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Quantitative Methods

Section 1. Introduction

Purpose of the study

The aim of this study is to examine and assess the impact of the stability of company on the CEO's salary. From the sample of US companies, the researcher tried to evaluate the impact of the financial stability of company on the pay level of the CEO. By focusing on the theoretical framework of agency, the researcher expects that the formation of the high-stability level of company' permits to improve the level of salary awarded to the executives of companies.

Research aims and objectives

This study aims to assess the impact of the stability of company on the CEO's salary and the objectives are:

  • To evaluate the impact of sales of company on the salary of CEO
  • To analyse the impact of profit of company on the salary of CEO
  • To signify the impact of the market value of company on the salary of CEO

Research questions

How the stability of company create an impact on the salary level of the CEO?

Research Gap

While reviewing the literature, it was identified that there was a gap in the studies conducted to examine company stability and CEO salary. In many previous studies, the different conclusions were drawn regarding the topic. There were some of the studies that showed that there was a positive correlation between the company stability and CEO's salary (Bryan and Mason, pp 1-10). On the contrary, there were some of the studies conducted that showed that there was no impact on company stability on the salary level of CEO (Fisch et al., 2018). Moreover, there were also some of the studies conducted that showed there was an adverse impact on CEO salary and company stability (Francis et al., 2015). Therefore, after conducting so many studies, examining the impact of both the variables was still an outstanding issue. Moreover, it was also identified that past studies regarding the subject were restricted to America, Europe, China, and Japan.

Existing literature

This study relates to many existing studies and in this regard, many studies conducted from which one study was from Greckhamer (2016) in which the researcher examined and identified the association between the salary of CEO and stability of company. The researcher identified the sample of the company of the US and in the study, it was estimated that as per the pay for stability sensitivity (PPS), the company’s stability positively impacts the CEO’s salary. Moreover, Kazan et al., (2016) also stated that there was a positive relationship between the stability of company and the salary level of the CEO. It was further observed from the study that the association was the outcome of the changes made for the value of CEO holdings for stock options. In this regard, Sheikh et al., (2018) also assessed the association between the salary level of the CEO and the company’s stability. The study examined the stability of some of the sample company by using their returns of the stock market. In the study, there were around sixteen US company included, and it was concluded that the previous stability influences the existing salary, but this impact is not permanent. Smirnova and Zavertiaeva (2017) examined that the alterations in the PPS for the last forty years and current and previous year’s stability of company has a positive effect on the CEO’s salary (Usman et al., 2015).

Outline of the study

This study initially starts with the objectives and hypothesis, then the researcher conducted a literature review to assess the results of past studies. In Section 2, the researcher supported the literature with the theoretical basis and conceptual framework. In section 3, the researcher analysed the data and the methodology obtained. In section 4, the econometrics results were measured and in section 5, the findings and results were concluded.

Section 2. Conceptual Framework

Theories for the assessment of this relationship

For this study, there are two theories used that include agency theory and stakeholder theory.

Agency theory (AT)

The AT is that in which one party tries to delegate the work to another party. The parties are known as principal and agent. As per this theory, the managers are hired by company to form higher stability and returns for the company. However, in a practical scenario, this is not the case always. Francis et al., (2016) identified that three features are used to reduce the agency problems that include the improvement of directors' observing for managers, the agency equity ownership, and discipline mischievous managers. Jian and Lee (2015) suggested to apply different schemes of incentives for managers and under these schemes, the managers have been rewarded financially for increasing the interest of shareholders. These incentives include salary for the managers encompassing the CEO. The motivation level of managers and CEOs will enhance and this will create a positive impact on the stability of company.

Stakeholder’s theory

Each of the stakeholders of the company enhances the company’s value. As the managers are regarded as the company’s stakeholders, the CEO is included in this consideration. As per the theory, the CEO is affected based on the results of the company. If the company stability will be positive, it will eventually make the position of the CEO stronger. Raithatha and Komera (2016) explained that the view of commercial expenditure for the change of CEO when they purchase or receive the stock of the company. As a result, the transformation in the structure of salary or formulating proper incentives for the CEO provide positive results to the companies.

