Advertisement

  • Loading metrics

Open Access

Peer-reviewed

Research Article

Assessing corporate climate action: Corporate climate policies and company-level emission reductions

Abstract

Private investment decisions are expected to play a decisive role in redirecting capital flows in line with the Paris Agreement. The financial sector and policymakers have emphasized the role of corporate climate action and climate-related disclosure, including backward-looking emissions figures and forward-looking information on corporate climate policies to enable investors to reallocate capital to firms with promising emission reduction pathways. However, there is at best inconclusive evidence on the relationship between corporate climate policies and subsequent company-level emission reductions. Previous research was limited by small sample sizes and short observation periods, impeding the analysis of time-lagged effects or the inclusion of company-level fixed effects. To overcome these shortcomings, we draw on a new dataset with 17,198 observations from 1,749 companies that disclosed their corporate climate policies between 2010 and 2022. While our results show only a weak link between individual policies and company-level emissions, we find some evidence for an improved climate performance for absolute emissions for companies that introduced a comprehensive corporate climate policy mix. This is in line with public policy research that has found comprehensiveness to be an important dimension for public policy mixes and emphasizes the role of a mix of corporate climate policies rather than relying on individual measures.

Citation: Klaaßen L, Lohmüller C, Steffen B (2024) Assessing corporate climate action: Corporate climate policies and company-level emission reductions. PLOS Clim 3(11): e0000458. https://doi.org/10.1371/journal.pclm.0000458

Editor: Lily Hsueh, Arizona State University, UNITED STATES OF AMERICA

Received: April 26, 2024; Accepted: September 6, 2024; Published: November 13, 2024

Copyright: © 2024 Klaaßen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Additional data to support our findings can be found in the electronic supplementary material. The dataset built for this study is based on proprietary data from CDP which are widely-used finance and environmental industry datasets but have to be paid for. All related subscriptions come with strict licensing conditions that they cannot be passed on to non-subscribers. We confirm that any researcher will be able to obtain the datasets in the same manner that we have obtained them and access is typically provided through university libraries. Accordingly, replication should be possible. Data access request can be directed to the authors (lena.klaassen@gess.ethz.ch and bjarne.steffen@gess.ethz.ch) or partnerships@cdp.net.

Funding: L.K. and B.S. have received funding from the EU Horizon 2020 research and innovation program, European Research Council (grant agreement no. 948220, project no. GREENFIN) for this project, including for the salary of both researchers. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Lena Klaaßen is a co-founder of CCRI GmbH, a company providing data on sustainability aspects of cryptocurrencies and blockchain systems. To our knowledge, cryptocurrencies and blockchain systems do not play a decisive role in the sample of the present study. Christian Lohmüller is an employee at SYSTEM Ltd. He started this position after his research stay at the Climate Finance and Policy Group at ETH Zurich.

Introduction

Climate change mitigation requires decarbonization across all parts of society [1,2]. While the leading role of governments to steer emission reductions is uncontested, the potential of the private sector in combating climate change is increasingly acknowledged (Hsu et al., 2019; Kudłak, 2019; Kuramochi et al., 2020; Steffen, Schmidt, & Tautorat, 2019; UNFCCC, 2016). One area where private action is particularly important is the re-direction of capital flows, because in market economies, capital allocation is primarily achieved by private investment decisions. In principle, changing investor preferences, driven by increased recognition of the need for decarbonization or regulatory pressure, should lead to a reallocation of capital towards firms with more promising emission pathways, as long as investors have access to the required information basis to identify these firms [3–6]. To this end, regulatory requirements concerning corporate climate action by companies–with the ultimate goal of facilitating the re-direction of capital in line with investors’ climate concerns–are increasingly considered as part of public climate policymaking [7–10]. At the same time, the private financial sector has also emphasized the role of corporate climate action [7,11–13] and business organizations around the world are increasingly facing legislative and stakeholder pressures to reduce their greenhouse gas (GHG) emissions and decarbonize their operation [14]. As a consequence, information on corporate climate policies has increased strongly over the past decade with over 18,000 companies reporting climate-related information in 2022 through CDP (formerly: Carbon Disclosure Project) as the largest global disclosure system, up from below 3,000 in 2010 [15]. However, the effectiveness of (disclosed) corporate climate policies for re-directing capital is increasingly challenged and also empirical evidence supporting the impact of disclosure on emission reductions remains scarce [9,16,17].

The fundamental idea of disclosing corporate climate policies is that investors can make well-informed decisions to reduce portfolio emissions and climate risks. To enable investors to effectively decarbonize their portfolio emissions, it is a prerequisite that the disclosed corporate climate policies are informative concerning a company’s future GHG emissions. If corporate climate policies are not linked to future emissions, expecting investor-led capital reallocation to companies that demonstrate greater mitigation effort is hopeless.

Despite past research on the relationship between corporate climate policies and subsequent emission reductions, the empirical evidence remains inconclusive. Existing research on this topic exhibits two shortcomings: First, sample sizes are often small with only a few hundred companies and observation periods are typically short with less than five years. This is partly due to the relatively nascent practice of disclosing corporate climate policies which is often conducted in an unstandardized way. Consequently, until recently, conducting large-N analyses involving a substantial number of observations over multiple years, which would enable the analysis of time-lagged effects or the control for company-level fixed effects (FEs), was not feasible. Second, the vast majority of previous studies investigate only the effect of single corporate climate policies in isolation, such as policies for emission reporting [18,19], setting of emission reduction targets [20] or establishing climate-related corporate governance [21,22]. Decades of experience with public climate policy on a national and transnational level, however, have shown that effective policy strategies require a mix of different instruments. Concerning national climate policy, the literature on policy mixes describes how different policies work in conjunction [23–26]. However, on the corporate level, there is no research investigating whether a comprehensive mix of corporate climate policies spanning multiple complementary areas is associated with improved climate performance.

To address these gaps, this article applies theory from the public policy literature to the corporate context and investigates the link between corporate climate policies and improved climate performance in a ‘large-N’ analysis including the effect of installing a comprehensive corporate climate policy mix ranging across four key areas: targets, governance, implementation, as well as monitoring, reporting, and verification (MRV). Based on CDP and the financial database Refinitiv, we build a dataset consisting of disclosed corporate climate policies of 1,749 companies based in OECD countries from 2010–2022. The dataset includes over 17,198 observations which enables us to analyze time-lagged effects and control for company-level FEs. Our results suggest that single corporate climate policies do not show a clear association with subsequent climate performance (no significant link over specifications). However, we find some evidence that a comprehensive mix of policies is of relevance for improved climate performance in terms of absolute emissions. Notably, the level of evidence varies across different measures of comprehensiveness. While the first measure of comprehensiveness (which requires only one policy from different complementary areas) loses its significance when also controlling for company fixed effects, the second measure of comprehensiveness (which requires the introduction of all corporate climate policies) remains significant. This finding is in line with companies not cherry-picking specific policies, but introducing an entire range of policies showing a stronger association with emission reductions. The results for emission intensities as the dependent variable remain inconclusive.

