Skip to Content
MDPIMDPI

Advanced

SustainabilitySustainability
PDF
  • Article
  • Open Access

12 February 2025

35 Pages

Sustainable Business as a Force for Good in the Context of Climate Change: An Econometric Modelling Approach

and
1
Environment Europe Foundation, The Hague Humanity Hub, Fluwelen Burgwal 58, 2511CJ Hague, The Netherlands
2
SAA—School of Management, University of Torino, Via Ventimiglia, 115, 10126 Torino, Italy
*
Author to whom correspondence should be addressed.
Sustainability2025, 17(4), 1530;https://doi.org/10.3390/su17041530
This article belongs to the Section Economic and Business Aspects of Sustainability
Version Notes
Order Reprints

Abstract

Global CO2 concentrations continue to rise despite significant efforts to decarbonize and reduce greenhouse gas emissions. This paper examines the role of sustainable business in reducing and limiting global CO2 concentrations based on daily CO2 data from the Mauna Loa Observatory. Based on the theory of the carbon cycle, factors considered significant in determining global CO2 concentrations include emissions, affected by economic variables like the crude oil price and Dow Jones Sustainability Index but also absorption capacity, affected through biomass growth by astronomical variables such as total solar irradiance and cosmic rays. Considering pair-wise correlations between variables, particular attention is drawn to the fact that in the COVID-19 pandemic, when everyone was working from home, cars were not allowed on the roads, and planes were not flying, the correlation between the Dow Jones Sustainability Index and the global CO2 concentration was negative. The article tests the hypothesis that business can be a force for good and make a meaningful contribution towards reducing global CO2 concentrations. To this end, it offers an integrated model of global CO2 concentrations built according to the theory of the carbon cycle based on 2195 daily observations, including all the variables outlined above. The results confirm the hypothesis that business, expressed in the form of Dow Jones Sustainability Index, can play a role in reducing the global CO2 concentrations. A range of policy conclusions is drawn.

1. Introduction

The transformation of business models for sustainability, the role of impact investment as a transformational force and the role of business in driving sustainable progress have been embraced by a whole number of advocates including Cohen (2020) [1], Eccles, Ioannou, and Serafeim (2014) [2], Elkington (2021) [3], Carney (2021) [4], and Polman (2022) [5]. In this paper, we establish if sustainable business performance, as expressed in the Dow Jones Sustainability Index, impacts the global concentrations of CO2 and can be ultimately considered a force for good. For the purposes of this paper, we define a “force for good” as the ability of businesses to create measurable positive impacts on societal and environmental outcomes beyond merely generating profit. This encompasses actions that contribute to reducing global CO2 concentrations, fostering equitable economic development, and enhancing long-term sustainability [6,7,8,9,10,11,12]. To this end, we review recent contributions to the field of ESG investment, build a comprehensive econometric model of global CO2 concentrations, and try to explain the variance in CO2 emissions based on a whole range of variables. By doing so, we aim to determine whether sustainable business practices, as reflected in the Dow Jones Sustainability Index (DJSI), can substantively reduce CO2 levels and be considered a true “force for good”. The policy conclusions will follow.

