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In this assessment you have to use AXS 50 website and download annual reports of top 50 company's of Australia of year 2014,2015,2016 and use this two variables.

1. independent director
2. performance ( profit/loss)

Make detail reports of your findings in a form of table and find a correlation between your findings and you to make a relation about this two variables. you can make your own questions while making correlation and help me with this analysis of year 2014,2015,2016.

Problem Statement

The most ideal career path for a student of Master of Professional Accounting student would be to become a professional accountant. This research is about the study of the business performances of top 50 Australian companies. The project background, research aims and objectives and the literature review will constitute the first part.  In the second part, the research methodology, findings, discussions and conclusions will be explained.

Fro the last few decades, general public get more interests in the way of companies performing business and affecting the environment. This is mainly because different people have different types of interests. Some are interested in shopping. So they will be concerned about the retail stores and companies and would like to know about their profits or losses. Some people are into investments. They will be interested in knowing the status of a financial company and judge from there the appropriate company to choose. Similarly, people with different interests are concerned about different types of industries. Thus, this research has been conducted.

The main aim of this research is to study the business performance of top 50 Australian Companies over three financial years 2014, 2015 and 2016. Thus, the following research questions can be framed to analyze the aim of this research:

  • To what extent is the profit of the firm associated to the remuneration of the directors?

This section of the study aims to focus on different theories that contains the information on the relationship between the remuneration earned by the directors and the profits of the companies. The basic theories that have been included in this section are the theory of the agencies and the dependency theory of the resources. Moreover, discussion of the corporate law has also been done to establish the relationship between the variablesdirectors’ remuneration and profits of the companies and also by discussing the board diversity of expertise. Further, the gap in the literature will be identified along with the limitations of this study.

The major work that this board performs is exercising the control and the provision which is related to the observation of management. This role which the board performs has been evaluated via the theory of the agency. When ownership and control of the assets are separated, the problem related to the agents arises. Moreover, the shareholders cannot influence any control over the management practically. It is not possible for the shareholders to do so. A major role has been played by the board to oversee the management and protect the shareholders’ rights along with equitable treatments (Terjesen, Couto & Francisco, 2016). This conflict can give rise to some moral risks and invalid information. As a result of this conflict, the directors are able to collect a lot more information. With the help of this information collected, they try to gain the trust of the principal and this might result in the fact that that this act will go for opposing the principal (Low, Roberts & Whiting, 2015).

Research Aims and Research Questions

According to the theory, the managers will not be involving themselves in any kinds of behaviours that will be disadvantageous to the organization. The values of the shareholders are increased due to the effectiveness of the agents. The need for monitoring the issue further will thus be minimized as the cost of transaction will be increased. It is never possible to agree completely with the shareholders in each and every such situation. Hence, according to the corporate governance domain, it is important to find out a solution that will be effective to control the stakeholders association and minimize the conflict between them (Adams et al., 2015).

According to some observations, the organizational operating area is inclusive of the ecosystem. The factors that are significant in this case are raw materials, labour and capital. The better the availability of these factors, the ore will be the success of the company. Developing strategic connections with other companies is critical. To do this, the directors have come up with a theory. According to this theory, at least two of the major responsibilities of the directors must be taken care of (Kaczmarek, Kimino & Pye, 2014). In order to retain the employees, the directors will have to pay the employees a proper remuneration. This is one of the factors for the retention of the employees (Triana, Miller & Trzebiatowski, 2013).

Now, as the employees will be working more for the company, the company will be earning more profit based on the performance of the employees. This profit will influence the remuneration earned by the independent directors. With the increase in the profits earned by the company, it can be assumed that the remunerations earned by the directors will increase. All the payments of the company are done on the basis of the profits earned by the company. Thus, the profits earned by the companies at the end of the financial year is said to be influencing the remunerations earned by the independent directors (Ferreira, 2015).

Very little research studies have been there in which the expertise of the directors and the professional background have been analysed until today. According to Gray and Nowland (2015), the board of expertise has been formed by the directors and they will be providing with the classification of the expertise that the directors possess into 11 different groups. These groups are formed of the groups of accountants, bankers, doctors, engineers, academics, consultants, scientists, lawyers, politicians, executives and other CEO’s (Nielsen & Nielsen, 2013). In accordance to the researchers, the board of expertise can be as diversified as stated above but the performance of the firm is not dependent on this diversity. There has been found a negative association between these non-business expertise and the performance of the firm (García-Meca, García-Sánchez & Martínez-Ferrero, 2015).

