The effect of carbon performance on corporate financial performance in a growing economy

Fortune Ganda (Faculty of Management and Law, University of Limpopo, Polokwane, South Africa)

Social Responsibility Journal

ISSN: 1747-1117

Publication date: 1 October 2018



This study aims to examine the impact of carbon performance on firm financial performance by using Republic of South Africa CDP company data from 2014 to 2015.


The study considered 63 companies on the Republic of South Africa CDP database. Content analysis was used to extract both carbon performance data and firm financial data. The data were analysed using panel data analysis and partial derivative approaches.


The findings indicate that carbon performance produces a positive relationship with return on equity (ROE) and return on sales (ROS). Conversely, it generates a negative relationship with return on investment (ROI) and market value added (MVA). Furthermore, the study highlights that carbon performance pays and that the relationship with financial performance (ROE, ROS, ROI and MVA) deepens as the corporate growth rate increases.

Practical implications

Companies that integrate carbon performance initiatives reap substantial financial gains, and this relationship is strengthened as the company’s growth rate increases.


The research questions and data collected from Republic of South African CDP firms are original and provide important evidence on the impact of carbon performance on firm financial indicators. Furthermore, many empirical studies focus on highly industrialised countries; this study examines this issue in the emerging South African economy which has experienced rapid growth of emissions in recent years. While most previous studies on the relationship between carbon performance and firm financial performance used a single class of corporate financial measures, this study used both accounting- and market-based indicators. It also investigated how firm growth moderates the association between carbon performance and diverse financial performance measures. Finally, pressure exerted by green stakeholders since the introduction of the Johannesburg Stock Exchange’s sustainability criteria in 2004, as well as government policies, has a profound impact on the South African business context; it is hence important to examine corporate environmental management activities in the context of the association between carbon performance and firm performance.



Ganda, F. (2018), "The effect of carbon performance on corporate financial performance in a growing economy", Social Responsibility Journal, Vol. 14 No. 4, pp. 895-916.

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Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

1. Introduction

In recent years, there has been increased interest in the impact of human activities on the natural environment (Nga, 2009). Corporations are the largest emitters of carbon that is largely responsible for climate change (Ganda, 2013). Governments around the world have adopted different approaches to encourage companies to mitigate the effects of climate change by adopting methods to reduce carbon emissions. There is a growing body of research on least developed, growing and highly industrialised economies to determine the factors which motivate and/or hinder corporate carbon performance (Kumarasiri and Jubb, 2016). Furthermore, stakeholder demand for increased green consciousness means that carbon performance is a major key to long-term survival for most companies. However, this could involve increased costs during a time of global financial uncertainty (Doran and Ryan, 2012). This investigation of whether carbon performance improves firms’ financial performance is thus timely. Corporate carbon performance initiatives attract green investment and thus offer financial benefits. However, there is a paucity of empirical evidence on corporate greening behaviour in African countries. This study evaluated the impact of carbon performance on firm financial performance within the South African corporate sector for the period 2014 to 2015. Company growth was explored as a moderator of this association based on the assumption that companies are highly likely to gain financially through improved carbon performance when the firm’s growth rate is increasing and/or high.

In recent years, the South African government has tightened corporate sustainability requirements in line with global sustainability standards and national sustainable development goals. Among other measures, this is evident in the proposed carbon tax to be introduced in 2017 (SA Treasury, 2015), the 2003 White Paper on Renewable Energy which advocated for increased adoption of green energy technologies (Department of Minerals and Energy, 2003b), the Energy Efficiency Strategy (DME, 2005) and the National Strategy for Sustainable Development (NSSD) (2011-2014) that informed the NSSD 2 (2015-2020) (Department of Environmental Affairs, 2011b). Such initiatives have become imperative because of the country’s growing emission problems that are fuelled by heavy reliance on non-renewable energy sources and increasing consumer and corporate demand for energy-intensive products (Winkler and Marquand, 2009). The DEA (2013) notes that 93 per cent of South Africa’s (SA’s) energy is sourced from coal. The country’s economy is characterised by energy-intensive industrial firms, and its energy sector accounts for 82 per cent of all greenhouse gas emissions. Furthermore, reports show that SA’s emissions rose by 25 per cent from 2000 to 2010 with the energy (from 75.1 to 78.7 per cent) and waste (from 2.8 to 3.6 per cent) sectors being major contributors. Since SA is a growing economy, its mitigation approach will require all citizens to embrace pro-environmental, socially responsibility values in tandem with efforts to promote economic growth and improve people’s welfare. Thus, this article is directed to companies as South African and global citizens. By tracing the effect of carbon performance on corporate financial performance, it aims to motivate companies to become green and develop green opportunities which also enhance welfare and health improvement.

The article makes a number of contributions to the body of knowledge in this field. First, many empirical studies focus on highly industrialised countries. This study examines this issue in relation to the emerging South African economy that has experienced rapid growth of emissions in recent years. Furthermore, while previous research investigated the relationship between carbon performance and firm financial performance using a single class of corporate financial measures, this study used both accounting- and market-based indicators. It also investigated how firm growth moderates the association between carbon performance and diverse financial performance measures. Finally, pressure exerted by green stakeholders since the introduction of the Johannesburg Stock Exchange (JSE’s) sustainability criteria in 2004 (CDP, 2010), as well as government policies (Department of National Treasury, 2013), has a profound impact on the South African business context. The study’s findings will thus assist corporate decision-makers to respond positively to this environment.

The article comprises six sections. Following this introduction, Section 2 presents the study’s theoretical framework. This is followed by a literature review in Section 3 on the effects of carbon performance on firm financial performance and a discussion on the Republic of South Africa’s carbon emissions policy. Section 4 presents the empirical analysis, and the results are examined in Section 5. Section 6 presents a conclusion.

2. Theoretical framework: legitimacy, stakeholder and institutional theories

The legitimacy theory highlights the significance of social approval in promoting a firm’s survival. Legitimacy is a broad perspective in which corporate activities are identified as acceptable and compatible with society’s beliefs, values, meaning and norms. Some schools of thought add that legitimacy represents positive corporate externalities which are shared by society once that society has scrutinised corporate practices in its diverse social structures (Burritt and Schaltegger, 2010). More specifically, Deephouse and Carter (2005, p. 331) argue that legitimacy depends on “meeting and adhering to the expectations of social system’s norms, rules and meanings.… [Reputation relates to a] comparison of organisations to determine their relative standing”. As such, the firm is accepted by society and continues to operate when the public is convinced that their interests have been addressed. Thus, companies implement carbon performance practices to be responsible and accountable to society and acquire a desirable corporate reputation. According to Lindblom (1994), the four corporate legitimation strategies are social reporting to communicate the company’s efforts to address stakeholder interests, public education and information dissemination on relevant concerns, symbolic efforts to achieve legitimacy without altering performance and/or meeting societal demands and incorporating popular perspectives in conformance with business operations. Burritt and Schaltegger (2010) and Deephouse and Carter (2005), among other scholars, used this theory to illustrate how carbon performance influences corporate financial performance.

