Use SPSS analysis and write report to determine how this information can be used to identify the factors that influence chief executive remuneration
Assignment
Read carefully the case notes overleaf. Consider the information shown in the appendix.
Determine how this information can be used to identify the factors that influence chief executive remuneration.
Then write a report for the Directors of Prudent A which addresses these issues.
Remember, the Directors of Prudent A are not experts in statistical analysis. Hence you will need to explain what you are and why, as well as the meaning of your results.
In structuring your report you may wish to consider the following framework. This does not mean that you simply respond to (a) to (d) below, but rather that you formulate headings and sub-headings for your report using the framework as a starting point.
(a) A graphical representation of the data and a discussion of any issues or patterns which arise from this exercise. It would be for you to decide upon the exact data to use and the appropriate graph(s).
(b) Univariate and bivariate analysis and discussion which looks at the possible determinants of CEO remuneration.
(c) Multivariate analysis and associated discussion which makes use of the data provided in Financial Modelling Assignment 2016 - 2017.xls (see appendix I).
(d) Any other issues, problems or additional complications which you feel should be conveyed to the Directors of Prudent A with respect to your analysis.(issues of the analysis, think about the data, this part as recommendation)
1,500 words + Data Extraction + SPSS analysis + graphs/tables.
Chief Executive Remuneration
You have recently been appointed as an analyst within PMC Inc. PMC is a UK consultancy company that undertakes independent research for client organisations.
Your first client is a large pension company (Prudent A) that has most of its assets invested in the UK stock market. Prudent A has a well diversified portfolio of UK shares that covers most industries, although the emphasis tends to be on medium and large sized firms.
The Directors of Prudent A are concerned about the remuneration (salary plus bonuses) that the CEOs of these firms receive and want to commission some independent research which looks at whether this remuneration is in some way related to the performance of the firm or results from the position and power of the chief executive.
You have been asked to undertake some quantitative analysis looking at this issue. While you are familiar with various different aspects of statistics and a number of statistical packages you have not undertaken a project of this nature before. Hence you start by conducting a literature search.
This search proves beneficial and you find that there are a number of existing studies which look at the factors that determine chief executive remuneration, although none specifically in a UK context.
Most of these studies consider whether CEO pay is determined by the performance of the company they manage or whether it simply relates to the influence which the CEO has over the board of directors.
Various measures of company performance have been used including accounting profit, shareholder wealth and growth in sales. It has also been suggested that the size of the firm can have an impact on CEO remuneration and hence this has frequently been incorporated in empirical work. CEO influence over the board of directors has usually been measured by the proportion of executive directors on the board. Executive directors are individuals who work for the company in question (usually senior managers). Hence their position in the organisation is dependent at least to some extent on decisions made by the chief executive. In contrast, non-executive directors are not employees of the company nor are they affiliated to the company in any way. Some studies have further suggested that if the CEO is also the chairman of the board of directors then this person will have even more influence over decisions made by the board. Hence a measure designed to incorporate this effect has sometimes been included in empirical work.
From the material you have identified you draw up a list of specific variables which can be used to measure the possible influences on CEO remuneration and collect numerical data on each of these (details of the data can be found in Appendix I). You also calculate the natural logarithm of some of these variables since it has been suggested by some authors that the use of such transformed data can reduce the impact of outliers.
You now need to consider how you will analyse this information. In addition you need to consider how you will explain the approach(es) you have adopted and the implication of your analysis given that the Directors of prudent A are not experts in quantitative or statistical methods.
Appendix I
The data for to this assignment can be found in Financial Modelling Assignment 2016 - 2017.xls. This information relates to a large sample of medium and large sized firms. In total there are 280 observations. The first 5 observations are shown below. All data is annual.
Variable definitions:
Salary: CEO remuneration (salary, bonuses, etc.) £'s.
Dir: Number of directors on the board, No.
Exec: Number of executive directors on the board, No.
Assets: Book value of firms assets, £m. Measure of firm size.
Exec1: Proportion of executive directors on the board.
Dummy: 1 if the CEO and chairman of the board is the same person, 0 otherwise.
Sgrow: Sales growth, proportionate growth.
Exret: Excess return, proportion. Calculated as the return on the companies shares on and above the industry average (company return minus industry average). Measure of shareholder wealth.
Lassets: Natural logarithm of firm assets figures.