2. Literature Review

Environmental, social, and governance (ESG) investment has become an important player in the global financial markets. According to Bloomberg Intelligence, the projected ESG assets under management of USD 53 trillion will represent approximately 36.9% of the total global assets under management by 2025, assuming a steady growth rate of 6.5%. The UN Principles for Responsible Investment define ESG as “the key factors used to measure the sustainability and societal impact of an investment in a company or business” [13]. ESG factors are increasingly important for investors, companies, and other stakeholders to assess risks, opportunities, and long-term performance. Many studies have examined various dimensions of ESG investing and reporting and have been predominantly focused on measuring the impact on financial performance. We conducted a rigorous and structured literature review of the major contributions to the ESG field, as shown in Table 1. In the table, the major studies are described in terms of the country of focus, methodology used, and the key findings. Below, we examine some of the contributions in more detail.
The findings indicate that ESG investing has, on average, performed similarly to conventional investing and sometimes even better [10,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]. More specifically, recent research demonstrates that there is a positive relationship between ESG and financial performance for 58% of the studies focused on operational metrics, such as ROE, ROA, or stock price, with 13% showing neutral impact, 21% showing mixed results, and only 8% showing a negative relationship (Whelan et al., 2021) [33]. According to some studies, ESG investing has been found to provide asymmetric benefits, particularly during social or economic crises, while in other studies, it has been demonstrated that companies with high engagement with ESG managed to perform better in periods of crisis thanks to high levels of resilience and lower volatility in the market [34]. Overall, ESG integration as a strategy has been shown to be more effective than screening or divestment (Krosinsky and Purdom, 2016) [35].
ESG is clearly a strategic priority for many businesses and interested stakeholders nowadays; indeed, it has been found that many studies were focused on analyzing the internal and external drivers of ESG engagement. According to Crace and Gehman (2023) [36], the most significant drivers came from within the firm and directly from the CEO. Furthermore, the authors indicate that negative ESG performance is usually correlated with external factors, whereas positive ESG performance has to deal with internal ones. These findings support a previous analysis of internal drivers made by Eccles et al. (2011) [37], who stated the significant influence of the board of directors and firm’s governance on the level of ESG engagement. In more sustainably-minded corporations, boards are more keen on overseeing environmental and social issues, while management compensation may include sustainability metrics alongside financial ones.
Table 1. Literature review table.
Eccles and Serafim (2013) [57] provide a step-by-step approach that helps in defining materiality in the ESG context. To achieve this aim, companies need to take four steps: establish which ESG issues are most important for their specific economic sector; estimate the potential financial savings stemming from resolving these issues; achieve the improvements and implement significant innovations in products, procedures, and, ultimately, business models; and finally share the innovations with stakeholders. Naturally, integrated reporting, which combines financial and ESG performance data into a single document, is a powerful tool to assist this process [25]. Freiberg et al. (2020) [16] investigated how ESG issues become material in financial fields in the context of the Purdue Pharma business case. The authors designed a framework that follows five steps on a journey that starts with the identification of a particular externality (related to an ESG issue) and reaches the disclosure of a specific regulation that tries to manage that specific ESG issue. Thus, the concept of materiality, as well as the level of impact, have a high relevance in this context.
Porter et al. (2019) [61] indicated that investors must consider social factors alongside financial metrics, recognizing their influence on long-term competitive advantage (shared-value investing), but in the article, they also criticize the efficiency of traditional ESG rankings and particularly its link with alpha generations or those born in the 21st century. The importance of effective communication between companies and investors regarding the economic value of social impact has increased noticeably; examples of the success of this type of investment are Generation Investment Management and Summa Equity.
Several authors acknowledge that investors should allocate capital toward companies driving social progress profitability, where capitalism is harnessed to address society’s most pressing needs while generating sustainable shareholder returns. The new movement called the B-Corp movement is built entirely around the idea that business could be a force for good. By embracing shared-value thinking, investors can unlock growth, foster innovation, and contribute to a more equitable and prosperous future for all stakeholders. ESG scores have gained prominence as primary financial tools for constructing green portfolios and evaluating companies’ performances in the field of responsible investment, as well as for enhancing transparency, trust, and credibility among stakeholders [38,41]. ESG scores mitigate risks associated with environmental or social scandals by anticipating potential negative impacts on investments. Companies that prioritize ESG considerations stand to gain not only enhanced market value but also improved financial performance and reduced risk exposure, which are, indeed, integral components of corporate strategy and value creation [38,39]. Friede et al. [42] also discussed the evolving landscape of environmental, social, and governance criteria within investment decisions and highlighted the slow adoption of sustainable investment practices among mainstream investors despite the significant assets managed under Principles for Responsible Investment signatories. Liennenluecke (2021) [41] argues that even if there is a shift toward sustainable investments, there are many challenges in the market due to weaker institutions, less stringent regulatory environments, and limited transparency.
Although there has been a higher interest in nonfinancial information since the late 1990s [25,62] (with the observed growth from 20 reporting organizations in 1999 to over 12,000 companies today), it has been noticed that the correlation between financial returns and such practices is not equivalent among environmental, governance, and social issues. Indeed, Huang (2019) [49] argues that environmental ESG measures tend to exhibit a stronger relationship with operational financial performance measures compared to social or governance ESG measures. Eccles et al. (2011) [56] instead state that environmental and governance metrics are the ones which investors are more interested in. Equity investors show more interest in ESG disclosure and GHG emissions data compared to fixed-income investors. This study also highlights disparities between broker–dealers and money managers with the same distinction as the previous ones. Serafim and Yoon (2022) [55] studied market reactions to diverse ESG news items and assessed the predictive power of ESG performance scores. The key findings reveal substantial market reactions to financially material ESG news, particularly positive news related to social capital issues like product impact. The study challenges traditional assumptions about investor responses to ESG news and underscores the evolving role of ESG considerations in investment strategies. Positive ESG news, especially regarding product quality and safety, drives significant market reactions, while negative news impacts market performance, particularly concerning customer welfare and GHG emissions. The research highlights the importance of unexpected news in influencing market dynamics and emphasizes the selective nature of market reactions to ESG news.
Menicucci and Paolucci (2022) [43] pointed out the effects of ESG in the banking sector. They assessed the feasibility of enhanced corporate governance, reduced environmental impact, and social responsibility programs. Environmental commitments positively impact efficiency and trust, while social initiatives may challenge profitability. Corporate governance, especially board diversity and risk governance, correlates positively with performance [63]. The empirical findings suggest varying impacts of ESG dimensions on bank performance, highlighting the complex relationship between ESG factors and profitability.
One of the consequences of the increase in engagement with ESG activities has been the development of ESG reporting and integration [63]. Organizations like Global Reporting Initiatives (GRIs), the Sustainability Accounting Standard Board (SASB), the International Integrated Reporting Committee (IIRC), and the Carbon Disclosure Project (CDP) are playing a crucial role in promoting disclosure and accountability [53,56]. Efforts by organizations like the Global Sustainable Investment Alliance and sustainable stock exchanges aim to improve ESG data availability and quality. There is still skepticism about the data’s accuracy, specifically in relation to data imputation methods that should be transparent to ensure the consistency and reliability of the data [53]. Linked to this trend, although there has been an increase in the number of sustainability reports published to enhance transparency, there is still the need for improvements in ESG reporting. Arvidsson et al. (2021) [50] underscore the importance of aligning ESG reporting with global standards and addressing sustainability challenges through proactive policies and enhanced reporting practices.
Eccles et al. (2014) [2] studied the difference in performance between 90 high-sustainability firms of the mid-1990s with similar low-sustainability firms. The main conclusions of their research are that high-sustainability firms exhibit a stronger governance structure, link executive compensation to sustainability metrics, engage stakeholders more proactively, and disclose more nonfinancial data. This suggests that integrating social and environmental issues into business strategies may yield long-term financial benefits and improve stakeholder relationships. Regarding corporate performance, high-sustainability firms tend to outperform low-sustainability firms over the long term. Overall, the results show that high-sustainability firms exhibit superior performance, with ESG activities as a source of competitive advantage, which helps companies in the SRI in the long term [37]. However, Eccles et al. argue that high-sustainability firms may underperform due to constraints imposed by their sustainability culture, or they may outperform due to better human capital, supply chains, community relations, and innovation. However, in the study proposed, high-sustainability firms significantly outperform low-sustainability firms, with annual abnormal performances higher by 4.8% on a value-weighted basis and 2.3% on an equal-weighted basis and exhibiting lower volatility in their performance.
Serafim and Yoon (2011) [58] examined the effects of sustainability disclosure regulations on corporate practices and valuations, and they highlighted that while the disclosure of ESG information could enhance firm value through improved management practices and stakeholder perceptions, it also imposes potential costs and risks on firms. In fact, they individualized positive aspects: improvement in management practices, operational efficiency, enhanced stakeholder trust, the attraction of socially responsible investors, and improved access to capital. The negative effects are that compliance costs could strain financial resources, and mandatory disclosure may reveal proprietary or competitively sensitive information, potentially causing strategic risks or disadvantages negatively affecting firm value. In another study, Serafim and Yoon (2022) [55] investigated whether consensus ESG ratings predict future ESG-related news and how disagreement among raters affects this predictive ability. Despite challenges in assessing ESG rating quality due to disagreement among raters and the multidimensional nature of ESG issues, consensus ratings can forecast future news. Positive ESG news prompts a market response, although firms with high ESG ratings show smaller reactions, suggesting such news is already priced in. Firms with low rating disagreements experience stronger stock price reactions, indicating higher expectations for future news. ESG ratings from different providers vary in predictive ability, with the most predictive rating influencing future stock returns, particularly in cases of high disagreements. Overall, ESG ratings serve as proxies for market expectations and can forecast future news and stock returns despite rating disagreements. While acknowledging that predictive ability is just one aspect of rating quality, the findings highlight the importance of ratings in reflecting organizational commitments to ESG outcomes. Furthermore, Broadsrock et al. (2020) [34] found that firms with higher ESG ratings experience smaller stock price declines and lower volatility during periods of crisis, with a specific study about stock prices during the pandemic period (COVID-19).
In contrast with the previous findings, Halbritter and Dorfleitner (2015) [48] state that ESG portfolios do not exhibit significant return differences between companies with high and low ESG ratings. The study finds that the influence of ESG variables on returns is inconsistent across different ESG rating providers, indicating that the relationship is highly dependent on the specific rating methodology. Over time, there appears to be a diminishing impact of ESG variables on returns, therefore suggesting a potential weakening of the relationship between CSP and CFP.
The article provided by Babynina et al. (2023) [40] identifies significant ESG issues within the Russian business landscape, highlighting that the main challenges include a lack of understanding at the corporate level regarding the real impact of sustainable development projects, insufficient skills among employees, and limited financial resources, as well as external factors like geopolitical dynamics and regulatory frameworks. That is why the solution proposed is the creation of the National ESG Alliance and the development of an ESG Infrastructure Atlas.
A study by Sadiqa et al. (2022) [24] explores global challenges arising from industrial expansion and limited engagement in environmental and social initiatives despite increasing awareness. It discusses the 2030 Agenda for Sustainable Development, comprising 17 SDGs targeting environmental, social, and economic sustainability. ESG criteria are pivotal in evaluating firms’ commitment to these goals, emphasizing environmental protection, social welfare, and corporate governance. Collaborative efforts from businesses are crucial to achieving the SDGs, with effective environmental policies and social governance practices facilitating progress. Corporate governance ensures accountability and transparency, enhancing financial and social performance. In ASEAN countries, progress varies across social, environmental, and economic indicators. While strides have been made in poverty reduction and gender equality, environmental challenges persist. The article stresses the need for enhanced environmental, social, and corporate governance to accelerate SDG attainment [24].
The Brazilian case studied by Miralles-Quirós et al. (2018) [46] states that investors positively value CSR practices in Brazilian listed firms according to the value-enhancing theory. However, while the market significantly values environmental practices, it does not equally value all three pillars of ESG. Specifically, social and corporate practices in environmentally sensitive industries generate significant added value in stock prices.
The analysis conducted by Strekalina et al. (2023) [47] delves into the intricate dynamics between ESG performance and financial outcomes, reflecting the evolving landscape where businesses increasingly integrate sustainability into their operations, pointing out that there is not a universally accepted positive/negative impact of ESGP on FP. Furthermore, the paper points out geographical variations in the ESG-FP relationship, noting differences between developed and emerging economies. While advanced economies may have stronger regulatory frameworks and shareholder activism, emerging markets face unique challenges related to institutional capacity and information dissemination. It is, therefore, important to study geographical influences on the ESG financial performance relationships, particularly within emerging markets like the BRICS countries, where each country adapts the sustainable development agenda differently. The studies reviewed here are summarized in Table 1.

