This paper shows calculation of a sample about 500 observations using a software SPSS which analyzes and explains the effects of the share holding structure on corporate performance. The recent studies of Jensen and Meckling 1976, Fama and Jensen 1983, and Hart 1983 indicate that the managerial ownership of shares in a firm create conflicting forces on the behavior of management in the form of convergence of interest effect and the effects of reinforcement. Other former studies suggested that there is link between the managerial stake and the market value of the firm is positive as a result of the convergence of management and shareholder interests. However, this link is observed as negative owing to the managerial stake strengthens at a large scale and involves management from the corporate control. The paper is designed and structured to present to JP Drew. The paper is structured into first section which provides the scatter plot and descriptive statistics table showing the variables features. In order to explain the correlation between the Market to Book and Value (MBV) and other controlling variables, the next section demonstrates the findings of this. Third section of paper shows the evaluation of dependent variable using explanatory variables. The conclusion of the paper presents the interpretation and other findings of the report.

Methodology

The descriptive statistics, correlation analysis and regression analysis are the approaches used in the report. In order to understand the methodology used in the report it is vital to comprehend these approaches by analyzing and giving a brief overview. The below is the analysis of the approach: At first, the descriptive analysis is the preliminary feature of the quantitative collection of data. The reason to use descriptive statistics is to provide summary of a quantitative set of data utilizing the data to make inference relevant to population to which data are analyzed. Moreover, the correlation is a statistical technique which is used to represent the strength of relationship between the variables. However, it is a single number which shows the relationship and connection between the two variables. In addition, the third approach which is used in this paper is regression analysis. The regression analysis model includes the analysis and model of several variables when the focus is on the relationship between dependent variable and one or more than one independent variables.

Descriptive Statistics

The Market to Book Value has been used in this report as a dependent variable. The aim to use descriptive statistic in this report is to determine the performance of company and other variables are considered as independent variables which affect the Market to Book Value. The following two scatter plots show the evident relationship between the MBV and the independent variables which are ownership concentration and size or total assets of company. Above figure shows the relationship between MBV and size of the company. Considering the figure, it is clear that there is no relationship between the total assets of the company and the Market to Bok Value. Thus, it cannot be declared if there is any relationship between the two variables from the scatter plot. The above figure of scatter plot is also showing the relationship between the Market to Book Value and the ownership concentration. Through the figure it can be observed that there is relationship between MBV and Concentration as it shows perfect correlation with each other. Therefore, it can be stated that two variables can rise and fall together. The scatter plot in above figure shows the trends of distribution between the two variables rather than just describing the information about the relationship between ownership structure and performance of company. Therefore, it is important to analyze the relationship between the Market to Book Value and Ownership Concentration. Hence, the descriptive statistics is demonstrated by the means of the analysis of concrete variables which includes the range of value, maximum and minimum, mean and standard deviation.

Descriptive Statistics

N Range Minimum Maximum Mean Con 500 36.1 21.3 57.4 37.456 Identity 500 3 3 6 4.38 Industry 500 2 1 3 1.75 MBV 500 1.94 1.04 2.98 1.8729 ROCE 500 31.3 23.2 54.5 39.718 Size 500 348761 66751 415512 2.11E5 Valid N (listwise) 500 As it is observed in the above table that the mean value of return on capital used and which is also termed as ROCE, MBV and Con, they are approximately around 39.7, 1.8 and 37.5 respectively. The sets of data shows that the average of the proportion of ROCE has occupied about 39.7%, the mean percentage of Ownership Concentration is occupied about 37.5% and the average market to book value is approximately about 1.9% in the entire data set. In addition, the standard deviation for ROCE, Con, and MBV are approximately about 6.9, 6.7 and 0.35 respectively. These values show that ROCE, Con and MBV are 6.9 percent, 6.7 percent and 0.35 dispersed from the mean. It also shows that according to the representation of table, the value of size is outstanding and remarkable. The value of the size shows the price of the total assets in the company. Moreover, the above also shows the minimum and maximum value of size which is 66751million and 415512 million respectively while the range of the size is 348761 million. Thus, it can be considered that the range value of the size is balanced between the minimum and maximum. Hence, the conclusion can be formulated from the data results which are evidence that most of the variables are large numerical values as a result of the size of company. Commonly, it is possible that most of the data sets gathered from the large company. Considering the above points, the next section will be indicating the facts that the correlation between the Market to Book Value and other control variables which can include the relationship between MBV and Size using the correlation matrix.

Correlation Analysis

According to the illustration given in the table below, explanatory variable concerning Con and ROCE, Industry and Con, Industry and ROCE have positive correlation using the substantial levels of 0.01, 0.05 and 0.005 respectively. In addition, the table given below is also showing a positive correlation between ROCE and MBV at substantial level of 0.01, whereas industry and identity are negatively correlated to MBV at the significant level of 0.01. The industry means the sector in which the company operates and the identity means the identity of the largest owner. Thus, it can be taken into account that different significant levels have different degrees of correlation between the dependent and the independent variables. Moreover, the table below is showing the positive negative correlation between one control and one dependent variable rather than showing cleat effects using bivariate analysis. The bivariate analysis shows the analysis of two variables determining the empirical relationship between those two variables.

