The Impact of ESG Activities on the Financial Stability of Energy Firms in Developing Asia Pacific
FaridaTitikKristanti1
AlvinZikro1
DyahPutriPuspitasari2✉Emaild.p.puspitasari@soton.ac.uk
FitrizalSalim3
ToniHeryana4
1Department of Accounting, School of Economics & BusinessTelkom UniversityBandungIndonesia
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Department of Strategy, Innovation and Entrepreneurship, Southampton Business SchoolUniversity of SouthamptonSouthamptonUnited Kingdom3Department of Management, School of Economics & BusinessTelkom UniversityBandungIndonesia
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Faculty of Economics and Business EducationUniversitas PendidikanIndonesiaFarida Titik Kristanti1, Alvin Zikro2, Dyah Putri Puspitasari3 (corresponding author), Dwi Fitrizal Salim4, Toni Heryana5
1Department of Accounting, School of Economics & Business, Telkom University, Bandung, Indonesia
2Department of Accounting, School of Economics & Business, Telkom University, Bandung, Indonesia
3Department of Strategy, Innovation and Entrepreneurship, Southampton Business School, University of Southampton, Southampton, United Kingdom. E-mail: d.p.puspitasari@soton.ac.uk
4Department of Management, School of Economics & Business, Telkom University, Bandung, Indonesia
5Faculty of Economics and Business Education, Universitas Pendidikan Indonesia
Abstract
This study investigates the impact of Environmental, Social, and Governance (ESG) performance on the financial distress of energy companies in developing Asia-Pacific countries. Using panel data from 30 firms over the 2014–2023 period, the research applies fixed effects estimation and the Generalized Method of Moments (GMM) for robustness checks. The findings reveal a positive relationship between the environmental pillar (ENV) and financial distress, suggesting that increased environmental activities may create short-term financial pressure—particularly under the legitimacy demands of global climate commitments. In contrast, the social (SOC) and governance (GOV) pillars show negative associations with financial distress, emphasizing their role in strengthening stakeholder relationships and enhancing firm stability. By highlighting how ESG components differentially influence financial vulnerability, this study contributes to the literature through a combined lens of stakeholder theory and legitimacy theory. It offers practical implications for policymakers, sustainability-oriented investors, and corporate leaders seeking to navigate climate transition risks. Importantly, the findings underscore ESG adoption as a strategic path for reducing stranded asset exposure and achieving financial resilience—thereby directly supporting Sustainable Development Goals, particularly SDG 13 (Climate Action) and SDG 12 (Responsible Consumption and Production). Energy companies in developing economies can leverage ESG practices not only to safeguard financial performance, but also to catalyze broader contributions toward a just and sustainable energy transition.
Keywords:
Developing countries
Energy sector
ESG performance
Financial distress
Sustainability
I.
Introduction
The Paris Agreement's commitment to limit global warming to 2°C—while striving for 1.5°C relative to pre-industrial levels—presents a complex dilemma for developing countries in the Asia-Pacific region. On one hand, the region remains heavily reliant on fossil fuels to drive economic development and alleviate poverty (Janardhanan & Mitra, 2017). On the other hand, these global commitments necessitate capping cumulative emissions, requiring a substantial share of fossil fuel reserves to remain untapped. Climate policies such as carbon cap-and-trade, carbon taxes, and clean air regulations are increasingly accelerating the transition toward low-carbon technologies. As a consequence, energy companies—recognized as significant contributors to global warming since 1965 (Ploeg & Rezai, 2020)—face an escalating risk of stranded assets in the form of coal, oil, and gas reserves that can no longer be productively exploited in a low-emission economy.