3. Analysis

In this paper, we attempt to connect the global CO2 concentrations with a range of variables, including corporate sustainability performance, to understand if businesses could really be a force for good. CO2 concentrations are defined as the amount of carbon dioxide present in a given volume of air, typically expressed in parts per million (ppm), representing the ratio of CO2 molecules to every one million air molecules, providing a standardized metric for scientific, environmental, and industrial applications. We obtained the data on atmospheric CO2 concentrations from the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory, specifically from their Mauna Loa Observatory dataset, which provides long-term measurements of monthly mean CO2 levels [64].
The key hypothesis of our study H0 can be formulated as follows: sustainable business can be considered a force for good in relation to one of the key challenges of our time, climate change, expressed through the global CO2 concentrations in the atmosphere. The additional hypothesis H1 to be tested will address the feasibility of building an econometric model of global CO2 concentrations using daily data, “explaining” these concentrations through a range of astronomical variables (total solar irradiance and cosmic rays), economic variables (oil prices and the Dow Jones Sustainability Index) and a possible autoregressive component.

3.1. Dow Jones Sustainability Index

The Dow Jones Sustainability Index (DJSI) is a global benchmark that tracks the performance of the top 10% of companies (325 companies in 2023) from various sectors based on their sustainability practices, evaluated using criteria such as economic, environmental, and social performance, corporate governance, and transparency.
The index is structured as follows: The Capital Goods sector represents 11.16% of the total, followed by Banks with 9.71%, Materials and Financial Services each at 8.63% and 6.12%, respectively. Pharmaceuticals, Biotechnology, and Life Sciences also make up 6.12%, while Equity Real Estate Investment Trusts (REITs) and Energy contribute 4.68% each. The Food, Beverage and Tobacco, Health Care Equipment and Services, Insurance, Semiconductors and Semiconductor Equipment, Technology Hardware and Equipment, Transportation, and Utilities sectors each represent 4.32%. Software and Services accounts for 5.76%, while Commercial and Professional Services, Consumer Discretionary Distribution and Retail, Consumer Staples Distribution and Retail, and Semiconductors and Semiconductor Equipment are each represented at 3.24%. Media and Entertainment has 3.96%, and Consumer Durables and Apparel stands at 2.88%, the same as Consumer Services and Consumer Staples Distribution and Retail. The Automobiles and Components sector accounts for 2.16%, and Household and Personal Products is the smallest at 1.08%. The index represents companies headquartered in the following countries: USA (54), Japan (37), Taiwan (30), Republic of Korea (22), France (21), UK (16), Italy (15), Spain (15), Thailand (15), Germany (13), Australia (10), Brazil (8), Netherlands (8), Switzerland (8), Canada (4), Sweden (5), Colombia (4), and Finland (4).
The index was pioneered in 1999 and has become the benchmark for assessing the sustainability of companies worldwide. Figure 1 presents the dynamics of the daily Dow Jones Sustainability Index between 2012 and 2021. We see an overall positive trend, with downward spikes in the middle of the COVID-19 pandemic.
Figure 1. Daily Dow Jones Sustainability Index, 2012–2021.

3.2. Brent Crude Oil Price

The dynamics of Brent crude oil prices are influenced by a range of factors, including the decisions made by the OPEC (Organization of the Petroleum Exporting Countries) regarding production quotas and geopolitical events such as wars or crises, like the Middle East Crisis of the 1970s and the Iranian Revolution, which can disrupt supply and lead to price volatility, as well as shifts in global demand and economic conditions that further impact the price of oil. One can hypothesize that the DJSI is positively correlated with the oil price, providing a safe haven for investors who experience oil price shocks.
Further analysis reveals that the Dow Jones Sustainability Index is inversely correlated with the Brent crude oil price (Figure 2) when the years 2012, 2013, and 2014 are taken into consideration and positively correlated when the years 2012, 2013, and 2014 are excluded (Figure 3). The regression model that describes the relationship between crude oil price and the Dow Jones Sustainability Index with the years 2012, 2013, and 2014 taken into account (Figure 3) is statistically significant, and the coefficient is negative. If the time horizon changes, however, the relationship becomes strongly positive, as one would expect. In this way, companies are investing in sustainability to avoid the shocks of the high oil price. This is particularly relevant for the period 2014–2022, as Figure 4 outlines.
Figure 2. Daily Down Jones Sustainability Index and oil price, 2012–2022 (blue line corresponding to the left hand axis: oil price; orange line corresponding the right-hand axis—DJSI).
Figure 3. Brent crude oil price and Dow Jones Sustainability Index.
Figure 4. Crude oil Brent price and the Dow Jones Sustainability Index (2014–2022).
So, what is actually going on here? What makes the years 2012, 2013, and 2014 so different (Figure 5)? In mid-2014, the hedge fund positions in Brent and WTI futures dropped rapidly, approximately around the month of July. At the same time, in the USA, 2013 and 2014 resulted in the fastest growth in the production of oil in history. The US output increased from 5 mln bpd in 2008 to approximately 8.5 mln bpd in 2014, with output increasing by 160,000 bpd in 2011, 850,000 bpd in 2012, 950,000 bpd in 2013, and 1.2 mln bpd in 2014. On 27 November 2014, the OPEC announced that it would keep its current production at 30mln bpd. The oil price by that time had already fallen to USD 77 per barrel and dropped even further to USD 59.
Figure 5. Dow Jones Sustainability Index and the crude oil price (2012, 2013, and 2014).

3.3. Global CO2 Concentrations

In its Synthesis Report, the IPCC states that “atmospheric CO2 concentrations reached 410 parts per million (ppm) in 2019, higher than at any time in at least 2 million years”. The global concentrations of CO2 in the atmosphere continue to increase (Figure 6). This is a powerful illustration that the problem of climate change is far from being solved.
Figure 6. Global CO2 concentrations, 1960–2025. Source: NOAA.
Global concentrations of CO2 are primarily driven by human activities that release large amounts of carbon dioxide into the atmosphere. The major sources include the burning of fossil fuels for transportation (air, land, and sea), energy production, heating, industrial processes, and the agriculture sector, which contributes significantly through practices such as deforestation, livestock production, and the use of synthetic fertilizers. Additionally, resource-intensive sectors, like manufacturing and construction, further exacerbate CO2 emissions through energy consumption and material extraction. These activities contribute to the accumulation of greenhouse gases, which trap heat in the atmosphere and drive climate change. Potential remedies to reduce CO2 emissions include transitioning to cleaner energy sources, such as nuclear and renewable technologies (wind, solar, and hydro), adopting sustainable agricultural practices, embracing sustainability in production and consumption, and transforming business models to prioritize environmental responsibility. These measures aim to reduce dependence on fossil fuels, promote energy efficiency, and foster a more sustainable, low-carbon global economy.
When we explore the connections between the Dow Jones Sustainability Index and the global CO2 concentrations depicted in Figure 7, we clearly see that increases in the Dow Jones Sustainability Index have been associated with increases in global CO2 concentrations (Figure 7).
Figure 7. DJSI and CO2 concentrations.
On the other hand, the correlation we see between the oil price and global CO2 concentrations is indeed very curious (Figure 8). What we see is a clear negative relationship where rising oil prices imply a lower CO2 concentration in the atmosphere, which emphasizes the potential value of carbon and energy taxes, which we explored in [65]. This is particularly striking because the data were collected on a daily basis.
Figure 8. Oil price and CO2 concentrations at Mauna Loa Observatory.
During the pandemic, however, when nobody was allowed to use their private cars and the global travel industry collapsed, the situation changed. During the months of the pandemic, the increases in the Dow Jones Sustainability Index were negatively correlated with the global CO2 emissions, confirming the role of sustainable business as a force for good; however, this was only during the pandemic when we did not consume petrol or fly across the oceans.

