Political ideology of corporate decision makers and GHG emission
reductions
Master thesis
Wouter Albertus Kroes
S3826821
MScBA Change Management
This study furthers understanding of legitimacy theory and upper echelons theory by studying the role of individual value systems in interpreting legitimacy requirements by organisational leaders, and how these
interpretations are translated into perceived scopes of corporate responsibility. It does so by means of a series of panel regression analyses, testing the effect of CEO political orientation on corporate GHG emission reductions. The results do not indicate statistically significant relationships between the variables,
but nonetheless this study contributes to existing literature by novel combination of theory streams, and indicating areas for future research.
Introduction
Pollution and reduction of carbon footprints is a much debated topic both in society and academic literature, and increasing attention is paid to drivers of companies’ CSR activities (Bansal & Roth, 2000; Chin et al., 2013)). Legitimacy theory is an often used theory to explain external drivers, and argues that companies should meet societal norms and standards in order to gain legitimacy for their practices
(Suchman, 1995; Bitektine & Haack, 2015; Suddaby et al., 2017). However, as these norms are inherently subjective, understanding how they are being interpreted by decision makers, as well as what determines the importance they assign to them may provide insight into how such forces influence corporate decision making. For this, it is important to understand what drives executives’ decision making processes. Upper echelons theory argues that executives’ experience, personalities, and core values are important determinants in their decision making processes (Hambrick & Mason, 1984; Hambrick, 2007), and evidence suggests that CEOs’ political ideologies are representative of their core values, and thus are useful to study their
companies’ CSR performance (Schwartz, 1996; Jost et al., 2003; Jost, 2006). However, the influence of CEO political ideology on company performance on reducing its carbon footprint remains unclear. As such, this study analyses the influence of CEO political ideology on companies’ greenhouse gas (GHG) emission reduction.
A great deal of research has been done on voluntary and mandatory corporate emissions disclosure and the managerial motivations that drove the decision making behind it (e.g. Deegan, 2002; Mobus, 2005; Prado-Lorenzo et al., 2009; Choi et al., 2013; Chu et al., 2013; Lewis et al., 2014). Several studies draw on legitimacy theory, which argues that companies are part of their environment and have no inherent right to resources, but that companies should operate in a legitimate fashion by adhering to social contracts with their environment and society (Mathews, 1997; Chu et al., 2013; Schaltegger & Hörisch, 2017). By disclosing emissions, managers try to gain (or maintain) the legitimacy their companies need to survive. However, public expectations and pressure to develop CSR policies and behave ethically is increasing (Aaronson, 2003). As legitimacy theory argues that companies gain legitimacy by honouring their social contract with society, and that these contracts change as societal demands and expectations change (Suddaby et al., 2017), it could therefore also explain external, societal pressure on companies to reduce their carbon emissions. As cleaner forms of production and other forms of operation are being expected, legitimacy is expected to be gained not by solely disclosing emissions, but rather by reducing them. Such expectations, and whether companies live up to them, determine the legitimacy judgements about companies (Bitektine & Haack, 2015). It is in companies’ best interest to conform to such legitimacy judgements, as their survival may, at least partly, depend on it as customers are more likely to consume goods and services from companies that are regarded as legitimate, and investors are more likely to invest in companies that live up to social responsibility expectations (Chu et al., 2013; Di Giuli & Kostovetsky, 2014; Bitektine & Haack, 2015; Bitektine et al., 2020).
such legitimacy. Investments in the reduction of emissions lead to increased corporate expenditure, without adding tangible value to any product or service. They could, however, add intangible value in the eyes of those that value ‘green’ products. What, then, is deemed to be the bare minimum to gain legitimacy? As constructs of legitimacy are inherently subjective (Suchman, 1995; Bitektine & Haack, 2015), subjective norms held by executives, or their interpretations of such norms may determine, or at least influence,
executives’ legitimacy constructs with regard to what is deemed to be necessary for legitimacy (George et al. 2006; Lewis et al., 2014), and arguably also their scope of corporate responsibility in reducing emissions.
In terms of carbon emissions, companies can report these at different levels. The Carbon Disclosure Project (CDP) identifies three ‘scopes’ of emissions: (1) direct from own operations, (2) indirect from first-tier suppliers, including power generation, and (3) indirect further up and down their supply and value chains (Carbon Disclosure Project, 2020; Greenhouse Gas Protocol, 2020; Labutong & Hoen, 2018). Arguably, corporate action across these three levels may vary depending on what decision makers interpret to be the scope of their responsibility to reduce emissions, based on their judgement of what is deemed necessary to be legitimate. Arguably, those that feel greater social/moral responsibility towards others will feel that they have to do more to gain legitimacy than those that feel more individualistic and focus on their own interests. Some CEOs/BODs may only focus on creating and/or maximising shareholder value, a narrow scope of
responsibility and as such are likely to invest as little as possible in reducing emissions. They may, for instance, only focus their efforts on the first scope, while others may assume a broader scope of
responsibility, and tailor their efforts in emission reductions to the interests of multiple stakeholders and reduce emissions in the second and third scope as well.