Literature Review (Theoretical and empirical)

Considering these theories, there has been a study conducted by Clifford and Lindsey (2016) in which it was identified that there was a positive association between the salary level of CEO and company stability. It was concluded in those studies that the company stability is higher when the discretion of managers and the pay of CEO are aligned. This was also supported in the study of Jaskiewicz et al., (2017) that the cash salary of the CEO was positively associated with the stability of company. Li et al., (2015) also identified in his study that the relation of pay and stability has been positive and significant. These associations are explained through the alignment of the interests of shareholders and CEOs for using efficient contracts of salary. In this regard, the AT supports the results because it was identified that the rewards schemes were in the form of monetary rewards to the CEO that might restrict alignment differences. Malik and Makhdoom (2016) compared CEO PPS between privately and public company. It was identified that in both types of company the association between the companies’ financial stability with the salary level of the CEO was positive. Moreover, Hill et al., (2016) emphasised on the share-based pay for the CEO and its effect on the stability of company. This was because the CEO’s who get the payments based on share are more motivated and as a result, the stability of companies also increase and that also increase their remuneration. The enhancement in the stability can be supported by stakeholder theory that states that when the CEO purchases or gets the shares of the company, it positively affects the stability of company.

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Conceptual framework

Figure 1: Framework: Author’s illustration


H1: There is an impact of sales of company on the CEO's salary

H2: There is an impact of profit of company on the CEO's salary

H3: There is an impact of the market value of company on CEO's salary

Section 3. Data and methodology 

Sources of data and measurement of variables 

The dataset includes information regarding the CEO for U.S. companies. The dataset was collected from Bloomberg Business Week. There were initially around 177 observations and the researcher extended the observations to 100 more that include the accumulated sample from 277 company. The collected data was secondary and it was published data which means that the data was not collected by the researcher himself and obtained the data from the authentic websites. The variables were mostly interval because there were no categories formed and neither there was ranking in the data, however, the two variables that include university attending and postgraduate studies were nominal because they were included as a dummy variable in the study.

Exploratory data analysis 

In this part, the researcher has analysed the correlation test and summary statistics to check the patterns in the dataset and assess whether there is a deviation in the dataset or not. For this, the researcher carried out descriptive statistics and correlation tests.

Table 1: Descriptive Statistics

From the above table, it has been identified that mean values and standard deviation (SD) values are quite huge and this shows that there is high variation in the dataset. Moreover, the higher values of SD indicate that the values of the dataset are not closer to the mean values and there is high variation in the dataset. The mean value for some variables is a lot and for some variables, it is lesser because of the size of company and profits they earn.

Moreover, the researcher also assessed the patterns of the dataset and for that, the researcher used a correlation test. This test is used to assess the strength of the relationship between the variables. The results of the correlation test are demonstrated below:

Table 2: Correlation 

It was identified from the above table that CEO salary with the other indicators of financial stability has been less correlated because the values are around 0.3. Moreover, the sales and profit and sales and market values are moderately correlated. Profits and market value are highly correlated. This table suggests that the values for the CEO's salary and financial stability indicators are not much correlated with each other.

Regression model

For this study, the researcher has taken the CEO's salary as a dependent variable (DV) and sales, profit, and market values as independent variables (IV). For assessing these variables, the researcher has used multiple linear regression (MLR). MLR has been used because there are three IVs and one DV. The results are demonstrated below:

Table 3: Regression

As per the results of MLR, it has been identified that at a 5% significance level, all the variables are statistically insignificant because the sig values for sales are 0.068, for-profits the sig value is 0.200 and for market value, the sig value is 0.140. The results showed that sales, profits, and market values are not significant to the salary of the CEO. The equation of MLR includes the error term as well in the equation that means that there are other variables as well that also create an impact on DV and they are not taken into consideration with other IVs.