3.4. Total Solar Irradiance

Total solar irradiance (TSI) refers to the amount of solar energy that reaches the Earth’s atmosphere per unit area, typically measured in watts per square meter (W/m²). It represents the total energy output of the sun, including all wavelengths of electromagnetic radiation. TSI is not constant; it varies slightly over time due to solar cycles, with small fluctuations that can influence the Earth’s climate.
TSI is crucial for plant growth because it provides the energy necessary for photosynthesis, the process by which plants convert light energy into chemical energy to fuel their growth and development. Photosynthesis relies on light absorption by chlorophyll in plant cells, and TSI directly affects the intensity of this light. Higher solar irradiance typically leads to more efficient photosynthesis, promoting stronger plant growth. On a larger scale, variations in TSI can influence agricultural productivity, ecosystems, and the global carbon cycle, as plants play a vital role in carbon sequestration.
Figure 9 clearly illustrates a negative relationship between the total solar irradiance and the CO2 concentrations in the atmosphere, which points toward the role of photosynthesizing biomass as a decarbonization force.
Figure 9. TSI (total solar irradiance) and CO2 concentrations from 2012 to 2020.

3.5. Cosmic Rays

Cosmic rays are high-energy particles from outer space that reach Earth’s surface and influence atmospheric and biological processes. According to Svensmark (2000) [66], cosmic rays can help form cloud condensation nuclei, which influence cloud formation and precipitation patterns. This indirect effect on weather, particularly rain, is crucial for plant growth, as water is essential for seed germination and overall plant health. Research by Ormes (2018) [67] also suggests that cosmic ray activity can influence long-term weather patterns, potentially altering rainfall and, thereby, affecting agricultural productivity.
Furthermore, cosmic rays have been shown to influence plant growth at the genetic level. Studies suggest that exposure to cosmic rays can enhance seed germination rates by inducing genetic mutations, which may improve stress resistance and growth in certain plant species. A study referenced in Frontiers in Plant Science (2023) [68] supports this, showing that exposure to radiation, including cosmic rays, can trigger faster germination and stronger seedling development in certain plants.
Additionally, research by Dengel (2009) [69] found that galactic cosmic rays could increase photosynthesis in tree canopies and affect tree ring growth, suggesting that cosmic rays can influence both tree vitality and long-term growth patterns. These effects, although subtle, demonstrate the potential role of cosmic rays in enhancing plant productivity, influencing genetic adaptations, and promoting healthier ecosystems over time.
As our previous research indicates [70], TSI and cosmic rays undoubtedly are connected with the global climate variables, and here, we try to establish if daily concentrations of CO2 emissions respond to these aggregates (Figure 10).
Figure 10. Daily CO2 concentrations and cosmic rays.
Figure 10 illustrates that there is an undoubted correlation between cosmic rays and global CO2 concentrations, and this correlation tends to be positive.
In order to understand all the potential factors involved, we built a full-scale econometric model of global daily CO2 concentrations and examined the role of sustainable business as a force for good.

4. Model Building

4.1. Modeling CO2 Concentrations in Levels

We built a dynamic econometric model aimed at explaining the daily fluctuations in global CO2 concentrations in the atmosphere. The model building rested on the theoretical understanding of which factors should affect CO2 concentration both at the level of emissions and at the level of absorption, and this process combines two phases: modeling relationships in levels and modeling the relationships in differences and combining the models following the so-called error–correction modeling [71,72,73,74].
The methodological framework we used in our modeling (Figure 11) is largely based on the understanding of the carbon cycle. It is characterized by sources of CO2 emissions, represented by the economy, which is influenced by the Dow Jones Sustainability Index of most sustainable companies and the oil price, among other factors. The resulting emissions will be higher or lower depending on the combination of these factors, with one of the crucial factors being the efforts by the largest companies to reduce their CO2 emissions. The opposite side of the equation affecting the concentrations of CO2 in a positive way is the biomass represented by the Plants box. This is, in turn, influenced by astronomical factors such as solar energy and cosmic rays, which have already been illustrated in our previous work [70]. Although this framework might be seen as a simplification of reality, every model is a reasonable simplification of reality with the crucial elements and connections emphasized and the less relevant omitted.
Figure 11. Methodological framework.
The modeling was carried out with the help of the advanced econometric analysis package OxMetrics. The first step in the modeling process was to model the relationships in levels. This initial model is illustrated in Figure 12. We can see that the modeled CO2 concentrations follow the observed in quite a close way, with the observed shown by the red line and the fitted by the blue line. Based on 2195 observations, we established that daily CO2 concentrations in the global atmosphere are very auto-correlated, have a positive impact from the Dow Jones Sustainability Index, a negative impact from the oil price, a positive impact from cosmic rays, and a positive impact from total solar irradiance (Table 2 and Figure 12).
Figure 12. Model of CO2 concentrations in levels using daily data.
Table 2. Coefficients in the CO2 model in levels.
We note the good values of Adjusted R2 (0.990716), the AIC of −0.692693, and some issues with the autocorrelation, normality, and heteroskedasticity of residuals. We note that the Dow Jones Sustainability Index tends to contribute approximately 1% to the explanation of the variance in daily CO2 concentrations. Figure 13 presents the residuals in the levels model.
Figure 13. Residuals in the levels model.

4.2. Modeling CO2 Concentrations in Differences

Modeling the process at hand in differences to examine the short-run dynamics, we obtained the model presented in Figure 14 and Table 3.
Figure 14. Differences model of D (CO2).
Table 3. Coefficients in the differences model.
We note the R2 of 0.155267 and the AIC of −0.834095.

4.3. Final Combined Model

When we combined all the elements into the integrated model to build a model examining both the long-run and the short-run, we obtained the model depicted in Figure 15 and Table 4. We can definitely observe a much closer fit between the actual CO2 concentrations data and the fitted data.
Figure 15. Integrated model of global CO2 concentrations (2012–2022).
Table 4. Model coefficients in the integrated model.
In the integrated model (Figure 15 and Table 4), we still observe autocorrelation of CO2 concentrations, which is to be expected, as it represents the inertia in the system. Crude Brent oil now features a positive coefficient, the TSI square features a negative coefficient, and the CCR square features a negative coefficient, while the Dow Jones Sustainability Index also features a negative coefficient, confirming our H0 hypothesis that a sustainable business can be a force for good. We have improved the residuals (Figure 16), our Adjusted R2 to 0.999993 and the AIC to −7.82265, which is excellent. The inclusion of the decimal date variable allowed us to make sure that the model has much more stable coefficients than before (Figure 17).
Figure 16. Residuals in the final model.
Figure 17. Coefficient stability in the final model. Red line represents cumulative sum of recursive residuals (CUSUM), the green lines are critical bounds for the stability test, at a 95% confidence level. If the red line (test statistic) stays within the green bounds, it indicates that the model parameters are stable over the sample period.
The reduction in the Akaike Information Criterion (AIC) from −0.692693 in the levels model to −7.82265 in the combined short-run and long-run final model indicates a substantial improvement in the model’s performance. The AIC is a widely used metric for evaluating the quality of statistical models, balancing the goodness of fit with model complexity. A lower AIC value reflects a model that better explains the observed data without overfitting.
The initial levels model, with an AIC of −0.692693, primarily captured the long-run relationships between variables. While this approach provided some insights, the relatively higher AIC suggests limitations in its ability to fully account for the dynamics of the system. By contrast, the final model incorporates both short-run dynamics and long-run relationships, leading to a significantly lower AIC of −7.82265. This marked reduction demonstrates that the inclusion of short-term adjustments, such as fluctuations or lagged effects, substantially enhances the explanatory power of the model.
Importantly, this improvement in the AIC signifies that the added complexity of the combined model is justified by its ability to capture more of the variability in the data. The short-run components complement the long-run framework, allowing the model to better reflect real-world processes, such as immediate responses to external factors or transient deviations from equilibrium.
Overall, the reduction in the AIC highlights the superior performance of the combined model, making it a more robust and reliable tool for understanding the dynamics of the system under study.
The residual analysis displayed in the top panels confirms that the model is highly robust and well-specified. The residual plot over time (top right) exhibits no visible trends or patterns, indicating that the errors are randomly distributed and the model effectively captures the underlying data dynamics. The histogram of residuals (bottom left) aligns closely with a normal distribution, centered at zero with minimal skewness, further validating that the model errors are unbiased and normally distributed. Additionally, the autocorrelation (ACF) and partial autocorrelation (PACF) functions (bottom right) show no significant lags, suggesting that the residuals are not autocorrelated and the model has successfully accounted for time-dependent structures in the data.
The long-term stability of the model’s coefficients, as illustrated in the bottom series of charts, underscores its reliability. All coefficients remain stable over the examined period, with confidence intervals tightly surrounding the point estimates. This stability signifies that the relationships captured by the model between predictors and the response variable are consistent over time, even in the presence of external variations. The absence of significant deviations or abrupt changes further confirms the robustness of the model, making it an excellent tool for forecasting and interpreting long-term dynamics.