In order to understand how CEOs interpret what is necessary to gain legitimacy, we need to look at what drives their decision making. To gain this understanding, this study draws on upper echelons theory, which argues that executive decision making is driven by executives’ personalities, experience, and values (Hambrick & Mason, 1984; Hambrick, 2007). Many studies into companies’ internal drivers of CSR activity have used upper echelons theory to explain top executives’ influence on decision making (e.g. Schwartz, 1996; Jost et al., 2003; Jost, 2006; Lewis et al., 2014). While existing literature on upper echelons theory mainly focuses on executives’ experience and personalities, the influence of executives’ values on the decision making of companies has received considerably less attention (Chin et al., 2013). However, those that do, have studied the effect of CEOs’ political ideology on corporate CSR activity, as political ideology serves as a reliable indicator of core values (Schwartz, 1996; Jost, 2006; Chin et al., 2013; Di Giuli & Kostovetsky, 2014). Thus, using political ideology as an indicator of executives’ values, as done by Chin et al. (2013), and testing its effect on companies’ carbon emission levels, this study aims to gain an
understanding of how decision makers interpret legitimacy requirements in terms of the scope of their responsibility to reduce carbon emissions. This culminates in the following research question:
RQ: “What influence does political orientation of CEOs have on the scope of the responsibility their
companies take in reducing carbon emissions?”
environmental management literature by studying how such interpretations can serve as antecedents of emission reduction decisions.
The remainder of this paper will be structured as follows. The next section provides an overview of current literature on the theories underpinning this study, based on which hypotheses are formulated. Section 3 describes the methodology applied to the testing of hypotheses, the results of which are presented in section 4. Section 5 provides a discussion of these results, as well limitations to this study and areas for further research.
Literature Review
Legitimacy Theory
Legitimacy theory has been studied intensively for several decades, and while some disagreements exist as to its properties, where it exists and how it can be gained (e.g. Suchman, 1995; Bitektine & Haack, 2015; Suddaby et al., 2017; Bitektine et al., 2020), a generally accepted definition of legitimacy was formulated by Suchman (1995), who argued that legitimacy is: “a generalized perception or assumption that the actions of an entity are desirable, proper, or appropriate within some socially constructed system of norms, values, beliefs, and definitions” (Suchman, 1995; p.574). Following this definition, it can be said that legitimacy acts as some objective construct that is independent of individual opinions.
However, legitimacy is a two-level construct (Tost, 2011) which is formed individually and
subjectively at the individual (micro) level. These individual evaluations represent an individual evaluator’s judgement of social acceptability approval of an organisation and/or organisational practices (Dornbusch & Scott, 1975; Bitektine & Haack, 2015). These individual judgements are aggregated and generalised at the collective (macro) level, where they gain a degree of objectivity (Bitektine & Haack, 2015), and as such represent the collective approval of organisations and organisational practices (Suchman, 1995) and the collective consensus that an organisation and its practices are appropriate or acceptable for its social context (Weber, 1978; Bitektine & Haack, 2015; Suddaby et al., 2017).. As such, legitimacy is often regarded as some intangible (Gardberg & Fombrun, 2006), operational (Suchman, 1995) resource, and organisations act upon collective legitimacy judgements, which may differ from individual evaluators’ opinions (Bitektine & Haack, 2015; Suddaby et al., 2017).
At the individual level (micro), legitimacy exists as individual beliefs about legitimacy (Suddaby et al., 2017), which are based on individual perceptions of macro-level judgements, and depend on the set of norms against which organisations or actions are benchmarked (e.g. economical, ethical). Using different norms may lead to different legitimacy judgements (Bitektine & Haack, 2015).
responsibility of their companies’ emission reductions, we must understand how their decision making works. Upper echelons theory may provide a better insight in this process.
Upper Echelons Theory and Political Ideology As Reflection Of Core Values
As mentioned in the introduction to this paper, upper echelons theory argues that executives’ decision making is determined by their experience, personalities, and their values (Hambrick & Mason, 1984; Hambrick, 2007). Prior studies that have tested upper echelons theory have mostly focused on executives’ experience and personalities, but few have studied the effects of their values in decision making (e.g. Simsek et al., 2005; Chin et al., 2013). A possible explanation for this apparently little interest in this element of upper echelons theory is that it may be difficult to develop an objective measure for an inherently subjective construct (Chin et al., 2013).
