Questions such as ‘Are South African executives’ packages linked to performance?’ come to mind when reading various newspapers, as well as academic and business articles. Concerns regarding excessive remuneration packages of chief executive officers (CEOs) have been added to an ongoing concern about the widening gap between the remuneration of executives and ordinary employees, as well as their large termination payments with a perceived lack of justification (Theunissen, 2010).

The focus of this study was Schedule 2 state-owned entities (SOEs) in South Africa. State-owned entities play a vital role in the economies of many countries, and the outrage over what many consider to be excessive CEO remuneration warrants research and plays an important role throughout South Africa (Corporate Governance of State-Owned Enterprises in Africa, 2009). Despite the highly publicised incompetence and poor performance of some SOEs, convincing evidence proposes that SOEs remain relevant (Boko & Yuan Jian, 2011; Mbo & Adjasi, 2017).

Crafford (2012) postulates that various stakeholders hold diverse views regarding how SOEs should benchmark their remuneration. State-owned entities have mostly ignored the remuneration guidelines of the Department of Public Enterprises (DPE), which insists that they need to be benchmarked against the private sector (Crafford, 2012). In 2011, a new guideline was established, intended to serve as an improvement on the 2007 guideline. However, not all South African SOEs adopted and implemented the guidelines (Maloa & Bussin, 2016, p. 10).

The link between pay and performance has for some time now come under increased scrutiny, from the media and the public as well as from an academic perspective, that excessive remuneration is not aligned with SOE performance (21st Century Pay Solutions, 2012). Two cases in point follow, the first being the R9467 million total remuneration (TR) that Brian Molefe – Eskom’s former acting CEO – received during the 2015/2016 financial year (Peyper, 2016). The TR packages that Eskom executives received during the 2015/2016 financial year amounted to R75.33m, compared to the R50.61m paid in the previous financial year (Peyper, 2016). Second, South African Airways’ (SAA) former suspended CEO, Monwabisi Kalawe, received almost R2.7m after his resignation (Majangaza, 2015).

Over and above the millions of rands paid out to SOE CEOs, government has had to ‘bail out’ a number of SOEs over the years to keep them afloat. For example, during 2015, Eskom received a R23 billion bailout from government (Fripp, 2015). South African Airways has been surviving on state-guaranteed loans for the past few years. In addition, SAA posted a loss of R1.5bn in the 2015/2016 financial year (Gerber, 2016). During 2017, the South African government announced that SAA will receive an undisclosed sum from the National Revenue Fund in order to pay back loans of approximately R2.3bn to Standard Chartered Bank (Rothpletz, 2017). Rothpletz (2017) reports that SAA, in total, has borrowed R19bn from government.

State-owned entities, unlike private companies, receive the larger part of their revenue from the National Treasury (who collects from the taxpayer) and are supposed to serve the public. However, the remuneration of top executives in SOEs seems to be competing with that of private companies. Consequently, consumers pay high tariffs for the products and services of SOEs such as Eskom, while consumers should be benefiting from the funding paid to Eskom by South Africa’s National Treasury (Ngwenya & Khumalo, 2012). In addition, the remuneration of CEOs of SOEs is of special importance to sustainable public service provision (Ngwenya & Khumalo, 2012; Papenfuss & Schmidt, 2016).

The focus of this study was on Schedule 2 SOEs in South Africa. Taking into consideration the important role that SOEs play in the economic prosperity of a country, the outrage over what many consider to be excessive CEO remuneration warrants research. The main problem, which informed the present study, is therefore the excessive remuneration packages that CEOs in SOEs receive, despite poor performance, and government ‘bail out’ of some of these SOEs.

From past research on executive remuneration and company performance, there seems to be no real consensus on the relationship between executive remuneration and company performance. This is partially because of the diverse set of disciplines involved in these studies and the wide variety of methods used to investigate the questions (Florin, Hallock & Webber, 2010). In addition, for the private sector there are numerous studies in scientific journals on the level, design and determinants of executive directors’ remuneration (Bussin & Nel, 2015; Jensen & Murphy, 2004; Jeppson, Smith & Stone, 2009; Ngwenya & Khumalo, 2012). However, with regard to studies on SOEs, the literature reports on very few empirical studies (Papenfuss & Schmidt, 2016).