The stakeholder theory posits that companies are responsive to the demands of their internal and external partners in adopting corporate policy and implementing strategic decisions. Freeman (1984, p. 46) defines stakeholders as “any group or individual that can affect or be affected by the realisation of a company’s objectives”. Thus, the theory postulates that a company’s ability to operate rests on its strategic inclusion of stakeholder interests in decision-making. In recent times, stakeholder demands have reflected growing global concern relating to shifts in weather conditions, increased natural disasters, rising sea and oceanic levels and increased greenhouse gas emissions. Companies are morally obligated to adopt effective carbon performance initiatives to reduce environmental damage and climate change. Notable stakeholders that play major roles in influencing corporate carbon performance include green government, through stringent carbon taxes alongside green legislation; green consumers, by way of boycotts and high preference for green products regardless of price; green employees that prefer working in high carbon performing firms; and green investors who give preference to green portfolios and independent environmental interest groups. Wood (1991) highlights that stakeholders play three roles in relation to corporate sustainability. They are the source of expectations in relation to what is considered acceptable and unacceptable corporate practices; they experience the impacts of corporate conduct (both actions and output), and stakeholders assess how the company has addressed societal expectations, as well as how firm initiatives have affected all internal and external partners.

The institutional theory traces the linkages between a firm and society within the organisational dimension of economic governance (Brammer et al., 2012). Scott (1995, p. 33) defines “Institutions [as consisting] of cognitive, normative, and regulative structures and activities that provide stability and meaning to social behaviour. Institutions are transported by various carriers – cultures, structures and routines – and they operate at multiple levels of jurisdiction”. The theory assumes that companies are affected by broader social frameworks such as public legislation, private regulations and non-governmental organisations that monitor their business practices. It follows that these social structures influence both business initiatives and procedures. In relation to carbon performance, the institutional theory is not founded upon organisational policy and strategic direction but broader societal interests (Hahn et al., 2010). A company’s ability to address institutional pressure will also depend on its capacity to accommodate incompatible organisational demands by mitigating the effects of compliance (through bargaining with regulatory bodies) and/or changing expectations (through influencing its main partners). In doing so, it draws on its specific attributes. The theory thus focuses on the factors that transform society along with organisational frameworks, routines, schemas, norms, values and rules that affect the behaviour of a firm’s stakeholders. In their studies, Brammer et al. (2012) and Hahn et al. (2010) used this theory to demonstrate how sustainability concerns affect firm financial performance.

These three theories are not independent of one another, but overlap in demonstrating a specific social event. The stakeholder theory in tandem with the institutional theory is imperative in describing how corporate legitimacy can be achieved from a societal perspective. From an organisational perspective, the interconnectedness between the stakeholder and institutional theories (the effect of investor, employee-management and consumer decisions) is instrumental in shaping legitimacy which will be the outcome of corporate activities and decisions through major internal and external players’ decisions. The stakeholder theory shows how the company responds to internal and external partners’ interests to survive, whilst the institutional theory stresses corporate consciousness in embracing socially acceptable values, norms and meanings. Thus, stakeholders, alongside institutional mechanisms, are able to create strong foundations which sustain and consider societal interests in the short- and long-run. To understand environmental influences on a company, I integrate the legitimacy, stakeholder and institutional perspectives to generate a framework which distinguishes the macro- and micro-factors that impact carbon performance initiatives in corporate contexts (Figure 1).

From Figure 1, the macro-setting refers to those external groups who exert pressure or are affected by the company’s carbon performance activity interests. From the stakeholder theory, these are, namely, national green laws, green industrial regulations and green interest’s group’s forces. In relation to the legitimacy theory, the macro-setting groups may have influence on the company’s carbon performance activities, but they do not control important company resources. On the other hand, micro-setting are internal groups comprising domestic interest groups that have connections with the firm and are empowered to use power over decisions on carbon performance. From the stakeholder theory these are, namely, green consumer interests, green employee demands and green investor forces. To conclude through deploying the institutional theory, the macro-setting and the micro-setting represent those institutional pillars and/or champions who demonstrate how their forces on firms have the ability to condition each respective company decision in the matter of carbon performance.

This paper’s inclusion of variables, namely, return on equity (ROE), return on investment (ROI), return on sales (ROS) and market value added (MVA), in the investigation of the carbon performance-firm financial performance within the South African context is justified in the legitimacy, stakeholder and institutional theoretical framework (as evidenced in Figure 1) on the basis of inherent features of these variables. First, MVA indicates the financial value derived when the difference involving market value of the firm and the amount of capital contributed by company investors has been computed. In cases where market value is lower than amount of invested capital then company managers have failed to add value with equity which was made available to them by company investors. ROS is the ratio used to obtain the proportion of profits acquired from sales. Hence, ROS is imperative to ascertain the capability of the company’s managers to effectively obtain financial gains from a particular level of sales. ROE accounts for corporate profitability through indicating the amount of profit produced with funds invested by corporate shareholders. In this vein, is the net income generated as a percentage of shareholders equity, thereby indicating how a firm uses investments to obtain earnings growth. ROI measures investment efficiency, as it considers the amount of investment return relative to the costs of that investment. ROI is normally derived by dividing the financial benefit of an investment with cost of the investment. The attributes of these financial variables (ROE, ROS, ROI and MVA) demonstrate that they consider various stakeholder interests in the company who possess diverse influences and also control which conditions the company to implement decisions which follow and/or not follow a carbon performance orientation. Thus this paper draws from the stakeholder, legitimacy and institutional theories through demonstrating which company partners (internal and external) possess how much influence and control along with how they fundamentally support the company to gain and sustain superior carbon performance. In the same vein, green demands from the company’s macro and micro-setting exert forces on companies to respond through carbon performance which ultimately affects company’s financial performance (ROE, ROS, ROI and MVA). This will eventually make it easier and/or rather difficult for a company to realise its goal of optimising company value by way of positive financial performance, and vice versa.

3. Carbon performance and firm financial performance

Studies on carbon performance and corporate financial performance have produced varied results. While some indicate mixed associations, others demonstrate positive and/or negative relationships.

3.1 Carbon performance and firm financial performance: mixed relationship

A recent study by Luo and Tang (2014) found mixed associations between carbon performance and firm performance. The study analysed the effects of carbon tax on firms’ financial performance using 48 diversified Australian firms from the Carbon Disclosure Project. Cross-sectional analysis of 336 firm observations revealed that corporate direct emissions (Scope 1) were significantly related to abnormal firm returns, but indirect emissions (Scope 2) did not have a significant association. The study found that most companies had poor carbon policies and that investors are highly likely to penalise companies which directly emit large amounts of carbon. Saka and Oshika’s (2014) study also obtained mixed results. These authors investigated the effect of carbon emissions and reported on firm value by considering 1,094 observations on Japanese Carbon Disclosure Project companies from 2006 to 2008. Using the Ohlson model and multiple regression analysis, the results indicate that firm carbon emissions develop a negative association with corporate market value of equity, but the reporting of carbon management had a positive relationship. The authors urged Japanese firms to minimise carbon emissions and to improve reporting of such environmental information to enhance their corporate green image.

