional study examining the relationship between the audit committee characteristics and performance in company. The data is collected from published annual reports downloaded from the internet. All the annual report is available in Bursa Malaysia web site.
3.6 Sample Selection
This study focuses on the four largest industry sectors of listed companies in the Main Market. These four sectors are consumer products, industrial products, properties and trading/service sectors. This four sectors are having the high market capitalization..Subsequently, for each sector, the company is chosen according the stratified sampling method. The total companies that are listed in the four major industries is 684. From this total population proportionate stratified sampling are using to determine the sample size 169 companies.
Stratified random sample selection is chosen in order to have general representative sample from a significant proportion of the listed companies, with regard to the extent of audit committee characteristics on company performance. Therefore, the results obtained are able to be generalised to Malaysian listed companies in the respective industrial sectors. The researcher acknowledged the possibility of inconsistencies in the analysis and result, but according to Kyereoah-Coleman (2007) the differences that occur are very small impact on the results sacrificing authenticity. A sample size of 169 is acceptable for statistical analysis, as according to Fisher (2007), under the standard of minimum sample size of 30 is satisfactory and the amount of sample is proposed by Sekaran's (2003); the sample reflects the total population. Furthermore, the sample must be large enough to provide sufficient reliability, but not too further as this will be a waste of resources. A rule of thumb showed that the samples should be somewhere between 100-1000 units and not more than ten percent of the population (Alreck & Settle,1995). This rule of thumb hence suggests that the maximum sample size is somewhere in the range 100-500 units.
Data is sourced from individual company annual reports. These annual reports are available and downloadable from the website of Bursa Malaysia (http://announcements.bursamalaysia.com).
Table 3.1 Summary of Sample size
No of companies
Trading and Services
3.7 Analysis of data and Research design
The findings of the study will be analyzed using the Statistical Package for the Social Sciences (SPSS) computer program for windows Version 17. The analysis of the data was performed in two stages : (1) check the normality; and (2) statistical procedures: descriptive statistic, correlation analysis and regression analysis.
3.7.1 Test of Normality
Test of normality employed several descriptive plots on the data set. In this study, normal probability plots are plotted to visually examine the distribution of data. The exploratory data analysis employed two types of probability plots to demonstrate that the data came from a normal distribution. In the Normal Q-Q plot for firm performance, the observed values seemed to cluster along a straight line, providing an indication that the data were normally distributed (Figure 3.2). Normality test will help to justify which type of test to further be carried out either parametric or non-parametric for inferential statistics. Thus, Kolmogorov- Smirnov statistics is used to determine the normality of data in this study. If the result from the test marked a significance level which is greater than 0.05 (p>0.05), it is assumed that the data is normally distributed. Two types of correlation tests that can be applied are the Pearson and Spearman coefficient. If the data is normally distributed (p>0.05), parametric test (Pearson) is applicable. On the other hand, the non-parametric test (Spearman) is applicable if the data is not normally distributed (p<0.05).
Figure 3.2 : Test of Normality
a. Lilliefors Significance Correction
Figure 3.3 : Normal Q-Q Plot
Similarly, the observed values of the Detrended Q-Q plot in Figure 3.2, as well clustered randomly around the horizontal zero line to imply that the data of firm performance are sampled from an approximately normal distribution.
Figure 3.4 : Detrended Normal Q-Q Plot
3.7.2 Descriptive Statistics
According to Leary (2001), descriptive statistics is a powerful tool to describe and understand the data so that they can be easily comprehended by others. The descriptive statistics employed in this study are as followed: (1) measures of central tendency; (2) measures of variability; and (3) frequency distribution. These statistics are used to extract and summarize quantitative information from the sample.
Measures of central tendency helped to find a single index that could represent the whole set of measure. This study utilized the mean or average to describe the data in terms of average values. Mean is chosen due to the variables investigated in this study such as the dependent variable and the independent variables. Ary et al., (1996) reported that mean could give a more precise measure than all the different measures of centrality such as the median or mode as it takes into account the value of every score. It is also more stable compared to other measures of central tendency especially when the samples are randomly drawn from the target population.
This study also employed the most commonly used measure of variability and standard deviation to find out the dispersion or variability of the data set. Since it is also an interval statistic as the mean, it could be used to describe the degree of dispersion of all the interval variables (dependent and the independent variables). Frequency distribution is used to extract important features of the quantitative data of the study. The original data collected are grouped and presented in a summarized form by constructing appropriate tables and charts.
Statistics such as means, standard deviations, range percentages are also used to summarize and describe the data. A combination of these statistics helped to provide a more comprehensive description of the data presented. It is the aim of this study to identify the level of firm performance before correlating with the independent variables of the study. Descriptive statistics are also employed to summarize and describe the data pertaining to the demographic profiles of respondents in the study.
3.7.3 Correlation Statistics
According to Ary, et al., (1996), correlation statistic is a statistical technique used to measure the strength of the association or co-variation that exists between two quantitative variables. The strength of the relationship between two variables are measured by the coefficient of correlation, R, whose values may range from -1 to +1. If the direction of the relationship between two variables is positive, it means that high scores of one variable are associated with high scores of another variable and vice versa. When the relationship existed, correlation coefficient can also determine the strength of the relationship whether the variables have a strong relationship or a weak relationship. The closeness of the correlation coefficient to one implies a strong relationship between the two variables. When the correlation coefficient is zero, there is no correlation between the two variables.
Since the data in this study is not normal distributed, the appropriate method to test the correlation is using the Spearman's Correlation Coefficient Matrix under non parametric test.
3.7.4 Level of Significance
Empirical researcher would need to establish the extent of error before the research was conducted in order to determine the statistical significance of the findings. It is important in order to calculate the probability of making errors in drawing conclusions from the study. According to Lowenberg and Conrad (1998), establishing the statistical significance would help the researcher to decide the extent to which the results might be due to chance or systematic effect and it could assist in determining the extent to which findings from the sample could be generalized to the targeted population.
In this study, a ninety-five percent confidence level (p < 0.05) is set as the criterion level for determining statistical significance. This level has been fixed based on the arguments provided by established statisticians. For instance, according to Cramer (1997), the level of p < 0.05 is the conventional probability for decision that the result is not due to chance
3.7.5 Multiple Regression
Multiple regression is a statistical technique that allows researcher to predict someone's score on one variable on the basis of their scores on several other variables. In order to test the relationship between the dependent variable and independent variable, hierarchical multiple regression is most appropriate technique, it because this study have employed the control variable.
This study employed a quantitative research methodology to assess dependent variables that existed. A descriptive correlation approach was used to determine the relationship between the selected independent variables and firm performance, the dependent variable. Data were collected using a validated and reliable research instrument as it appropriateness, practicality and reliability for use in the local setting were assessed before it was administered. This research instrument was finally administered to a representative sample drawn from the population of the study to enable the researcher to make inferences or generalization from the sample statistics to the population understudied. The size of the sample of the data collection is based on the total number of population. After the data were collected, they were analyzed using a combination of statistical analysis such as descriptive statistics, correlation statistics and multiple regression analysis to answer the research questions.