The primary research objective was to determine whether there is a relationship between CEO remuneration and SOEs’ performance over a 9-year period (2006–2014). Further, in view of the importance and the important role SOEs play, it becomes important to understand the measures that drive their performance. However, this remains a poorly researched area in organisational science (Mbo & Adjasi, 2017). The secondary research objectives were to determine the following:

This study contributes to the knowledge on the relationship between CEO remuneration and the performance of Schedule 2 SOEs in South Africa. In addition, there is insufficient understanding of what combination of variables positively influences SOE performance (Mbo & Adjasi, 2017). This research therefore sought to contribute to an enhanced understanding in this respect. This research will be of particular interest to investors and other stakeholders, such as unions and regulators, who expect CEOs’ remuneration to be aligned with the SOEs’ performance. A contemporary statistical package, named EViews, was used in analysing the data. EViews is specifically designed to analyse longitudinal panel data, unlike the traditional SPSS, which is not specifically designed for this set of data.

A more detailed review of the literature follows in the next section. The research design section outlines the longitudinal, quantitative, archival research method selected and describes the statistical analysis employed. The results of the study are then presented and discussed. The article concludes with a brief discussion of the research limitations and practical implications for remuneration practitioners.

Executive remuneration refers to the FP, short-term incentives and long-term incentives (LTIs), and related benefits awarded to those who occupy the most senior decision-making positions in private and public-sector enterprises (Bussin, 2011). The design of remuneration schemes is a key factor that affects the behaviour and awareness for acting in accordance with the overriding aims of the public authority. Moreover, pay seems key in attracting, recruiting and retaining executives in the public management environment. This is especially true where executives need to be recruited from the private sector (Jerry, Pan & Tian, 2011; Ngwenya & Khumalo, 2012; Papenfuss & Schmidt, 2016). Walker (2010) concurs with this notion and postulates that companies can attract the best executives by providing a competitive remuneration package.

For the purpose of this article, the focus is on FP and TR. These can be defined as follows:

Attractive CEO remuneration packages are created to ensure that the company is able to attract and retain the best possible CEOs (Bussin & Modau, 2015). In their study, Maloa and Bussin (2016) found that attractive remuneration packages are determined to a large extent by the size of the organisation, type of industry and job function.

Researchers generally use financial performance as a measure of company performance (Demirer & Yuan, 2013). Numerous studies have used accounting-based measures, such as net profit (NP), return on equity (ROE) and return on assets (ROA), together with market-based measures, such as stock price and total shareholder return, as measures of company performance (Nourayi & Mintz, 2008). Papenfuss and Schmidt (2016) posit that 9 out of 11 studies on SOEs used financial performance ratios (measures by accounting and/or stock return) to examine the pay–performance relationship. Nearly all studies of SOEs used financial figures to examine associations between company performance and the level of CEO remuneration, for example, Otieno (2011), Minhat and Abdullah (2014), He, Conyon and Shaw (2013), Ngwenya and Khumalo (2012) and Mbo and Adjasi (2014). However, despite the numerous studies, there seems to be limited consensus on the optimal measure of company performance (Bussin & Modau, 2015).

Pay–performance sensitivity refers to the relationship between remuneration outcomes and measures of company performance, with not one conclusive measure but rather a broad set of variables (Bussin, 2015). Several research studies have shown the diverse nature and contrasting results of the study. With regard to the private sector, many South African empirical studies (i.e. Bradley, 2011; Bussin & Blair, 2015; Bussin & Modau, 2015; Scholtz & Smit, 2012; Theku, 2014) and international empirical studies (inter alia, Gigliotti, 2012; Murphy, 1985; Otieno, 2011; Tariq, 2010; Tian, 2013) have investigated the pay–performance relationship of CEO remuneration. The majority of these scientific studies did not provide evidence of a concrete pay–performance relationship with regard to the private sector.

As opposed to studies that focused on the private sector, there are very few empirical studies for SOEs regarding the relationship between CEO remuneration and company performance. In fact, Maloa and Bussin (2016) concluded that the literature in scientific journals on the subject of the investigation of executive remuneration in South African SOEs is limited. International studies, such as Minhat and Abdullah (2014), He et al. (2013), Jerry et al. (2011) as well as Kato and Long (2006), considered listed SOEs from the national government level of Asian countries. From a South African perspective, studies conducted on SOEs include Otieno (2011), Ngwenya and Khumalo (2012) and Maloa (2015). However, Maloa’s study focused on the transformation as an element of executive remuneration in South African SOEs. Interestingly, Mbo and Adjasi (2017) argue that a developing view could be that SOEs do perform well depending on the variables used to measure performance.

A number of researchers concluded that there is a positive relationship between CEO remuneration and company performance (Dai, 2014; Demirer & Yuan, 2013; Jensen & Murphy, 1990; Murphy, 1985; Ozkan, 2011; Zigler, 2011). The bulk of these studies were conducted in the UK and the USA. Studies conducted on SOEs, and where a positive relationship was found between CEO remuneration and company performance, are those reported by Xin and Tan (2009) and Chen, Ezzamel and Cai (2011). Otieno (2011) and Ngwenya and Khumalo (2012) conducted studies on South African SOEs. Otieno (2011), aimed to determine the relationship between financial performance and executive remuneration in South African SOEs within the context of the agency theory. Otieno’s (2011) findings revealed a positive relationship between executive remuneration and company performance. Ngwenya and Khumalo (2012) found a positive relationship between CEO remuneration (base salary) and the size of SOEs as measured by total revenue and number of employees.