Younis et al. (2016) investigated the effect of adopting green supply chains on firm performance by scrutinising 971 ISO14001-certified companies and non-certified UAE manufacturing companies. Using factor analysis and multiple-regression approaches the study highlighted that environmental performance, green buying and environmental collaborations had a significant effect on corporate operational performance. However, it found that only green buying had a positive relationship with firm economic performance and reverse logistics generated a positive association with firm social performance. Furthermore, UAE companies were of the view that green supply chains enhance a firm’s image, promote employee job satisfaction and improve employees’ health and safety. Nga (2009) evaluated the impact of ISO 14000 on the corporate performance of 49 ISO integrating and 32 non-ISO integrating Malaysian companies. Using the t-test, the study showed that ISO certification has positive effects on ROE but there was no evidence of an improvement in sales and capitalisation. Besides increased business expenses, the study concludes that ignoring ecological costs results in increased intergenerational poverty and equity. Singh et al. (2016) examined the effect of maximising environmental spending on corporate economic performance among a sample of 120 companies from 30 nations. By using PROCESS software, the results indicate that spending on pollution control has a negative relationship with firm economic performance. On the other hand, product stewardship had a positive association. The study also found that corporate green capabilities are vital in leveraging resources.

3.2 Carbon performance and firm financial performance: positive relationship

Another set of studies illustrates a positive relationship between carbon performance and firm financial performance. Khojastehpour and Johns (2014) explored the impact of corporate environmental responsibilities on firm image and profitability by conducting an extensive review of previous studies. They found that environmental responsibility had a positive association with both firm image and profitability. The study concludes that companies that integrate green practices enhance their reputation and improve profitability as consumers reward them through green buying. Yu and Ting (2012) investigated the relationship between corporate financial development and environmental sustainability (Carbon Disclosure Leadership Index, direct and indirect emissions, and carbon intensity) among 369 FTSE Global 500 companies from 31 countries. The study found that firms are prepared to engage in carbon reporting and greening in countries that have sophisticated financial practices and offer investors effective protection.

Kumarasiri and Jubb (2016) appraised the links between emissions reduction and the management accounting techniques of 18 listed Australian companies from 2012 to 2013. They found that financial implications, rather than mere disclosure, were the prime reason companies incorporated emissions reduction issues in management accounting approaches. The study noted that under-utilisation of management accounting approaches results in minimal carbon emissions reduction. Research in Europe also indicates positive relationships. For example, Doran and Ryan (2012) investigated the determinants of corporate eco-innovation among 2,181 Irish companies from 2006 to 2008. The study revealed that eco-innovation was more significant in determining firm performance than non-eco-innovation. It also highlighted that since legislation stimulates eco-innovation, there is no trade-off between eco-innovation and increased financial gain.

Cajias and Piazolo (2013) surveyed the impact of energy use on firm financial performance in the German construction sector. The research showed that energy-efficient buildings generate increased financial gains of up to 3.15 per cent as well as 0.76e/m2 higher rent compared to non-energy-efficient buildings. The study concluded that energy efficiency is an important influence on investment decisions (willingness to buy, reduced emissions, quality issues, health and social welfare and reduced depreciation) as well as the performance of investment portfolios. De Klerk et al. (2015) analysed the impact of social responsibility reporting on the corporate share prices of 100 UK firms from 2007 to 2008. The results show that high levels of social responsibility disclosure (through broadened environmental practice) are related to increased firm share price. The study concludes that social responsibility disclosure provides significant information to shareholders, which surpasses firm financial accounting information, as such disclosure is associated with share prices. Mishra and Suar (2013) investigated whether strong orientation towards natural environmental issues affects corporate policy on the natural environment. Their survey included 150 listed and non-listed Indian manufacturing companies. The results indicate that high levels of corporate attention to natural environmental concerns results in increased firm profitability, as well as high corporate environmental performance. High green performance and increased financial status boost shareholders’ confidence.

3.3 Carbon performance and firm financial performance: negative relationship

Some schools of thought argue that carbon performance does not achieve improved corporate profitability. García-Sánchez and Prado-Lorenzo (2012) evaluated the emission initiatives and corporate financial performance of 282 USA S&P 500 Index companies in 2007. Emissions management practices generated a negative association with corporate financial performance. This was evident in increased investment assets, reduced profits as a result of annual asset depreciation and the stock market that negatively valued companies’ green performance. Lee et al. (2013) explored whether high and low sustainability stocks generated varied performance among US companies from 1998 to 2007. The study found that there was no significant variance in relation to the risk-adjusted performance of both high and low sustainability stocks. Furthermore, there were no variations in relation to company book-to-market factors, size and portfolio formation. The authors concluded that mainstream investors are generally neither interested in companies’ ethical initiatives nor do they consider whether the firm integrates sustainability principles. Thus, companies which incorporate sustainability principles encounter the same problems as those that do not invest in social, environmental and governance issues.

Newell and Lee (2012) investigated whether the social, environmental and governance dimensions of corporate social responsibility affected 16 real estate investment trusts (REITs) in Australia (A-REITs) from 2005 to 2010. The findings show that social, environmental and governance practices were not significant in explaining A-REITs’ performance when compared to financial measures (gearing, beta, size and book-to-market value). This is attributed to the fact that A-REIT investors have not yet allocated a separate price to each of these sustainability dimensions; there is hence less focus on such practices in making investment decisions. Menzel et al. (2010) examined whether firms generate high financial returns through green manufacturing using a sample of nine automotive and eight pharmaceutical companies in Europe. The results demonstrate that there is no meaningful association between green manufacturing and firm financial performance. The authors note that companies show evidence of discontinued corporate green operations. The fact that firms in different sectors use diverse resources and that the study considered a short period (four years) had an impact on its results.

In conclusion, it is apparent that there are different perspectives on the effect of sustainability practices on corporate financial performance. Given increased interest in carbon performance rating, the following hypothesis is developed:


A firm’s carbon performance rating is positively associated with financial performance.

3.4 Moderating impacts of firm growth

Studies have found that company growth can moderate the influence of carbon performance on firm financial performance. For example, such growth possibly accelerates green technology maturation, thereby mitigating the green risks that are intrinsic in long-term technologies (Green, 2006). Therefore, while companies which invest in carbon reduction technologies are perceived as adding risk (owing to being new and the fact that viability is highly uncertain), they also have greater prospects of high financial returns when the firm is experiencing high growth. In contrast, companies that do not invest in new technologies experience low financial gains. Similarly, carbon reduction technologies are unlikely to result in high profits if the firm is experiencing low growth and/or is declining. Furthermore, high growth firms are likely to adopt strong, organic and highly integrated operating systems (Ajagbe and Ismail, 2014) to comply with environmental laws. This motivates the firm to introduce further carbon reduction technologies which improve firm carbon performance and ultimately profits. On the other hand, firms with low growth rates normally have loosely designed institutional frameworks that may be more mature, inflexible and bureaucratic and normally produce standardised commodities (Feeser and Willard, 1990). Such firms do not put much emphasis on improving their carbon performance rankings and thus do not improve their financial returns. Furthermore, high-growth firms attract new players who introduce current ideas (Hillbrand, 2006), enabling the company to integrate more green technologies and policies to protect its reputation and sustain high profitability. A green corporate image might not be as important for a firm experiencing low growth. Some schools of thought have also argued that high-growth companies are normally young industries that take greater risks to remain competitive (Bos and Stam, 2013) and are hence more likely to incorporate superior green ideas, innovation and strategies that result in increased carbon performance than low-growth firms that are viewed as old and no longer green proactive.