While the observational nature of the data does not permit to fully identify causal mechanisms, our FE specifications describe patterns concerning which corporate climate policies (or which mix of them) are associated with future emission reductions and can thereby serve as an indicator for climate-conscious investment choices. This is especially relevant as climate-conscious investors are interested in identifying suitable companies that reduce their emissions in the future and therefore need potential predictors that may guide them in the portfolio compilation Our paper makes two important contributions. First, we contribute new empirical evidence on the informative value of corporate climate policies on companies’ climate performance while overcoming some of the methodological challenges that have hampered prior research on corporate climate performance. Due to our large dataset, our results show which corporate climate policies (or which mix of them) are associated with future emission reductions and can thereby serve as an indicator for climate-conscious investment choices. Second, we contribute new evidence to the broader debate concerning the role of effective corporate climate action. Specifically, our paper applies theory from the public policy mix literature and extends the very limited body of research on corporate climate action, which has long been constrained because prior research has seldom been able to observe outcomes of different corporate climate policy mixes. Hence, our paper develops a conceptualization of comprehensive corporate climate policy mixes and extends the theory on corporate climate policies by beginning to grow empirical research on which mixes are associated with subsequent emission reductions. The results of this large-n study may serve as a basis for policy makers to design disclosure mandates in a way that they require information from complementary areas to enable investors to identify companies with effective corporate climate strategies. At the same time, the informative value of corporate climate policies for future emission pathways remains inconclusive. Public policymaking should therefore refrain from relying too strongly on the effect of corporate climate action for effective capital redirection.

The remainder of the paper is organized as follows. Section 2 presents the theoretical foundation and the research hypotheses. Section 3 displays the empirical design. Section 4 assesses the results on the relation of corporate climate policies and climate performance. Section 5 discusses and concludes the paper.

Theoretical foundation and hypothesis development

Sustainability disclosure theory and related literature

While this paper focuses on the relation between corporate climate policies introduced among already disclosing companies and climate performance, there are several related research strands routed in sustainability disclosure theory. One of the earlier strands, evolving since the early 2000s, focuses on the type of companies that disclose sustainability-related information as well as their underlying motivations. Specifically, initial studies focused on whether the act of disclosure indicates poor performance (legitimacy view) or good performance (management-oriented view) [27,28]. According to the legitimacy theory, organizations disclose sustainability information as a result of stakeholder and shareholder pressure, to obtain, maintain and repair their organization’s legitimacy in society’s perception [27,29–31]. Following this theory, poor sustainability performance leads to greater external pressure, resulting in enhanced levels of sustainability disclosure. The management view, on the contrary, argues that organizations disclose sustainability information to communicate their need to improve sustainability performance. Here, sustainability disclosure is a valuable tool for companies to establish measurement and management practices that can help them reduce their sustainability impact [32–34].

More recently, research has increasingly focused on the specific case of climate-related disclosure. To this end, business management literature explores the factors that drive corporate participation in the CDP as the largest global disclosure system for climate-related disclosure as well as similar programs, including firm-internal dynamics (e.g., [35–38]), governance structures affecting the corporate level (e.g., [39–41]). Specifically, the existence of senior managers promoting sustainability practices and the adoption of ESG (environmental, social, and governance) principles into business decisions are identified as drivers for participation in voluntary climate action and disclosure programs [37,38]. Going beyond, [41] finds that among firms making voluntary disclosures, regulatory pressure was associated with higher levels of carbon disclosure in firms with favorable management structures and practices involving the agency of corporate management. More broadly, [40] finds that, in developed countries, corporate, domestic, and global governance interact and mediate each other as drivers of participation in CDP while the main drivers of participation and the extent of voluntary climate-related disclosure in developing countries are corporate management structures and practices, the stringency of domestic regulatory institutions, and their interactions.

In addition to the increased focus on the specific case of climate-related disclosure, the focus also moved from understanding what drives disclosure to the relation of climate-related disclosure on future climate performance. However, existing evidence remains contradictory. [42] found a positive relationship between climate-related disclosure and climate performance, while [22] found that companies adopting voluntary reporting guidelines, such as the guidelines from the Global Reporting Initiative (GRI), are more likely to implement emission reduction policies but do not improve their climate performance. [43] finds mixed evidence on the association of climate-related disclosure and climate performance. While non-GHG-intensive sectors engage in “cheap talk” regarding their voluntary disclosure, GHG-intensive sectors show a positive association between basic climate-related disclosure and climate performance. [44] found no correlation between GRI reporting and a company’s emissions. In terms of mandatory carbon disclosure, [19,45,46] found a positive relationship between mandatory reporting and emission reductions for absolute emissions as well as emission intensities, while [18] found that companies affected by mandatory disclosure improved their emission intensity (emissions in relation to company size) significantly more than unaffected companies, but not their absolute emissions.

Individual corporate climate policies

Concerning public policymaking, there is ample evidence that national climate policies have had an effect on emissions reductions [47]. With the introduction of the recommendations of the Financial Stability Board’s Task Force on Climate-related Financial Disclosures (TCFD) in 2017, the disclosure of corporate climate policies has gained momentum in the corporate world [48]. The TCFD recommends disclosure across four management areas, including governance, strategy, risk management, as well as metrics and targets, which have been integrated into most sustainability reporting standards [13]. The ultimate idea is that the introduction of corporate climate policies is associated with climate performance. As outlined above, this notion is supported by the management-oriented view in the financial disclosure literature, which argues that disclosed corporate climate policies are associated with climate performance as their implementation and related defined measures, processes and responsibilities subsequently lead to improved climate performance [32–34]. For instance, introducing an emission reduction target may shape operational and emission-relevant decisions on various levels of the company or introducing mitigation initiatives may lead to direct changes in company guidelines and behaviors.

Accordingly, we propose the following hypothesis:

  1. H1: The adoption of corporate climate policies is associated with an improvement in climate performance.

While this argument may appear trivial, it is not a given in this context. Some companies may introduce corporate climate policies primarily to enhance or repair their organization’s perceived legitimacy in society, without necessarily resulting in actual emission reductions [27,29–31]

To date, the empirical evidence on the link between corporate climate policies and climate performance remains inconclusive (see Table A in S1 Text for an overview of previous literature). [20] studied the relationship between emission reduction targets on subsequently reduced emissions but found no overall association between setting GHG emission reduction targets with emissions reductions and only a significant association between absolute targets (rather than intensity targets) and emission reductions. [49] analyzed the relationship between corporate climate strategy and reduction initiatives and a company’s GHG emissions but also did not find a significant link of these implementation tools and emission levels. Conversely, [50] find that corporate decarbonization activities are associated with emission reductions on the facility level but the main drivers of corporate facility decarbonization are state-level climate policies. [22] found that governance tools, such as executive compensation are associated with reduced emission intensities, but no link to absolute emission reductions could be identified. [51] found that an internal carbon price also adhering to the group of governance mechanisms is significantly associated with lower emission intensities. [52] investigate the relationship between environmental audits and third-party verification, which fall in the area of MRV and found corporate climate policies to be more strongly associated with emission reductions if accompanied by a third-party audit. Still, the vast majority of studies are limited to investigating single corporate climate policies or a very narrow area of possible corporate climate policies. If there is a broader scope of corporate climate policies covered, they are usually represented by an aggregated score, disguising the effect of policies from specific areas [21,52,53]. There is only one study by [54] that builds on 23 disentangled corporate climate policies but finds only very limited evidence that these policies are associated with a company’s GHG emissions. However, the analysis is based on a relatively small data set of fewer than 500 companies with corporate climate policies data from 2010 and emissions data from 2009 and 2010 (hence no effect over time could be studied).

Hence, this calls for a revaluation of the link between corporate climate policies and climate performance across a wider range of policies and based on an extended dataset.