Lsalary: Natural logarithm of CEO remuneration figures.
|
Salary
|
Dir
|
Exec
|
Assets
|
Exec1
|
Dummy
|
Sgrow
|
Exret
|
Lassets
|
Lsalary
|
|
830632
|
18
|
7
|
22065
|
0.39
|
1
|
0.25
|
0.24
|
10.00
|
13.63
|
|
1571662
|
14
|
5
|
19597
|
0.36
|
1
|
0.76
|
0.32
|
9.88
|
14.27
|
|
428640
|
15
|
2
|
32123
|
0.13
|
1
|
-0.09
|
-0.05
|
10.38
|
12.97
|
|
970376
|
12
|
11
|
17788
|
0.92
|
1
|
-0.01
|
0.24
|
9.79
|
13.79
|
|
1024938
|
14
|
3
|
34710
|
0.21
|
1
|
0.13
|
0.23
|
10.45
|
13.84
|
Criteria for a good assignment:
- good understanding of key concepts and ideas
- some imagination and originality
- development of argument so that the whole assignment hangs together.
When you write your assignment, consider the following:
- Before you begin, work out on paper a detailed outline of the structure of your assignment and the arguments you will develop.
- In the introduction, you should set out your main themes and intentions: describe the issue you are addressing, identify its main components, and indicate what you are going to do in the body of your essay.
- Break down your arguments into main parts - use this as a basis of your assignment that will then be divided up into several sections (you may want to have section title for each section).
- Build up your argument point-by-point, section-by-section, so that you develop a picture that slowly develops in the reader's mind.
- Always try to put yourself in the position of a critical reader, ask yourself how s/he would react to your assignment, how s/he would understand it, be persuaded by it.
- Do not simply describe the ideas you're dealing with, provide a critical evaluation.
- Summarise your arguments in a conclusion. What is the main significance of what you have been saying?SPSS
Tasks
1. Load winter.xls into SPSS.
2. In the Wintergreen study, to what extent are academic ability and parents' education related to one another? Use scatterplotof the data to assess any relationship.
3. Assess the above by using the correlation coefficient.
4. Are students from urban communities rated similarly to those from rural communities in terms of their advisor evaluation?
5. Do students in each of the three groups of advisor evaluation have similar average values in terms of academic ability scores?
6. What are the effects of parent's education (pe), gender (g) and community type (c) on academic ability (aa)?
Tips for task 2
From the Graphs pull-downmenu, select Legacy Dialogs followed by Scatter/Dot. You will see a dialog box asking you to choose a type of scatterplot. Click on Simple Scatterand then the Define button. Choose variable "aa" for the y-axis and choose variable "pe" for the x-axis. Next, click the Titles button, type "Scatterplot" for Title Line 1, type "academic ability and parents' education" for Title Line 2, and click the Continue button. Finally, click the OK button and take a look the chart that is produced. Can you see any relationship between these two variables?
Tips for task 3
The correlation coefficient is a statistic commonly used to assess the strength of a relationship between two variables that are linearly related each other. To obtain the correlation coefficient, from the Analyze pull-down menu, select Correlate then choose Bivariate. When you see the relevant dialog box, select the variables "aa" and "pe", and choose the Pearson correlation coefficient, then click the radio buttons for two-tailed test of significance and Flag significant correlations.Finallyclick OK to run the Correlation procedure.
Tips for task 4
One of the most common ways of looking at the association between two categorical variables is to use the chi-square statistic.
a) To answer this question, we need to cross-tabulate the two variables and look at the percentage of students from each community type who were evaluated into each of the three categories of likelihood to succeed. We would then test the similarity of the two distributions using the chi-square statistic.
b) To create the cross-tabulation, from the Analyze pull-down menu, select Descriptive Statistics then choose Crosstabs.Whenyou see the dialog box, select community type "c" for the row variable and advisor evaluation "ae" for the column variable, then click the Statistics button. In the next dialog box, click the box next to chi-square, then press the Continue button. Next, click on the Cells button and select the Observed count box, as you will be interested in the number of cases in each cell of the table, and the Row percentages box. Click the Continue button, then click the OK button.
Tips for task 5
In this question, we are interested in an independent variable that has more than two groups. We need to use the analysis of variance (ANOVA) procedure, a one-way ANOVA. From the Analyze pull-down menu, select Compare means, then choose One-Way ANOVA.Afteryou see the dialog box, select academic ability "aa" as the dependent variable and advisor evaluation "ae" as the factor (that is, the independent variable). Click the Options button. In the Statistics box, choose Descriptive and Homogeneity of variance to test whether or not the groups had equal variances (an assumption of the ANOVA procedure). Now click the Continue button to return to the original dialog box, then press the OK button to run the procedure.
Tips For Task 6
To conduct this analysis (i.e. regression), from the Analyze pull-down menu, select Regression, then choose Linear.Whenthe dialog box appears, select "aa" as the dependent variable and "pe", "g" and "c" as the independent variables. Choose theStatistics button and click on the boxes to specifyestimates, model fit, and descriptives.Then click on Continue to return to the main regression dialog box. Finally, click on the OK button to run the analysis.
Attachment:- assignment 2_16_1903.zip