From the above discussion, it is thus apparent that a firm’s growth rate moderates the association between carbon performance and firm financial performance (Russo and Fouts, 1997). Therefore, the following hypothesis is suggested:


The level of firm growth will moderate the association between carbon performance and firms’ financial performance; the higher the company growth rate, the higher the positive effect of carbon performance on corporate financial performance.

3.5 Carbon emissions policy in South Africa

As highlighted in the Carbon Tax Policy Paper of the Republic of South Africa (Department of National Treasury, 2013), the carbon emissions policy emphasises the need to reduce greenhouse gas emissions and to facilitate the transition to a green economy. Total greenhouse gas emissions amounted to 380, 461 and 547 million tonnes, respectively, in 1994, 2000 and 2010 (Department of National Treasury, 2013). The energy sector, which includes electricity production, the petroleum refining industry and the transport sector contributed more than 80 per cent of these emissions. Other high-emitting sectors are agriculture and industry that contributed 8.4 and 7 per cent, respectively. The National Climate Change Response White Paper (Department of Environmental Affairs, 2011a) provided for mandatory disclosure of carbon emissions by all industries and companies which emit more than 100,000 tonnes of greenhouse gases per year or use electricity which results in more than 100,000 tonnes of emissions. More recently, SA proposed the introduction of a carbon tax. This will involve a direct levy on the quantity of a company’s emissions. It primarily affects Scope 1 emissions generated from fuel combustion and gasification (Department of National Treasury, 2013). Indirect emissions (Scope 2) produced from a company’s application of purchased heat, steam and/or electricity will be managed by complementary mechanisms along with inducements. The country has also proposed energy efficiency tax incentives. The South African government supports the production of fossil fuels through green energy technologies by means of the renewable energy independent power producer (REIPP) programme. The energy efficiency and demand-side management (EEDSM) programme aims to support energy efficiency by supplying renewable energy systems to business entities. In the same vein, excise duties on liquid energy sources (for example, diesel and petrol) along with electricity produced from fossil fuels are part the Republic’s efforts to reduce emissions. A tax rebate system for carbon sequestration initiatives such as Carbon Capture and Storage (CCS) (Department of National Treasury, 2013) is planned. The Integrated National Electrification Programme (INEP) was adopted to provide clean, safe and reliable energy to academic institutions, clinics and households. Alternative and cleaner energy sources, as well as energy-efficient approaches to transport, have also been supported in the transport industry. National policies such as the National Climate Change Response White Paper, which seeks to stabilise carbon emissions and enhance long-run transition to a climate-resilient, green society and economy (Department of Environmental Affairs, 2011a); the Industrial Policy Action Plan (IPAP) that promotes the greening of SA’s industrial sector (Department of Trade and Industry, 2010); and the New Growth Plan that establishes vital measures for green economic development and green employment creation (Economic Development Department, 2010) are the country’s major carbon emissions control strategies. The Integrated Resource Plan (IRP) for electricity along with White Paper on Renewable Energy Policy, which promotes broader integration of green technologies (Department of Energy, 2011; Department of Minerals and Energy, 2003b); the Energy Efficiency Strategy that supports cost-effective procedures to address energy demands using environmentally friendly techniques; and the IRP, which embraces green strategies and growth plans in relation to energy provision and security (Department of Minerals and Energy, 2003a) are also critical developments in SA’s carbon emissions management policy.

4. Empirical analysis

4.1 Sample

The group of companies considered for the study comprised firms assigned carbon performance ratings through CDP South Africa. This set of the top 100 firms on the JSE by market capitalisation cuts across diverse industrial categories. The CDP requests information on climate change risks and prospects from these companies on behalf of 822 organisational investors who have assets valued at more than $US95tn (CDP South Africa, 2015). Hence, the CDP assists companies to control carbon emissions and mitigate climate change and/or green risks. For their part, investors are able to assess the green risks linked to their investments. The study used company data from 2014 to 2015 using carbon performance ratings (CP ratings). The final sample was 63 companies for both years. The remaining 37 companies were excluded because of a lack of CP ratings and/or financial data. The sample consisted of energy (two companies), industrial (five companies), materials (16 companies), health care/pharmaceuticals (one company) and materials (16 firms). Telecommunication (three firms), financial (18 firms), consumer staples (12 firms), health care (distribution and service) (two firms) and consumer discretionary (four firms) were also included.

4.2 Independent variable

The independent variable was CP rating that were determined according to CDP South Africa’s specifications (CDP South Africa, 2015). CDP South Africa (2015, p. 2) states that, carbon “performance is rated in bands from A to E, with an A being the highest band”. In considering CDP South Africa ratings which are in symbolic form, the ratings were converted to numerical form for easier analysis. As such, 1 represents firms which obtained performance rating A and B (highest performance) by CDP South Africa; 2 represents medium performance (shown by the median band C); and 3 indicates the lowest performance level (ratings D and E). Studies on corporate sustainability that have adopted this rating format include Dagiliene (2013) and Kwon et al. (2016). In addition, there is no lag period between the carbon performance of a particular company and its financial performance; CDP South Africa (2015, p. 2) confirms that “the performance score assesses the level of action, as reported by the company, on climate change mitigation, adaptation and transparency” and that “The questionnaire is sent to the top 100 companies on the JSE by market capitalisation as at the beginning of January […]” Hence, the CDP survey is conducted on an annual basis. In this case, CP ratings were directly retrieved from CDP South Africa’s database.

4.3 Dependent variables

The dependent variables were a mix of accounting-based and market-based financial measures. The accounting-based indicators were ROE, ROI and ROS, whilst MVA represents the marked-based performance measure. ROE indicates company profitability by showing the amount of profit the firm produced in relation to stockholders’ investments. ROI is a financial indicator used to compare firm profitability and/or the efficiency of diversified corporate investments. ROS is a ratio used to analyse firm operational efficiency, i.e. profit generated per South African rand of sales. Finally, MVA indicates the market valuation of the company, less invested capital. Data on ROE, ROI, ROS and MVA were collected from the INET BFA database.