Combining corporate climate policies

While the vast majority of studies are limited to investigating single corporate climate policies, it seems more realistic that a set of complementary policies is associated with emission reductions. To this end, we draw on public policy literature that has extensively investigated how different policies work in conjunction for an effective policy mix on the national or supernational level [23–26]. One important characteristic of policy mixes is comprehensiveness which implies that beyond targets and high-level planning elements, there is the need for at least one instrument in the mix that is dedicated to their implementation [24]. The positive effect of a comprehensive policy mix on policy outcome is also shown by empirical public policy studies [55,56]. Applied to the corporate context, it seems plausible that targets are most likely fulfilled through related implementation policies, which need to be governed as well as monitored to track the progress. Following this argumentation, enacting corporate climate policies in just one isolated area (e.g., targets) cannot prove successful if not accompanied by policies from other areas such as governance, implementation as well as MRV, which therefore requires a ‘comprehensive corporate climate policy mix’. Following this argumentation, we propose the following hypotheses:

  1. H2: The adoption of a comprehensive corporate climate policy mix (i.e., including targets, governance, implementation, and MRV measures) is associated with an improvement in climate performance.

Materials and methods

Data and sample

We draw on a dataset of the CDP climate change and supply chain program public responses from 15,827 companies between 2010 and 2022, which we complement with other company-specific data extracted from Refinitiv. CDP constitutes the most extensive global database on corporate climate policies and GHG emissions data, with disclosing companies making up more than half of global market capitalization and spanning most regions and industries. Investors constitute one of the main user groups with over 680 financial institutions and over US$130 trillion in assets requesting information from their portfolio companies through CDP [57]. The CDP database is also widely used in academic research on sustainable finance [58–60].

We define the final sample for our analysis in three steps aiming to maximize its relevance to public policymakers currently implementing (or considering implementing) disclosure mandates (see Fig A in S1 Text for a graphical representation of the sample selection). First, we focus on companies with headquarters based in OECD countries where disclosure mandates are primarily introduced or considered so far (e.g., the Corporate Sustainability Reporting Directive in the European Union or the SEC proposal on enhanced climate-related disclosure in the US). Second, we limit the sample to the companies reporting GHG emission data (scope 1 and 2) for at least 5 years to be able to observe the potential link between corporate climate policies and subsequent emission reductions for our sample companies over a longer time period. Third, we reduce the sample to companies that report an ISIN (International Securities Identification Number) at least once between 2010 and 2022. This enables us to match the CDP data with company-specific data from Refinitv.

The resulting sample consists of 1,749 companies and 17,198 observations between 2010 and 2022. As of 2019, the sample’s scope 1 emissions (3.39bn t CO2e) represent 9.2% of global emissions, while the sample’s scope 2 (location-based) emissions (0.63bn t CO2e) account for another 1.7% of global emissions which together is more than the total annual emissions of the European Union [61]. The sample is an unbalanced panel dataset as not every company reported to CDP every year, and not every observation contains data for every variable (some corporate climate policies have not been surveyed in the earlier years). It is also important to note that our sample does not constitute a random sample. While CDP invites most publicly traded and larger corporations to disclose, reporting is voluntary, and some companies decide not to publish. Thus, we cannot assess whether the act of disclosing itself is associated with subsequent emission reductions, and we cannot rule out that there is misrepresentation in the disclosure (e.g., motivated by greenwashing), although CDP reports has been found to be more comprehensive and accurate compared to corporate sustainability reports as they leave less leeway for own interpretation [62,63]. Nevertheless, the sample should serve well to assess the informative value of disclosed corporate climate policies, as CDP-reporting companies form likely the relevant set for investors aiming to decarbonize their portfolio emissions. On top, the large share of global emissions covered suggests relevant insights for public policymakers concerning the potential role of corporate climate action for capital reallocation. However, it should be noted that potential predictors for future emissions reductions identified for this sample which is focused on publicly traded and larger corporations from OECD countries may not serve as predictors in a similar way for other types of companies. Large companies may face higher pressure to show progress in reducing their emissions once corporate climate policies are communicated and therefore they could be a better predictor for large corporations compared to small ones. At the same time, small corporations might face less pressure to communicate corporate climate policies in the first way and thus might even take them more seriously if they decide to do so which would rather speak for a stronger predictive power of corporate climate policies for small companies.

Variables and regression model

For the dependent variable, we operationalize the climate performance as a continuous variable by using absolute emissions as well as emission intensities. Emission intensities are calculated by dividing absolute emissions by the company’s total revenue, following previous studies [19,20,42,49,53]. The carbon footprint of a company can be divided into three categories of emissions: scope 1 refers to direct emissions from a company’s own activities, scope 2 refers to emissions from the production of purchased energy (especially electricity), and scope 3 refers to emissions from up- and downstream activities along the value chain [64]. In our regression model, we rely on scope 1 and scope 2 location-based emissions as dependent variable. We solely rely on scope 2 location-based emissions and do not consider scope 2 market-based emissions in the dependent variable, as the latter have only been introduced by CDP in 2016 and have been criticized for not reflecting real emission reduction as they largely rely on the purchase of renewable energy certificates [65]. We do not include scope 3 emissions in our dependent variable following [20,49,51] since companies have only limited direct influence on those emissions through corporate climate policies, and they are subject to large inconsistencies and incompleteness [62,66,67]. The lack of comparability of scope 3 data prevails not only across companies but also within one company over time. Even if we looked at only one company over time, there would be a lack of comparability of scope 3 emissions levels as many companies increased their effort on scope 3 emission measuring and reporting over time (e.g., moving from initially only including business travel, to later covering the full scope of value chain emission including purchased goods and services and used of sold products). Additionally, scope 3 emissions are often estimated based on secondary data (e.g., by using spend-based emission factors–see [68])–and thus do not represent “actual”/primary data which could be influenced by corporate climate policies. To our knowledge, there is no paper with a similar analysis that includes scope 3 emissions in the dependent variable (see Table A in S1 Text for a detailed overview of existing literature).

For the independent variables, we extract corporate climate policies from CDP adhering to the four key areas as discussed above: targets, governance, implementation and MRV. The CDP dataset covers a wide range of corporate climate policies. We focus on questions with binary or categorical answers since long, individual answers are unlikely to serve in large-N analyses conducted by investors to decide whether to include a company in a climate-oriented portfolio. The main strategies to integrate ESG criteria used by institutional investors revolve around exclusion and avoidance, norm-based and inclusionary screening or best-in-class approaches. These are often done following a rule-book-based approach applied to criteria of good comparability in order to decide on exclusion or inclusion or by looking at objective metrics such as the emission intensity compared to investors [69]. This approach results in 13 corporate climate policies spread across the four key areas (see Table 1). We then operationalize the raw CDP data in three steps: First, the responses to all CDP questions belonging to the same corporate climate policies are collected across all years and CDP programs. Second, the responses are standardized: Since most CDP questions (and answer options) changed multiple times between 2010 and 2022, we match them thematically with near-same questions in other years. Third, the answers are operationalized for the statistical analysis by converting answers to a binary format (see section 3 in S1 Text for more details).

thumbnail
Download:
Table 1. Overview of the corporate climate policies studied (treated as binary–YES/NO).

https://doi.org/10.1371/journal.pclm.0000458.t001

Beyond the single policies shown in Table 1, we also use two different measures for comprehensiveness as independent variables: The comprehensive policy mix I requires the introduction of at least one policy from each of the four areas shown in Table 1 (targets, governance, implementation, MRV). Absolute target, board-level oversight, strategic integration and scope 3 disclosure or science-based target, monetary incentives, value-chain engagement and scope 1 verification are two examples for how a comprehensive policy mix I could look like. The comprehensive policy mix II requires the introduction of all corporate climate policies that have been included in the CDP questionnaire in a given year. We do not require the introduction of a science-based target or an internal carbon price for the completion of the comprehensive policy mix II. This is due to their unique characteristics (described in Section 4.1) which result in much lower adoption rates compared to other corporate climate policies especially in the first years of introduction (leading to a drop in companies with comprehensive policy mix II close to zero which would distort the effect). All other policies must be existent as soon as they are included in the CDP questionnaire to meet the requirements of the comprehensive policy mix II. For example, in 2013, value chain engagement needs to be introduced by a company to have a comprehensive policy mix II. Importantly, we also differentiate in the policy mix definition between our dependent variables as we exclude intensity targets for both types of mixes for regressions with absolute emissions as depedent variable and exclude absolute targets for both types of mixes for regressions with absolute emissions as dependent variable. The rationale behind this approach is that absolute targets aim to reduce absolute emissions, while intensity targets aim to reduce emission intensities. Since a substantial share of companies only introduced one of the two targets (see Section 4.1 for descriptive results), allowing intensity targets for policy mix I and requiring them for policy mix II would distort the effect on absolute emissions (or vice versa for absolute targets for emission intensities).