Literature Review

According to the discussed theories of the agencies and the resource dependencies, different effective boards would be effective in enhancing the shareholders’ wealths and the performance of the organizations. The homogeneous boards of the directors never used to consider the different viewpoints of the backgrounds of gender, age, wealth and ethnicity (Perryman, Fernando & Tripathy, 2016). The directors who do not have very good access with the CEO of the company will be under strict monitoring (Martín-Ugedo&Minguez-Vera, 2014).

A lot of theories are present in support of the matter of the relation of the board of directors and the shareholders’ wealth. This research is mainly based on the profit of the organization and remunerations earned as a result by the independent directors. The profit of the organization is in turn dependent on the shareholders. Thus, the above literature was worth discussing. The “UK Corporate Governance Code 2014”, “Sarbanes-Oxley Act 2002” and the “ASX Corporate Governance Principles and Recommendations 2014” improve the beliefs of the independent directors. This research explores the dependencies of the remunerations of the board of directors of a company with the profit earned by the company in a financial year.

The main aim of this research is to study the business performance of top 50 Australian Companies over three financial years 2014, 2015 and 2016. To do this research, the yearly profits of the companies and the remuneration of the directors of the respective companies are collected from the annual reports of the respective companies. The data thus collected for this research can be termed as secondary data as the data was collected from previous records and not directly from the field of research. The 50 companies that were selected belonged to various sectors such as utilities, materials, financials, consumer discretionary, industrials, energy, health care, real estates, consumer staples, information technology and telecommunication services. The profits and the remunerations of the directors of these different sectors will be compared in this study.

Quantitative data, such as earnings per share and year-end share prices are collected from annual reports and financial websites. Miles, Huberman and Saldana (2013) mentioned that it is appropriate to use quantitative methods for researches that measure facts on variables where reliability is important, a large number of samples and data can be analyzed statistically. They will be analyzed by using correlation and regression analysis and by using t-test, so as to find out the relationship between directors remuneration and business performance. MS Excel software is used to conduct the analysis.

Agency Theory

This is the first part of the analysis. In this part, the average remuneration of the directors earned at the end of each financial year for each of the 11 sectors of the 50 selected companies. Also, the average profit earned by the companies for these three years for the 11 sectors of 50 companies will also be determined and discussed.

This is the second part of the analysis. In this part the research questions will be answered. To do that some hypothesis will be framed and the truthfulness of those hypotheses will be tested using appropriate statistical techniques. To test the research question, whether there is any relation between the remuneration of the directors and the firm’s performance, correlation and regression analysis has been conducted.

Following the above discussions and the research questions framed above, the following hypothesis can be framed.

Null Hypothesis (H01): There is no association between the remuneration earned by the directors of the companies and the profits of the top 50 ASX listed companies.

Alternate Hypothesis (HA1): There is significant difference between the remuneration earned by the directors of the companies and the profits of the top 50 ASX listed companies.

At first, from the data collected, a descriptive study of the observations has been done. It can be seen that, of the 50 selected companies, one company belongs to the Consumer discretionary sector, three companies belong to the consumer staples sector, 5 companies belong to the energy sector, eleven companies belong to the financial sector, three companies belong to the healthcare sector, one company belong to the information technology sector, nine companies belong to the materials sector, 9 companies deal with real estates, one telecommunication services providing company and finally 2 companies from the utilities sector. The average remuneration and profit for the three years 2014, 2015 and 2016 is given in table 1. In the table 1, 2014 R, 2015R and 2016R are represented as the total remuneration earned by the directors of the company in the financial years 2014, 2015 and 6016 respectively. Again, 2014P, 2015P and 2016P are represented as the performance (profit/ loss) of the firm for the years 2014, 2015 and 2016 respectively. It can be seen clearly from the calculations in table 1 that the maximum amount of remuneration is paid by the consumer discretionary. It can also be seen that in the chosen sample, only one company falls under this category. Thus, it can be said that the consumer discretionary type of industry requires a lot of employments and thus the cost is high. Thus, there are very less industries in this sector. Information technology and telecommunication services experience the least amount of remuneration to be paid to the directors.

The Dependency Theory of the Resources

From the results of the analysis, it can also be seen that most profitable industry in Australia is the consumer staples industry. The energy sector, information technology sector and telecommunication services have experienced the least amount or a negligible amount of profit. In 2015, the energy sector suffered from a loss annually. This informationis shown in figure 1 and 2.