Geographically, the Asia-Pacific region is particularly vulnerable to stranded assets, with the coal sector being the most exposed (Dulong, 2023). This risk is further amplified by the possibility of misjudging future energy demand, potentially leading to an oversupply of commodities that generate lower-than-expected returns and ultimately become stranded. Even in the absence of new environmental policies, continued investment in fossil fuel infrastructure may result in economic disruption on a scale comparable to the 2008 global financial crisis (Mercure et al., 2018). Such losses—projected at $1–4 trillion globally—could be aggravated by aggressive climate goals or sustained overproduction by low-cost fossil fuel suppliers amid declining demand (Hubacek & Baiocchi, 2018).
Stranded assets represent a systemic financial risk for energy companies, potentially leading to overvaluation, inflated asset prices, carbon bubbles, and economic instability. These mispriced assets may provoke widespread losses and significant wealth redistribution. This concern is compounded by an increased risk of asset impairments—particularly in carbon-intensive industries like energy (Zhao et al., 2023). Inaction in the face of climate change only heightens the likelihood of financial distress; however, this can be mitigated through early decarbonization and robust sustainability integration.
ESG practices offer a strategic framework for energy firms to manage the financial risks associated with stranded assets. Firms with strong ESG performance have been shown to attain higher credit ratings and lower default probabilities (Boubaker et al., 2020). Solid environmental performance can reduce financial constraints, as market actors increasingly perceive sustainable behavior as added value (Qureshi et al., 2021). On the social front, strong performance is associated with lower debt costs and improved credit ratings, enhancing a firm’s attractiveness to lenders (La Rosa et al., 2018). Effective governance also boosts corporate reputation, reduces financing costs, and increases shareholder returns (Wang et al., 2024). ESG practices thus operate as a risk-mitigation strategy—enabling firms to manage reputational, political, and regulatory risks more proactively (Godfrey, 2005). For energy firms in the Asia-Pacific, this may offer a practical path to reducing stranded asset exposure and building sustainable business models amid global decarbonization.
Despite growing attention to stranded asset–related risks, significant gaps remain in the literature. The theoretical gap stems from the lack of integration between stakeholder theory and legitimacy theory in research on ESG’s role in managing financial distress (Dulong, 2023; Ploeg & Rezai, 2020; Scott Cato & Fletcher, 2020). The contextual gap reflects the limited focus on ESG–financial distress relationships in the specific setting of Asia-Pacific energy markets, which are dominated by developing economies under high decarbonization pressure (Boubaker et al., 2020; La Rosa et al., 2018). Lastly, the methodological gap involves the absence of comprehensive studies analyzing ESG’s legitimacy mechanisms and stakeholder engagement, especially in relation to the global transition toward the 2°C climate target.
This study seeks to address these gaps by integrating stakeholder and legitimacy perspectives to analyze how ESG performance influences the risk of financial distress in energy firms operating across developing Asia-Pacific countries. Specifically, it explores whether ESG scores significantly affect the likelihood of financial distress within this sector.
The contributions of this research are threefold. First, the study draws on a sample of 30 energy firms from developing Asia-Pacific economies over the 2014–2023 period—offering empirical insight into ESG dynamics under acute decarbonization pressures. Second, the findings can inform policymakers aiming to enhance ESG frameworks and encourage more responsible investment. Third, sustainability-focused investors and corporate leaders may leverage these insights to strengthen decision-making and implement ESG-driven strategies for managing stranded asset risks. The findings reveal that ESG performance has a negative relationship with financial distress—suggesting that high-performing ESG firms are more financially resilient.
The remainder of this paper is structured as follows: the second section reviews the relevant literature; the third section outlines the research methodology; the fourth section presents the analysis and results; and the fifth section provides conclusions and implications.
II.