CEO salary = 699.53 + 0.013sales +0.178profits +0.012marketvalue +µ

Estimation strategy

For this study, the estimation strategy has been used by the researcher for conducting the analysis of regression, and estimating the econometric models is the ordinary least square (OLS) method. This method has been used by the researcher in different standardised situations that provide optimal results. While conducting the OLS method, the researcher has considered different assumptions and that might create econometrics issues during estimation. The first assumption is that the parameters of the model have to be linear that means that the regression coefficients do not enter the function that is estimated as exponents (Wu et al., 2018). The IVs are obtained from the random sample and they are variable. Moreover, there is no perfect collinearity among the dependent variables. Through, the correlation test, it was identified that there are fewer chances of multi-collinearity because the IVs are moderately correlated with each other.  

Section 4. Econometrics results

Econometrics estimates 

Table 4: Model summary

Table 5: ANOVA

Based on the above two tables, it was identified that the overall model is statistically significant because the F-value is 12.56 i.e. 4 the benchmark value for F-test. Moreover, the sig value is also less than a 5% significance level that is 0.00 that shows the overall model is significant. Moreover, the researcher also analysed the goodness of fit test through R-square value. As the researcher has used MLR technique, as a result, the adjusted R-square value is analysed. As per the results, the value if Adjusted R-square is 11% that is very low that shows that 11% of the change in DV is caused by a change in IVs. The researcher also conducted one diagnostic test that is demonstrated below: 

Table 6: Diagnostic Test

Through the above diagnostic test, the researcher examined whether there exists multi-collinearity or not. As can be seen from the above values of VIF that they are from 1.8 to 2.4. This shows that there is no multicollinearity. If the values of VIF are more than 6, then there might be a chance of multicollinearity.

As far as the value of the estimated coefficient is concerned that is R-value which is 0.34 that shows the extent of the relationship between CEO salary and sales, profit, and market values is not much higher and there is a weak correlation among them.

Hypothesis testing

Through the above results, the hypothesis for this study was tested and the hypothesis summary is mentioned below:



There is an impact of sales of company on the CEO's salary


There is an impact of profit of company on the CEO's salary


There is an impact of the market value of company on CEO's salary


Table 7: Hypothesis summary

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Theory testing

These results are testing the Agency theory and Stakeholder theory because the results of this study show that there is no impact on the financial stability of company on CEO salary. This has been due to two major reasons. The first reason is that there are a lot of agency problems that are occurred by the company that result in either the over salaries of the CEOs and that results in poor company stability. Another reason is the alterations in the salary structure of the CEO that transforms the cash-based to an equity-oriented structure.

Results correlated with existing studies

This study failed to identify any impact of financial stability on the salary of the CEO. In this regard, Perryman et al., (2016) conducted a study on the charisma of the CEO with the salary and its impact on company stability. The researcher in the study failed to prove that there is no impact on company stability on the CEO's salary and did not get any significant results. It was identified that there is a need to pay more attention to the CEO's responsibilities and the amount of remuneration paid to them. In this regard, agency theory plays a key role that explains the relationship between owners and managers. Moreover, Peng et al., (2015) also got similar findings that also identified there is no relationship between the salary of the CEO and the stability of company. These studies support the results of this study.  

Section 5. Conclusion

The results of this study show that there is no impact on sales, profit, and market value on the salary of the CEO. The overall model was statistically significant and there was a weaker correlation among the variables. Through the diagnostic test, there was no sign of multi-collinearity and as per descriptive statistics, there was high variation in the dataset.

Practical implications

This study can be implemented by the HR professionals of different companies to set the pay scale according to the job roles and responsibilities and they should not consider the financial stability of companies.

Future research areas

This study can further be enhanced by incorporating more variables related to the stability of company and it can be enhanced by conducting mixed approach research in which the results can be supported through observations and perceptions of respondents. 


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Fisch, J., Palia, D. and Solomon, S.D., 2018. Is Say on Pay All about Pay: The Impact of Company Stability. Harv. Bus. L. Rev., 8, p.101.

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