Table 1: Average Remuneration and Profit (Industry Wise)

Type of Industry

2014R

2015R

2016R

2014P

2015P

2016P

Consumer Discretionary

$89,215.77

$61,802.21

$79,374.72

$167.90

$279.50

$360.20

Consumer Staples

$46,504.96

$44,715.37

$44,295.87

$5,550.63

$4,555.23

$3,942.00

Energy

$19,754.75

$23,974.94

$26,128.48

-$1.24

-$129.59

$110.54

Financials

$31,838.17

$34,112.22

$37,367.84

$2,650.28

$3,103.62

$2,574.74

Health Care

$14,214.11

$16,079.91

$20,878.03

$667.35

$715.26

$736.37

Industrials

$35,398.01

$31,004.71

$40,980.64

-$190.56

$508.02

$606.80

Information Technology

$3,207.46

$2,675.30

$2,161.65

$254.53

$157.28

$161.80

Materials

$12,578.60

$17,332.63

$17,592.61

$2,403.74

$782.30

$1,284.47

Real Estate

$15,065.98

$18,150.61

$14,478.15

$2,048.43

$1,639.11

$1,726.50

Telecommunication Services

$3,207.46

$2,675.30

$2,161.65

$254.53

$157.28

$161.80

Utilities

$60,775.96

$66,481.89

$26,183.08

$540.45

$316.40

$60.15

 

 Figure 1: Bar Graph comparing the director’s remuneration in 3 years across different sectors.

 

Figure 2: Bar Graph comparing firm performance (profit / loss) in 3 years across different sectors.

Next, the remunerations of the directors are compared with the profits or losses of the companies. The correlation table shows the relationship between the two factors. It can be seen from the table that in 2014, the performance of the firm is very weakly correlated with the remuneration of the directors. Thus, with the increase in profit, nothing can be said about the increase or decrease of the variable. In the year 2015, it can be seen that there is also very weak relation between director’s remuneration and performance of the firm. The same result is established from the correlation table for the financial year 2016. Thus, from here, it can be said clearly that the performance of the firm do not depend on the remuneration earned by the directors of the company. The correlation table is shown in table 2 and the information discussed above is shown diagrammatically in figure 3, 4 and 5.

Table 2: Correlation Table

2014R

2015R

2016R

2014P

2015P

2016P

2014R

1

2015R

0.813721

1

2016R

0.722094

0.660145

1

2014P

0.052509

0.061876

0.005919

1

2015P

0.079985

0.066264

0.041818

0.839833

1

2016P

0.194624

0.162132

0.163569

0.815351

0.828129

1

 

 Figure 3: Scatter Plot showing the relationship between director’s remuneration and Company’s performance for the financial year 2014 (profit / loss). 

 

Figure 4: Scatter Plot showing the relationship between director’s remuneration and Company’s performance for the financial year 2015 (profit / loss).

The linear regression analysis considers two types of variables, independent variable and dependent variable. Here, one Dependent Variable – “Company Profits” and Independent Variable – “Total Remuneration earned by the Directors”. The regression has been done using the software Excel. The R squared results have been obtained from the regression analysis. Ony one independent variable has been considered here. The hypothesis fort the regression analysis can thus be stated as follows:

Null Hypothesis (H01): There is no association between the remuneration earned by the directors of the companies and the profits of the top 50 ASX listed companies in 2014.

Alternate Hypothesis (HA1): There is significant difference between the remuneration earned by the directors of the companies and the profits of the top 50 ASX listed companies in 2014.

Board diversity of expertise

Table 3: Regression analysis for the year 2014

 

The model summary shows that the regression results are 5.25% good fit as only 5.25% variations of errors can be explained using the regression line. The F statistics results is 0.132 which is less than the critical value of F shows that the unexplained variations are more for the profits in the top 50 ASX companies. Even the significant value is greater than 0.05, illustrating insignificant results. The regression line for the independent and the dependent variables can be given as:

Company profits = 1612.475 + 0.006 * Total Remuneration of the Directors

The hypothesis for the second regression analysis for the financial year 2015 re given below:

Null Hypothesis (H02): There is no association between the remuneration earned by the directors of the companies and the profits of the top 50 ASX listed companies in 2015.

Alternate Hypothesis (HA2): There is significant difference between the remuneration earned by the directors of the companies and the profits of the top 50 ASX listed companies in 2015.