4.4 Control variables

The control variables are Firm Size, Capital Intensity, Leverage and Growth. These data were gathered from the INET BFA database. Capital Intensity is expressed as the ratio of firm assets to sales. Firm Size is defined as the natural logarithm of net sales volume (Iwata and Okada, 2011). Sales fluctuate rapidly and differ significantly with the size of company; hence, the natural logarithm is adopted. Leverage is the ratio of total debts to total assets, implying that it indicates how much debt was used to finance assets. Growth indicates the annual growth rate of sales. An interaction term formed by multiplying CP rating and Growth was added. The interaction term is commonly highly correlated to the individual variables considered, generating multicollinearity alongside unstable regression values. The approach proposed by Aiken and West (1991) was adopted to mitigate this challenge. This involves de-meaning and/or centring the variables involved through subtracting the mean of each variable from its observed values. It should be noted that values for variables that do not have the interaction term do not require altering. It follows that multiplication of the demeaned factors (CP rating and Growth) reflects minute correlation with the original terms when it is applied thereafter.

4.5 Econometric specifications

Multiple linear regression analysis is widely applied in the literature to investigate the relationship between corporate carbon performance and its financial value (Younis et al., 2016; Singh et al., 2016; Cajias and Piazolo, 2013) and was used to analyse the data in this study. As the data were for a two-year period (2014-2015), a panel data regression approach involving the integration of cross-sectional and time series data was used. Thus, the basic specification from an ordinary least squares regression approach is:

(1) FinancialPerformancei,t=β0+β1(CarbonPerformanceratingi,t)+β2(Growthi,t)+β3(FirmSizei,t)+β4(Leveragei,t)+β5(CapitalIntensityi,t)+β6(Carbonperformancerating×Growthi,t)+(εi,t)
where, β0 is the intercept; i = 1, 2,…,N pertains to the cross-section unit; t = 1, 2,…,T refers to the period; βk is the gradient parameter; ɛi,t is the random error and Firm Financial Performancei,t = ROE, ROI, ROS and MVA.

Previous studies indicated that poor carbon performance that inevitably increases environmental degradation precedes poor corporate financial practice (King and Lenox, 2001). In this context, ordinary least squares approach was vital to establish a linear association involving carbon performance and the financial performance indicators. For example, MVA provides insights into the future financial status of the company. Because of the incorporation of cross-sectional and time series data, the ordinary least squares regression approach (which is an approach for determining the estimates of a particular mathematical model through reducing the square of the difference involving the actual data together with the predicated framework) was not adequate for the analysis. Thus, the panel data regression method was a relevant technique (Elsayed and Paton, 2005). The two most commonly applied estimation techniques in panel data regression are the fixed effects model (FEM) and the random effects model (REM), as they comprehensively account for any possible unobserved heterogeneity in the panel data set (Neumayer, 2003).

In this context, the FEM is based on the assumption that the slope coefficients of the explanatory and/or independent variables are the same for all the companies. As such, the intercept in the regression framework is permitted to vary among individual companies in light of the fact that each individualised and/or cross-sectional unit may have unique and particular attributes. Dummy factors can be used to consider the varying intercepts. As the FEM permits for group-specific constant term, unaccounted variances involving companies are considered (Fiala, 2008). For instance, issues such as corporate culture, strategic policy, market power, competitive advantage and geographic position, among other factors that are different between companies, are considered. Of importance is that FEM requires that explanatory variable changes (instead of their baseline level) be linked with dependent variable changes. The major disadvantages of the FEM compared to REM is that variables that have scant time-variation are ineffectively determined and the coefficients of time-invariant factors are not computed (Neumayer, 2003). As such, REM is more efficient, as the model uses the cross-sectional (between) along with time-series (within) variation of data. The REM is also known as the error component model. It assumes that the intercept of an individualised and/or cross-sectional unit indicates a random extraction from the broader population with a constant mean estimated value. In this case, the individualised intercept is indicated as a deviation from the identified constant mean estimated value. The Hausman test and Breusch–Pagan test are model specification tests which can be applied to decide between FEM and REM and/or the pooled model (Hausman, 1978). The pooled OLS, FEM and FEM models were used to control for company-specific effects.

5. Results

This section presents the study’s main findings (Table I).

Table I presents a summarised descriptive evaluation. The mean of MVA is greater than that of ROE, ROS and ROI. In relation to MVA, the typical measure which indicates the variance involving firm market value and capital additions of investor groups is 3.3847. The representative measure of net income generated for each rand of sales is 0.0671. The value of return on a business investment relative to investment costs is 0.0935. The typical measure of profits generated by a business in relation to the book value of a shareholder’s equity is 0.1365. The carbon performance grade of the companies under study over the considered period is estimated at 1.6905. The means of the control variables, namely, Growth, Firm Size, Leverage and Capital Intensity are 0.0606, 16.9673, 0.5762 and 1.2105, respectively. The maximum value of 1.2444 for Leverage possibly indicates that some companies in the sample are typical capital asset-intensive companies (e.g. heavy manufacturing) which rely more on borrowed funds to acquire assets. In this regard, debt is cheaper in that particular company’s capital structure. CP rating is a categorical variable; a minimum value of 1 indicates high carbon performance, with 3 being the lowest carbon performance value. The mean of the demeaned interaction variable CP Rating × Growth is 0.0143. Its maximum value is 0.4886 and its minimum value is −0.3653. Skewness is a measure of symmetry or more specifically the absence of symmetry. In this case, data distribution should look the same on the right and the left in relation to the central location point. The evidence indicates that the data for ROE, ROI, ROS, Firm Size and Capital Intensity are skewed to the left, implying that the left tail is long compared to the right tail. Conversely, the data for MVA, CP rating, Growth, Leverage and CP Rating × Growth is skewed to the right, implying that the right tail is long relative to the left tail. Kurtosis informs the researcher on the amount of data in the tails and offers perspectives that explain how “peaked” the data distribution is. All data sets for the variables have positive kurtosis, which means that the data are heavily tailed. Thus, there is evidence of non-normality of data which is confirmed by the Jarque–Bera test (an approach based on sample kurtosis as well as sample skewness measurements) for normality.

Table II demonstrates that the CP rating develops a positive direct relationship with ROE, ROS and ROI, but its association with MVA is negative. Thus, the direct correlation analysis (in the case of ROE, ROI and ROS but not MVA) generally indicates that greening pays; that is, an increase in carbon performance generates increased corporate profitability. Nonetheless, it is important to run further tests which include the introduction of control variables to determine causal association and improve the robustness of the test findings. Of special interest is the trend of correlations involving the interaction term and its component variables. As I constructed the interaction variable used in the correlations along with regressions through multiplying the demeaned firm growth by CP rating variables, the correlations are satisfactory, as both are positive. Furthermore, the interaction term (CP rating × Growth) generates a positive association of 0.1101 and 0.1215 with CP rating and Growth, respectively. If the interaction term had not been demeaned, the correlations would have been 0.3303 and 0.8786 for CP rating and Growth, respectively. Therefore, the objective of producing an appropriate analysis which is free of multicollinearity was achieved. This interaction term has a positive association with ROE, ROI and ROS, but it is negatively related to MVA. Except for MVA and Firm Size, Growth has positive relationships with all the remaining variables. Except for ROS, MVA, Growth, Leverage and CP rating × Growth, Firm Size illustrates positive associations with the remaining variables. Leverage and Capital Intensity also indicate mixed relationships (some positive and negative direct associations) with other variables.

