Effectiveness of share-based payments to executives · Effectiveness of share-based payments to...

ACTUARIAL SOCIETY 2014 CONVENTION, CAPE TOWN, 22–23 OCTOBER 2014 | 319

Effectiveness of share-based payments to executivesBy Zafeer Motala and Niel Fourie

Presented at the Actuarial Society of South Africa’s 2014 Convention22–23 October 2014, Cape Town International Convention Centre

ABSTRACTShare-based payments are very commonly part of executive remuneration packages and, in recent years, have comprised a large proportion of executive compensation. This study entails an empirical analysis to identify whether the proportion of total executive remuneration granted in the form of share-based payments has an impact on company performance for companies listed on the JSE. It is hypothesised that by increasing the percentage of salaries that are comprised of share-based payments, this will in turn positively affect the performance of the company. It is believed that share-based payments reduce the issue posed by principal-agent theory by aligning the interests of the executives to that of the shareholders. Suitable company performance measures are identified to be accounting benchmarks: return on assets (ROA) and return on equity (ROE). The executive compensation structure of 19 South African retail companies was investigated over the 2008 to 2013 period to identify the level of share-based awards expensed by the company. Subsequently, a thorough regression analysis indicates that there is little evidence to support the hypothesis that a relationship exists between equity-based compensation and company performance.

KEYWORDSExecutive remuneration; return on assets (ROA); return on equity (ROE); share-based compensation; principal-agent theory

CONTACT DETAILSZafeer Motala, Tel: 072 275 4044; Email: [email protected] Fourie (supervisor), Email: [email protected]

320 | ZAFEER MOTALA & NIEL FOURIE EFFECTIVENESS OF SHARE-BASED PAYMENTS TO EXECUTIVES

ACTUARIAL SOCIETY 2014 CONVENTION, CAPE TOWN, 22–23 OCTOBER 2014

1. INTRODUCTIONSince the appointment of executives as agents for the purpose of managing a

company, there has been a need to align the interests of these agents to that of the shareholders of the company. The possibility of misaligned interests stem from the concept of principal-agent theory.

Although a little more broad, studies on senior executive compensation are typically based on the dominant framework suggested by agency theory (Bratton, 2005). Besley and Ghatak (2005) identify the definition of agency theory as “the separation of ownership and control, and hence, the importance of incentive contracts to align interests of shareholders and managers” (cited in Pepper, Gore & Crossman, 2013: 37). Clearly, the agents are viewed as the executives while the principals are seen as the shareholders. They go on to state that the underlying assumptions are that the agents are both rational, rent-seeking, that the companies are profit-seeking and that there is no non-pecuniary agent motivation. Logically, it is assumed that an agent’s utility is positively related to monetary incentives while negatively related to effort. This disjoint relationship creates a situation where the directors of the company can increase their rewards at the expense of the shareholders (Scholtz & Smit, 2012).

To resolve this agency problem incurred by the separation of ownership and control, economists strongly believe that a robust link is required between compensation and performance (Peng & Röell, 2008). This link has widely been accepted as share-based payments, along with remuneration committees and corporate governance measures.

The idea of remunerating executives in the form of share-based payments developed as an attempt to diminish the risks faced due to principal-agent theory. Hovy (2005) infers that equity plans based on performance would, in the future, be the most suitable instrument in aligning executive performance with shareholder wealth creation. Additionally, Pepper, Gore and Crossman (2013) believe it is a mistake to focus only on the alignment objective, without also considering the motivational aspect on the basis that interests cannot be aligned if executives are not properly motivated and thus, they push the idea of long-term incentive plans (LTIP). Similarly, Khoroshilov and Narayanan (2008) argue that the presence of profit-based and share-based components in compensation packages offers executives the proper incentives in order to maximise shareholder value.

Through these mechanisms, a portion of the risks and rewards associated with the company is shared by the executive directors. By inducing executives to have a proportion of their wealth invested in the company, there is a large motivational force to increase their own performance. However, while there is a general consensus regarding the existence of this component, there is no agreement as to the size of this incentive and in what form it should be offered. The aim of this study is to identify whether there exists any correlation between the proportion of these share-based components and the performance of the company.

Unfortunately, the current situation regarding share-based compensation has generated the belief that executives are benefiting unfairly and to extraordinarily large

ZAFEER MOTALA & NIEL FOURIE EFFECTIVENESS OF SHARE-BASED PAYMENTS TO EXECUTIVES | 321


extents. Mongalo (2003) alleges that share options allow executives to benefit when the company is excelling, but do not adequately, if at all, penalise these executives when performance is substandard. Woodburn (2008), too, cited in Scholtz and Smit (2012), posed the question whether directors should be entitled to salary increases and performance-related remuneration if the directors are unsuccessful in creating value and profits for the company’s shareholders. However, under the belief that managerial ownership may reduce agency problems, institutional investors and shareholder activists have tolerated and even encouraged these large grants of equity to executives (Ofek & Yermack, 2000).