Table 3: Regression analysis for the year 2015
 

The model summary shows that the regression results are 6.62% good fit as only 6.62% variations of errors can be explained using the regression line. The F statistics results is 0.212 which is less than the critical value of F shows that the unexplained variations are more for the profits in the top 50 ASX companies. Even the significant value is greater than 0.05, illustrating insignificant results.The regression line for the independent and the dependent variables can be given as:

Company profits = 1305.96 + 0.01 * Total Remuneration of the Directors

The hypothesis for the third regression analysis for the financial year 2016 re given below:

Null Hypothesis (H03): There is no association between the remuneration earned by the directors of the companies and the profits of the top 50 ASX listed companies in 2016.

Alternate Hypothesis (HA3): There is significant difference between the remuneration earned by the directors of the companies and the profits of the top 50 ASX listed companies in 2016.

Table 4: Regression analysis for the year 2016

 

The model summary shows that the regression results are 2.67% good fit as only 2.67% variations of errors can be explained using the regression line. The F statistics results is 1.320 which is less than the critical value of F shows that the unexplained variations are more for the profits in the top 50 ASX companies. Even the significant value is greater than 0.05, illustrating insignificant results. The regression line for the independent and the dependent variables can be given as:

Board heterogeneity and fit for purpose

Company profits = 1082.08 + 0.01 * Total Remuneration of the Directors

Conclusion

From the above discussions it can be thus concluded that the highest remuneration is earned by the directors of the consumer’s discretionary sector. Very little remuneration has been earned by directors of telecommunication sector and the information technology sector. The remunerations do not much differ from year to year in the same sector. It sometimes increases and decreases but on an average it remains the same. The most profitable firm is the consumer’s staple sector. It can also be observed that though this is the most profitable firm, the profit of the firm is decreasing gradually with the progression of years. From the correlation analysis, it is very clear that on all the three years, remuneration earned by the directors of the company do not depend on the performance of the company.

References

Adams, R. B., Haan, J., Terjesen, S., and Ees, H., 2015. Board diversity: Moving the field forward. Corporate Governance: An International Review, 23(2), 77-82.

Ali, A., Nakaa, N., and Abdelfettah, B., 2017. Chief Executive Officer attributes, board structures, gender diversity and firm performance among French CAC 40 listed firms. Research in International Business and Finance.

ASX 50 List - Data for ASX Top 50 Companies, 2017. Asx50list.com. Retrieved 5 October 2017, fromhttps://www.asx50list.com/

Chapple, L., and Humphrey, J. E., 2014. Does board gender diversity have a financial impact? Evidence using stock portfolio performance. Journal of Business Ethics, 122(4), 709-723.

Ferreira, D., 2015. Board diversity: Should we trust research to inform policy?. Corporate Governance: An International Review, 23(2), 108-111.

García-Meca, E., García-Sánchez, I. M., and Martínez-Ferrero, J., 2015. Board diversity and its effects on bank performance: An international analysis. Journal of Banking & Finance, 53, 202-214.

Harjoto, M., Laksmana, I., and Lee, R., 2015. Board diversity and corporate social responsibility. Journal of Business Ethics, 132(4), 641-660.

Kaczmarek, S., Kimino, S., and Pye, A., 2014. Interlocking directorships and firm performance in highly regulated sectors: the moderating impact of board diversity. Journal of Management & Governance, 18(2), 347-372.

Low, D. C., Roberts, H., and Whiting, R. H., 2015. Board gender diversity and firm performance: Empirical evidence from Hong Kong, South Korea, Malaysia and Singapore. Pacific-Basin Finance Journal, 35, 381-401.

Lückerath-Rovers, M., 2013. Women on boards and firm performance. Journal of Management & Governance, 17(2), 491-509.

Martín-Ugedo, J. F., and Minguez-Vera, A., 2014. Firm performance and women on the board: Evidence from Spanish small and medium-sized enterprises. Feminist Economics, 20(3), 136-162.

Miles, M.B., Huberman, A.M. and Saldana, J., 2013. Qualitative data analysis. Sage.

Nielsen, B. B., and Nielsen, S., 2013. Top management team nationality diversity and firm performance: A multilevel study. Strategic Management Journal, 34(3), 373-382.

Perryman, A. A., Fernando, G. D., and Tripathy, A., 2016. Do gender differences persist? An examination of gender diversity on firm performance, risk, and executive compensation. Journal of Business Research, 69(2), 579-586.

Terjesen, S., Couto, E. B., and Francisco, P. M., 2016. Does the presence of independent and female directors impact firm performance? A multi-country study of board diversity. Journal of Management & Governance, 20(3), 447-483.

Triana, M. D. C., Miller, T. L., and Trzebiatowski, T. M., 2013. The double-edged nature of board gender diversity: Diversity, firm performance, and the power of women directors as predictors of strategic change. Organization Science, 25(2), 609-632.

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