However, previous studies that have tested the effect of CEOs’ core values on corporate policies, or on CSR or CSR-related activity, have used political ideology as an indicator of core values (Chin et al., 2013; Di Giuli & Kostovetsky, 2014; Hutton et al., 2014). One’s political ideology seemingly provides a reliable depiction of one’s core values. Indeed, value theorists have, linked core values one might hold to political ideology (Rosenberg, 1956; Schwartz, 1996). In fact, evidence suggest that executives’ values are reflected in their political orientations (e.g. Layman, 1997; Barnea & Schwartz, 1998). According to Tedin (1987; 65): “the term ‘political ideology’ is sometimes defined as an interrelated set of attitudes and values about the proper goals of society and how they should be achieved…”, and Jost (2006; 635) argues that: “… ideology helps to explain why people do what they do; it organizes their values and beliefs”. An individual’s political ideology provides a reliable depiction of one’s core values, as it is shown to develop relatively early in life, and remain relatively stable over time (Jost et al., 2009; Hutton et al., 2014; Chow et al., 2021). Thus, using political ideology as an indicator of executives’ values, as done by e.g. Chin et al. (2013), one may gain an understanding of what degree of emission reduction they deem necessary to gain legitimacy. Liberal-Conservatism Scale
When it comes to understanding how an individual’s values are reflected in his/her/their political ideology, the liberal-conservative spectrum appears the most prevalent in existing literature (Schwartz, 1996; Jost et al., 2003; Jost, 2006; Jost et al., 2009; Chin et al., 2013). Existing literature from political science and social psychology sheds a light on how either conservative or liberal ideologies may express core values (Poole & Rosenthal, 1984). Broadly speaking, liberal ideologies are associated with more collectivist, social and environmental values. More specifically, research by Skitka & Tetlock (1993) uncovered that preference for equality, social change and shared responsibility are underlying characteristics for liberal ideologies. Additionally, Schwarz (1996) found that individuals with predominantly liberal ideologies show greater sensitivity towards all social issues, among others especially those related to the natural environment.
Translating values into a corporate context, liberal ideologies appear to be associated with broader stakeholder focus, as opposed to greater degrees of individualism, focus on shareholders’ interests, focus on efficiency, and less support for CSR expenditure associated with conservative ideologies (Tetlock, 2000; Gupta et al., 2017). Furthermore, conservative ideologies are associated with more risk averse
political ideologies are less likely to invest in reducing emissions where this does not serve purpose in terms of efficiency. This leads to the following hypothesis:
H1a: “The more liberal a CEO’s political ideology, the greater the overall reduction of emissions”
As liberals feel more shared responsibility for social issues, not only will they tend to seek to care for the interests of a broader group of stakeholders (Skitka & Tetlock, 1993; Schwarz, 1996), but they will also tend to do so in a broader organisational context. Conservatives, on the other hand, will likely prioritise individualism, focus on shareholders’ interests, and efficiency (Tetlock, 2000; Gupta et al., 2017). As such, they may be expected to focus and limit the scope of responsibility to their own business practices.
Additionally, whereas conservatives may deem it necessary to reduce the emissions caused by their own companies, they may tend not find it their responsibility to encourage their partners to do so too. They may tend to take a more pragmatic instead of ideologic stance toward selecting partners, prioritising efficiency over sustainability investments.
As such, I argue that liberals will not only be more likely to review and take responsibility for their own business practices, which may lead to greater degrees of emission reductions from their own operations (Scope 1), but that they perceive a scope of responsibility that extends beyond their own company and that they will be more likely to encourage their direct and indirect business partners to do so as well (Scopes 2 and 3). Additionally, it may also be the case that liberals will be more selective in choosing partners based on complementing values, which could both be expected to lead to greater degrees of emission reductions in the second and third scope as well. This leads to the following hypothesis:
H1b: “A more liberal CEO political ideology will perceive a larger scope of responsibility, which will lead
to comparably larger degrees of emission reductions in the second and third scopes”
Political Orientation of States
It is, however, not just internally held values that determine what is necessary to gain legitimacy. Legitimacy is primarily subject of external judgement, e.g. societal or governmental (Bitektine & Haack, 2015).
Internally held values may play a role in interpreting what is an appropriate scope of one’s responsibility/ what is necessarily required to gain legitimacy, but that interpretation hinges on the common understanding of legitimacy at a societal level (Tost, 2011; Bitektine & Haack, 2015; Suddaby et al., 2017; Bitektine et al., 2020). Marquis et al. (2013) found that local communities in which organisations play a role, are an
State of incorporation could thus have an effect on corporate sustainability behaviour. Schaltegger & Hörisch (2017), found that corporate sustainability practices are mainly driven by legitimacy seeking. This would suggest that companies pursue such practices in order to conform to socially held norms. It would also suggest that companies would behave more sustainably when the political orientation of the State in which they are incorporated, is predominantly liberal. In line with this, Di Giuli & Kostovetsky (2014) found that firms in democratic political environments behave more socially responsible. Incorporating the above into this study, and to analyse the effect of state-level political orientation on the relationship described in hypothesis 1a, the following hypothesis is formulated:
H2: “The more liberal the state political orientation, the stronger the effect between CEO political ideology
on emission reductions”
The next section elaborates on the methodologies applied to test the hypotheses formulated above.