It is clear that no consensus is held regarding the success of share-based remuneration in aligning interests and motivating executives in order to create value for shareholders. This study will investigate whether any empirical evidence supports this approach in remunerating executives.

2. MEASURES OF COMPANY PERFORMANCEIn order to investigate the relationship between company performance and

share-based payments, it is necessary to identify a suitable measure of company performance. In past research, academics have identified various indicators of company performance, although views on which indicators are most suitable have differed.

Scholtz and Smit (2012) use total assets, turnover and the share price as company performance variables in their study on whether executive remuneration affects company performance for South African companies listed on the Alternative Exchange. Core and Larcker (2002) also use companies’ share prices as the performance measure when investigating the performance consequences of mandatory increases in executive stock ownership. Similarly, Buck et al. (2003) used shareholder return based on the share price as the company performance measure in their study of LTIPs and executive pay with regard to UK companies and their performance.

Contrarily, De Wet (2012: 63) argued that “ground-breaking work conducted by Stewart (1991) and Stern (1993) introduced the concepts of economic value added (EVA) and market value added (MVA) as better performance measures of corporate performance.” This was opposed to the more traditional performance measures mentioned above. The reason for this belief is that ROA and ROE are accounting measures. This suggests that they are prone to manipulation through reporting and that they do not fully indicate the risk involved to a company as contained in the share price. Surprisingly, De Wet nonetheless concluded that there is a stronger relationship between executive compensation and the traditional measures, ROA and ROE, than with EVA and MVA. This may be due to the fact that South African shareholders place a greater emphasis on traditional measures when compensating executives. This leads to the view that South African shareholders need to shift away from these measures and toward value-creation measures when designing and implementing executive compensation plans (De Wet, 2012).

In a study conducted by Hamid Mehran (1995) on executive compensation



structure, ownership and company performance, a particular emphasis is put on the relationship between CEOs’ equity-based compensation and company performance. This bears a close relationship to the aim of this paper regarding the effectiveness of share-based payments. In Mehran’s study, the proxies for company performance are ROA and Tobin’s Q. Tobin’s Q is measured as the ratio of the market value of the company’s securities to the replacement cost of its tangible assets. Once again, these traditional measures were favoured over those suggested by De Wet (2012), Stewart (1991) and Stern (1993).

Conversely, Holmström and Tirole (1993) argue that “the share price is a better benchmark for company performance than any accounting measure as it is responsive to all value-relevant information, including informal items of news” (cited in Peng & Röell, 2008). They believe this is the reason shares and share options have such significant roles in optimising performance incentives for executives. However, Antle and Smith (1986) note that accounting returns are a significant factor considered by the remuneration committee when determining the level of compensation of employees. It is because accounting returns provide information to the board about the value added to the company by the executives (Paul, 1992). An implication of this is that executives have an incentive to make major corporate decisions and report income in such a way that affect accounting measures and thus, albeit indirectly, their compensation. However, it is difficult to manipulate the market for a significant length of time, thus negating any large effects of this bias.

These views support the idea that company performance should be measured using an accounting benchmark. Appropriately so, as accounting measures of company performance are standardised and well-supported to a large extent through the reporting standards set by IFRS.

3. REVIEW OF SIMILAR STUDIESThe majority of literature within this scope investigates the relationship between

total executive remuneration and some measure of company performance. However, since share-based payments could potentially contribute a large proportion of executive remuneration, it is worthwhile exploring past literature on this relationship. The literature comprised a wide range of published and peer-reviewed articles in journals, papers issued by universities as well as articles in popular publications.

While extensive research has been conducted on the relationship between executive compensation and company performance, it seems there is no concrete conclusion that holds (Bruce, Buck & Main, 2005; Scholtz & Smit, 2012). The following papers support the idea that executive compensation is positively correlated with company performance:

Scholtz and Smit (2012) believe that Murphy completed one of the first influential studies on this link in 1986. Murphy (1986) found that executive remuneration is statisti-cally linked to the performance of the company when company performance is meas-ured in shareholder return and growth in sales. Main (1991) also found evidence that the



alignment of interests between shareholders and executives is impacted by remuneration policies. Benito and Conyon (1999) and Main, Bruce and Buck (1996), studied the re-lationship in large UK companies and found a link between company performance and executive remuneration when the latter included share options. Similarly, O’Neill and Iob (1999) concluded that remuneration that includes share options is indeed linked to the performance of Australian organisations. A study by Scholtz and Smit (2012) found that there is a considerable link between executive remuneration and company perfor-mance for medium-sized companies listed on the Alternative Exchange.