Literature Rewiew
2.1 Theoretical background
This study uses two theoretical foundations to explain the relationship between ESG performance and financial distress risk in energy companies in emerging Asia Pacific economies. First, the stakeholder theory developed by Freeman (2001) provides a fundamental foundation by suggesting that firms should consider all stakeholders affected by their business objectives, not just shareholders. In the context of energy companies, stakeholder management through ESG performance includes managing environmental aspects for regulators and local communities, social aspects for employees and society, and governance for investors and creditors. Although Orts & Strudler (2009) criticize that the stakeholder framework is too broad and complex to operationalize practically, empirical evidence from Hillman & Keim (2001) shows that effective stakeholder management creates real shareholder value. Positive ESG performance can enhance a company's reputation and build trust with stakeholders, which can reduce the risk of financial distress by lowering the cost of capital, increasing access to funding, and strengthening stakeholder support when the company faces difficulties.
Second, legitimacy theory enriches understanding by emphasizing how companies adjust their operations to meet social expectations (Dowling & Pfeffer, 1975). This theory is particularly relevant for energy companies in the Asia Pacific region facing significant energy transition and sustainability pressures. From a legitimacy perspective, ESG performance is an attempt by companies to demonstrate that they operate by accepted social norms and values. By acting according to societal expectations, companies can justify their existence and reduce the risk of social pressures that can trigger financial distress (Suchman, 1995). Although legitimacy measurement is abstract and dependent on social perceptions (Hybels, 1995), more prominent and visible energy companies in the market often face more significant social pressure to demonstrate their legitimacy through sustainability practices (Schaltegger & Hörisch, 2017). Strong legitimacy through ESG performance helps companies reduce the risk of losing operating licenses, minimize community resistance and regulatory pressure, and avoid sanctions and additional costs that can trigger financial distress.
2.2 Environmental performance and financial distress
When ESG performance is considered at the individual level, ESG performance in the environmental dimension is stated to have a significant impact on financial distress. There is a negative correlation between a firm's ESG performance in the environmental dimension and the risk of financial distress; in other words, research conducted by Suganda and Kim (2023) found that businesses focusing on the environmental pillar can significantly reduce the risk of financial distress. Cohen's research (2023) supports This finding by the fact that environmental-based performance can improve a company's financial stability and reduce the risk of financial stress. Results from Aslan et al. (2021) show that companies in the energy sector have the highest risk of failure when negatively affected by environmental performance. Better environmental performance can help companies control risks better, reducing the likelihood of financial problems. Companies that manage their environmental impacts well are often better at managing operational risks, such as in the energy industry, where environmental aspects are critical to business operations. The author formulates the following hypothesis:
H1. The company's environmental pillar score has a negative impact on the likelihood of financial distress.
2.3 Social performance and financial distress
In addition, many studies have been conducted on the relationship between company performance regarding social aspects and financial distress. According to Dumitrescu et al. (2020), the performance of the social dimension significantly reduces the likelihood of financial distress. This finding is supported by Brogi et al. (2022), who found that the social dimension negatively correlates with financial distress. High social performance can serve as insurance as it limits the firm's sensitivity to risk (Braune et al., 2019). This increases profitability and preserves shareholder value during financial uncertainty and market depression. Companies with better social performance are also considered to have better credit and find it easier to obtain financing (Boubaker et al., 2020). This reduces the likelihood of default and financial problems, especially for businesses with strong governance mechanisms and intense market competition. The author formulates the following hypothesis:
H2. The company's social pillar score has a negative impact on the likelihood of financial distress.
2.4 Governance performance and financial distress
Governance is the last dimension of the corporate ESG performance component. Dumitrescu et al. (2020) show that good governance performance significantly impacts financial distress. This result aligns with research conducted by Aslan et al. (2021), who found a negative correlation between good management performance and corporate default risk. This suggests that better management practices reduce the likelihood of a company experiencing financial distress. Corporate failure can occur if corporate governance is not good. Good governance practices reduce agency costs, align the interests of management (agents) with the interests of shareholders (principals), and prevent selfish behavior that can cause financial problems (Ahmad et al., 2018). Governance can prevent agency bankruptcy by reducing costs and improving risk management. Good governance can distinguish success from failure (Sewpersadh, 2022). This is especially important during times of financial distress. The author formulates the following hypothesis:
H3. The company's governance pillar score has a negative impact on the likelihood of financial distress.