Table III shows that for all the models (pooled, REM and FEM), CP rating has positive relationships with ROE for the companies under study. A 1 per cent increase in carbon performance increases ROE by 0.0132537 per cent, 0.0038494 and 0.0040216 per cent in the pooled, REM and FEM models, respectively. This finding indicates that long-term investors in South African corporate settings are making green demands for companies to introduce expanded carbon performance technologies and strategy. These results concur with those of Khojastehpour and Johns (2014), Yu and Ting (2012) and Kumarasiri and Jubb (2016) but conflict with García-Sánchez and Prado-Lorenzo (2012), Lee et al. (2013) and Newell and Lee’s (2012) findings. The Hausman and Breusch–Pagan tests demonstrate that the REM is more appropriate. Hence, in terms of the REM model, CP Rating × Growth; Growth; Leverage and Firm Size have a positive connection with corporate ROE, but Capital Intensity demonstrates a negative link. As there is overwhelming evidence that higher carbon performance results in higher financial performance, further analysis is conducted using ROE (on the REM model), as this variable shows greater influence of corporate investors and/or stockholders on corporate policy and performance. Using partial derivatives, the following expression is generated:

(2) δ(ROE)/δ(Carbon performance rating)=0.0038494 +(0.0599519 × demeaned firm growth)

Equating expression (2) to 0, the growth rate will be equal to −0.064208. This implies that increasing the carbon performance of clean firms improved firm ROE when the growth rate was greater than −0.064208 for the firms under study. The number of firms above this threshold is 55 and 47 in 2014 and 2015, respectively. This outcome shows that greening pays and that such an association improves as the firm’s growth rate increases. Thus, H2 is confirmed.

Table IV demonstrates that the CP rating develops a positive association with ROI only in the pooled model, and the relationship is negative in the REM and FEM models. A percentage increase in carbon performance increases ROI by 0.0196158 per cent. This finding is consistent with Yu and Ting’s (2012) findings but contradicts those of Newell and Lee (2012). On the other hand, a 1 per cent rise in carbon performance decreases ROI by 0.0008059 and 0.0018694 per cent in the REM and FEM models, respectively. This finding agrees with Newell and Lee (2012) and Menzel et al. (2010) but disagrees with Mishra and Suar (2013) and De Klerk et al. (2015). The Hausman and Breusch–Pagan tests confirm that the REM model is the ideal framework for the ROI analysis. From the REM model, CP Rating × Growth; Growth; Leverage and Capital Intensity indicate positive relationships with firm ROI but Firm Size does not. As the REM model confirms that an increase in carbon performance is incompatible with high corporate ROI, further scrutiny using the partial derivatives is imperative to support or disregard the findings. Using the REM model in the analysis, the following expression is ascertained:

(3) δ(ROE)/δ(Carbon performance rating) =0.0008059 +(0.0395772 × demeaned firm growth)

Equating expression (3) to 0, the growth rate will be equal to −0.020363. Therefore, improving the carbon performance of environmentally unfriendly companies resulted in high firm ROI when the growth rate was higher than −0.020363. The total number of firms which are above this threshold is 50 and 47 companies in 2014 and 2015, respectively. This finding concurs with the ROE outcomes that showed that greening generates high profits by supporting the notion that the higher the company growth rate, the higher the positive effect of carbon performance on corporate financial performance. Therefore, H2 is accepted.

Table V illustrates that the CP rating established positive relationships with corporate ROS in all three models (pooled, REM and FEM). In this case, a percentage increase in carbon performance results in a 0.0597626, 0.0202103 and 0.0126457 per cent rise in ROS for the pooled, REM and FEM models, respectively. Thus, an increase in carbon performance produces increased company financial performance. This suggests that most corporate consumers and/or clients of the South African companies under study are environmentally conscious and demand that companies integrate carbon emission reduction initiatives alongside technologies. It thus seems that there is high visibility of CDP firms within South African corporate contexts. These results are congruent with Cajias and Piazolo (2013) and Mishra and Suar (2013) but conflict with Menzel et al. (2010) and Lee et al. (2013). The Hausman test and the Breusch–Pagan test support the REM model more than the FEM and pooled models, respectively, in the ROS analysis. From the REM model, CP Rating × Growth and Leverage generate a negative association with company ROS and Growth and Capital Intensity and Firm Size indicate positive relationships. To prove H2 for these firms, I also used the REM model and considered the partial derivative of the regression in relation to the carbon performance variable, generating the following:

(4) δ(ROE)/δ(Carbon performance rating) =0.0202103 +(0.1216506 × demeaned firm growth)

Equating expression (4) to 0, the growth rate will be equal to −0.166134. It follows that for the companies under study, improving carbon performance leads to high ROS if the firm growth rate is above −0.166134. In total, 61 and 58 companies in 2014 and 2015, respectively, are above the demeaned growth rate of −0.166134. Thus, H2 is accepted for these firms.

Table VI illustrates that carbon performance has a negative association with the dependent variable, MVA in all the models. This implies that greening produces decreased market value added among the companies under study. The result suggests that the South African market does not have high regard for carbon performance issues as long as the relevant regulatory requirements are complied with (Ganda, 2017). In this regard, a 1 per cent increase in carbon performance lowers corporate MVA by −0.9318344, 0.7706009 and −0.7667178 per cent in the pooled, REM and FEM models, respectively. These results support Menzel et al.’s (2010) findings, but contradict those of Mishra and Suar (2013). The REM model was determined to be the most suitable model after the Hausman and Breusch–Pagan tests. With reference to the REM model, CP Rating × Growth, Leverage, Growth, Capital Intensity and Firm Size established negative relationships with firm MVA. To prove H2 for the firms under study, I also used the REM model to consider the partial derivative of the regression in relation to the carbon performance variable, generating the following:

(5) δ(ROE)/δ(Carbon performance rating) =0.7706009 +(1.774245 × demeaned firm growth)

Equating expression (5) to 0, the growth rate will be equal to −0.43433. It follows that for these companies, improving carbon performance leads to high MVA if the firm growth rate is above −0.43433. All 63 companies in 2014 and 2015 are above the demeaned growth rate of −0.43433. Thus, H2 is accepted for these firms.

5.1 Analysis of overall results

This article investigated if the company CP rating is positively associated with financial performance using pooled OLS, FEM and REM models. The firm financial performance measures are ROE, ROI, ROS and MVA. A summary of the results is presented in Table VII.

The analysis shows that two financial accounting-based measures, namely, ROE and ROS, outweigh the other measure, ROI, in confirming that the CP rating has a positive relationship with firm financial performance among South African CDP firms. On the other hand, MVA, which is a long-run financial performance measure that demonstrates corporate investors’ expectations about the company’s future financial performance, has a negative relationship with carbon performance.