Conversely, Pepper, Gore and Crossman (2013) found that LTIPs are generally neither efficient nor effective in meeting their objectives due to the way in which executives frame choices, assess probability, perceive value and respond to uncertainty. They feel this is the case as executives cannot see any causal link between their actions and the reward outcomes, as is clear with short-term incentives such as annual bonuses. This led to a similar conclusion by Peng and Röell (2008) that option-based executive compensation leads to an excessive focus on the short-term share price instead of providing a long-term incentive. This equivalent idea of ineffectiveness was drawn upon by Pass (2003), as well as Buck et al. (op. cit.). Griner (1999) also found a number of results: there is no association between CEO stock option grants and changes in shareholder return, there is no relationship between compensation and shareholder return, but that there is a positive relationship between accounting-based performance and total compensation (Nowicki, Lippitt & Lewis, 2006).

However, in a study by De Wet (2012), it was found that executive compensation does have a significant relationship with company performance measured by EVA and MVA, but an even stronger relationship exists when compared to the traditional accounting measures, ROA and ROE. This study included the use of share-based payments and options. Likewise, Nowicki, Lippitt and Lewis (2006: 148) identified a human capital analysis by Emerman (2005) and found that “companies that differentiate employee bonuses based on staff performance and use share-based com-pensation financially outperform those that do not.” The authors suggest that the superior performance by these companies is attributable to these performance-related employee bonuses.

In an analogous study by Core and Larcker (2002), it was determined that by adopting a policy of mandatory share-ownership plans for executives, company performance subsequently increases. Although share option plans were not considered, it was found that by compelling senior management to become part-owners of the company, company performance consequently improves. The next step in this study is to determine whether share options and other share-based payment schemes have a similar impact.

In an alternative study which is of considerable importance, Khoroshilov and Narayanan (2008) took an alternative view on compensation packages and investigated the impact of this on executive performance, rather than company performance. If we maintain the belief that executive performance influences company performance, then



it is beneficial to consider their findings. Executive performance is divided into two areas: discovering strategies and implementation of previously discovered strategies. According to the authors, share-based compensation is necessary to push executives to put effort into discovering new strategies while profit-based compensation is used to incentivise executives into implementing strategies. This is because the discovery of strategies does not create immediate cash flows while the implementation of strategies does and it is known that profit-based salaries are influenced by cash flows. The study concluded that share-based compensation is entirely necessary to correctly motivate and increase performance of executives in the company. A logical assumption to make is that indicates that the performance of the company would improve too.

Ofek and Yermack (2000) conducted a study into the evolution of managerial ownership after equity-based compensation. They found that executives actively rebalance their personal portfolios when awarded equity-based compensation. It is believed that this can affect incentives to perform and thus the performance of the company. It was discovered that executives with low prior ownership of the company do not quickly sell their shares after being awarded share options. However, executives with large prior ownership do tend to sell shares once they are granted these awards. Furthermore, regardless of prior ownership, executives sell shares immediately after exercising their options. In conclusion, Ofek and Yermack noted that it is possible to impose performance incentives only up to a certain level of share ownership in a company. After this threshold, it may be necessary to place restrictions on sales of shares after being awarded. The question arises: does the awarding of these equity-based payments even go so far as to affect company performance in larger-sized companies if they are merely being sold immediately? An additional issue is that excessive selling of a stock may send negative signals to investors and affect the share-price implying that executives may wish to hold on to their stock awards longer.

Possibly the most closely related study is the investigation into the effect of executive compensation structure on company performance by Mehran (1995). Mehran suggests that form, rather than level, of compensation is what motivates executives to increase company value. He concludes that company performance is positively related to the percentage of equity held by executives as well as to the percentage of their compensation package that is equity-based. Mehran notes that Murphy (1985), along with Jensen and Murphy (1990), found a statistically significant relationship between level of pay and company performance. Furthermore, both suggest that there is a stronger relationship between share-based compensation and performance and that company value can be expected to increase by using more share-based remuneration.

The purpose of this current study is to identify whether a similar relationship exists using empirical evidence of companies listed on the JSE. It is important to note that when investigating compensation structure, Mehran used expected compensation and not realised. Thus, the measurement of share options excludes any change in value of the accrued stock of outstanding options. This is in line with the reporting standards surrounding share options mentioned above. In conclusion, Mehran deduces that both



Tobin’s Q and ROA are positively related to the percentage of executives’ total compen-sation that is equity-based as well as the percentage of shares held by these executives.

4. PAST DATA AND METHODOLOGIESThis section looks at the different types of data and methodology used in past

research. It is an essential component in the investigation into the relationship between share-based remuneration and company performance. The recommended data and various statistical techniques used by reviewed academics can aid the intentions of this study vastly.