Methods
Sample and Research Design
The hypotheses formulated in the previous section were tested by a series of random-effects panel regression models, using a sample of companies that were Standard & Poor’s (S&P) 500-listed between 2002 and 2008. The S&P500 provides a reliable sample as the index provides a comprehensive overview of companies in the United States’ economy, for it lists its 500 largest companies by market capitalisation and exclusively lists companies that are based in the US (Standard & Poor’s Global, 2021). As such, its data lends itself to be combined with data on political donations, which was gathered in the US as well (Federal Elections
Commission, 2021). The sample was limited by the available corporate emissions data, which covered only the aforementioned timespan, as well as the number of years for which data was available for each company.
A minimum of three data points is required to study any change in emissions over at least one year, taking into account as well that the emissions data was lagged by one year relative to the reference point of the first year for which data was available for each company. Additionally, several industries were excluded from the sample, based on their operational characteristics. Companies active in banking, insurance, financial services, and media were excluded as companies in these industries typically do not produce tangible products, and therefore likely produce rather marginal emissions compared to e.g. oil & gas companies or automobile parts producers, including them would skew the data and potentially influence the tested effects. The resulting sample includes 271 individual companies, and 1342 firm years of data.
Data
For robustness checks, an alternative The Database on Ideology, Money in Politics, and Elections (DIME) (Bonica, 2016) provided similar data on political ideology as the method of Chin et al. (2013) generated, but was computed using a different scoring mechanism for political ideology, which was created by Adam Bonica in his work on mapping political ideology (Bonica, 2014). Data from DIME was matched to the sample of CEOs, and subsequently used for robustness checks for the relationship that is hypothesised in H1a and H1b.
Data on emissions by companies was retrieved from a dataset compiled by Trucost (Trucost Plc, 2008), which provided data for each of the three distinct scopes of emissions. As the data on emissions that was available for this study only ranged from 2002 to 2008, the sample used was limited as such and set to this timespan. Data on the political orientation of states was retrieved from a dataset that has been created by Caughey & Warshaw (2016), and data for the control variables used pertaining to board information was retrieved from the BoardEx database, accounting data (e.g. firm size and sales) was retrieved from the Compustat database, and data on the return on assets and CSR score was retrieved from the Asset4 database. Independent Variable
To construct the independent variable in this study, CEO political orientation, for each CEO of the
companies in the sample, a political orientation score was calculated by assessing political contributions they made. In the US, all political donations of $200 and above have to be formally registered, and as such, a great collection of political donations data is available for research (Federal Elections Commission, 2021).
To generate political liberalism scores for the CEOs in the sample used in this study, the scoring method developed by Chin et al. (2013) has been applied. This method calculates an individual’s political ideology on a scale ranging from 0 to 1, with 0 indicating a fully conservative ideology and 1 a fully liberal ideology, incorporating four indicators of political donating: the number of unique donations, the monetary value of donations, the number of years in which donations were made, and the number of unique recipients of donations. For each indicator, the method scores liberalism by calculating number, amount, recipients, or years of donations made to democratic politicians as part of total number, amount, recipients, or years of donations made to either party (Chin et al., 2013, p.208).
Dependent Variable
Data on emissions by companies was specified for the three distinctive scopes of emissions (Carbon Disclosure Project, 2020; Greenhouse Gas Protocol, 2020). To test H1a, data on total GHG emissions was used. For each individual company in the sample, the data was lagged by one year relative to the reference year (the first available year for which data was available), and then subtracted from the preceding year in order to calculate the differences from year to year. This difference was then used as the dependent variable in the regression analyses.
State Political Orientation
To test the moderating effect of the political orientation of states on the effect between CEO political ideology and emission reductions, a measure from Caughey & Warshaw (2016) is used, which estimates the economic policy liberalism for each U.S. state. In their study, Caughey & Warshaw developed a
comprehensive methodology to measure state-level policy liberalism. The economic policy liberalism estimation is expected to best explain the effect state-level policy may have on the relationships hypothesised in H1a.
Control Variables
In testing the hypotheses, effects are controlled for several factors. First, industry could determine a
company’s scope of potential reductions it can make. As such, controlling for industry, the tests may indicate whether any relation holds or whether it may differ across industries.