5. Discussion

Let us take some steps to interpret the model that we managed to obtain, considering the meaning of each term in detail and its possible implications. To understand this model comprehensively, it is essential to consider the relationships between the variables, their statistical significance, and the underlying implications for atmospheric CO2 levels.

5.1. The Negative Constant

The negative constant of −6.17092 suggests an interesting starting point for the model. In the context of the equation, the negative constant can be seen as a baseline adjustment in the absence of all other influencing factors (e.g., CO2 from the previous day, economic activities, or commodity prices). This value may symbolize a potential long-term equilibrium in the Earth’s natural carbon cycle, one that existed before the rise of human industrialization.
Historically, before humans began significantly influencing the atmosphere, the Earth’s natural processes maintained relatively stable CO2 levels. As the planet’s ecosystems evolved, particularly with the rise of photosynthetic organisms, the amount of CO2 absorbed and emitted was approaching the state of dynamic equilibrium, creating a balance between carbon emissions and carbon sequestration. This natural equilibrium may be represented by the negative constant, signaling a period when nature operated in harmony and the Earth’s biosphere and geosphere functioned to stabilize atmospheric CO2 concentrations.
However, the negative constant also reflects the fragility of this equilibrium. It indicates that while natural systems may have once been capable of absorbing more CO2 than they emitted, this balance is no longer in place due to human activities. The overwhelming emissions from fossil fuel combustion, industrial processes, deforestation, and other anthropogenic activities are now pushing CO2 levels far above this natural baseline.

5.2. Decimal Date

The decimal date coefficient (0.00387243) suggests a gradual increase in CO2 concentrations over time, where the passage of time itself (as represented by the date) is positively correlated with increasing CO2 levels. This could indicate that, over the period under study, global CO2 concentrations have been steadily rising due to long-term trends like industrialization, increased human activity, and fossil fuel consumption. The statistical significance (p-value = 0.0002) confirms the reliability of this relationship.

5.3. CO2(t − 1) or Lagged CO2

The coefficient for CO2 (t − 1): 1.00034 is striking in its magnitude and statistical significance, which shows a very strong autoregressive effect, meaning that today’s CO2 concentrations are heavily influenced by the concentrations of the previous day. This makes sense given the nature of CO2 dynamics: concentrations do not change abruptly on a daily basis, and past emissions from human or natural sources influence present levels. The very high Part.R2 (0.9999) suggests that past CO2 concentrations account for a substantial portion of today’s CO2 levels, reflecting the inertia in the system and the persistence of atmospheric CO2.

5.4. Dow Jones Sustainability World Index (DJSI)

The Dow Jones Sustainability World Index coefficient (−0.0000160759) shows a negative relationship with global CO2 concentrations. This means that as the DJSI rises, indicating improvements in sustainability practices by businesses, CO2 concentrations tend to decrease. This finding aligns with the idea that more sustainable business practices, such as increased energy efficiency, a shift toward renewable energy sources, and better waste management, may help mitigate CO2 emissions and confirms our H0 hypothesis. The statistical significance (p-value = 0.0047) further confirms that this relationship is meaningful, though the effect size is modest, as indicated by the Part.R2 (0.0036).
This relationship suggests that a transition toward more sustainable business practices, the transformation of business models, and increased focus on ESG dimensions, as reflected in the DJSI, could have a tangible impact on reducing global CO2 levels, but they are not the sole factors influencing these concentrations [25,65,75,76].

5.5. Brent Crude Oil Price

The Brent crude oil price coefficient (0.000110840) shows a positive relationship between oil prices and CO2 concentrations. This suggests that as oil prices increase, global CO2 concentrations also rise. This could be interpreted in two ways: higher oil prices might lead to greater investment in fossil fuel extraction and related activities, or they may reflect increased energy consumption due to global demand. The statistical significance (p-value = 0.0019) and moderate Part.R2 (0.0044) suggest that this is a noteworthy, but not overwhelming, relationship.
This could be indicative of the economic structure, where fossil fuel reliance remains strong despite efforts to reduce emissions. Alternatively, this may point to a supply–demand effect in the energy markets, where higher prices lead to shifts in extraction and consumption behaviors.

5.6. CCR_SQUARE (Squared Terms of Cosmic Rays)

The coefficient for CCR_SQUARE (−0.00000000262072) reveals a significant nonlinear relationship between cosmic ray intensity and CO2 concentrations, with a highly significant t-value of −7.47 (p-value = 0.0000) and a Part.R2 of 0.0249. This indicates that cosmic rays influence CO2 levels in a manner that is not strictly linear, likely due to their role in cloud formation, which has indirect effects on CO2 dynamics.
Cosmic rays are known to affect cloud nucleation, and, in turn, this impacts rainfall patterns and atmospheric conditions favorable to plant growth. The negative sign of the coefficient suggests that increased cosmic ray activity could enhance cloud cover, leading to more favorable conditions for vegetation, which helps in reducing CO2 concentrations through increased photosynthesis and carbon sequestration. The squared term emphasizes that small changes in cosmic ray activity may have amplified effects on CO2 levels, possibly through the feedback loop where more cloud cover and rainfall lead to more plant growth, which, in turn, absorbs more CO2 from the atmosphere.
This result supports previous studies suggesting that cosmic rays, by influencing cloud formation and plant growth, can indirectly contribute to a reduction in atmospheric CO2 concentrations.

5.7. TSI_SQUARE (Squared Terms of Total Solar Irradiance)

The TSI_SQUARE coefficient −0.000000890689) is statistically insignificant (p-value = 0.1286) and has a very low Part.R2 (0.0011). This suggests that, within the scope of this model, total solar irradiance (TSI) does not have a strong influence on global CO2 concentrations when squared. However, the relationship might still warrant further investigation, especially when considering the cosmic ray effects that affect cloud formation and subsequent rainfall, which can indirectly impact plant growth and carbon sequestration.

5.8. D_CCR_4 (Differenced CCR Terms)

The D_CCR_4 coefficient (0.0000316413) represents the differenced term for carbon cycle dynamics over a four-day lag, and it shows a positive relationship with CO2 concentrations. This suggests that short-term variations in the carbon cycle can influence CO2 concentrations in the immediate term. The statistical significance (p-value = 0.0012) and moderate Part.R2 (0.0024) indicate that these short-term changes in the carbon cycle are relevant for daily CO2 dynamics.

5.9. ECM_DIFF (Error Correction Term)

The ECM_DIFF coefficient (0.999205) is highly significant (p-value = 0.0000) and demonstrates that error correction dynamics play a major role in the system. The coefficient’s value close to 1 indicates that the system is highly persistent, and deviations from the equilibrium state (whether caused by human activity or natural factors) are corrected very quickly. This suggests that global CO2 concentrations exhibit path dependence and tend to revert to a long-term trend or equilibrium once short-term disturbances are accounted for.