In the investigation into the relationship between executive compensation and EVA and MVA performance of companies, De Wet (2012) used data supplied by the financial data provider McGregor BFA for companies listed on the South African Johannesburg Securities Exchange (JSE). It spanned the five-year period from 2006 to 2010. One of the hypotheses tested was, “There is a statistically significant positive relationship between executive remuneration and EVA and MVA.” De Wet then performed a regression analysis using total remuneration as the dependent variable and created nine models each with a different combination of explanatory variables. The explanatory variables consisted of standardised EVA and MVA, weighted average cost of capital, ROA and ROE. Furthermore, the recommended robustness tests of endogeneity, serial correlation, heteroskedasticity, and stationarity were performed.

Likewise, Scholtz and Smit (2012) explored the link between executive remu-neration and company performance for South African companies listed on the Alter-native Exchange. The final sample used consisted of 58 companies whose data over the period from 2003 to 2010 were obtained from McGregor BFA. Similarly, a regression analysis was performed using executive remuneration as the dependent variable and turnover, earnings before interest, tax depreciation and amortisation (EBITDA), total assets and share price as the explanatory variables.

It seems, based on the specification of the dependent and explanatory variables, that both the models specified by De Wet (2012) and Scholtz and Smit (2012) suggest that the effect company performance has on executive remuneration was explored rather than the effect executive remuneration has on company performance. This uncertainty regarding the statistical correctness of the models will need to be verified before implementing any similar studies.

A paper prepared by Core and Larcker (2002) also performed a regression analysis although the aims of their study were slightly different. However, the dependent variable was still taken to be company performance measured by the natural logarithm of returns. In an alternative study, Nowicki, Lippitt and Lewis (2006) presented a model to explore the contributions to firm-value, rather than the traditional measures of company performance, through stock-based compensation plans. The actual value and the estimated firm value were compared. The actual value of a firm was calculated as the present value of all future benefits to its owners using the Earnings Capitalisation Model, while the estimated value was derived from accounting measures of both



earnings and stock-based compensation. The idea was that a firm would reflect a greater value than would be expected in the absence of stock-based compensation. The study concluded that there is a component of firm-value attributed to stock-based compensation. The data consisted of information obtained from the Research Insight (Compustat) database regarding 297 firms distinguished by six industry groups.

In the closely linked study by Mehran (1995), a regression analysis was performed on the executive compensation structure of 153 randomly-selected manufacturing companies in the USA during the 1979–1980 financial year. The analysis comprised of two base models: first with Tobin’s Q as the dependent variable and secondly with ROA. The explanatory variables to describe these performance measures were taken to be the percentage of: CEO’s equity-based compensation, shares and stock options outstanding held by CEO, shares held by all outside blockholders and the percentage of outside directors. This study merely needs to be adapted to account for other executives on the board of directors as well as obtaining data on companies listed on the JSE. Furthermore, the statistical technicalities seem more robust than those presented by De Wet (2012) and Scholtz and Smit (2012).

By incorporating the techniques described above and adapting them to fit the study under consideration, a vigorous investigation into the relationship between share-based payments and company performance for South African companies can be performed.

5. RESEARCH METHOD AND DATAThe data used in the study comprises of company records relating to eighteen

companies in the retail sector of the JSE and relates to the six-year period spanning 2008 to 2013. The decision to confine the study to the retail sector stems from the idea that companies in different sectors will have different influential factors on both the response and explanatory variables in the study. By exploring similar companies, homogeneity in the data is enhanced. The following information was collected:1) Return on assets,2) Return on shareholders’ equity,3) Total assets,4) Total executive emoluments,5) Expense recognised in consideration of share schemes,6) Number of ordinary shares held by executive directors, and7) Number of ordinary shares in issue.

Neither McGregor BFA nor Bloomberg could provide the complete set of necessary data, thus all records (1) through to (7) were collected from the relevant company’s annual financial statements to ensure consistency in the data. Furthermore, the data is limited to disclosed levels found only in the relevant annual financial statements pertaining to the executive directors and not that of the entire board of directors.

The research method chosen is a linear regression analysis in order to test the following hypothesis:



H1 = There is no statistically significant relationship between company performance and the proportion of equity-based compensation to executives directors.

The dependent variable is the measure of company performance as the aim of this study is to determine whether the independent variable, share-based executive compensation, is linearly related to this measure. Two separate models have been created for each measure, ROA and ROE. Additionally, data from each year is used to create a model representing the relationship in that year.

Using the data collected, the following additional statistics were calculated to be used in the regression analysis as explanatory variables:8) Natural log of total assets (LTA)9) Percentage of total remuneration as share-based awards (PSBA)10) Percentage ownership of ordinary shares by executive directors (PO). The

percentage of share-based awards was calculated by dividing the level of share-based awards in a given year by the sum of these awards and the total cash executive compensation. The percentage ownership of ordinary shares was calculated by finding the proportion of ordinary shares in a given year held by all executive directors to the number of ordinary shares in issue for the company.