In a Brazilian study conducted by Krauter and De Sousa (2013) during the period 2006–2007, no significant relationship was found between executive remuneration and corporate financial performance of sales growth and ROE. In South Africa, Bussin and Nel (2015) found a negative relationship between ROE and the guaranteed cost to company of the CEOs in the South African retail and consumer goods sector. Supporting this evidence, Kyalo (2015) found a weak negative relationship between executive remuneration and financial performance.

Minhat and Abdullah (2014) found no evidence of a pay-performance relationship in listed Chinese SOEs. Ngwenya and Khumalo (2012) found no positive relationship between CEO remuneration and SOE performance in South Africa (measured with ROA). In another South African study, Bradley (2013) investigated the relationship between CEO remuneration and company performance in the 40 largest public companies listed on the Johannesburg Stock Exchange for a 5-year period. Bradley (2013) found no relationship between CEO remuneration and measures of performance such as ROE, ROA, and earnings per share. Osei-Bonsu and Lutta (2016) examined the effectiveness of using CEO cash remuneration schemes in improving company performance in emerging markets. Osei-Bonsu and Lutta (2016) found no significant relationship between cash remuneration and ROA or ROE. Papenfuss and Schmidt (2016) examined the pay-performance relationship of executive directors from 176 SOEs in 11 sectors. They found no significant link between financial performance ratios (ROA and ROE) and the remuneration of executive directors.

It is evident that research conducted to establish the link between CEO remuneration and company performance metrics is inconclusive and that the results vary depending on the country, industry sector and the selected performance measures that were investigated (Bussin & Blair, 2015). Furthermore, the extent to which previous studies can aid the understanding of company performance in the context of SOEs remains a relatively unexplored area.

The research approach decided upon was a longitudinal, empirical quantitative study aimed at assessing the relationship between CEO remuneration and measures of company performance. This research was further a desktop study, archival in nature, using secondary data gathered from annual reports.

The research data utilised were obtained from Schedule 2 SOEs in South Africa for the period 2006–2014. The combined number of Schedule 2 SOEs were 21 as per the Department of National Treasury as on 30 April 2015 (see Table 1). The reason for using Schedule 2 SOEs for the purposes of this study was because these SOEs were (1) financially and operationally independent, (2) able to operate according to ordinary business principles and (3) self-funded (Public Financial Management Act, 1999). The number of Schedule 2 SOEs, the number of company performance measures used and the 9-year period (a large enough period) were seen as being sufficient for the research.

Because of the small target population, a sampling methodology was not employed and the entire population of 21 SOEs was used in the study. These 21 SOEs were subjected to the following criteria for inclusion in the study:

After implementing the selection criteria, 18 of the 21 Schedule 2 SOEs were included in the study.

The target population was South African Schedule 2 SOEs (N = 21). After applying the elimination process, a sample of 18 Schedule 2 SOEs was identified as usable for the purpose of the study (n = 18). Because there were various instances of significant differences in the descriptive results between the means and medians for the CEO remuneration components and company performance, the researchers reported on the medians. Medians are not affected by outliers compared to means, and generally when data sets have outliers, reporting the median as the central tendency of the data often gives a better ‘typical’ data value than the mean (Weiers, 2010).

Table 3 presents a summary of the descriptive statistics for FP received by CEOs in the 18 SOEs between 2006 and 2014. It is clear that there was an average year-on-year increase of 8% in FP. Because FP is often determined according to industry market surveys (Murphy, 1999), in most cases FP was not expected to decline during periods of poor financial performance (Kuboya, 2014).

Figure 1 shows a graphical presentation of the descriptive statistics for CEO FP. While the researcher did not consider inflation, it is evident from the graph that the increase in the mean and median fluctuated throughout the period of analysis. From Figure 1 it is evident that CEO FP did not experience the runaway growth claimed in the media. There was a slight increase in the median of FP during 2007, with the highest median of FP being in 2012.

Table 4 contains a summary of the descriptive statistics for TR received by CEOs in the 18 SOEs between 2006 and 2014. Total remuneration experienced an average year-on-year increase of 9% and a total increase of 93% over the period.

Figure 2 shows a graphical presentation of the descriptive statistics for CEO TR. From Figure 2 it is clear that TR fluctuated during the period under study. The decrease in TR during the 2009/2010 financial year could have been the fallout from the economic recession, while the decline during the 2012/2013 financial year could be attributed to the great number of acting CEOs during that period across the 18 SOEs.