We incorporate several control variables into our analysis (see Table E in S1 Text for the rationale behind each control variable and the related data source). These include the sector and regional location of the companies. In addition, we include additional company-specific and country-specific controls. For the company-specific controls, we consider total revenues as a proxy for company size, the debt ratio, and a binary variable to indicate whether a company was publicly traded during a specific year. To further account for variations, we calculate a company’s baseline emissions in relation to those of its sectoral and regional peers by determining the percentile of emissions for each sector, region, and year (see Table D in S1 Text for sector definitions). As country-specific control, we use the green financial policy density of the country of the company’s headquarter to account for the potential influence of green finance regulation, including disclosure mandates [7].

Table 2 shows the correlation between all independent variables shown in Table 1 and control variables which is reasonably low with correlation coefficients never exceeding 0.4 except for incentives and monetary incentives (0.811), scope 1 verification and scope 2 verification (0.885), and percentile of absolute emissions and percentile of emission intensities (0.889) (see Table F-R in S1 Text for all correlation coefficients on a yearly level). From a corporate management perspective, this seems plausible given that monetary incentives represent a specific kind of Incentives and scope 1 and scope 2 emissions are likely to be verified together. To avoid multicollinearity issues, we, therefore, exclude the variables incentives and scope 2 verification from the regression analyses, given that monetary incentives are the more stringent policy and scope 1 emissions are almost five times higher in our sample compared to scope 2 emissions. The high positive correlation of the percentile of absolute emissions and percentile of emission intensities also seems plausible given that high emitting sectors usually come with high absolute emissions as well as high emission intensities. However, this does not pose an issue for our model as they are never used in the same specification as only one of each is included in accordance with the dependent variable.

thumbnail
Download:
Table 2. Descriptive statistics and correlation coefficients.

https://doi.org/10.1371/journal.pclm.0000458.t002

We use a fixed effects (FE) model to evaluate the link between corporate climate policies and subsequent GHG emissions. Previous studies suggest a time lag exists between adopting corporate climate policies and potential reductions in GHG emissions (Dahlmann et al., 2019; Doda et al., 2016; Qian & Schaltegger, 2017). Following the findings of those studies, the model lags the emission data by one year, so emissions data of year t+1 are regressed on corporate climate policies of year t. To test H1, we run multiple specifications: We study each corporate climate policy separately (as did the vast majority of previous studies). Thus, we aim to establish benchmark specifications, which come closest to previous model setups. To test H2, we regress a dummy which indicates whether a company discloses a comprehensive corporate climate policy mix. We only include one type of comprehensive policy mix per regression specification. While all model results are presented in Section 4, S1 text provides additional sample descriptives. To summarize our regression model with Eq 1 being linked to H1 and Eq 2 being linked to H2: (1) (2) where Climate performancei,t+1 are the absolute emissions or emission intensity of company i in year t+1. a denotes the Corporate climate policy (Eq 1) disclosed by company i in year t, with Climate management practicesi,t,a,. and Comprehensive practices combination I/IIi,t being the respective dummy indicating if the policy or the mix is present. account for the company size, the capital structure, the ownership structure and the emission baseline of a company i in year t, sector c and region d. Green financial policy densityi,b represents the number of green finance regulations, including disclosure mandates, in country b in year t while εi,t,b,c,d denotes the error term. To control for additional confounders, all equations also include FEs at the year (αt), sector (γc) and region (δd) level—see Table C and Table D in S1 Text for a detailed overview of the regions and sectors applied (defined regions: Asia, Europe, North America, Ozeanien, South America). This is in line with previous studies such as [20] who also use year, region and sector FEs but goes beyond most previous studies which only applied sector and year FEs [70–73]. As more recent studies with larger datasets increasingly resort to year as well as entity-level FEs–either at the corporate or facility level [18,19,50,53], we also calculate each specification with company and year FEs to test the robustness of the main specification (while leaving out region and sector fixed effects in these specifications to avoid multicollinearity issues). For all our models we use robust standard errors which computed using the Huber-White heteroskedasticity-consistent estimator (see section 4.3 in S1 Text for Breusch-Pagan test results indicating the need for robust standard errors).

With our empirical design, we address potential biases that could affect the relationship between disclosed corporate climate policies and subsequent emission reductions and take measures to mitigate their impact on our results. Firstly, to address omitted variable bias, we employ company-level fixed effects next to year fixed effects in our analysis. By doing so, we also account for company-specific variables that may influence both the disclosure of corporate climate policies and emission reductions. This approach surpasses previous studies that have solely relied on sector-fixed effects, allowing us to capture a more nuanced understanding of the relationship between disclosure and emissions. Secondly, regarding reverse causality, we acknowledge that our focus lies on the predictive value of corporate climate policies for firm-level emission reductions rather than establishing causal relationships. Understanding the correlation between disclosure and emissions reduction can be valuable for investors and policymakers, irrespective of the direction of the effect. Lastly, concerning collider bias, we note that our sample comprises the relevant population for investors, namely large and publicly traded companies. We incorporate numerous control variables, including regulatory pressure represented by green financial policy density, to account for potential confounding factors. Even if unobservable factors influence company-level emissions, our analysis remains relevant for understanding the link between corporate climate policies and emissions reduction within this specific population. By addressing these potential biases and providing context for their relevance to our study, we aim to offer a comprehensive assessment of the relationship between disclosed corporate climate policies and subsequent emission reductions.

Results

Descriptive results

Fig 1 illustrates the evolution of corporate climate policies from 2010–2022. The number of disclosed implemented policies has grown from below 4,000 in 2010 to more than 14,000 in 2022 given that more and more companies of our sample reported to CDP (964 in 2010 and 1,405 in 2022). While corporate climate policies from the areas targets, governance, and MRV were already part of the disclosed corporate climate policies in 2010, implementation policies entered CDP in 2011.

thumbnail
Download:
Fig 1. Evolution of existent corporate climate policies (treated as binary–YES/NO) across sample companies from 2010–2022.

https://doi.org/10.1371/journal.pclm.0000458.g001

Zooming in on the single corporate climate policies of the four complementary areas shown in Fig 1 (right part), we see that the adoption increased substantially for all policies between 2010 and 2022. Some policies were adopted very quickly after their introduction to CDP (e.g., strategic integration at 88.5% or value chain engagement at 72.4% in the first year) while others entered on a rather low adoption level (e.g., internal carbon price at 18.9% or science-based targets at 6.8% in the first year). In 2022, five corporate climate policies were adopted by almost all companies in 2021, with adoption rates exceeding 90%: board-level oversight (100%), strategic integration (99%), value-chain engagement (98%), scope 3 disclosure (95%), mitigation initiatives (94%), and incentives (91%). High adoption rates (above 75% in 2022) were observed for monetary incentives (89%), scope 1 verification (83%), absolute targets (82%), and scope 2 verification (81%). Only three corporate climate policies were adopted by less than half of all companies in 2022: internal carbon price (49%), intensity targets (37%) and science-based targets (36%). Notably, neither absolute nor intensity targets are adopted by a very high number of companies, but almost 95% of organizations had at least one type of emission reduction target in 2022. Companies tend to either have absolute or intensity targets. The low adoption of an internal carbon price and science-based targets may be the result of their late introduction to CDP questionnaires in 2015 and 2017, but also their special nature, as the internal carbon price has been initially mainly attractive for certain sectors that were already targeted by carbon pricing (e.g., through the EU Emissions Trading System) and science-based targets have been governed by the newly set-up SBT initiative that had to establish itself and took time to develop (sector-specific) guidance.