To control for possible reverse causality, a measure for environmental CSR score is included. According to Di Giuli & Kostovetsky (2014), firms that display high levels of social responsibility may attract more liberal CEOs and board members, or deliberately headquarter in states with predominantly liberal political ideologies, meaning that emission reductions may be a result already high levels of CSR, and that CEOs are attracted for their liberalism and being complementary to the organisational ideology. As such, emission reductions would not be explained by CEOs’ political liberalism and state liberalism, but by
organisational political ideology (Schneider, 1987; Gupta et al., 2017; Di Giuli & Kostovetsky, 2014; Chow et al., 2021).
Several control variables for social scrutiny are included. Extant literature showed that isomorphic pressure from industry standards may influence organisational behaviour (DiMaggio & Powell, 1983; Hambrick et al., 2004; Shropshire & Hillman, 2007; Chin et al., 2013; Gupta et al., 2017), an effect which would not be explained by the independent variable. As such, a measure of industry average total emissions was included. This average was calculated by averaging the total emissions for all companies in the same industry (based on industry code), and excluding the focal firm. In addition, a control for GHG emissions performance relative to industry average emissions is also included in the models. Performance in this respect is calculated by subtracting industry average total GHG emissions from company specific total GHG emissions, for each individual year. Positive values for this variable thus indicate that the firm in question is emitting more than the industry average, representing greater impetus and isomorphic pressure to reduce emissions.
Additionally, several board-related measures are controlled for as these may interfere with the main effect of study. The board of directors is the decision making unit of a company, and since CEO political ideology is the variable of interest, influence and effects of the BOD on emission reductions need to be controlled for. As such, average liberalism of the board of directors was included, following the examples of Chin et al. (2013) and Gupta et al. (2017). Next, as proxy for power, a measure for CEO duality is included (Chin et al., 2013), as well as measures for board size and board independence (as percentage of outside directors) (Gupta et al., 2017). A measure for CEO gender is added to control for any CEO gender effect (Di Giuli & Kostovetsky, 2014). Lastly, a year effect dummy is added as well to see whether any effect is due to the mechanisms hypothesised.
Robustness Checks
To check the robustness of the models, an alternative measure for CEO political ideology was used to test the effect of political ideology on emission reductions. Bonica (2014), developed an alternative measure for political ideology, which was used instead of the method by Chin et al. (2013). Here, the spectrum of ideology scores ranges from -2, indicating a fully liberal ideology, to 2, indicating a fully conservative ideology.
Results
In this section, the results from the panel regression analyses are shown and described. Table 1 shows means, standard deviations, and the correlation matrix for the dependent, independent, and control variables
included in the models.
Table 2. Panel regression models of CEO political ideology on Δ total emissions (re)
Variables Model 1 Model 2 Model 3
Total assets (log) -46232.9 -43756.3 -47600.6
(116478.8) (115782.9) (119773.8)
Sales (log) -16193.8 -19966.5 -14003.1
(111137.5) (110199.0) (115143.3)
Return on assets 8590.7+ 8682.2+ 7980.9+
(4460.6) (4524.9) (4226.0)
Industry average total emissions -0.0997 -103 -101
(145) (147) (147)
Average BOD liberalism (CHIN) 9317.1 603245.2 576613.5 (532150.6) (586223.6) (613084.9) CEO duality 58710.8 47175.5 45668.2 (157895.2) (156382.4) (154247.5) Board size 21797.8 20792.2 23547.7 (25588.8) (25452.5) (26590.4) Board independence -1882.1 -2409.6 -1604.6 (7752.2) (7782.0) (8265.1) Emissions performance relative to industry average -0.0300** -0.0306** -0.0305** (0.00991) (0.0103) (0.0104) CSR score (environment) 105.5 142.6 420.1 (3236.1) (3221.9) (3118.2) Female CEO 801845.1 856462.7+ 903330.9+ (513751.7) (519442.5) (522321.1) B2B firm 34359.7 35156.1 32157.0 (107836.2) (109887.9) (111444.6)
CEO political ideology (CHIN) -550470.9 -747487.9
(394375.1) (622980.5)
State political orientation -146924.7
(145050.0) CEO political ideology * State political orientation 330097.9 (381970.2)
Constant 4710085.4 4911237.4 4772618.5
(6740280.9) (6854570.5) (6796049.5)
Year effect dummy Y Y Y
Industry effect dummy Y Y Y
Observations (firm years) 1342 1342 1342
Observations (firms) 271 271 271
Chi2 415.4 432.6 450.9
Table 2 shows the panel regression model outputs for the effect of CEO political ideology on the difference in total GHG emissions, as well as the effect of the moderating effect of state-level political orientation on the relationship between CEO political ideology and difference in total GHG emissions.
In model 2, hypothesis 1a was tested. Although the direction of the effect between CEO political orientation and difference in total GHG emissions turned out to be negative, as expected, the model shows no statistical significance for the studied main effect. Thus, no support was found for hypothesis 1a.