Correlations

MBV Identity Con Size ROCE MBV Pearson Correlation 1 -.252** .709** -.009 .405** Sig. (2-tailed) .000 .000 .846 .000 N 500 500 500 500 500 Identity Pearson Correlation -.252** 1 -.047 .003 -.049 Sig. (2-tailed) .000 .294 .951 .277 N 500 500 500 500 500 Con Pearson Correlation .709** -.047 1 .052 .584** Sig. (2-tailed) .000 .294 .243 .000 N 500 500 500 500 500 Size Pearson Correlation -.009 .003 .052 1 .070 Sig. (2-tailed) .846 .951 .243 .119 N 500 500 500 500 500 ROCE Pearson Correlation .405** -.049 .584** .070 1 Sig. (2-tailed) .000 .277 .000 .119 N 500 500 500 500 500 Industry Pearson Correlation -.522** .048 .088* .036 .102* Sig. (2-tailed) .000 .288 .048 .426 .022 N 500 500 500 500 500 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

Regression Analysis

In statistics, the regression analysis consists of such techniques used for analyzing various different variables. More particularly, regression analysis is helpful to comprehend the typical value of the dependent variable changes when one of the independent variable is altered. The Regression Analysis is the most commonly used analysis which aims to illustrate the prediction and it is also useful to understand the relationship of independent variables with the dependent variables. In this report, the reason to use the regression analysis is to define the effects on the MBV from the control variables. In order to use regression analysis model, there are four hypotheses developed and described below: Hypothesis 1: There is positive correlation between the ownership concentration and Market to Book Value. Hypothesis 2: There is also correlation between the Identity of the largest Owner and Market to Book Value. The variables are taken into account as quantitative variables and they form a quantitative distinction is the Identity and Industry Terms. Hypothesis 3: There is a negative correlation between the industries and Market to Book Value. Hypothesis 4: There is positive correlation between the industries which is the sector in which the Company operates its business and Market to Book Value.

Model Summary

Equation 1 Multiple R R Square Adjusted R Square Std. Error of the Estimate In the table given above, R square is the reflection of the squared- performance benchmark alters have impact on the performance of the fund. It is shown from the table above that analyzing R square can define that MBV has variation of approximately88.3%. Thus, the result of table shows that Market to Book Value can be considered as explanatory variables. Similarly, it can be stated that the primary, institutional investor, concentration, non-financial company and manufacturing are settled after the analysis of the Market to Book Value (MBV). Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) .128 .028 Con .039 .001 .738 dummybank .184 .013 .231 13.704 dummyi .143 .014 .176 10.539 dummyn .074 .014 .090 5.385 dummym .393 .011 .549 37.182 dummyp -.096 .013 -.110 -7.415 Dependent Variable: MBV From the above table given, it is observed that there is a positive correlation between the majorities of explanatory variables and the Market to Book Value at the higher level of correlation. Basically, primary is correlated with the Market to Book Value. Moreover, hypothesis 1 and hypothesis 2 must be accepted because they have positive correlation whereas hypothesis 3 and 4 cannot be accepted as primary has no relation with Market to Book Value. Thus, the result of the table 4 shows that it is evident that there is a mathematical equation to define the correlation between dependent variable and other control variables. Therefore, the equation can be explained as: From the above equation, it can be observed that Market to Book Value is impacted by these factors. If there is no relationship between the control variables and dependent variables, the Market to Book Value is equal to 0.128. Thus, the Market to Book Value can be the constant value. In addition, if other factors are constant, it is possible that every rising unit of ownership concentration is equal to 0.39 rise of Market to Book Value. In regard to industry, every rising unit of bank, institutional investors, and non-financial company can lead the growth of Market to Book Value to approximately 0.184, 0.143 and 0.074 respectively on the condition that other factors remain constant. With the increasing primary at the time of manufacturing, the Market to Book Value will improve at the same time to 0.393 and falls 0.096 respectively.

Conclusion

In the light of the data collected of 500 companies, the correlation between the independent variables MBV and other specific control variables have been observed and it was found that control variables affect the Market to Book Value. As the result shows that there is no correlation between the dependent variable MBV and size. As a result, it was observed that when more assets are bought to find the adjustment of the structure of ownership, whereas gaining a good performance of company is not possible. In addition, it was also observed that dependent variables MBV are influenced by the ownership concentration, Identity of the largest Owner and Industry and thus, all these factors have impact on the performance of the company. In the light of analyzed results offered above, these determinants of the Market to Book Value must help JP Drew to make a decision between the ownership structure and the performance of Company.

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The Impact Of Ownership Structure On Companies Finance Essay. (2017, Jun 26).
Retrieved June 23, 2024 , from https://studydriver.com/the-impact-of-ownership-structure-on-companies-finance-essay/

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