Concerning the two measures for comprehensiveness, we show two different specifications per mix that are subsequently used for the two different dependent variables as shown in Fig 2. The first specification only includes absolute targets (used for the regressions with absolute emissions as dependent variable) and the second specification only includes intensity targets (used for the regressions with emission intensities as dependent variable). Looking at the level of adoption for the four specifications, we observe that in 2022, more than 80% of companies reporting to CDP adopted the comprehensive policy mix I (including absolute targets) rising from a level of just under 35% in 2011. For the comprehensive policy mix II (including absolute targets), the share still amounts to almost 65% in 2022 up from a level of less than 10% in 2010. When only considering intensity targets instead of absolute targets in both policy mixes, the shares in 2022 are substantively lower (58% and 27%) representing the decline in intensity targets since 2017.

thumbnail
Download:
Fig 2.

Number of companies with a comprehensive policy mix I (A and B) and a comprehensive policy mix II (C-D).

https://doi.org/10.1371/journal.pclm.0000458.g002

Regression results

Fig 3 shows an overview of the results of the FEs regression model for all corporate climate policies with absolute emissions (panel a) and emission intensity (panel b) as the dependent variable while controlling for sector-, region-, and year-specific effects (green lines) and company- and year-specific effects (blue lines). The light green and light blue lines represent the coefficients for regressing GHG emissions on each corporate climate policy separately while the dark green and dark blue lines represent the models which include all 13 corporate climate policies at the same time.

thumbnail
Download:
Fig 3.

Relationship between corporate climate policies and absolute emissions (panel a) and emission intensities (panel b) as the dependent variable. The error bars represent the standard errors. Robust standard errors are computed using the Huber-White heteroskedasticity-consistent estimator. The specifications include either sector, region, and year fixed effects (green lines) or company and year fixed effects (blue lines). Across all specifications, log-transformed revenue the debt ratio, a dummy to indicate a public company, the percentile of emissions as well as the green financial policy density in the country of the company’s headquarters serve as control variables. The dependent variable includes scope 1 and 2 emissions and is lagged by one year. All specifications only include observations for which all variable data is present (the number of observations for each specification is shown in Tables 3–6).

https://doi.org/10.1371/journal.pclm.0000458.g003

In total, the vast majority of corporate climate policies is not statistically significantly associated with better or worse climate performance across specifications. When looking at the specifications including sector, region- and year FEs, we find absolute targets and science-based targets being associated with lower absolute emissions on a 0.1% and 1% significance level and internal carbon prices and scope 1 verification as well as monetary incentives associated with higher absolute emissions on a 0.1% as well as a 5% significance level, respectively (see Table 3). For emission intensities, science-based targets are associated with lower emission intensities on a 5% significance level but all other significant correlations are associated with higher emission intensities (see Table 4). However, when including company FEs instead of sector and region FEs, associations do not remain significant for absolute emissions for individual policies except for monetary incentives and internal carbon price although effect sizes decrease substantially while and strategic integration turns significantly correlated (see Table 5). For emission intensities, no significant association remains and science-based targets even turn from negatively correlated to being positively correlated (see Table 6). Overall, the findings on individual corporate climate policies remain rather inconclusive, especially when including company-specific FE, which is important to note given that the vast majority of previous studies did not additionally control for company-specific FE bias in their models, resulting in potentially misleading results. Based on the results, we find no evidence to support H1 as there is no clear indication of whether or which individual corporate climate policies are associated with an improvement in climate performance.

thumbnail
Download:
Table 3. Relationship between corporate climate policies and absolute emissions as the dependent variable with sector, region, and year fixed effects.

The dependent variable includes scope 1 and 2 emissions and is lagged by one year. All specifications only include observations for which all variable data is present. Robust standard errors are computed using the Huber-White heteroskedasticity-consistent estimator.

https://doi.org/10.1371/journal.pclm.0000458.t003

thumbnail
Download:
Table 4. Relationship between corporate climate policies and emission intensities as the dependent variable with sector, region, and year fixed effects.

The dependent variable includes scope 1 and 2 emissions and is lagged by one year. All specifications only include observations for which all variable data is present. Robust standard errors are computed using the Huber-White heteroskedasticity-consistent estimator.

https://doi.org/10.1371/journal.pclm.0000458.t004

thumbnail
Download:
Table 5. Relationship between corporate climate policies and absolute emissions as the dependent variable with company and year fixed effects.

The dependent variable includes scope 1 and 2 emissions and is lagged by one year. All specifications only include observations for which all variable data is present. Robust standard errors are computed using the Huber-White heteroskedasticity-consistent estimator.

https://doi.org/10.1371/journal.pclm.0000458.t005

thumbnail
Download:
Table 6. Relationship between corporate climate policies and emission intensities as the dependent variable with company and year fixed effects.

The dependent variable includes scope 1 and 2 emissions and is lagged by one year. All specifications only include observations for which all variable data is present. Robust standard errors are computed using the Huber-White heteroskedasticity-consistent estimator.

https://doi.org/10.1371/journal.pclm.0000458.t006

To test whether companies that disclose a comprehensive corporate climate policy mix are associated with improved climate performance (hypothesis 2), we show and overview of the regression results for the comprehensive policy mix I and the comprehensive policy mix II in Fig 4.

thumbnail
Download:
Fig 4. Relationship between the comprehensive policy mix I (i.e., at least one policy introduced from each of the four areas) and the comprehensive policy mix II (i.e., all corporate climate policies introduced that have been included in the CDP questionnaire in a given year) and absolute emissions (panel a) and emission intensities (panel b) as the dependent variable.

The error bars represent the standard errors. Robust standard errors are computed using the Huber-White heteroskedasticity-consistent estimator. The specifications include either sector, region, and year fixed effects as well as company and year fixed effects. Across all specifications, log-transformed revenue, the debt ratio, a dummy to indicate a public company, the percentile of emissions as well as the green financial policy density in the country of the company’s headquarters serve as control variables. The dependent variable includes scope 1 and 2 emissions and is lagged by one year. All specifications only include observations for which all variable data is present (the number of observations for each specification is shown in Tables 7 and 8).

