The Relationship between Executive Pay and Firm Performance

The Relationship between Executive Pay and Firm Performance


The study employs the agency theory in evaluating the correlation between CEOs compensation and performance levels. In the introduction part, the study introduces the topic, the objective of the study as well as the importance of the findings. The introductory part acknowledges that while compensation is vital in promoting the performance of the employees, there is the similar need to focus on the scandals that are linked to CEO’s pay and remuneration.  The other part is the methodology part which outlines the purpose of the research, the sample size, study design and the data collection methods. The methodology part introduces the agency theory and highlights its relations to the study (Akram et al. 2016. 50).

The study employs secondary data from past studies and compresses the performance of different global companies. The organizations used in the study are featured in both FTSE and LSE. The variables used to determine the performance of the companies are derived from their financial statements.  The statistical approach that is used in the paper is regression analysis as it offers a highlight of the link between compensation level and the performance levels.  On the other hand, there is the presentation of the results in a tabular form. These results indicate the average pay levels of the CEOs in the 40 FTSE companies featured in the study.  In the second table, there is the inclusion of the regression output that explains the relationship between these two variables.

The other part that is featured in the work is discussion and explains the finding of the study. There is the analysis of the multiple regressions that has a value of 46%. The part further explains different statistical results in the paper. The last part is the conclusion and offers a detailed summary of different parts the indicated parts, the purpose of the study and offers a final view on the study. There is an indication of ways that future studies can be improved.



CEO compensation is a widely discussed topic with the objective being to determine the correlation between the compensation levels and the performance levels. While there instances where they have been excessive compensation of the executive thus leading to scandals, there is the central need to determine the impacts of remuneration on and the performance levels of the managers.  Over the past two decades, there have been many studies that have been conducted to explore these correlations (Alves, et al. 2016, 190).  The need to improve the performance levels of organization and improve their competitive advantage has seen a review in the compensation policies.  The following research will contribute to other studies that attempt to explore this relation. In some organizations, executive compensation is seen as being mandatory as it aids in propelling the operations of an organization (Liz and Wang, 2016).

Despite the acknowledgement of the impacts that comes with remuneration, there is the view that organizations ought to put in place laws, regulations and policies to oversee this executive remuneration. Studies that call for the adoption of such regulations and laws indicate that there is the risk that executive remuneration may trigger scandals and conflict of interest.  The following study will include secondary sources and other studies that have been conducted in the past (Balafas et al. 2014). The incorporation of these trends will allow for a better understanding of the compensation trends and their impacts across the globe. The argument rests on the fact that different countries tend to have varying policies and regulations on the compensation of the executive (Lee and Isa, 2015, 35). The understanding of these impacts is critical as it would highlight ways that the productivity of the executive can be attained without leading to scandals.

Having a comprehensive pay structure is regarded as being essential as it ensures that such operations are aligned to the visions and goals of an organization (Hong and Minor, 2014, 200). Other than focusing on the impacts of executive compensation levels, there is an exploration of the factors that influence the pay levels. Such factors include the firm performance levels, the structure of the board of directors as well as characteristics of an organization. Through an exploration of 40 firms that are listed in the Financial Times Stock Exchange Index and London Stock Exchange., it is possible to determine the ongoing trends in many industries (Jenter and Kanaan, 2015). Nonetheless, there is the incorporation of the agency theory in analyzing the trends in these FTSE and LSE.


The main purpose of this text-based research is to explore the relationship between executive pay and firm’s performance. The research focused on the top 40 firms enlisted by the London Stock Exchange (LSE) in the Financial Times Stock Exchange Index (FTSE 100) at the end of 2018. The basis of this research is on the agency theory. According to this theory, the shareholders, the principals in the agency relationship, and the management which is the agent, are likely to have differing and clashing interests (Murphy, 1999, pp.2485-2490). The theory postulates that a firm is likely to incur direct and indirect costs due to the agency problem. Direct agency costs are incurred when the management of a company are unnecessarily spending at the expense of shareholders’ interest (Mengistae and Lixin, 2004, pp.615-637). According to the agency theory, one way of reducing agency cost is to have a proper compensation and incentive scheme for the directors (Eisenhardt, 1989, pp.57-74). In consideration of this theory, most research studies have postulated that firms are linking the compensation for their chief executive officers (CEOs) to their accounting based performance (Aduda, 2011, pp.130-139).

The study used secondary data obtained from various sources. As mentioned in the preceding section, LSE was the source from which the 40 of the FTSE companies was obtained. On the other hand, variables on the performance of the forty companies were obtained from their respective financial statements for the period ending 2017 or 2018.