6. Conclusions

This model of global CO2 concentrations reveals several insightful relationships between human activity, economic variables, and natural processes. While the negative constant hints at a potential historical equilibrium in the carbon cycle, human-driven emissions have clearly disrupted this balance. The model suggests that business sustainability and oil prices play significant roles, but autocorrelation and cosmic rays dynamics have the most substantial impact on explaining daily CO2 concentrations. The presence of error correction mechanisms also reinforces the idea that, despite fluctuations, CO2 concentrations tend to revert to long-term trends influenced by natural and anthropogenic factors.
Our hypothesis H1 is, therefore, confirmed as well, and we have been able to build a comprehensive model of daily CO2 concentrations examining the role of multiple factors. One of these factors, and this confirms our H0 hypothesis, is sustainable business, expressed by the Dow Jones Sustainability Index. By improving sustainability practices, reducing fossil fuel reliance, and understanding the complexities of the carbon cycle, it is possible to mitigate the rise in CO2 concentrations and work toward restoring a more balanced and sustainable atmospheric state.
Discussing the ways to make sure that businesses make an even greater contribution toward decarbonization globally, we need to touch upon several interconnected issues. The first set of questions relate to what is actually inside the Dow Jones Sustainability Index and how truly sustainable these companies are. Estimating the market capitalization in brackets, we note that the index still includes oil giants like Total Energies (USD 158.64 bln), Exxon Mobil (USD 542.20 bln), Chevron Corporation (USD 305.93 bln), and the mining giant Rio Tinto (USD 104.73 bln), as well as truly more sustainable and lower impact companies like Apple (USD 2.76 trln), Microsoft (USD 2.45 trln), Salesforce (USD 186.75 bln), Alphabet Inc. (USD 1.7 trln), Meta Platforms Inc. (USD 779 bln), Tesla (USD 836.59 bln), SAP (USD 158.25 bln), Vestas Wind Systems A/S (USD 23.71 bln), NextEra Energy, Inc. (USD 103.80 bln), Ørsted (USD 43.29 bln), Enel S.p.A. (USD 77.72 bln), JinkoSolar Holding Co., Ltd. (USD 2.90 bln), Iberdrola S.A (USS 90.03 bln), Munich Re (USD 32.7 bln), and Zurich Insurance (USD 60.65 bln). So the biggest question is what are the criteria for inclusion of the companies into the Dow Jones Sustainability Index, and should this be based on their Scope 3 CO2 emissions or emissions to turnover ratios, so that oil companies cannot be part of the index? The performance of companies that could be considered as a backbone of sustainability transition, e.g., solar panel suppliers Jinko Solar or Ørsted, has been less than spectacular, indicating a market myopia, which is highly surprising.
The second issue in relation to how to make sure businesses are playing a larger role is regulation. Focusing on the subject of our paper, we can remark not all countries in the world have introduced a carbon tax, with only several countries fully embracing it like Sweden [65]. A universal global carbon market has not yet been built. At the same time, there is no consistent regulation in the field of circular economy, with even European countries exhibiting conflicting signals. Many countries in Western Europe introduced landfill taxes; however, many continue to export waste abroad, and very few, if at all, supported them with incineration taxes to truly promote the circular economy. There is still very little in the way of regulation in the field of ecosystems and biodiversity impacts. In the EU, there are some signs of a growing impact of new standards and EU cross-border regulations. In the United States, there are multiple examples where whole states have legislated against using ESG criteria for the assessment of investment fund performance, trying to defend the infamous quote from Milton Friedman that “the business of business is to do business”. Robert Eccles has discussed these instances at length: they seem to be clear violations of the principles of the free market because if the customers demand ESG focus, the investment community should follow.
A more general question could be posed regarding how markets really value sustainability and whether there is an obstacle that we face in this context. How does business education embrace sustainability worldwide and how much do business leaders care? What could be said about the values and the deeply held beliefs of business leaders? There are, however, voluntary schemes, like the B-Corp, which encourage its members to make a legal change in their statutes to introduce the principle of respect to all stakeholders, not just the shareholders, thereby, changing the nature of conducting business itself. This example is very much in line with the sustainable business ideas presented by John Elkington, Ronald Cohen, and Robert Eccles.
Examining the connection between the sustainable business expressed in the Dow Jones Sustainability Index and global CO2 concentrations, we notice a high degree of auto-correlation in the global CO2 concentrations, with some impact of astronomical variables, like cosmic rays and total solar irradiance, and the limited but statistically significant impact of the oil price and the Dow Jones Sustainability Index. The fact that the Dow Jones Sustainability Index comes with a negative coefficient gives us some hope that businesses could be a force for good; however, many questions arise. The hypotheses we formulated at the start of the paper, namely, hypothesis H1 that business can be a force for good and make a positive contribution toward global decarbonization effort, as well as H2 that it is feasible to build a dynamic econometric model based on daily data on atmospheric CO2 concentrations and a range of economic and astronomic factors have both been confirmed.
It is obvious that without the involvement of businesses, it is very unlikely that a sustainability transition will ever take place. If we are going to see businesses as a true force for good, we need clearer regulations, better sustainability education for top managers, and a deep transformation of the business models addressing the most pressing issues of our time: climate change, biodiversity loss, and the waste crisis.