Model 3 tested hypothesis 2, and as can be seen, the overall effect of CEO political ideology on the difference in total GHG emissions appears to be stronger for more liberal political orientations of domestic states. However, neither effect showed statistical significance, and thus no support was found for hypothesis 2.
In terms of the effects that are controlled for in these studies, only some showed statistical significance. The effect of Return on assets (ROA) on the difference in GHG emissions showed to be
statistically significant (p<0.10). The direction of the effect turned out to be positive, which indicates that for every additional standard deviation in ROA, the amount of total GHG emissions would in fact increase. The effect of a company’s emissions performance relative to the industry average on the dependent variable showed statistical significance (p<0.01) in all three models, and the direction of the effect turned out as expected, indicating that emitting more than the industry average would decrease total GHG emissions. The effect of having a female CEO on difference in GHG emissions did not show statistical significance in the first model, but did show significance (p<0.10) in the models that tested the main effects of this study.
Table 3. Panel regression models of CEO political ideology on Δ share of scope 2+3 emissions (re)
Variables Model 1 Model 2 Model 3
Total assets (log) -0.00134 -0.00133 -0.00133
(0.00138) (0.00138) (0.00139)
Sales (log) 0.00108 0.00107 0.00106
(0.00152) (0.00153) (0.00154)
Return on assets -0.0000492 -0.0000490 -0.0000476
Table 3 shows the panel regression models for the effect of CEO political ideology on the difference in GHG emissions in scopes two and three, (as well as the moderating effect of state-level political orientation on the relationship between CEO political ideology and the GHG emissions difference in scopes two and three.) Model 2 tested hypothesis 1b. The overall effect of CEO political ideology on the difference in GHG
emissions in scopes two and three turned out to be as expected, hinting at reduced emissions for more liberal political ideologies. However, the effects show no statistical significance and as such, no support was found for hypothesis 1b. The only effect that showed statistical significance in the models in table 3, is that of CEO duality on the dependent variable (p<0.05). The effect was negative, which indicates that emissions in the second and third scopes are more likely to be reduced when the CEO of the focal firm also chairs the board of directors.
Robustness Checks
To check for robustness of the panel regression models, comparable analyses were made using different data for the independent variable and the control variable for BOD political orientation. Instead of using the scoring method of Chin et al. (2013), an alternative method, developed by Bonica (2014) was used to assess the political ideologies of CEOs. Apart from these different variables, identical regression analyses were run in order to check the robustness of the models when using a different independent variable.
CSR score (environment) 0.00000343 0.00000352 0.00000301 (0.0000609) (0.0000610) (0.0000616) Female CEO -0.00117 -0.00104 -0.00109 (0.00265) (0.00269) (0.00281) B2B firm 0.00134 0.00134 0.00135 (0.00298) (0.00299) (0.00299)
CEO political ideology (CHIN) -0.00131 -0.000876
(0.00496) (0.00549)
State political orientation 0.000197
(0.00191) CEO political ideology * State political orientation -0.000620 (0.00384)
Constant 0.00259 0.00307 0.00335
(0.0449) (0.0451) (0.0454)
Year effect dummy Y Y Y
Industry effect dummy Y Y Y
Observations (firm years) 1342 1342 1342
Observations (firms) 271 271 271
Chi2 . . .
Table 4. Panel regression models of CEO political ideology on Δ total emissions (re)
Variables Model 1 Model 2 Model 3
Total assets (log) -46650.4 -45154.6 -45105.6
(116739.9) (116614.6) (116518.2)
Sales (log) -15844.2 -18643.7 -18277.3
(110692.0) (110344.4) (110125.5)
Return on assets 8700.3+ 8855.9+ 8698.6+
(4534.9) (4555.1) (4600.8)
Industry average total emissions -0.0995 -100 -100
(145) (145) (145)
Average BOD conservatism (DIME) -119086.4 -275609.8 -302688.2 (232761.1) (266970.4) (292085.2) CEO duality 60095.3 51301.9 52516.6 (158443.6) (155580.1) (151351.6) Board size 21939.6 20401.5 21099.6 (25601.7) (25449.5) (25538.1) Board independence -1833.2 -2193.2 -2371.5 (7766.1) (7884.5) (7814.0) Emissions performance relative to industry average -0.0300** -0.0303** -0.0303** (0.00993) (0.00999) (0.0101) CSR score (environment) 84.80 43.33 135.1 (3247.9) (3240.3) (3251.4) Female CEO 800733.8 814032.6 854430.0 (513045.9) (526371.4) (520773.6) B2B firm 43603.5 48347.6 51470.1 (106219.1) (107856.0) (107279.4)
CEO political ideology (DIME) 137244.9 163724.1
(122662.8) (156410.0)
State political orientation -16768.0
(66146.0) CEO political ideology * State political orientation -58017.5 (83601.0)
Constant 4713761.5 4765431.4 4706974.3
(6691952.0) (6686189.5) (6727798.6)
Year effect dummy Y Y Y
Industry effect dummy Y Y Y
Observations (firm years) 1342 1342 1342
Observations (firms) 271 271 271
Chi2 409.4 401.6 410.8
Table 4 shows the panel regression models for the effect of CEO political ideology on the difference in total GHG emissions, as well as the effect of state-level political orientation on the relationship between CEO political ideology and the difference in total GHG emissions. Model 2 tested hypothesis 1a, and the overall effect turned out as expected (note that here, the effect is positive rather than negative due to the reverse distribution of the independent variable relative to the variable used in the original test). However, here too, the effect shows no statistical significance. Thus, this robustness check provided no support for hypothesis 1a. Model 3 tested hypothesis 2. Similar to the original models, the main effect here appeared to be stronger for more liberal political orientations of domestic states, as expected. But similar to the original models, too, the effects in this model showed no statistical significance and thus no support for hypothesis 2. Of the control variables, the effects that showed statistical significance are that of the ROA (p<0.10), and that of emissions performance relative to the industry average (p<0.01). The directions of both effects were the same as in the original models.