Table 5 presents a summary of the medians (averages) of the descriptive statistics of the company performance components selected for this research study: turnover (T), operating profit (OP), NP, ROCE, ROE, LR, solvency ratio (SR), AO and IFWE. Table 6 contains a summary of the standard deviations for the company performance components.

From the descriptive statistics, it is clear that most of the performance measures declined over the 9-year period. The decline in the median measures was as follows: T = 111%, OP = 56%, NP = 29%, ROCE = 74% and ROE = 52%. On the other hand, median LR rose by 56%, and SR increased by a mere 2% over the period.

The objective of this research was to determine the relationship between CEO remuneration (FP and TR) and the financial performance of South African Schedule 2 SOEs. The results of each of the remuneration components will be discussed in subsequent paragraphs.

The regression model included 144 balanced panel observations and 18 cross-sectional units over a period of 8 years, because of the inclusion of the AR (1) term. Five iterations were run to determine the optimum final regression model for FP, with the fifth model being regarded as the optimum model. Table 7 provides a summary of each individual regression model (with the t-statistics in parentheses).

As can be seen in Table 7, the DW test statistic was 2.5, indicating no serious serial correlation. Model 5 was regarded as the optimum model as the F-statistic increased to 62.54, in conjunction with an improvement of the adjusted R². The optimum model indicated that 63% (adjusted R² = 0.63) of the variation in FP was explained by company performance. Table 7 further indicates that audit opinion does not play a role in the determination of FP. It was also noted that the coefficient of NP was negative for all the models tested.

It is important to note that an amount of R19m TR for one of the SOEs in the year 2008 was omitted from the regression analysis, as it was identified as an outlier that had a significant impact on the fitting of a representative regression model. The regression model included 142 unbalanced panel observations and 18 cross-sectional units over a period of 9 years. Five iterations were run to determine the optimum final regression model for TR. The results of each individual regression model are summarised and presented in Table 8 (with the t-statistics in parentheses).

As can be seen from Table 8, the DW test statistic was 2.74, indicating no serious serial correlation. The last regression, Model 5, in Table 8, was regarded as the optimum model, as the F-test statistic increased to 43.41, indicating an optimal fit for the model. Further reduction of independent variables resulted in a decrease in the F-statistic and adjusted R² value. The optimum model also explained 64% (adjusted R² = 0.64) of the variance in TR. The findings from Model 5 indicate that there is a relationship between TR and each of the following components: OP, NP, LR, ROCE and IFWE in South African SOEs.

From a practical point of view, this research identified certain performance measures that are of importance in determining CEO remuneration. State-owned entity boards and remuneration committees should meticulously consider turnover, OP, NP, liquidity and IFWE when determining CEO remuneration. This study therefore determined specific performance indicators affecting CEO remuneration in SOEs. By using these performance measures, SOE remuneration committees can determine the relationship between CEO remuneration and company performance based on reliable and statistically defensible measures. Further, by using these measures, SOE management can ensure that the correct measures are used to determine the remuneration components. In addition, the value of this research is that remuneration committees and SOE boards now have empirical evidence to determine CEO remuneration according to performance measures that are positive and significant to Schedule 2 SOEs. If these measures are implemented within SOEs, they could be considered to enhance the Code in King IV.

Based on the research findings, a framework merging financial measures needs to be developed and formalised with a link to SOE objectives. The frameworks, with clear performance measures linked to them, should be effectively monitored under a governance structure.

The research was limited to South African Schedule 2 SOEs and therefore excluded all other public entities. The conclusions may therefore not be generalisable to other entities without more research. In addition, this research only investigated the specific relationship between company performance and CEO pay and did not include information on the causal factors influencing CEO remuneration and the financial performance of the organisation. Another limitation could be the use of profitability as a measure of company performance. This is subject to criticism, as executives can manipulate profitability indicators (Attaway, 2000; Ngwenya & Khumalo, 2012). Therefore, the use of these measures in the present study could have had an effect on the results.

It is recommended that future studies focus on the specific industries within which SOEs operate. This recommendation is based on findings from, for example, Duffhues and Kabir (2008), as well as Goh and Gupta (2010), who found that the type of industry within which a company operates significantly influences the CEOs’ remuneration. In addition, the relevance of IFWE in relation to the components of CEO remuneration in SOEs was noted. However, there is a paucity of literature that either supports or disagrees with this finding. It is therefore recommended that future studies explore this relationship in more depth. As Conyon (2006) suggested, financial incentives are only one factor motivating executives. Executives are as likely to be motivated by other factors such as intrinsic factors of the job, career concerns, social norms and the like. It is therefore recommended that future studies include these factors in their study.