The article also analysed whether the company growth rate moderates the link between carbon performance and firm financial performance. The summarised findings are presented below.

The results in Table VIII show that, over the two-year period, the financial performance indicators for more than 70 per cent of the companies were above the estimated growth rate computed by partial derivative techniques in the REM regression model. Hence, the author concurs with Russo and Fouts (1997) that companies that adopt carbon performance practices generate improved financial gains and that this relationship is strengthened as the company growth rate increases.

5.2 The link between the results and the theories presented

The mixed results presented in this article suggest that corporate carbon performance is influenced by the organisational context in which a company operates, thereby confirming the legitimacy, stakeholder and institutional theories. The market-based measure MVA generates a negative association with financial performance but most accounting-based measures (ROE and ROS but not ROI) produce positive relationships. These findings illustrate that carbon performance is not simply implemented at a company’s own discretion, but it is a function of organisational contexts and that the effect varies in accordance with the distinct characteristics of the financial performance indicator under scrutiny. It follows that management needs to embrace carbon performance to satisfy societal demands (such as JSE regulations, the King III and IV ethical codes, CDP regulations and the interests of green consumers, employees and suppliers), as well as achieve the company’s internal goals and objectives. The findings show that the nature and extent of corporate carbon performance are strongly influenced by external interests. In improving their carbon performance, companies are able to improve their relationships with the wide range of stakeholders that inhabit their environment. The three theories’ (legitimacy, stakeholder and institutional) perspectives in relation to carbon performance are supported by Bowen (1953, p. 6) who describes socially responsible practice as “the set of moral and personal obligations that the employer must follow, considering the exercise of policies, decisions or courses of action in terms of objectives and values desired by society”. Given the study’s mixed findings, management should examine the sources of legitimacy in relation to their institutional green stakeholders. They should take these stakeholders’ views into account, as well as determine the linkages and deviations in the different markets the company operates in, so as to determine the required level of carbon performance.

5.3 Implications for policymakers

This article supports the view that in most cases improved carbon performance can occur in tandem with sustained or even improved financial performance. In light of this, the South African government could adopt further measures to improve current policies in relation to the business sector. First, there is need to introduce carbon budgets at industrial level so as to improve carbon performance, as some industries have very high levels of carbon emissions. Mandatory disclosure of statistics in relation to the various types of greenhouse gases in the business sector is also imperative to identify appropriate ways to improve carbon performance. This is necessary because some carbon performance practices effectively reduce certain types of greenhouse gases but not others. The government also needs to commit financial resources to develop advanced low-carbon technologies. Financial institutions that provide capital to firms should be encouraged to take the environmental impact of a firm’s operations into account when appraising their project proposals. Finally, society at large should participate in the formulation of carbon performance policy. This inclusive approach is essential to overcome public distrust of government’s position in relation to business operations.

5.4 Implications for business

The continued growth of carbon emissions poses a threat to businesses’ very existence. The effects of climate change are becoming increasingly apparent and include floods, droughts, tsunamis, hurricanes, tropical diseases and water shortages, as well as increased costs (green investment risks, carbon taxes, the cost of green technologies, high insurance costs, green image risks and business disruptions because of weather effects). There is, thus, a need to adopt effective techniques that improve carbon performance in all production processes to reduce harmful environmental impacts and ensure business survival. Examples include green employee awareness programmes, improved resource efficiency, green energy and lighting, recycling, waste management and carbon capture and storage. In managing the monetary risks associated with carbon performance, companies should consider the business environment, including regulatory and market risks, as well as firm analysis and/or forecasts. Efficient employment of corporate capabilities is vital to promote growth.

5.5 Implications for welfare and health improvement

The article demonstrated that carbon performance activities produce improved financial returns and this relationship is strengthened as the company growth rate increases. This suggests that carbon performance is central in improving welfare and health of people and all society inhabitants. In general, carbon performance initiatives are more widely adopted in highly industrialised countries. However, low-income markets offer significant growth potential in terms of carbon performance initiatives that can sustain good health and improve livelihoods. For example, biomass stoves and solar energy have the potential to considerably improve the health of women in low-income markets. Innovative technologies that promote efficient water consumption are ideal in water-stressed areas and both reduce emissions and result in energy savings. Biomass applications produce energy from waste (thus improving waste management) and create green jobs. Reforestation and hydro-schemes improve the standard of living of the general population by improving air quality and promoting water security. Companies that promote high-quality carbon performance operations generate both direct (for instance, lower cost energy) and indirect benefits (minimising the negative effects associated with waste production).

6. Conclusion

This article investigated the association between carbon performance and firm financial performance using data from South African CDP companies over a two-year period (2014-2015). Various firm financial performance measures were used to provide a detailed analysis of stakeholder perspectives of carbon performance issues. The findings indicate that carbon performance produces a positive relationship with ROE and ROS, but a negative relationship with ROI and MVA. Thus, the effect of carbon performance varies depending on which financial measures are considered, as each is influenced by the behaviour of a specific corporate stakeholder. The article also examined the extent to which firm growth is capable of moderating the association between carbon performance and firm financial performance. The results from the ROE, ROS, ROI and MVA analysis showed that increased carbon performance generates high profits and that the relationship is strengthened as firm growth increases. Future studies should consider longitudinal analysis perspectives so that the results generated over time are able to determine the carbon performance behaviour of these companies in relation to their financial performance. Moreover, further research should focus on broadening the model by integrating other factors such as corporate visibility (media), environmental regulations, recessions and firms’ strategic holdings.


Framework showing the factors which impact carbon performance practices in corporate contexts

Figure 1

Framework showing the factors which impact carbon performance practices in corporate contexts

Summarised statistics for sample companies

Variable ROE ROI ROS MVA CP rating Growth Firm size Leverage Capital intensity CP rating × Growth
Mean 0.1365 0.0935 0.0671 3.3847 1.6905 0.0606 16.9673 0.5762 1.2105 0.0143
Median 0.1398 0.098 0.0641 0.6785 1.000 0.0450 17.079 0.5332 1.2987 0.0131
Maximum 0.8339 0.659 4.055 62.270 3.000 0.4200 19.6538 1.2444 120.1994 0.4886
Minimum −0.7748 −0.7614 −6.689 −13.417 1.000 −0.2700 11.6328 0.0925 −306.4119 −0.3653
SD 0.21087 0.1787 0.972 9.5426 0.8622 0.1318 1.3493 0.2442 35.8955 0.1219
Skewness −0.8043 −1.3303 −1.5743 3.7075 0.6394 0.1924 −0.6696 0.3162 −5.1057 0.3204
Kurtosis 7.9634 10.236 24.3354 21.7721 1.6575 3.5177 4.2585 2.3472 47.4548 5.9751
Jarque–Bera 142.92 312.04 2,441.84 2138.71 18.047 2.1844 17.7299 4.3367 10922.65 48.6241
Probability 0.000000 0.00000 0.00000 0.00000 0.00012 0.3359 0.00014 0.1144 0.000000 0.0000
Sum 17.1978 11.788 8.449 426.467 213.000 7.6386 2137.88 72.604 152.5291 1.7976
Sum Sq. Dev. 5.5583 3.994 117.877 11382.8 92.9286 2.1722 227.578 7.4562 161060.9 1.8575
Observations 126 126 126 126 126 126 126 126 126 126

