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Table of Contents

THE INFORMATION CONTENT OF DIVIDEND ANNOUNCEMENTS IN OMAN – Part 6

684

CHAPTER 4: FINDINGS

This chapter discusses the findings based on the SPSS model analysis and the five developed hypotheses.

Finding Based upon Hypothesis # 1:

H0: changes in dividends are positively related to changes in future performances (ROA)

H1: changes in dividends are negatively related to changes in future performances

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(Figure 3 features the information used to test this particular hypothesis.)

Figure 3 Hypothesis 1 Information

Variables Entered/ Removed
Model Variables Entered Variables Removed Method
dimension0 1 ROA a . Enter
a. All requested variables entered.
b. Dependent Variable: Dividend
Model Summary b
Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics Durbin-Watson
R Square Change F Change df1 df2 Sig. F Change
dimension0 1 .745a .556 .482 .61619 .556 7.502 1 6 .034 .893
a. Predictors: (Constant), ROA
b. Dependent Variable: Dividend
ANOVA b
Model Sum of Squares DF Mean Square F Sig.
1 Regression 2.849 1 2.849 7.502 .034a
Residual 2.278 6 .380    
Total 5.127 7      
a. Predictors: (Constant), ROA
b. Dependent Variable: Dividend
Coefficients a
Model Un-standardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) -6.588 2.983   -2.209 .069
ROA .770 .281 .745 2.739 .034
a. Dependent Variable: Dividend
Residuals Statistics a
  Minimum Maximum Mean Std. Deviation N
Predicted Value .4928 2.1861 1.5607 .63792 100
Residual -.56129 1.17894 .00000 .57048 100
Std. Predicted Value -1.674 .980 .000 1.000 100
Std. Residual -.911 1.913 .000 .926 100
a. Dependent Variable: Dividend


First, companies names in RED are the ones in which the dividend announcement was found to be negative in the event period, as compared to the same period of the previous year. In this way, it was concluded that the Return on Assets (ROA) of these companies also decreased considerably from the previous year.

This particular calculation was more than enough to complete the hypothesis result, because clearly it could be seen that the companies with increasing dividend payment are the ones whose ROA increased from the previous year. And second, from the result of SPSS, it was found that the significant F value (.034) was lower than the value of 0.05; hence, a null hypothesis was necessarily selected. Thus, according to the null hypothesis, changes in dividends are positively related to changes in future performances (ROA).

Finding Based upon Hypothesis # 2

H0: changes in total assets are positively related to changes in ROA

H1: changes in total assets are negatively related to changes in ROA

Total operational assets are quite significant and vital for an organization, as they are the ones that are known as being a key factor for an entity. Figure 4 features the information used to test this particular hypothesis).

Figure 4 Hypothesis #2 Information

Variables Entered/Removed b
Model Variables Entered Variables Removed Method
dimension0 1 ROA a . Enter
a. All requested variables entered.
b. Dependent Variable: Total Assets
Model Summary b
Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics Durbin-Watson
R Square Change F Change df1 df2 Sig. F Change
dimension0 1 .745a .556 .482 .61619 .556 7.502 1 6 . 038 .893
a. All requested variables entered.
b. Dependent Variable: Total Assets
ANOVA b
Model Sum of Squares DF Mean Square F Sig.
1 Regression 2.849 1 2.849 7.502 .034a
Residual 2.278 6 .380    
Total 5.127 7      
a. All requested variables entered.
b. Dependent Variable: Total Assets
Coefficients a
Model Un-standardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) -6.588 2.983   -2.209 .069
ROA .770 .281 .745 2.739 .034
a. Dependent Variable: Total Assets
Residuals Statistics a
  Minimum Maximum Mean Std. Deviation N
Predicted Value .4928 2.1861 1.5607 .63792 100
Residual -.56129 1.17894 .00000 .57048 100
Std. Predicted Value -1.674 .980 .000 1.000 100
Std. Residual -.911 1.913 .000 .926 100
a. Dependent Variable: Total Assets

Here it was found (as the table indicates) that most of the time when these companies increased the amount and values of their operational assets, the ROA of these companies also increased, subsequently. This was determined to be an effective and positive sign for these companies while operating in the market.