Table 1 highlights the descriptive statistics pertaining to the data over the period 2008 to 2013.

Table 1 Descriptive statistics

ROE ROA LTA PSBA POMean 31.63532 20.42393 22.75786 0.27810 0.01930Median 30.10000 17.56000 22.91492 0.22165 0.00720Maximum 116.87000 107.60000 25.01042 0.81593 0.11888Minimum 1.60000 4.30000 18.48911 0.00000 0.00002Std. Dev. 16.54760 13.22837 1.00021 0.23272 0.04108

From the above table it is clear that, over the six-year period, the maximum percentage of share-based awards formed 81.59% of the executives’ total remuneration. This occurred during the 2010 financial year of Shoprite Holdings Ltd. However, this was after an outlier of 86.64% found in the 2011 Massmart Holding Ltd. financial year was removed. It is not necessary to consider the 81.59% in the Shoprite Holdings Ltd. data as an outlier as it was found that this statistic is consistently high for the company, ranging from 72% to 87% during the 2009–2012 period. The minimum percentage gain was 0% found in many instances where share-based awards lost their value or were not exercised. This was particularly evident in the 2008 financial year and is attributable to the universal recession as a decline in the share price understandably reduces the



value of share-based awards. With regard to the percentage of ordinary shares held by executive directors, the maximum holding occurred at the end of the 2011 financial year for Famous Brands Ltd. while the minimum over the period was found at the end of the 2008 financial year of Tiger Brands Ltd. Additionally, no companies reported a loss over the period as seen by the positive minimum ROA and ROE figures.

Before the regression analysis can be performed a check for co-linearity must be done. Table 2 shows the correlations between the variables included in the analysis.

Table 2 Correlations between variables

ROE ROA LTA PSBA POROE 1.00000 0.27523 –0.14946 0.06119 –0.06413ROA 0.27523 1.00000 –0.30729 –0.13946 –0.05338LTA –0.14946 –0.30729 1.00000 0.22706 –0.06255PSBA 0.06119 –0.13946 0.22706 1.00000 –0.08868PO –0.06413 –0.05338 –0.06255 –0.08868 1.00000

Upon examination of this table it is clear that none of the explanatory variables are correlated with each other or with the response variables. The low magnitudes of the correlation coefficients indicate that co-linearity between the variables does not exist and it is safe to perform the regression analysis.

The specified measures of company performance were then regressed on the explanatory variables in different combinations, in order to find whether a significant relationship exists. Models of the form,

0 1 1 β β β ε= + +…+ +i p p iY X X .

were fitted, where Yi represents the i th company’s measure of performance, βp represents the pth coefficient, Xp represents the pth explanatory variable and εi representing the i th

error term, assumed to be independent and normally distributed. Six sets of models were produced; a set for each financial year over the six-year period.

6. RESULTSTwo models were fitted in each financial year to determine the relationship

the proportion of equity-based compensation has on each measure of company performance, ROA and ROE. Model 1 contains only the constant term and the natural log of total assets. Model 2 contains the above variables as well as the percentage of total remuneration as share-based awards with model 3 replacing this with the executive directors’ percentage of ownership. Model 4 contains all the variables. All the variables in the regression analysis are continuous. The full results of the models fitted can be found in the appendix. Below are the summarised results of the fitted models using ROA as the dependent variable.



Table 3 Summary of results: ROA as dependent variableModel (max variables)

1(2)

2(3)

3(3)

4(4)

2013Number of sig. variables 1 0 0 0F-statistic (p-value)

2.612(0.128)

1.251(0.319)

1.215(0.328)

0.770(0.533)

R2 0.157 0.160 0.157 0.1612012Number of sig. variables 2 2 2 2F-statistic (p-value)

6.785**(0.019)

3.304*(0.065)

3.526*(0.058)

2.196(0.137)


3.269*(0.091)

1.536(0.250)

1.592(0.241)

1.013(0.421)


5.107**(0.038)

2.802*(0.092)

2.215(0.146)

1.633(0.230)


2.24(0.155)

1.174(0.338)

1.175(0.342)

0.866(0.488)


5.739**(0.029)

3.400*(0.061)

2.278(0.145)

1.991(0.174)

R2 0.264 0.312 0.275 0.352

Note: ***, **, * indicate statistical significance at the 1%, 5% and 10% levels respectively. The number of significant variables is measured at the 10% level.

In the above table, it is clear that not many models reflected any significant F-statistics. The 2012 data produced reliable models with three of the four models returning an F-statistic significant at the 10% level, at least. This is seen in models 1, 2 and 3 with F-statistics of 6.785, 3.304 and 3.526, respectively. These models produced p-values of



1.9%, 6.5% and 5.8%. However, when all the variables were included in model 4, the model produced was not significant. Similarly, in 2010 and 2008, only model 2 was significant at the 5% level with F-statistics of 2.802 and 3.400, respectively.