https://doi.org/10.1371/journal.pclm.0000458.g004

When looking at absolute emissions (Fig 4A), we find both measures for a comprehensive policy mix to be significantly correlated with lower absolute emissions on the 1% level when including sector, region and year FEs. Looking at the effect sizes, we see that the two measures for comprehensiveness are associated with decreased absolute emissions of 711.4 or 792.9 kt CO2e in the main specification (Table 7) which corresponds to 21% or 23% of the average absolute emissions of all observations in our sample, respectively. When including company and year FEs, the comprehensive policy mix I turns insignificant while the comprehensive policy mix II remains significant on the 5% level, although effect sizes decrease substantially to almost half of the level in the main specification (see Table 8). This highlights the importance of also looking at the effect of company fixed effects as they have a strong influence on significance levels and effect sizes. Our findings support our hypothesis that a comprehensive mix of policies from different areas serves as an indicator for subsequent emission reduction. However, our findings indicate that introducing any corporate climate policy from each area is associated less clearly with emission reductions than introducing the entire range of policies available. For emission intensities (Fig 4B), we find only the comprehensive policy mix II to be significantly correlated with higher intensities on the 1% level. However, the correlation’s significance dissipates when including company fixed effects (Table 8). As outlined in the Descriptive Results section, neither absolute nor intensity targets are adopted by a very high number of companies, but almost 95% of organizations had at least one type of emission reduction target in 2022. Consequently, the rationale to only consider absolute targets for absolute emissions and intensity targets for emission intensities is that they tend to be introduced by different companies (which apparently pursue different decarbonization goals, i.e., on absolute or relative bases, reflecting the nature of their business. As initially assumed, we do not find any significant correlation of the policy mixes and emission reductions of absolute emissions or emission intensities if we allow for any target in the comprehensive policy mix I or require all targets in policy mix II.

thumbnail
Download:
Table 7. Relationship between the comprehensive policy mix I (i.e., at least one policy introduced from each of the four areas) and the comprehensive policy mix II (i.e., all policies introduced that have been included in the CDP questionnaire in a given year) and absolute emissions (specifications 1+2) and emission intensities (specifications 3+4) as the dependent variable with sector, region, and year fixed effects.

The dependent variable includes scope 1 and 2 emissions and is lagged by one year. All specifications only include observations for which all variable data is present. Robust standard errors are computed using the Huber-White heteroskedasticity-consistent estimator.

https://doi.org/10.1371/journal.pclm.0000458.t007

thumbnail
Download:
Table 8. Relationship between the comprehensive policy mix I (i.e., at least one policy introduced from each of the four areas) and the comprehensive policy mix II (i.e., all policies introduced that have been included in the CDP questionnaire in a given year) and absolute emissions (specifications 1+2) and emission intensities (specifications 3+4) as the dependent variable with company and year fixed effects.

The dependent variable includes scope 1 and 2 emissions and is lagged by one year. All specifications only include observations for which all variable data is present. Robust standard errors are computed using the Huber-White heteroskedasticity-consistent estimator.

https://doi.org/10.1371/journal.pclm.0000458.t008

Based on our results, we find support for H2 as comprehensive policy mixes show significant correlations but only for absolute emissions as the dependent variable. Notably, the level of evidence varies across different measures of comprehensiveness.

Discussion and conclusion

In this article, we assess corporate climate action by addressing the question of whether the existence of corporate climate policies (or a mix of them) is associated with improved climate performance. In line with previous studies, we find mixed empirical evidence for the link between individual policies and subsequent emission reductions. Our results suggest, in line with findings from public policy research, which has extensively studied the need for complementary instruments, that single corporate climate policies do not show a clear association with subsequent climate performance (no significant link over specifications). However, we find that a combination of policies in a comprehensive policy mix is of relevance for improved climate performance with effect sizes in line with a decrease of 21% or 23% of the average absolute emissions of all observations in our sample, respectively, for the two measures of comprehensiveness in our main specification. Notably, the level of evidence varies across different measures of comprehensiveness. While the first measure of comprehensiveness which requires only one policy from different complementary areas loses its significance when also controlling for company fixed effects, the second measure of comprehensiveness which requires the introduction of all corporate climate policies remains significant. This finding indicates that companies that do not cherry-pick specific policies but introduce an entire range of policies show a stronger association with emission reductions.

Notably, our findings only apply to absolute emissions as the dependent variable and not emission intensity which can be due to several reasons. One is that emission intensity is a more subjective metric compared to absolute emissions given that there are multiple ways to scale emissions (although scaling by revenues as we did is the most established approach). Given that absolute emissions are considered the more relevant metric from a public policy viewpoint [20] and also gain increased relevance in the sustainable finance literature [74,75], we believe our findings provide extremely valuable insights on the association with corporate climate policy mixes. At the same time, our findings underline the importance of differentiating between emission intensity and absolute emission [76] and we would argue that it is reasonable to assess both metrics as they are complementary to each other. Additionally, our research design only allows for measuring the comprehensiveness of a corporate climate policy mix and does not consider other dimensions that have been found to be relevant in public policy mixes such as the stringency of the underlying instruments [77–80]. Previous literature focusing on individual policies such as [20] has attempted to measure the stringency of instruments by including different nuances of a policy (e.g., scope of a target). Consequently, further research could build on our findings on the relevance of policy mixes and combine them with an assessment of instrument stringency. Such approaches could be also applied beyond the CDP universe of our sample which is mainly limited to larger and public companies and does not allow to draw conclusions about companies that do not report through the CDP. Another area for further investigation is better understanding the effect of corporate climate policies compared to state-level or local regulatory climate actions. Initial studies, such as [50], have begun comparing effects at the facility level. However, given that many companies operate globally, a next step could be to include a diverse set of regulatory actions from various jurisdictions to derive a comprehensive picture at the corporate level. This approach goes beyond merely controlling for financial policies at the headquarters level, as done in our specifications.

For investors, our results indicate that single corporate climate policies have only limited informative value for a company’s future GHG emissions. This makes it difficult for investors to differentiate ‘the good from the bad’ from an outside-in perspective. This is specifically problematic for sectors that are still considered high-carbon sectors today but are essential to decarbonize and require appropriate financing for doing so. However, our results show that a comprehensive policy mix may be a helpful indicator to identify potential portfolio companies for successful shareholder engagement which is one of the commonly proposed approaches to drive fossil fuel phase-out [11]. Thus, climate-conscious investors should not only take a closer look at corporate governance structures, which have been found to be positively linked to financial performance [81,82], but also at the mix of corporate climate policies specifically designed to improve climate performance.

For public policymakers, and societal actors more broadly, our results have twofold implications. The initial evidence that we identified for the association of corporate climate policy mixes with absolute emission reductions may represent a starting point in the design of mandatory disclosure requirements. To enable investors to identify companies with effective corporate climate strategies, disclosure mandates should require information across complementary areas to enable assessing the comprehensiveness of the applied corporate climate policy mix. More generally, however, our findings draw a rather inconclusive picture of the general relationship of corporate climate policies and climate performance, which is in line with previous literature. However, we cannot rule out that there is also a certain level of misrepresentation in CDP questionnaires that leads to an exaggeration of the seriousness of the taken climate action (e.g., motivated by greenwashing) and causes the weak link between corporate climate policies and actual emissions reductions. This calls for further research to analyze the reliability of reporting (i.e., through case studies and small-n analyses) and to investigate the underlying incentives of introducing and disclosing corporate climate policies to lay the foundation to test causal mechanisms. Based on the current evidence, mandating the disclosure of corporate climate policies may at best complement a public policy mix aiming to redirect capital. Relying too heavily or even completely on the power of disclosure and corporate climate action seems illusive.