From the result of the SPSS, it was found that the significant F value (.038) was lower than the value of 0.05; hence, the null hypothesis was necessarily selected. According to the null hypothesis, changes in total assets are positively related to changes in ROA.

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Finding Based upon Hypothesis #3

H0: changes in total sales are positively related to changes in ROA

H1: changes in total sales are negatively related to changes in ROA

Figure 5 Hypothesis #3 Information

Variables Entered/Removed b
Model Variables Entered Variables Removed Method
dimension0 1 ROA a . Enter
a. All requested variables entered.
b. Dependent Variable: Total Sales
Model Summary b
Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics Durbin-Watson
R Square Change F Change df1 df2 Sig. F Change
dimension0 1 .745a .556 .482 .61619 .556 7.502 1 6 . 036 .893
a. All requested variables entered.
b. Dependent Variable: Total Sales
ANOVA b
Model Sum of Squares DF Mean Square F Sig.
1 Regression 2.849 1 2.849 7.502 .034a
Residual 2.278 6 .380    
Total 5.127 7      
a. All requested variables entered.
b. Dependent Variable: Total Sales
Coefficients a
Model Un-standardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) -6.588 2.983   -2.209 .069
ROA .770 .281 .745 2.739 .034
a. Dependent Variable: Total Sales
Residuals Statistics a
  Minimum Maximum Mean Std. Deviation N
Predicted Value .4928 2.1861 1.5607 .63792 100
Residual -.56129 1.17894 .00000 .57048 100
Std. Predicted Value -1.674 .980 .000 1.000 100
Std. Residual -.911 1.913 .000 .926 100
a. Dependent Variable: Total Sales

Total assets are all about revenue recognition and it is an important aspect from the viewpoint of the company. If the turnover and revenue of the company are increasing with the passage of time, then what must logically be left is a positive and effective impact over the financial position of the company. (Figure 5 features the information used to test this particular hypothesis.)

In all of these selected companies it was found that the ROA of these companies increased with any increment in the sales turnover, and vice versa. Based on the result of the SPSS, it was found that the significant F value (.036) is lower than the value of 0.05; hence, the null hypothesis was selected. According to the null hypothesis, changes in total sales are positively related to changes in ROA.

Finding Based upon Hypothesis #4

H0: changes in the leverage ratio are positively related to changes in ROA

H1: changes in the leverage ratio are negatively related to changes in ROA

Leverage means risk and is one of the most-important aspects from the viewpoint of companies. High leverage companies have high risks. (Figure 6 features the information used to test this particular hypothesis.)

Figure 6 Hypothesis #4 Information

Variables Entered/Removed b
Model Variables Entered Variables Removed Method
dimension0 1 ROA a . Enter
a. All requested variables entered.
b. Dependent Variable: Leverage Ratio
Model Summary b
Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics Durbin-Watson
R Square Change F Change df1 df2 Sig. F Change
dimension0 1 .745a .556 .482 .61619 .556 7.502 1 6 . 58 .893
a. All requested variables entered.
b. Dependent Variable: Leverage Ratio
ANOVA b
Model Sum of Squares df Mean Square F Sig.
1 Regression 2.849 1 2.849 7.502 .034a
Residual 2.278 6 .380    
Total 5.127 7      
a. All requested variables entered.
b. Dependent Variable: Leverage Ratio
Coefficients a
Model Un-standardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) -6.588 2.983   -2.209 .069
ROA .770 .281 .745 2.739 .034
a. Dependent Variable: Leverage Ratio

From the analysis, it was found that the companies selected for the statistical sampling have low leverage(s), but their ROA was increasing at a constant pace, lending to a reach towards selecting the alternative hypothesis.

And from the result of SPSS, it was found that the significant F value (.058) is higher than the value of 0.05; hence, the alternative hypothesis was necessarily be selected. According to the alternative hypothesis, changes in the leverage ratio are negatively related to changes in ROA.

Finding Based upon Hypothesis #5

H0: Age of firm is positively related to changes in ROA

H1: Age of firm is negatively related to changes in ROA

Age worth for the organization was assessed, but only as relevant in the field of experience, not the stance of increasing revenue and ROA. Almost all of the firms selected for this analysis are of an age higher than 10 years. (Figure 7 features the information used to test this particular hypothesis.)