The results of the models with ROE as the dependent variable are summarised in Table 4.

Table 4 Summary of results: ROE as dependent variableModel (max variables)

1(2)

2(3)

3(3)

4(4)

2013Number of sig. variables 0 0 0 2F-statistic (p-value)

1.017(0.330)

0.862(0.445)

1.171(0.341)

1.198(0.352)


2.528(0.131)

4.385**(0.032)

4.249**(0.036)

4.931**(0.017)


1.153(0.300)

3.252*(0.070)

1.62(0.235)

2.652*(0.096)


0.899(0.357)

0.564(0.581)

0.549(0.590)

0.345(0.793)


4.452*(0.052)

2.272(0.140)

2.313(0.141)

1.476(0.275)


0.129(0.725)

0.235(0.793)

0.116(0.892)

0.101(0.958)

R2 0.008 0.030 0.019 0.027Note: ***, **, * indicate statistical significance at the 1%, 5% and 10% levels respectively. The number of significant variables is measured at the 10% level.



When ROE was modelled as the dependent variable, only the 2012 data returned sig-nificant models. All of models 2, 3 and 4 were significant at the 5% level returning F-statistics of 4.385, 4.249 and 4.931, respectively. Additionally, these models repre-sented more of the data than any other models fitted, as seen by the R-squared values of 36.9%, 37.8% and 53.2%.

When testing this relationship, Mehran (1995) suggested that it is necessary to control for the size of the company in the models. Accordingly, the natural log of total assets was used as a proxy for the company size. A brief perusal of the full results found in the appendix indicates that ROA is consistently linked to LTA with a negative coefficient when included as the only variable in the model. This implies that an increase in the total assets of the company results in a decrease in the return on assets for that year, all else held constant. This is an expected result when the derivation of the financial ratio is understood. Furthermore, it is seen that LTA alone did not have any significant relationships with ROE in any individual year, with the exception of 2009. This indicates that the total asset value, or the size of the company, does not have any significant effect on the return generated as a percentage of issued ordinary equity.

In summary, very few models identified any significant relationship between the measures of company performance and the proportion of share-based awards (as a percentage of total compensation) as well as the percentage of ownership, both when tested alone and simultaneously. This is clearly seen by the low number of significant variables in tables 3 and 4.

In 2012, all combinations of the explanatory variables of interest resulted in significant relationships when modelled against ROE. Table 5 presents the findings of the model including all variables as it boasts the greatest R-squared value and thereby indicating that it describes the data most efficiently.

Table 5 Model of ROE regressed on the 2012 data including all variables

Dependent Variable: ROEVariable Coefficient Std. error t-Statistic ProbabilityIntercept 306.154 77.381 3.934 0.00171LTA –12.261 3.421 –3.584 0.00333PSBA 26.928 12.995 2.072 0.05869PO –220.356 87.544 –2.517 0.02575Weighted statisticsResidual standard error 10.52 F-statistic 4.931R-squared 0.5322 Probability of F-statistic 0.01677Adjusted R-squared 0.4243

The data from 2012 yields the best fitting model with an R-squared value of 53.22% and an adjusted R-squared value of 42.43%. Additionally, all variables are found to



be significant at some level. LTA and PO are significant at the 5% level while PSBA is significant at the 10% level. However, the coefficient of PO is negative indicating that in 2012 companies with a lower percentage of ordinary shares held by executive directors yielded a greater ROE. Notably, the p-value for this model is 1.68% indicating a great significance.

In 2011, a similar result to that in Table 5 was found. ROE was linked to PSBA at the 5% level while LTA was linked at the 10% level. This is shown in Table 6 below.

Table 6 Model of ROE regressed on 2011 data

Dependent Variable: ROEVariable Coefficient Std. error t-Statistic ProbabilityIntercept 202.728 85.591 2.369 0.0328LTA –8.123 3.855 –2.107 0.0536PSBA 34.557 15.393 2.245 0.0414Weighted statisticsResidual standard error 12.94 F-statistic 3.252R-squared 0.3172 Probability of F-statistic 0.0692Adjusted R-squared 0.2196

However, as before, the R-squared and adjusted R-squared values of 31.72% and 21.96% are particularly low demonstrating a weak correlation to the data observed in 2011.

Alternatively, a visual perspective on the data is shown below. Figure 1 shows the percentage of total remuneration in share-based awards for each retail company over the period in a clustered bar graph. The correlation between this and the company’s ROE for the full period is also plotted on the line graph. Additionally, the average ROE experienced by the companies over the period is plotted. The data are plotted in descending order of correlation between PSBA and ROE. Mr Price Ltd. showed the greatest correlation of 0.96 while Tiger Brands experienced a correlation of –0.92 over the six-year period.