Table 5. Panel regression models of CEO political ideology on Δ share of scope 2+3 emissions (re)
Variables Model 1 Model 2 Model 3
Total assets (log) -0.00134 -0.00134 -0.00136
(0.00138) (0.00138) (0.00138)
Sales (log) 0.00110 0.00110 0.00112
(0.00152) (0.00152) (0.00152)
Return on assets -0.0000483 -0.0000484 -0.0000403
(0.000101) (0.000101) (0.000100) Industry average total emissions -6.05e-11 -6.02e-11 -9.17e-11 (9.37e-10) (9.39e-10) (9.39e-10) Average BOD conservatism (DIME) -0.00280 -0.00273 -0.00309 (0.00572) (0.00659) (0.00679) CEO duality -0.00462* -0.00462* -0.00440* (0.00213) (0.00215) (0.00217) Board size 0.000299 0.000300 0.000297 (0.000487) (0.000492) (0.000488) Board independence 0.0000724 0.0000726 0.0000551 (0.000114) (0.000113) (0.000115) Emissions performance relative to industry average -4.01e-11 -4.00e-11 -4.04e-11 (8.30e-11) (8.36e-11) (8.25e-11) CSR score (environment) 0.00000337 0.00000339 0.000000351 (0.0000609) (0.0000609) (0.0000610)
Female CEO -0.00112 -0.00113 -0.00185
Table 5 shows the panel regression models for the effect of CEO political ideology on the difference in GHG emissions in scopes two and three, as well as the moderating effect of state-level political orientation on the relationship between CEO political ideology and difference in GHG emissions in scopes two and three. Model 2 tested hypothesis 1b. The overall effect of CEO political ideology on the difference in GHG emissions in scopes two and three turned out to be as expected, but show no statistical significance and thus no support was found for hypothesis 1b. Similar to the original models, the only effect that showed statistical significance in the models in table 3, is that of CEO duality on the dependent variable (p<0.05). Here too, the effect was negative, which indicates that emissions in the second and third scopes are more likely to be reduced when the CEO of the focal firm also chairs the board of directors.
Discussion
This study set out to combine the perspectives of legitimacy theory and upper echelons theory so as to gain a better understanding of how objective macro-level legitimacy judgements about the organisation are
interpreted and how such interpretations are translated into decisions pertaining to reductions in GHG emissions. By combining these two major literature streams, it was attempted to show that CSR decisions are not only shaped by external judgements and isomorphic pressures in the organisational environment, but also by individual value systems against which interpretations are made. To do so, in this paper, the effect of CEO political ideology on GHG emission reductions was studied to understand if and how core values determine a CEO’s perceived scope of responsibility to reduce GHG emissions of his/her/their company. It was expected
B2B firm 0.00129 0.00129 0.00122
(0.00300) (0.00296) (0.00293)
CEO political ideology (DIME) -0.0000658 -0.00163
(0.00217) (0.00241)
State political orientation -0.000780
(0.000997) CEO political ideology * State political orientation 0.00217 (0.00153)
Constant 0.00590 0.00587 0.0100
(0.0439) (0.0441) (0.0442)
Year effect dummy Y Y Y
Industry effect dummy Y Y Y
Observations (firm years) 1342 1342 1342
Observations (firms) 271 271 271
Chi2 . . .
that the more liberal a CEO, the greater the reductions and the greater the scope of responsibility perceived. The results from this study do, however, not indicate a significant relationship between CEO political ideology and emission reductions. This is not in line with previous studies on the subject of political orientations and CSR decisions (Chin et al., 2013; Gupta et al., 2017), which did indicate that such
relationship exists. However, it must be noted that the study by Gupta et al. showed a relationship between CSR decisions and organisational political ideology, and not CEO political ideology specifically. This factor may be important in understanding why no support was found for the hypotheses in this study, and raises the questions of the importance of CEO power/influence in the board of directors when it comes to decisions pertaining to CSR/GHG emissions, and the relation to organisational political ideology.