III.
Research Methodology
3.1 Sampling and data collection
This research utilizes accounting and ESG data for the energy sector in emerging Asia Pacific countries for 2014–2023 extracted from the Refinitiv Eikon database. Refinitiv Eikon was chosen because it provides comprehensive real-time and historical data, with consistent ESG assessments using more than 400 metrics that enable in-depth analysis for longitudinal studies (Rajesh & Rajendran, 2020). The selection of the Asia Pacific region is based on its unique characteristics, where, over the past 20 years, the region has maintained the highest economic growth rate compared to other regions and is dominated by developing countries (IMF, 2023). This focus on developing countries is important given that most previous ESG studies have focused on developed country contexts with established regulatory infrastructure (Poll, 2022), creating a gap in understanding the dynamics of ESG implementation in developing countries with different institutional challenges. Through analyzing the trend and impact of ESG performance on financial distress in the energy sector, this study is expected to encourage awareness of the importance of ESG and the development of a stronger regulatory framework in developing countries.
Regarding sample selection, we follow the same procedure as (Abdi et al., 2020) to include a sample of energy sector companies that have available information. Purposive sampling has a criterion: energy sector companies must have complete accounting and financial data for all research variables. The result is 30 energy sector companies from developing countries in Asia Pacific. Panel A of Table 1 presents the sample distribution by country, while Panel B outlines the energy sub-sectors represented by the selected companies according to the Refinitiv Eikon.
Panel A. Sample distribution by country | ||
|---|---|---|
No. | Country | Company selected |
1 | China | 10 |
2 | India | 5 |
3 | Indonesia | 5 |
4 | Malaysia | 5 |
5 | Thailand | 5 |
Total sample | 30 | |
Panel B. Sample representation by sub-sector | ||
No. | Sub-sector | Company selected |
1 | Oil, Gas & Consumable Fuels | 24 |
2 | Energy Equipment & Services | 6 |
Total sample | 30 | |
3.2 Variable definitions
We choose the Altman Z-score as the dependent variable to test the relationship between sustainability performance through ESG and financial distress. This aligns with previous research by Altman et al. (2017), who demonstrated the Altman Z-score to measure financial distress. The independent variable includes ESG performance, which consists of 3 main pillars: environmental, social, and governance. This aligns with previous research (Shi et al., 2023), which shows its relevance to measuring corporate sustainability performance. We also select control variables such as liquidity, profitability, and leverage to account for factors affecting the relationship between sustainability performance through ESG and financial distress. Each control is carefully selected based on theoretical and empirical evidence from previous studies, including, (Abbas & Ahmad (2011) and Agarwal & Bauer (2014).
The current ratio serves as a measure of liquidity. The liquidity variable is relevant because it indicates a company's ability to meet its short-term obligations, which can signal early financial distress. EBIT/current liabilities serve as a measure of profitability. Profitability is an appropriate variable because it reflects a company's effectiveness in generating profits, which can be used to measure its resilience to financial distress. Debt to asset ratio serves as a measure of leverage. The leverage variable is also relevant because it indicates the level of debt usage in the firm's capital structure, which can reflect the risk of financial distress and the firm's ability to fulfill its obligations to creditors. These control variables significantly influence a firm's financial distress in line with the existing literature.
3.2.1 Dependent variable
The Altman Z-score is a powerful tool for measuring financial distress and has been used effectively to analyze the impact of ESG disclosures on financial distress (Useche et al., 2024). The Altman Z-score (Altman, 1968) is a five-factor MDA model that is claimed to correctly predict the bankruptcy of 95% of publicly traded manufacturing companies one year before failure (and 72% two years prior). Subsequently, a modified Z-score model was adapted to expand the scope of company characteristics that can be tested to predict the risk of financial distress using Altman's model (Altman et al., 2017). This model has been adapted to the conditions of companies from both the private and public sectors and engaged in manufacturing and non-manufacturing industries. In addition, the modified Z-score model can more accurately predict the risk of financial distress of firms from developing country backgrounds as it applies weighted coefficients and excludes the activity ratio or revenue to total assets ratio to filter the function from possible sector- and country-related distortions (Li et al., 2014). Our dataset includes energy sector companies in emerging Asia, so we adopt the modified Z-score model.