In view of the above-mentioned theory, the hypothesis held in that executive pay is positively correlated to various measures of firm performance. In the study, the dependent variable of the model was the CEOs’ fixed pay and the variable pay. Fixed salaries are the compensations which are not dependent on the firms’ performance. However, the study postulates that shareholders, as well as the labour market, depending on the firms’ performances when fixing the executives’ pay. CEOs’ variable salaries entail bonuses, long term incentive programs (LTIP), and short term incentive programs (STIP). In the model, both fixed and variable pay were combined to yield a single dependent variable. On the other hand, a total of seven predictor variables were used in the regression model. The first variable (X1) was the return on asset (ROA). ROA is a financial metric which expresses earned income as a ratio of the total assets. Thus, it depicts how a firm is leveraging on its assets to yield profits. The second independent variable was the size of the firm (X2). In the model, the size was represented by a firm’s total assets as indicated in the audited financial statement. The third independent variable was leverage (X3). This was representing the firms’ total liabilities which consist of both long term and short term obligations. The fourth variable (X4) was the earning per share (EPS). EPS is the net income attributable to ordinary shareholders distributed to the total number of outstanding ordinary shares. The fifth independent (X5) variable was the percentage of non-executive directors in the board of directors. According to the United Kingdom’s Companies Act, at least 50% of the board of directors should be non-executive members. The sixth independent variable was the dividend yield (X6). This is the dividends paid expressed as a proportion of the share’s value. The last independent variable of the model was the age of the firm in years (Davies and Rickford, 2008, pp.48-71).

Regression analysis was used as the main statistical approach to test the relationship between executive pay and firms’ performance. The main reason for settling on regression is that it is a robust statistical technique which has been proved to model the cause and effect relationship of two or more variables. In addition, regression analysis is a simple statistical procedure whose outputs are easy to understand and interpret. On the other hand, t-test statistics will be used as the main approach to testing the hypothesis. In addition to multiple regression and t-test, descriptive statistics of the executive pay and firms’ performance will be calculated with the focus placed on the means, variances, standard deviations, maximums and minimums. Regression analysis, t-test, and descriptive statistics were undertaken using excel spreadsheet due to its numerous advantages. For example, an excel spreadsheet is a free program which is contained in Microsoft suit. In addition, Excel is a program which is easy to be sued as compared to other statistical software.


Table 1: Descriptive Statistics Summary

CEO TOTAL PAY (Million gbp) 7.25 3.57 15.30 2.90
ROA 3.21 4.63 11.00 -9.70
SIZE (Billion GBP) 231.71 313.32 923.00 6.60
LEVERAGE (Billion GBP) 181.40 267.94 777.00 3.60
EPS (pence) 283.42 537.78 1800.00 -57.00
% OF NON-EXECUITVE DIRECTORS 67.60 10.34 92.00 50.00
DIVIDEND YIELD % 3.87 2.07 7.95 0.11
AGE  (Years) 88.25 60.53 253.00 19.00


Table 1 above presents a summary of descriptive statistics for the 40 FTSE companies. From the table, it is evident that the CEOS of the 40 companies earned an average total pay of 6.21 million in the year 2017. In this case, while there was an executive who earned as high as 15.30 million, the lowest paid CEO over the year was given a total of 1.50 million. In regard to the ROA, the statistic indicates that the 40 companies had an average return of 4.97% with a leading company having the highest ROA of 24%. It is also notable that there is a company which had a negative return of -9.70%. In terms of assets and liabilities, the 40 companies had averages of £237 and £196 billion respectively. On the same note, it is observable that one of the firms had assets worth £ 2.5 trillion and liabilities amounting to £ 2.3 trillion. Concerning shares earnings, it is apparent that 40 companies had an average value of £253.91. On the other hand, the statistics reveal that all the 40 companies are conforming to the companies act requirement on the composition of the board of directors. From the table above, it is clear that amongst the 40 FTSE firms, the least proportion of non-executive to executive directors is 50% while there is a company which has a 92% composition of its board as non-executive directors (Jizi, 2017, pp.640-655). In table 1 above, it is observable that the 40 firms had an average dividend yield of 3.96% in 2017. In respect to age, there is a firm which is as old as 292 years amongst the FTSE 40 firms. The youngest firm in the group has only 8 years. However, the average age of 84 indicates that the FTSE companies are those which have been in existence for quite a good number of years.