Although there is little evidence of any statistically significant link between PSBA and ROE across the industry as shown by the models fitted, the isolated data of each company shows something more. The figure indicates a slight tendency for the average ROE over the period to follow the trends in PSBA. This can be seen with the drop in average ROE to match a drop in PSBA from Mr Price to Woolworths, Clicks to JD Group, as well as from Spar to Illovo. Similarly, observable increases occur from JD Group to Pick n Pay, Tongaat Hulett to Lewis Group and Illovo through Oceana to Massmart. These trends suggest that there may be a relationship between the PSBA to executive directors and the average return on equity experienced by the companies during the six-year period. It is possible that the volatility of PSBA within a given company erodes any likelihood of statistical significance between the two variables,



Figure 1 Clustered bar graph showing the percentage of total remuneration in share-based awards for each company, average ROE and correlation between the two for the period.



thus leading to statistically insignificant models as summarised in tables 3 and 4 and in full in the appendix, tables 7 to 18.

In summary, out of thirty-six models fitted using PSBA or PO or both, only five indicated a statistically significant relationship between either of these and the specified measure of company performance. Furthermore, all five of these models linked the equity-based compensation to ROE rather than ROA. However, the visual description of the data hints at a relationship between PSBA and average ROE rather than a correlation during an individual year. Ultimately, this trend needs to be investigated more rigorously before any concrete conclusions can be drawn.

7. CONCLUSION AND FURTHER RESEARCHThe results of this study provide little evidence that there is any significant

relationship between proportion of equity-based compensation (as a percentage of total compensation) to executive directors and company performance, at least for the period spanning 2008 to 2013. Moreover, the significant relationships found link equity-based compensation to ROE only. In contrast, Mehran’s (1995) empirical findings suggest that more emphasis must be put on executive compensation and specifically its struc-ture as it is a determinant of company performance. However, this evidence supports American-based companies and says little regarding the effect equity-based compen-sation has on performance in South African companies. Additionally, the executive compensation structures examined in the study relate only to the CEO.

With regard to research on South African companies, very little has been done on the structure of executive compensation and the presence of equity-based remuneration. Studies done by De Wet (2012) and Scholtz and Smit (2012) investigate a relationship with total executive remuneration although they omit any distinct characteristics present due to equity-based remuneration. Furthermore, the regression analyses suggest that the effect company performance has on total directors’ remuneration was investigated, rather than the reverse. This yields debatable results and holds little comparison to the study completed above.

Given the data on 18 South African, JSE listed, companies, there are inconsistent results as to whether the relationship under investigation is present. Undoubtedly, no relationship between proportion of equity-based compensation to executives and ROA exists during the considered period. However, whether the same can be said regarding ROE is uncertain. Under the investigated period, only the 2012 data produces strong results supporting the hypothesis. These differing findings suggest that the data found in 2012 may be an outlying example and therefore insufficient to conclude strongly on the relationship found. Furthermore, the visual description of the data suggests that a relationship may exist, but in relation to the average ROE instead. Given the above conclusion, there is not enough evidence to reject the hypothesis that executive compensation has no effect on company performance. As a result, the efficiency of share-based awards to eliminate issues arising from principal-agent theory is still debatable and additional research is still necessary.



There are various opportunities for further research. The possible relationship between the percentage of total remuneration in share-based awards and the average return on equity for the period is a potential starting point for further investigation into this topic. Future studies could include a larger number of JSE listed companies from more than one sector. Although this would increase heterogeneity in the data, these effects can be corrected for. Similarly, a study which dives deeper into the remuneration structure of executive and non-executive directors will be able to conclude further on the effect that compensation has on company performance. Additionally, the strength of the different forms of equity-based compensation can be explored to determine the ideal compensation package for executive directors.

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APPENDICESResults of models included in the study

Table 7 Results of 2013 data with ROA as dependent variable

Model 1 2 3 4Constant 127.423* 121.701 129.783 122.102LTA –4.756 –4.436 –4.854 –4.453PSBA –4.201 –4.177PO –5.342 –0.832F-statistic (p-value)

2.612(0.1283)

1.251(0.3186)

1.215(0.3284)

0.7696(0.5329)

R2 0.1572 0.1614 0.1574 0.1614Adjusted R2 0.09705 0.03233 0.02781 –0.04831

Table 8 Results of 2013 data with ROE as dependent variable

Model 1 2 3 4Constant 121.160 146.722 186.679 230.733*LTA –4.021 –5.450 –6.738 –9.037*PSBA 18.769 23.955PO –148.290 –174.160F-statistic (p-value)

1.017(0.3303)

0.862(0.4451)

1.171(0.3406)