Correlation coefficients among variables

Variable 1 2 3 4 5 6 7 8 9 10
1. ROE 1
2. ROI 0.9393 1
3. ROS 0.1228 0.2258 1
4. MVA 0.2309 0.3142 0.4481 1
5. CP rating 0.0314 0.0815 0.1254 −0.0621 1
6. Growth 0.1131 0.0781 0.0754 −0.0314 0.1166 1
7. Firm size 0.0157 0.0028 −0.0222 −0.1928 0.0002 −0.0254 1
8. Leverage 0.3887 0.3292 −0.2960 −0.1835 −0.1031 0.1921 −0.0739 1
9. Capital intensity −0.0378 0.0180 0.5939 0.0167 0.0687 0.0956 0.1333 −0.1757 1
10. CP Rating × Growth 0.1794 0.2269 0.0262 −0.0384 0.1101 0.1215 −0.0735 0.1557 −0.0205 1

Carbon performance rating and firm financial performance (ROE)

Variable Pooled model REM FEM
Coefficient Standard error Coefficient Standard error Coefficient Standard error
CP rating 0.0132537 0.0208651 0.0038494 0.0065619 0.0040216 0.0067801
CP Rating × Growth 0.2071241 0.1527315 0.0599519 0.0461085 0.0416577 0.0478491
Growth 0.0308565 0.1388924 0.0256553 0.0789813 0.0061651 0.086817
Leverage 0.3276842*** 0.0762757 0.1495814** 0.0380059 0.1195047*** 0.0410005
Capital intensity 0.0001119 0.005065 −0.0000131 0.0000876 −0.0000234 0.0000887
Firm size 0.0078421 0.0131998 0.0023215 0.002654 0.0018342 0.0027054
Constant −0.2125246 0.23395 0.0020742 0.059265 0.0288168 0.0557151
R2 0.1723 0.1691 0.1681
Wald (χ2) 17.07
F statistic 4.13 1.58
Breusch-Pagan test (χ2) 60.62***
Hausman test (χ2) 4.18
No. of observations 126 126 126 126 126 126





denotes significant at 1%, 5% and 10% significance level, respectively

Carbon performance rating and firm financial performance (ROI)

Pooled model REM FEM
Coefficient Standard error Coefficient Standard error Coefficient Standard error
CP rating 0.0196158 0.0178672 −0.0008059 0.0077507 −0.0018694 0.0081528
CP Rating × Growth 0.2592246* 0.130787 0.0395772 0.0543238 0.0074566 0.0575363
Growth −0.0318668 0.1189363 0.02985 0.088729 0.0192207 0.1043933
Leverage 0.242696*** 0.0653164 0.116862 0.04333045 0.0734347** 0.0493012
Capital intensity 0.0003566 0.0004337 0.00000867 0.0001055 −0.000014 0.0001066
Firm size 0.0039386 0.0113033 −0.0002268 0.0031758 −0.0009072 0.0032531
Constant −0.1481947 0.2000336 0.0290829 0.0668342 0.068543 0.0669948
R2 0.15553 0.1217 −0.1032
Wald (χ2) 7.98
F statistic 3.65 0.47
Breusch–Pagan test (χ2) 57.74***
Hausman test (χ2) 6.12
No. of observations 126 126 126 126 126 126





denotes significant at 1, 5 and 10% significance level, respectively

Carbon performance rating and firm financial performance (ROS)

Pooled model REM FEM
Coefficient Standard error Coefficient Standard error Coefficient Standard error
CP rating 0.0597626 0.0809383 0.0202103 0.0718779 0.0126457 0.0924351
CP Rating × Growth 0.4264073 0.5924638 −0.1216506 0.5050547 −0.3205449 0.6523399
Growth 0.3533786 0.5387802 0.0770362 0.6294304 −0.6915509 1.183599
Leverage −0.8622738*** 0.2958826 −0.6080938* 0.3271211 −0.2385044 0.5589711
Capital intensity 0.0152337*** 0.0019648 0.0139921*** 0.0011346 0.0139063*** 0.0012089
Firm size −0.0779537 0.0512038 0.0051934 0.0330134 0.0227905 0.036883
Constant 1.740078 0.9075202 0.2752238 0.6231657 −0.174275 0.7595781
R2 0.4127 0.3891 0.3424
Wald (χ2) 166.73
F statistic 13.94 23.09
Breusch–Pagan test (χ2) 41.73***
Hausman test (χ2) 5.37
No. of observations 126 126 126 126 126 126





denotes significant at 1%, 5% and 10% significance level, respectively

Carbon performance rating and firm financial performance (MVA)

Pooled model REM FEM
Coefficient Standard error Coefficient Standard error Coefficient Standard error
CP rating −0.9318344 0.9933306 −0.7706009* 0.4410759 −0.7667178 0.4695948
CP Rating × Growth −1.117962 7.271124 −1.774245 3.09051 −1.265858 3.314058
Growth 0.9429176 6.612281 −0.3665265 5.012291 −0.0689041 6.012992
Leverage −8.041871** 3.631275 −3.363348 2.451169 −1.918949 2.83972
Capital intensity 0.0034189 0.0241134 −0.0012332 0.0060187 −0.0006909 0.0061414
Firm size −1.488294** 0.6284079 −0.2346512 0.1811006 −0.1716755 0.1873755
Constant 34.79952 11.13771 10.65383 3.789769 8.721057 3.858857
R2 0.0839 0.0568 0.0453
Wald (χ2) 7.02
F statistic 1.82 0.78
Breusch–Pagan test (χ2) 56.91***
Hausman test (χ2) 2.86
No. of observations 126 126 126 126 126 126





denotes significant at 1%, 5% and 10% significance level, respectively.

Summary of the results of the pooled OLS, fixed and REM s

VariablePooled OLSFEMREMOverall supported model
ROE Positive Positive Positive REM
ROI Positive Negative Negative REM
ROS Positive Positive Positive REM
MVA Negative Negative Negative REM

Summary of findings on how the firm growth rate moderates the association between carbon performance and company financial performance

Variable Threshold (Growth rate) determined No. of firms above the threshold in 2014 No. of firms above the threshold in 2015 Total number of firms in 2014 and 2015
ROE −0.0642 55 (87.3%) 47 (74.6%) 63
ROI −0.0203 50 (79.4%) 47 (74.6%) 63
ROS −0.1661 61 (96.8%) 58 (92.1%) 63
MVA −0.4343 63 (100%) 63 (100%) 63


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Corresponding author

Fortune Ganda can be contacted at:

About the author

Fortune Ganda is based at the Faculty of Management and Law, University of Limpopo, Polokwane, South Africa.