References

  1. 1. Bataille C, Waisman H, Colombier M, Segafredo L, Williams J, Jotzo F. The need for national deep decarbonization pathways for effective climate policy. Climate Policy. 2016;16(sup1):S7–S26.
  2. 2. IPCC. CLIMATE CHANGE 2023 Synthesis Report Summary for Policymakers; 2023. Available from: https://www.ipcc.ch/report/ar6/syr/downloads/report/IPCC_AR6_SYR_SPM.pdf.
  3. 3. Monasterolo I, Battiston S, Janetos AC, Zheng Z. Vulnerable yet relevant: the two dimensions of climate-related financial disclosure. Climatic Change. 2017;145(3–4):495–507.
  4. 4. Busch T, Bauer R, Orlitzky M. Sustainable Development and Financial Markets. Business & Society. 2016;55(3):303–29.
  5. 5. Egli F, Schärer D, Steffen B. Determinants of fossil fuel divestment in European pension funds. Ecological Economics. 2022;191:107237.
  6. 6. Jeanne A, Demaria S, Rigot S. What are the drivers of corporates’ climate transparency? Evidence from the S&P 1200 index. Ecological Economics. 2023;213:107945.
  7. 7. Steffen B. A comparative analysis of green financial policy output in OECD countries. Environ. Res. Lett. 2021;16(7):74031.
  8. 8. Steffen B, Michaelowa A. Policies for climate finance: Status and research needs. PLOS Climate. 2022;1(10):e0000083.
  9. 9. Bhandary RR, Gallagher KS, Zhang F. Climate finance policy in practice: a review of the evidence. Climate Policy. 2021;21(4):529–45.
  10. 10. Hidalgo-Oñate D, Fuertes-Fuertes I, Cabedo JD. Climate-related prudential regulation tools in the context of sustainable and responsible investment: a systematic review. Climate Policy. 2023:1–18.
  11. 11. McDonnell C, Gupta J. Beyond divest vs. engage: a review of the role of institutional investors in an inclusive fossil fuel phase-out. Climate Policy. 2023:1–18. pmid:38533313
  12. 12. TCFD. Recommendations of the Task Force on Climate-related Financial Disclosures; 2017. Available from: https://assets.bbhub.io/company/sites/60/2021/10/FINAL-2017-TCFD-Report.pdf.
  13. 13. IFRS. IFRS Foundation announces International Sustainability Standards Board, consolidation with CDSB and VRF, and publication of prototype disclosure requirements; 2021. Available from: https://www.ifrs.org/news-and-events/news/2021/11/ifrs-foundation-announces-issb-consolidation-with-cdsb-vrf-publication-of-prototypes/.
  14. 14. Block JH, Sharma P, Benz L. Stakeholder Pressures and Decarbonization Strategies in Mittelstand Firms. J Bus Ethics. 2023:1–23.
  15. 15. CDP. Mainstreaming transparency; 2023. Available from: https://www.cdp.net/en/companies/companies-scores.
  16. 16. Ameli N, Drummond P, Bisaro A, Grubb M, Chenet H. Climate finance and disclosure for institutional investors: why transparency is not enough. Climatic Change. 2020;160(4):565–89.
  17. 17. Ameli N, Kothari S, Grubb M. Misplaced expectations from climate disclosure initiatives. Nat. Clim. Chang. 2021;11(11):917–24.
  18. 18. Bauckloh T, Klein C, Pioch T, Schiemann F. Under Pressure? The Link Between Mandatory Climate Reporting and Firms’ Carbon Performance. Organization & Environment. 2022:108602662210833.
  19. 19. Downar B, Ernstberger J, Reichelstein S, Schwenen S, Zaklan A. The impact of carbon disclosure mandates on emissions and financial operating performance. Rev Account Stud. 2021;26(3):1137–75.
  20. 20. Dahlmann F, Branicki L, Brammer S. Managing Carbon Aspirations: The Influence of Corporate Climate Change Targets on Environmental Performance. J Bus Ethics. 2019;158(1):1–24.
  21. 21. Luo Le, Tang Q. Corporate governance and carbon performance: role of carbon strategy and awareness of climate risk. Account Finance. 2021;61(2):2891–934.
  22. 22. Haque F, Ntim CG. Executive Compensation, Sustainable Compensation Policy, Carbon Performance and Market Value. Brit J Manage. 2020;31(3):525–46.
  23. 23. Kern F, Howlett M. Implementing transition management as policy reforms: a case study of the Dutch energy sector. Policy Sci. 2009;42(4):391–408.
  24. 24. Rogge KS, Reichardt K. Policy mixes for sustainability transitions: An extended concept and framework for analysis. Research Policy. 2016;45(8):1620–35.
  25. 25. Schmidt TS, Sewerin S. Measuring the temporal dynamics of policy mixes–An empirical analysis of renewable energy policy mixes’ balance and design features in nine countries. Research Policy. 2019;48(10):103557.
  26. 26. van den Bergh J, Castro J, Drews S, Exadaktylos F, Foramitti J, Klein F, et al. Designing an effective climate-policy mix: accounting for instrument synergy. Climate Policy. 2021;21(6):745–64.
  27. 27. Patten DM. The relation between environmental performance and environmental disclosure: a research note. Accounting, Organizations and Society. 2002;27(8):763–73.
  28. 28. Clarkson PM, Li Y, Richardson GD, Vasvari FP. Revisiting the relation between environmental performance and environmental disclosure: An empirical analysis. Accounting, Organizations and Society. 2008;33(4–5):303–27.
  29. 29. Castelo Branco M, Lima Rodrigues L. Communication of corporate social responsibility by Portuguese banks. Corporate Communications: An International Journal. 2006;11(3):232–48.
  30. 30. Cormier D, Gordon IM, Magnan M. Corporate Environmental Disclosure: Contrasting Management’s Perceptions with Reality. J Bus Ethics. 2004;49(2):143–65.
  31. 31. Patten DM. An insider’s reflection on quantitative research in the social and environmental disclosure domain. Critical Perspectives on Accounting. 2015;32:45–50.
  32. 32. Burritt RL, Schaltegger S. Sustainability accounting and reporting: fad or trend? Accounting, Auditing & Accountability Journal. 2010;23(7):829–46.
  33. 33. Boons F, Strannegård L. Organizations Coping with Their Natural Environment. International Studies of Management & Organization. 2000;30(3):7–17.
  34. 34. Schaltegger S, Wagner M. Integrative management of sustainability performance, measurement and reporting. IJAAPE. 2006;3(1):1.
  35. 35. Wegener M, Elayan FA, Felton S, Li J. Factors Influencing Corporate Environmental Disclosures. Accounting Perspectives. 2013;12(1):53–73.
  36. 36. Ben-Amar W, Chang M, McIlkenny P. Board Gender Diversity and Corporate Response to Sustainability Initiatives: Evidence from the Carbon Disclosure Project. J Bus Ethics. 2017;142(2):369–83.
  37. 37. Hsueh L. Transnational Climate Governance and the Global 500: Examining Private Actor Participation by Firm-Level Factors and Dynamics. International Interactions. 2017;43(1):48–75.
  38. 38. Hsueh L. Opening up the firm: What explains participation and effort in voluntary carbon disclosure by global businesses? An analysis of internal firm factors and dynamics. Bus Strat Env. 2019;28(7):1302–22.
  39. 39. Delgado-Márquez BL, Pedauga LE, Cordón-Pozo E. Industries Regulation and Firm Environmental Disclosure: A Stakeholders’ Perspective on the Importance of Legitimation and International Activities. Organization & Environment. 2017;30(2):103–21.
  40. 40. Hsueh L. Corporations at a crossroads: How multilevel governance interactions shape participation and effort in private governance regimes. Governance. 2019;32(4):715–60.
  41. 41. Hsueh L. Voluntary climate action and credible regulatory threat: evidence from the carbon disclosure project. J Regul Econ. 2019;56(2–3):188–225.