As mentioned in Gupta et al. (2017), it could be the case that an organisation as a whole already leans toward either liberal or conservative ideology and subsequent decision making, and attracts a CEO whose political ideology is complementary, which could potentially strengthen organisational ideology, but renders CEO ideology of insignificant influence. Furthermore, a CEO’s influence on decision-making concerning emission reductions, and decision-making in general, is dependent on his/her their power in the board of directors (Simsek et al., 2005; Chin et al., 2013). This study did include a control variable for this factor by means of measuring CEO duality, as well as for BOD political ideology, which served as a proxy for organisational political ideology, however neither showed to have a statistically significant effect on emission reductions. This would suggest that emission reductions are not affected by political ideologies of organisations as a whole and the complementarity of CEO political orientation, but mainly by isomorphic pressures from the environment. A notable result from the tests in this respect, is that emissions performance relative to the industry average did show to have a statistically significant effect on GHG emission reduction. As this was a control variable for isomorphic pressure exerted on firms, this effect supports the notion that organisational legitimacy seeking is influenced by external norms and industry standards.
Another possible explanation for the absence of any significant results may be found in the
specificity of the dependent variable in this study. An important distinction needs to be made between CSR practices as a compilation of many different practices with social relevance, and the specific element of GHG emission reduction as part of CSR activity as a whole. In contrast to previous studies, which focused on CSR activity as a whole (Chin et al., 2013; Gupta et al., 2017), the present study singled out GHG emission reductions as subject of interest. The expectation was that there would be a relationship between CEO political ideology and such reductions, based on the evidence that a similar relationship appears to exist between CEO and organisational political orientation, and CSR activity. The fact that the present study does not indicate such relationship, might suggest that CSR activity may in fact be used as just a PR/marketing tool, a way of appearing to be doing good as an organisation, without actually making tangible progress in reducing GHG emissions, a notion previously alluded to by Deegan, 2019.
Limitations and Future Research
States with a republican president in office. This may have had effects for state-level policies that could be of influence on corporate emission reductions. Using a sample that covers a larger range of years, such
influence could be analysed, potentially providing different results. In addition to this, the urgency to reduce emissions is ever growing, and using more data that is more up-to-date may reflect this urgency in corporate behaviour with regard to their emission reductions.
Next, the indicators used for political ideology have been applied in previous studies and serve as representative indicators of one’s core values (Rosenberg, 1956; Schwartz, 1996; Layman, 1997; Barnea & Schwartz, 1998; Jost et al., 2006; Chin et al., 2013), they are strongly linked to a binary system of liberalism-conservatism, which means that the generalisability of the results to companies in countries with different political spectra is limited (Chow et al., 2021). Furthermore, using political donations data to measure individuals’ political ideologies, following the methods devised by Chin et al. (2013) and Bonica (2014), they may be imprecise methods to quantify the construct of political ideology (Chin et al., 2013; Chow et al., 2021), and as such be imprecise indicators of one’s core values.
This study added to literature on legitimacy theory by studying how political ideology, representing value systems, influences individuals’ interpretations of legitimacy judgements. In their study, Gupta et al. (2017), argue that the effect of political ideology becomes more pronounced when isomorphic pressures are smaller. This study did include variables to control for isomorphic pressures, but it did not study the interplay between such pressures and political ideology as such. It should be noted that Gupta et al. (2017) measured political ideology at the organisational level, rather than the individual level, but nonetheless it provides an interesting avenue for future research.
Conclusion
In this paper, two major literature streams, those on legitimacy theory and on upper echelons theory, were combined to study the effect of CEO political orientation on GHG emission reductions. It was attempted to show that not only isomorphism and isomorphic pressures in the organisational environment shape corporate CSR decision making, but also what role individual value systems, against which external legitimacy
judgements are interpreted, play.
This way, this study set out contribute to the legitimacy theory literature by studying how individual interpretations of legitimacy judgements are shaped by personal value systems and ideology. It also
contributed to upper echelons theory and environmental management literature by furthering the research on antecedents of CSR decision making, as well as the understanding of the role of personal values play in the decision making process, specifically pertaining to emission reductions. Despite the non-significance of the results yielded with this study, combining the streams of legitimacy theory and upper echelons theory should be further explored in future research.
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