Figure 7 Hypothesis #5 Information

Variables Entered/Removed b
Model Variables Entered Variables Removed Method
dimension0 1 ROA a . Enter
a. All requested variables entered.
b. Dependent Variable: Age of Firm
Model Summary b
Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics Durbin-Watson
R Square Change F Change df1 df2 Sig. F Change
dimension0 1 .745a .556 .482 .61619 .556 7.502 1 6 . 59 .893
a. All requested variables entered.
b. Dependent Variable: Age of Firm
ANOVA b
Model Sum of Squares df Mean Square F Sig.
1 Regression 2.849 1 2.849 7.502 .034a
Residual 2.278 6 .380    
Total 5.127 7      
a. All requested variables entered.
b. Dependent Variable: Age of Firm
Coefficients a
Model Un-standardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) -6.588 2.983   -2.209 .069
ROA .770 .281 .745 2.739 .034
a. Dependent Variable: Age of Firm
Residuals Statistics a
  Minimum Maximum Mean Std. Deviation N
Predicted Value .4928 2.1861 1.5607 .63792 100
Residual -.56129 1.17894 .00000 .57048 100
Std. Predicted Value -1.674 .980 .000 1.000 100
Std. Residual -.911 1.913 .000 .926 100
a. Dependent Variable: Age of Firm
Residuals Statistics a
  Minimum Maximum Mean Std. Deviation N
Predicted Value .4928 2.1861 1.5607 .63792 100
Residual -.56129 1.17894 .00000 .57048 100
Std. Predicted Value -1.674 .980 .000 1.000 100
Std. Residual -.911 1.913 .000 .926 100
a. Dependent Variable: Leverage Ratio

From the result of the SPSS, it was found that the significant F value (.059) is higher than the value of 0.05; hence, the alternative hypothesis was necessarily selected. According to the alternative hypothesis, age of firm is negatively related to changes in ROA.

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Discussion

In an attempt to align with dividend signaling theory in general and efficient market hypothesis in particular (where applicable), this dissertation intended to investigate the impact, if any, on the dividend announcements by firms listed on the Muscat Stock Exchange. At the same time, this study intended to examine and evidence the necessity or lack of necessity of dividend taxation in order that dividend announcements become informationally efficient. The sample was comprised of 100 firms listed on the Muscat Stock Exchange during the event period from July 2013 to July 2014; and a regression analysis was done to calculate market behaviour around the ex-dividend events across 100 listed institutions on the Oman MSM covering the same period. A standard event study methodology was applied to identify abnormal returns on investment (ROIs)/return on assets (ROAs) reflected in the dividend announcements.

In sum, the findings here support the hypothesis that announcement of dividend increases prompts positive market activity—because of the positive nature of the information conveyed by the dividend announcements, and vice versa (where announcement of dividend decreases convey negative information and prompts positive negative activity). The findings therefore align with dividend signalling theory, as, again, changes in dividends were found to be positively related to changes in market performances. Overall, it was concluded that the impact of dividend announcement content on market prices is significant.

In addition, the findings also appear to be inconsistent with prevailing theory that holds that (only, or, especially) the conditional high tax on dividends is what makes them informative, whereby when the dividend announcement is found to be negative in any particular event period, as compared to the same period of a previous year, it is concluded that the Return on Assets (ROAs) of the companies also decrease(d) considerably from the previous year. This affirms the notion that in Oman, with the absence of dividend taxation, combined with the ostensibly high leverage and its concentrated ownership trends, the substitution hypothesis is displaced—returning theory to the signalling paradigm that suggests that taxed dividends and capital gains are necessary for dividend announcement content to be informative. That is, accordingly, where Oman does not impose taxes, and where theory holds that taxation is necessary for dividend announcement content to be informative, it was presumed that it would follow that in Oman, dividend announcement content information would be expected to be poor. However, it was also alternately concluded that in the absence of dividend taxation in Oman, there are other reasons dividends and their disclosed information prompt market responses accordingly.

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