1.198(0.3522)

R2 0.06774 0.1171 0.1527 0.2305Adjusted R2 0.001149 –0.01874 0.02232 0.03811


Model 1 2 3 4Constant 165.646*** 174.203** 196.527** 200.334**LTA –6.348** –6.787** –7.618** –7.816**PSBA 4.4559 2.001PO –71.483 –71.247F-statistic (p-value)

6.785**(0.01915)

3.304*(0.06471)

3.526*(0.05753)

2.196(0.1374)

R2 0.2978 0.3058 0.335 0.3363Adjusted R2 0.2539 0.2133 0.24 0.1831




Model 1 2 3 4Constant 158.718* 219.200** 254.904*** 306.154***LTA –5.655 –8.761** –9.607** –12.261***PSBA 32.226** 26.928*PO –223.535** –220356**F-statistic (p-value)

2.528(0.1314)

4.385**(0.03166)

4.249**(0.03612)

4.931**(0.01677)

R2 0.1365 0.3689 0.3777 0.5322Adjusted R2 0.08248 0.2848 0.2888 0.4243


Model 1 2 3 4Constant 120.807** 117.522* 137.444* 131.811*LTA –4.399* –4.232 –5.070 –4.765PSBA –1.448 –3.395PO –40.836 –45.406F-statistic (p-value)

3.269*(0.09068)

1.536(0.2495)

1.592(0.2407)

1.013(0.4207)

R2 0.1789 0.1799 0.1968 0.2021Adjusted R2 0.1242 0.06275 0.07321 0.002686


Model 1 2 3 4Constant 124.342 202.728** 193.548* 242.985**LTA –4.139 –8.123* –6.983 –9.661**PSBA 34.557** 29.796*PO –160.566 –120.461F-statistic (p-value)

1.153(0.2999)

3.252*(0.0692)

1.62(0.2353)

2.652*(0.09622)

R2 0.07137 0.3172 0.1995 0.3987Adjusted R2 0.009459 0.2196 0.07639 0.2484




Model 1 2 3 4Constant 102.684** 95.532** 98.922** 94.605*LTA –3.765** –3.270* –3.512* –3.209PSBA –6.946 –7.742PO 5.863 –1.440F-statistic (p-value)

5.107**(0.03813)

2.802*(0.09246)

2.215(0.1459)

1.633(0.2301)

R2 0.242 0.272 0.2404 0.2737Adjusted R2 0.1946 0.1749 0.1319 0.1061


Model 1 2 3 4Constant 85.728 92.285 99.339 100.388LTA –2.441 –2.868 –2.960 –3.034PSBA 7.339 1.882PO –32.006 –30.231F-statistic (p-value)

0.8993(0.3571)

0.564(0.5806)

0.5485(0.5898)

0.3449(0.7934)

R2 0.05321 0.06994 0.07266 0.07373Adjusted R2 –0.005959 –0.05407 –0.05982 –0.14


Model 1 2 3 4Constant –189.813 –223.256 –254.853 –314.303LTA 9.566 –17.222 12.361 15.184PSBA –25.198PO 133.107 162.193F-statistic (p-value)

2.24(0.1552)

1.174(0.3379)

1.175(0.342)

0.8659(0.4876)

R2 0.1299 0.1436 0.1637 0.191Adjusted R2 0.07194 0.02125 0.02436 –0.02958




Model 1 2 3 4Constant –258.912* –221.049 –332.602* –297.760LTA 13.194* 11.363 16.362* 14.708PSBA 19.499 14.768PO 132.951 115.905F-statistic (p-value)

4.452*(0.05207)

2.272(0.1398)

2.313(0.1414)

1.476(0.2748)

R2 0.2289 0.2451 0.2783 0.287Adjusted R2 0.1775 0.1372 0.158 0.09252


Model 1 2 3 4Constant 137.520** 136.149** 158.083** 166.838**LTA –5.249** –5.122** –6.207* –6.474**PSBA –10.385 –13.540PO 206.553 167.139F-statistic (p-value)

5.739**(0.02918)

3.4*(0.06056)

2.278(0.145)

1.991 (0.1739)

R2 0.264 0.3119 0.2752 0.3519Adjusted R2 0.218 0.2202 0.1544 0.1751


Model 1 2 3 4Constant 66.700 68.232 94.055 89.565LTA –1.490 –1.633 –2.643 –2.506PSBA 11.605 6.944PO 34.152 54.368

F-statistic (p-value)0.1286

(0.7246)0.2354

(0.7932)0.116

(0.8915)0.1011

(0.9577)R2 0.007971 0.03043 0.01897 0.02684Adjusted R2 –0.05403 –0.09885 –0.1445 –0.2386

Note: ***, **, * indicate statistical significance at the 1%, 5% and 10% levels respectively.

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