Table 2: Regression Output

Regression Statistics
Multiple R 46.27%
R Square 21.41%
Adjusted R Square 4.22%
Standard Error 3.244
Observations 40.000
  df SS MS F Significance F
Regression 7.000 91.749 13.107 1.245 0.308
Residual 32.000 336.802 10.525
Total 39.000 428.551      
  Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 0.700 4.170 0.168 0.868 -7.794 9.194 -7.794 9.194
X Variable 1 -0.042 0.107 -0.395 0.696 -0.260 0.176 -0.260 0.176
X Variable 2 0.005 0.010 0.445 0.659 -0.016 0.025 -0.016 0.025
X Variable 3 -0.006 0.011 -0.515 0.610 -0.028 0.017 -0.028 0.017
X Variable 4 0.002 0.001 1.847 0.074 0.000 0.005 0.000 0.005
X Variable 5 0.095 0.056 1.703 0.098 -0.019 0.209 -0.019 0.209
X Variable 6 -0.420 0.292 -1.438 0.160 -1.015 0.175 -1.015 0.175
X Variable 7 0.005 0.009 0.558 0.581 -0.013 0.023 -0.013 0.023


In table 2 above, the statistics which are significant in establishing the relationship between executive pay and performance of a firm are the multiple regression and adjusted R square. In this case, the multiple R produced by the regression is 46.27% while the adjusted R2 is 4.22%. On the other hand, the coefficients of X1 to X7 produce the following regression equation:

Y = 0.7- 0.042 X1 + 0.005 X2 – 0.006 X3 +0.002 X4 + 0.095 X5 – 0.420 X6 + 0.005 X7.


Accordingly, a multiple regression value of 46% is an indication that only 46% of the variance in the CEO’s pay is explained by the changes in the predictors of firms’ performance. On the other hand, a very low adjusted R-square of 4.22% shows that the variables are poorly fitting the regression model. In table 2 above, it is notable that the F-statistic of the model is 0.31. Since this value is far much greater than the significance level of 0.05, the implication is that the entire model does not have the anticipated predictive capability. The t-statistic values of all the 7 coefficients are either below 2 or greater than 2. In this case, the respective coefficients of all the independent variables are not significant as far as the model is concerned. Similarly, all the P-values of the 7 coefficients are bigger than 0.05 significant level. In this regard, the null hypothesis that the coefficients can be relied on in predicting the CEOs’ pay is rejected. On the other hand, it is evident that the coefficients for the ROA, Leverage, and dividend yields are negatively correlated to the CEO’s pay. The implication is that as those variables increase, the CEO’s pay is brought down. The coefficients for the size of the firm, EPS, proportion of non-executive directors, and the age of the firms are positively correlated to the CEO’s pay. Even though the P-value and t-statistic have shown that the coefficients are not significant, the positive values are pointing out to some important relationship between the variables. For example, a positive relationship of CEO’s pay and the size of the firm implies that as an entity gets larger, it is in a position to provide better pay for the directors (Haque, 2017, pp.347-364).

Generally, the regression analysis has failed to corroborate the agency theory which postulates that performance-based pay is capable of increasing firms’ performance. However, it is notable that variables such as the EPS, firms’ size, and the age of a firm influence the CEO’s pay but in an insignificant way (Ntim et al., 2017. Pp.1-43; Cao et al., 2018).


Through the incorporation of the agency theory, it is evident that there are both negative and positive links of CEO compensation levels. The trend is despite the fact that the agency theory expects that there be a close association between the CEO pay and the performance levels. CEO serves as the agents and is answerable to the shareholders who serve as the principals. While the principals are concerned of the profitability of the organization, the CEO tends to focus on the salary and remuneration levels. It holds that there is often the risk of incongruent goals. Improving the salary and remuneration levels of the CEO is seen as being one of the ways that this incongruence in the goals can be addressed. Based on the study, a high remuneration level ensures that the CEOs are motivated to implement the strategies and goals of the principal.

Compensating the top mangers implies that they would eb keener on improving the productivity levels of an organization. The findings of the study infer that the CEO and top managers should be compensated more as compared to being punished. Punishment such as demotion or reduction in the pay levels is likely to trigger conflicts of interest between the principal and the agent. The study notes that many of the CEO scandals in different organizations are prompted by the pursuits of the agent’s interest as opposed to those of their principals. Rather than ensuring that there is the attainment of the set organizational goals, there is the risk that the CEOs would be keener on increasing their pay levels.

It is this realization that prompts the need of having stringent regulations and laws to oversee these processes. The findings explain that they ought to be a well outlined structure that determines the compensation levels of the CEOs. Nonetheless, these compensation structures ought to be in line with the vision and objectives of an organization. The failure to have such regulations may lead to a reduction in the profit margins due to the high level of the CEOs remunerations. The remuneration of the top managers is an imporabt topic as it dictates the performance of an organization and its ability to attain the set objectives. It further ensures that remuneration actvties are done in line with the set regulations and policies thus reducing scandals.

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