Author Contributions

Conceptualization, S.E.S.; methodology, S.E.S.; validation, S.E.S.; formal analysis, S.E.S.; investigation, S.E.S.; data curation, S.E.S.; writing—original draft preparation, E.G. and S.E.S.; writing—review and editing, S.E.S.; visualization, S.E.S.; supervision, S.E.S.; project administration, S.E.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Cohen, R. Impact: Reshaping Capitalism to Drive Real Change; Ebury Press: London, UK, 2020; p. 256. [Google Scholar]
  2. Eccles, R.G.; Ioannou, I.; Serafeim, G. The Impact of Corporate Sustainability on Organizational Processes and Performance. Manag. Sci. 2014, 60, 2835–2857. [Google Scholar] [CrossRef] [Scilit]
  3. Elkington. Green Swans: The Coming Boom in Regenerative Capitalism; Fast Company Press: Austin, TX, USA, 2021. [Google Scholar]
  4. Carney, M. Value(s): The Must-Read Book on How to Fix Our Politics, Economics and Values; William Collins: Glasgow, Scotland, 2021; p. 608. [Google Scholar]
  5. Polman, P. Net Positive: How Courageous Companies Thrive by Giving More Than They Take; Harvard Business Review Press: Brighton, MA, USA, 2022. [Google Scholar]
  6. Catalyst. The Bottom Line: Connecting Corporate Performance and Gender Diversity; Catalyst: New York, NY, USA, 2020. [Google Scholar]
  7. Ferri, G.; Pini, M. Environmental vs. Social Responsibility in the Firm. Evidence from Italy. Sustainability 2019, 11, 4277. [Google Scholar] [CrossRef] [Scilit]
  8. Kell, G. The Remarkable Rise of ESG, Forbes. 2018. Available online: https://www.forbes.com/sites/georgkell/2018/07/11/the-remarkable-rise-of-esg/#549a69021695 (accessed on 1 June 2024).
  9. Khan, M.; Serafeim, G.; Yoon, A. Corporate Sustainability: First Evidence on Materiality. Account. Rev. 2016, 91, 1697–1724. Available online: http://www.aaajournals.org/doi/abs/10.2308/accr-51383 (accessed on 1 June 2024). [CrossRef] [Scilit]
  10. Sparkes, R. Socially Responsible Investment: A Global Revolution; Wiley: Hoboken, NJ, USA, 2002. [Google Scholar]
  11. UN Global Compact. Who Cares Wins: Connecting Financial Markets to a Changing World; UN Global Compact: New York, NY, USA, 2005. [Google Scholar]
  12. UNDESA. A Briefing Note on Addis Ababa Agenda on Financing Sustainable Development and Developing Sustainable Finance; UNDESA: New York, NY, USA, 2015. [Google Scholar]
  13. UN. Principles for Responsible Investment. 2025. Available online: https://www.unpri.org/ (accessed on 21 January 2025).
  14. Cheng, B.; Ioannou, I.; Serafeim, G. Corporate social responsibility and access to finance. Strat. Manag. J. 2014, 35, 1–23. Available online: https://onlinelibrary.wiley.com/doi/abs/10.1002/smj.2131 (accessed on 1 June 2024). [CrossRef] [Scilit]
  15. El Ghoul, S.; Guedhami, O.; Kwok, C.C.; Mishra, D.R. Does corporate social responsibility affect the cost of capital? J. Bank. Finance 2011, 35, 2388–2406. Available online: https://econpapers.repec.org/article/eeejbfina/v_3a35_3ay_3a2011_3ai_3a9_3ap_3a2388-2406.htm (accessed on 1 June 2024). [CrossRef] [Scilit]
  16. Fulton, M.; Kahn, B.; Sharples, C. Sustainable Investing: Establishing Long-Term Value and Performance. 2012. Available online: http://dx.doi.org/10.2139/ssrn.2222740 (accessed on 1 June 2024).
  17. Gabriel, V. Environmentally sustainable investment: Dynamics between global thematic indices. Cuad. De Gest. 2019, 19, 41–62. [Google Scholar] [CrossRef] [Scilit]
  18. Giese, G.; Lee, L.E.; Melas, D.; Nagy, Z.; Nishikawa, L. Performance and risk analysis of index-based ESG portfolios. J. Index Investig. 2019, 9, 46–57. [Google Scholar] [CrossRef] [Scilit]
  19. Giese, G.; Lee, L.E.; Melas, D.; Nagy, Z.; Nishikawa, L. Foundations of ESG Investing: How ESG Affects Equity Valuation, Risk, and Performance. J. Portf. Manag. 2019, 45, 1–15. [Google Scholar] [CrossRef] [Scilit]
  20. Giese, G.; Nagy, Z.; Lee, L.E. Deconstructing ESG Ratings Performance Risk and Return for E, S and G by Time Horizon, Sector and Weighting. J. Portf. Manag. 2020, 47, 94–111. [Google Scholar] [CrossRef] [Scilit]
  21. Hartzmar, S.M.; Sussman, A.B. Do Investors Value Sustainability? A Natural Experiment Examining Ranking and Fund Flows. J. Financ. 2019, 74, 2789–2837. [Google Scholar] [CrossRef] [Scilit]
  22. Maiti, M. Is ESG the succeeding risk factor? J. Sustain. Finance Invest. 2020, 11, 199–213. [Google Scholar] [CrossRef] [Scilit]
  23. Nguyen-Taylor, K.; Martindale, M. Financial Performance of ESG Integration in US Investing (Principles for Responsible Investment, London). 2018. Available online: https://cdn2.hubspot.net/hubfs/4256284/PRI_Financial-performance-of-ESG-integration-in-US-investing_2018.pdf (accessed on 1 June 2024).
  24. Sadiqa, M.; Ngob, T.Q.; Pantameec, A.A.; Khudoykulovd, K.; Ngane, T.T.; Tan, L.P. The role of environmental social and governance in achieving sustainable development goals: Evidence from ASEAN countries. Econ. Res. Ekon. Istraživanja 2022, 36, 170–190. [Google Scholar] [CrossRef] [Scilit]
  25. Shmelev, S.E. Ecological Economics: Sustainability in Practice; Springer: Berlin/Heidelberg, Germany, 2012; p. 248. [Google Scholar]
  26. Fiskerstrand, S.R.; Fjeldavli, S.; Leirvik, T.; Antoniuk, Y.; Nenadić, O. Sustainable investments in the Norwegian stock market. J. Sustain. Finance Invest. 2020, 10, 294–310. [Google Scholar] [CrossRef] [Scilit]
  27. UK Government Actuary’s Department. Investment Bulletin; UK Government Actuary’s Department: London, UK, 2019.
  28. UNDESA. SDG Investing: Advancing a New Normal in Capital Markets; UNDESA: New York, NY, USA, 2017. [Google Scholar]
  29. UNDP. The SDG Impact Practice Standards for Private Equity Funds; UNDP: New York, NY, USA, 2019. [Google Scholar]
  30. UNEP FI. SDG Investment Case; UNEP FI: Geneva, Switzerland, 2019. [Google Scholar]
  31. UNEP FI. Fiduciary Duty in the 21st Century; UNEP FI: Geneva, Switzerland, 2020. [Google Scholar]
  32. University of Oxford and Arabesque Partners. From the Stockholder to the Stakeholder: How Sustainability Can Drive Financial Outperformance (March 2015). Available online: https://arabesque.com/research/From_the_stockholder_to_the_stakeholder_web.pdf (accessed on 1 June 2024).
  33. Whelan, T.; Atz, U.; Van Holt, T.; Clark, C. ESG and Financial Performance: Uncovering the Relationship by Aggregating Evidence from 1000 Plus Studies Published between 2015–2020; NYU Centre for Sustainable Business: New York, NY, USA, 2021; p. 19. [Google Scholar]
  34. Broadstock, D.C.; Chan, K.; Cheng, L.T.; Wang, X. The role of ESG performance during times of financial crisis: Evidence from COVID-19 in China. Finance Res. Lett. 2021, 38, 101716. [Google Scholar] [CrossRef] [Scilit]
  35. Krosinsky, C.; Purdom, S. Sustainable Investing: Revolutions in Theory and Practice; Routledge: Abingdon, UK, 2016. [Google Scholar]
  36. Crace, L.; Gehman, J. What Really Explains ESG Performance. In Disentangling the Asymmetrical Drivers of the Triple Bottom Line; Organization & Environment: Washington, DC, USA, 2023; Volume 36. [Google Scholar]
  37. Eccles, R.; Ioannou, I.; Serafeim, G. The Impact of a Corporate Culture of Sustainability on Corporate Behaviour and Performance, National Bureau of Economic Research, Working Paper 17950. 2011. Available online: http://www.nber.org/papers/w17950 (accessed on 1 June 2024).
  38. Clément, A.; Robinot, É.; Trespeuch, L. The use of ESG scores in academic literature: A systematic literature review. J. Enterprising Communities: People Places Glob. Econ. 2023, 19, 92–110. [Google Scholar] [CrossRef] [Scilit]