  42. 42. Qian W, Schaltegger S. Revisiting carbon disclosure and performance: Legitimacy and management views. The British Accounting Review. 2017;49(4):365–79.
  43. 43. Hsueh L. Do businesses that disclose climate change information emit less carbon? evidence from S&P 500 FIRMS. Clim. Change Econ. 2022;13(02).
  44. 44. Belkhir L, Bernard S, Abdelgadir S. Does GRI reporting impact environmental sustainability? A cross-industry analysis of CO 2 emissions performance between GRI-reporting and non-reporting companies. MEQ. 2017;28(2):138–55.
  45. 45. Jouvenot V, Krueger P. Reduction in Corporate Greenhouse Gas Emissions Under Prescriptive Disclosure Requirements; 2019. Available from: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3434490.
  46. 46. Tomar S. Greenhouse Gas Disclosure and Emissions Benchmarking; 2023. Available from: http://ssrn.com/abstractid=3448904.
  47. 47. IPCC. Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; 2022. Available from:
  48. 48. Ding D, Liu B, Chang M. Carbon Emissions and TCFD Aligned Climate-Related Information Disclosures. J Bus Ethics. 2023;182(4):967–1001.
  49. 49. Damert M, Paul A, Baumgartner RJ. Exploring the determinants and long-term performance outcomes of corporate carbon strategies. Journal of Cleaner Production. 2017;160:123–38.
  50. 50. Leffel B, Lyon TP, Newell JP. Filling the climate governance gap: Do corporate decarbonization initiatives matter as much as state and local government policy? Energy Research & Social Science. 2024;109:103376.
  51. 51. Zhu B, Xu C, Wang P, Zhang L. How does internal carbon pricing affect corporate environmental performance? Journal of Business Research. 2022;145:65–77.
  52. 52. Aslam S, Rehman RU, Asad M. Linking environmental management practices to environmental performance: The interactive role of environmental audit. Pakistan Journal of Commerce and Social Sciences (PJCSS). 2020;14(1):99–119. Available from: https://www.econstor.eu/handle/10419/216866.
  53. 53. Luo Le, Tang Q. The real effects of ESG reporting and GRI standards on carbon mitigation: International evidence. Bus Strat Env. 2022.
  54. 54. Doda B, Gennaioli C, Gouldson A, Grover D, Sullivan R. Are Corporate Carbon Management Practices Reducing Corporate Carbon Emissions? Corp. Soc. Responsib. Environ. Mgmt. 2016;23(5):257–70.
  55. 55. Costantini V, Crespi F, Palma A. Characterizing the policy mix and its impact on eco-innovation: A patent analysis of energy-efficient technologies. Research Policy. 2017;46(4):799–819.
  56. 56. Reichardt K, Rogge K. How the policy mix impacts innovation: Findings from company case studies on offshore wind in Germany. Environmental Innovation and Societal Transitions. 2016;18:62–81.
  57. 57. CDP. CDP Media Factsheet; 2022. Available from: https://cdn.cdp.net/cdp-production/comfy/cms/files/files/000/003/419/original/CDP-Media-Factsheet.pdf.
  58. 58. Fang M, Tan KS, Wirjanto TS. Sustainable portfolio management under climate change. Journal of Sustainable Finance & Investment. 2019;9(1):45–67.
  59. 59. Kouloukoui D, Marinho , Marcia Mara de Oliveira, Da Gomes SMS, Kiperstok A, Torres EA. Corporate climate risk management and the implementation of climate projects by the world’s largest emitters. Journal of Cleaner Production. 2019;238:117935.
  60. 60. Tuhkanen H, Vulturius G. Are green bonds funding the transition? Investigating the link between companies’ climate targets and green debt financing. Journal of Sustainable Finance & Investment. 2022;12(4):1194–216.
  61. 61. Ritchie H, Roser M, Rosado P. CO₂ and Greenhouse Gas Emissions; 2020. Available from: https://ourworldindata.org/co2-and-greenhouse-gas-emissions.
  62. 62. Klaaßen L, Stoll C. Harmonizing corporate carbon footprints. Nat Commun. 2021;12(1):6149. pmid:34686675
  63. 63. Depoers F, Jeanjean T, Jérôme T. Voluntary Disclosure of Greenhouse Gas Emissions: Contrasting the Carbon Disclosure Project and Corporate Reports. J Bus Ethics. 2016;134(3):445–61.
  64. 64. Greenhouse Gas Protocol. A Corporate Accounting and Reporting Standard; 2004. Available from: https://ghgprotocol.org/corporate-standard.
  65. 65. Bjørn A, Lloyd SM, Brander M, Matthews HD. Renewable energy certificates threaten the integrity of corporate science-based targets. Nat. Clim. Chang. 2022;12(6):539–46.
  66. 66. Busch T, Johnson M, Pioch T. Corporate carbon performance data: Quo vadis? Journal of Industrial Ecology. 2022;26(1):350–63.
  67. 67. Nguyen Q, Diaz-Rainey I, Kitto A, McNeil BI, Pittman NA, Zhang R. Scope 3 emissions: Data quality and machine learning prediction accuracy. PLOS Climate. 2023;2(11):e0000208.
  68. 68. Stenzel A, Waichman I. Supply-chain data sharing for scope 3 emissions. npj Clim. Action. 2023;2(1):1–7.
  69. 69. OECD. OECD Business and Finance Outlook 2020: Sustainable and Resilient Finance; 2020. Available from: https://www.oecd-ilibrary.org/sites/b854a453-en/index.html?itemId=/content/component/b854a453-en.
  70. 70. Moussa T, Allam A, Elbanna S, Bani‐Mustafa A. Can board environmental orientation improve U.S. firms’ carbon performance? The mediating role of carbon strategy. Bus Strat Env. 2020;29(1):72–86.
  71. 71. Tang Q, Le Luo. Carbon Management Systems and Carbon Mitigation. Australian Accounting Review. 2014;24(1):84–98.
  72. 72. Jiang Y, Fan H, Zhu Y, Xu JF. Carbon disclosure: A legitimizing tool or a governance tool? Evidence from listed US companies. Financ Manag Account. 2023;34(1):36–70.
  73. 73. Coen D, Herman K, Pegram T. Are corporate climate efforts genuine? An empirical analysis of the climate ‘talk–walk’ hypothesis. Bus Strat Env. 2022;31(7):3040–59.
  74. 74. Bolton P, Kacperczyk M. Are Carbon Emissions Associated with Stock Returns? Comment. Rev Financ. 2023.
  75. 75. Bolton P, Kacperczyk M, Samama F. Net-Zero Carbon Portfolio Alignment. Financial Analysts Journal. 2022;78(2):19–33.
  76. 76. Busch T, Hoffmann VH. How Hot Is Your Bottom Line? Linking Carbon and Financial Performance. Business & Society. 2011;50(2):233–65.
  77. 77. Frondel M, Horbach J, Rennings K. What triggers environmental management and innovation? Empirical evidence for Germany. Ecological Economics. 2008;66(1):153–60.
  78. 78. Rogge KS, Schleich J, Haussmann P, Roser A, Reitze F. The role of the regulatory framework for innovation activities: the EU ETS and the German paper industry. IJTPM. 2011;11(3/4):250.
  79. 79. Rogge KS, Schneider M, Hoffmann VH. The innovation impact of the EU Emission Trading System—Findings of company case studies in the German power sector. Ecological Economics. 2011;70(3):513–23.
  80. 80. Schmidt TS, Schneider M, Rogge KS, Schuetz MJ, Hoffmann VH. The effects of climate policy on the rate and direction of innovation: A survey of the EU ETS and the electricity sector. Environmental Innovation and Societal Transitions. 2012;2:23–48.
  81. 81. Nag T, Chatterjee C. Exploring Linkages Between Corporate Governance and Business Performance: Does Good Corporate Governance Lead to Enhanced Business Value? South Asian Survey. 2020;27(1):37–61.
  82. 82. Affes W, Jarboui A. The impact of corporate governance on financial performance: a cross-sector study. Int J Discl Gov. 2023:1–21.