  39. Wang, N.; Pan, H.; Feng, Y.; Du, S. How do ESG practices create value for businesses? Research review and prospects. Sustain. Accounting, Manag. Policy J. 2022, 15, 1155–1177. [Google Scholar] [CrossRef] [Scilit]
  40. Babynina, L.; Kartashova, L.; Busalov, D.; Chernitsova, K.; Akhmedov, F. Effective ESG Transformation of Russian Companies in the New Environment: Current Challenges and Priorities. Acad. J. Interdiscip. Stud. 2023, 12, 113–128. [Google Scholar] [CrossRef] [Scilit]
  41. Linnenluecke, M.K. Environmental, social and governance (ESG) performance in the context of multinational business research. Multinatl. Bus. Rev. 2021, 30, 1–16. [Google Scholar] [CrossRef] [Scilit]
  42. Friede, G.; Busch, T.; Bassen, A. ESG and financial performance: Aggregated evidence from more than 2000 empirical studies. J. Sustain. Finance Invest. 2015, 5, 210–233. [Google Scholar] [CrossRef] [Scilit]
  43. Menicucci, E.; Paolucci, G. ESG Dimensions and Bank Performance: An Empirical Investigation in Italy; Emerald Publishing Limited: Bradford, UK, 2022. [Google Scholar]
  44. Schoenmaker, D.; Schramade, W. Investing for long-term value creation. J. Sustain. Finance Invest. 2019, 9, 356–377. [Google Scholar] [CrossRef] [Scilit]
  45. Freiberg, D.; Rogers, J.; Serafeim, G. How ESG Issues Become Financially Material to Corporations and Their Investors; Harvard Business School: Boston, MA, USA, 2020. [Google Scholar]
  46. Miralles-Quirós, M.M.; Miralles-Quirós, J.L.; Gonçalves, L.M.V. The Value Relevance of Environmental, Social, and Governance Performance: The Brazilian Case. Sustainability 2018, 10, 574. [Google Scholar] [CrossRef] [Scilit]
  47. Strekalina, A.; Zakirova, R.; Shinkarenko, A.; Vatsaniuk, E. The Impact of ESG Ratings on Financial Performance of the Companies: Evidence from BRICS Countries. J. Corp. Financ. Res. 2023, 17, 93–113. [Google Scholar] [CrossRef] [Scilit]
  48. Halbritter, G.; Dorfleitner, G. The wages of social responsibility—Where are they? A critical review of ESG investing. Rev. Financial Econ. 2015, 26, 25–35. [Google Scholar] [CrossRef] [Scilit]
  49. Huang, D.Z.X. Environmental, social and governance (ESG) activity and firm performance: A review and consolidation. Account. Finance 2021, 61, 335–360. [Google Scholar] [CrossRef] [Scilit]
  50. Arvidsson, S.; Dumay, J. Corporate ESG reporting quantity, quality and performance: Where to now for environmental policy and practice? Bus. Strat. Environ. 2022, 31, 1091–1110. [Google Scholar] [CrossRef] [Scilit]
  51. Kotsantonis, S.; Pinney, C.; Serafeim, G. ESG Integration in Investment Management: Myths and Realities. J. Appl. Corp. Finance 2016, 28, 10–16. [Google Scholar] [CrossRef] [Scilit]
  52. Setyahuni, S.W.; Handayani, R.S. On the value relevance of information on environmental, social, and governance (ESG): An evidence from Indonesia. J. Crit. Rev. 2020, 7, 50–58. [Google Scholar]
  53. Kotsantonis, S.; Serafeim, G. Four Things No One Will Tell You About ESG Data. J. Appl. Corp. Finance 2019, 31, 50–58. [Google Scholar] [CrossRef] [Scilit]
  54. Serafeim, G.; Yoon, A. Stock price reactions to ESG news: The role of ESG ratings and disagreement. Rev. Account. Stud. 2023, 28, 1500–1530. [Google Scholar] [CrossRef] [Scilit]
  55. Serafeim, G.; Yoon, A. Which Corporate ESG News Does the Market React To? Financial Anal. J. 2022, 78, 59–78. [Google Scholar] [CrossRef] [Scilit]
  56. Eccles, R.G.; Serafeim, G.; Krzus, M.P. Market Interest in Nonfinancial Information. J. Appl. Corp. Finance 2011, 23, 113–127. [Google Scholar] [CrossRef] [Scilit]
  57. Eccles, R.G.; Serafeim, G. The Performance Frontier: Innovating for a Sustainable Strategy, Harvard Business Review. 2013. Available online: https://hbr.org/2013/05/the-performance-frontier-innovating-for-a-sustainable-strategy (accessed on 1 June 2024).
  58. Serafeim, G.; Yoon, A. The Consequences of Mandatory Corporate Sustainability Reporting, Harvard Business School Working Paper. 2011. Available online: http://www.hbs.edu/research/pdf/11-100.pdf (accessed on 1 June 2024).
  59. Stubbs, W. Sustainable Entrepreneurship and B Corps. Bus. Strat. Environ. 2017, 26, 331–344. [Google Scholar] [CrossRef] [Scilit]
  60. Elkington, J. Enter the Triple Bottom Line. In The Triple Bottom Line: Does It All Add up; Henriques, A., Richardson, J., Eds.; Routledge: Abingdon, UK, 2004. [Google Scholar]
  61. Porter, M.E.; Serafeim, G.; Kramer, M. Where ESG Fails? Institutional Investor. Available online: https://www.institutionalinvestor.com/article/2bswdin8nvg922puxdzwg/opinion/where-esg-fails (accessed on 16 October 2019).
  62. MSCI. MSCI World ESG Leaders Index; MSCI: New York, NY, USA, 2021. [Google Scholar]
  63. McKinsey & Company. Diversity Wins: How Inclusion Matters; McKinsey & Company: New York, NY, USA, 2020. [Google Scholar]
  64. NOAA (National Oceanic and Atmospheric Administration). Trends in Atmospheric Carbon Dioxide: Mauna Loa CO2 Monthly Mean Data; NOAA: Silver Spring, ML, USA, 2025. Available online: https://gml.noaa.gov/ccgg/trends/mlo.html (accessed on 18 January 2025).
  65. Shmelev, S.E.; Speck, S.U. Green fiscal reform in Sweden: Econometric assessment of the carbon and energy taxation scheme. Renew. Sustain. Energy Rev. 2018, 90, 969–981. [Google Scholar] [CrossRef] [Scilit]
  66. Svensmark, H. Cosmic Rays and Earth’s Climate. Space Sci. Rev. 2000, 93, 175–185. [Google Scholar] [CrossRef] [Scilit]
  67. Ormes, J.F. Cosmic Rays and Climate. Adv. Space Res. 2018, 62, 2880–2891. [Google Scholar] [CrossRef] [Scilit]
  68. Dixit, A.R.; Meyers, A.D.; Richardson, B.; Richards, J.T.; Richards, S.E.; Neelam, S.; Levine, H.G.; Cameron, M.J.; Zhang, Y. Simulated galactic cosmic ray exposure activates dose-dependent DNA repair response and down regulates glucosinolate pathways in arabidopsis seedlings. Front. Plant Sci. 2023, 14, 1284529. [Google Scholar] [CrossRef] [Scilit]
  69. Dengel, S.; Aeby, D.; Grace, J. A relationship between galactic cosmic radiation and tree rings. New Phytol. 2009, 184, 545–551. [Google Scholar] [CrossRef] [Scilit]
  70. Shmelev, S.E.; Salnikov, V.; Turulina, G.; Polyakova, S.; Tazhibayeva, T.; Schnitzler, T.; Shmeleva, I.A. Climate Change and Food Security: The Impact of Some Key Variables on Wheat Yield in Kazakhstan. Sustainability 2021, 13, 8583. [Google Scholar] [CrossRef] [Scilit]
  71. Engle, R.F.; Granger, C.W.J. Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica 1987, 55, 251–276. [Google Scholar] [CrossRef] [Scilit]
  72. Hendry, D. Dynamic Econometrics; Oxford University Press: Oxford, UK, 1995. [Google Scholar]
  73. Hendry, D.; Nielsen, B. Ecomometric Modelling. In A Likelihood Approach; Princeton University Press: Princeton, NJ, USA, 2007. [Google Scholar]
  74. Hendry, D.; Doornik, J. Empirical Model Discovery and Theory Evaluation; MIT Press: Cambridge, MA, USA, 2014. [Google Scholar]
  75. Shmelev, S.E.; Shmeleva, I.A. Global urban sustainability assessment: A multidimensional approach. Sustain. Dev. 2018, 26, 904–920. [Google Scholar] [CrossRef] [Scilit]
  76. Shmelev, S. (Ed.) Sustainable Cities Reimagined: Multidimensional Assessment and Smart Solutions; Routledge: Abingdon, UK, 2019. [Google Scholar]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Article Metrics

Citations

Article Access Statistics

Journal Statistics
Multiple requests from the same IP address are counted as one view.
Sustainable Consumption in Context: A Cross-Cultural Study of Social Representations
Previous
A Muti-Scenario Prediction and Spatiotemporal Analysis of the LUCC and Carbon Storage Response: A Case Study of the Central Shanxi Urban Agglomeration
Next