Altman himself used MDA to build this model, and the modified Altman Z score uses the coefficients and variables from the following equation:
Z-Score = 6.56X1 + 3.26X2 + 6.72X3 + 1.05X4 + 3.25
Where X1 = working capital/total assets, X2 = retained earnings/total assets. X3 = earnings before interest and taxes (EBIT)/total assets, X4 = market value equity/total liabilities, and a constant coefficient of 3.25 for companies in developing countries.
Based on the discrimination zone, companies with a Z-score above 2.6 indicate a low probability of bankruptcy. In contrast, companies with a Z-score below 1.1 indicate a high probability of bankruptcy. Companies with low Z-scores are considered less financially sound when used as a proxy for financial risk.
3.2.2 Independent variable
This study measures energy sector sustainability using Refinitiv Eikon's ESG pillar scores. ESG stands for Environmental, Social, and Governance. Refinitiv combines over 450 indicators into scores from 0 (low) to 100 (high). These scores capture four key areas: environmental management (managing carbon emissions and resource use), worker well-being (ensuring health, safety, and diversity), stakeholder relations (fulfilling community and customer responsibility), and governance (structuring boards and upholding ethics) (EIKON, 2017; Grisales & Caracuel, 2021). Each ESG pillar focuses on a specific part of sustainable business.
Environmental pillar (ENV): This pillar evaluates corporate strategies for managing ecological impacts across natural systems, such as emissions, resource use, and ecosystem protection. It assesses firms' ability to mitigate risks such as regulatory penalties, pollution liabilities, and resource shortages, while also identifying opportunities for environmental innovation. Notably, research suggests that strong environmental performance can reduce litigation risk and disruptions, thereby potentially lowering financial vulnerability (Broadstock et al., 2021).
Social pillar (SOC): This pillar shows how a company works with people. It covers employees, workplace safety, community engagement, and product responsibility. It indicates whether a company can build trust, which matters for reputation and for dealing with workers and customers. In the energy sector, it also shows if a company can maintain trust to keep operating. This affects access to resources, government approval, and market acceptance (Porter & Kramer, 2011; Grisales & Caracuel, 2021).
Corporate governance (GOV) pillar: This pillar examines how the company is run. It includes board independence, executive accountability, and shareholder protection. It also covers systems to ensure compliance with rules. It shows if managers' actions align with long-term shareholder goals and if there is clear oversight. Good governance reduces conflicts, makes information reliable, and helps the company stay strong during hard times. This matters in developing Asia-Pacific regions where rules may be weaker (Aguilera et al., 2015). Strong governance demonstrates reliability. It may help the company secure funding and reduce borrowing costs. This can lower the risk of financial problems.
Variable category | Variable name | Abbreviation | Measurement |
|---|---|---|---|
Dependent variable | Altman Z-score | Z | The modified Altman bankruptcy prediction model is used to predict a firm's likelihood of financial distress. It is calculated as Z = 6.56 (working capital/total assets) + 3.26 (retained earnings/total assets) + 6.72 (EBIT/total assets) + 1.05 (market value of equity/book value of total liabilities), with a constant of 3.25 calibrated for emerging market firms. |
Main variables | Environmental pillar score | ENV | Environmental stewardship rating (0-100) from Refinitiv Eikon ESG, indicating the company's performance in managing its environmental impacts. |
Social pillar score | SOC | Stakeholder engagement and social responsibility index (0-100), Refinitiv Eikon ESG, reflecting a company's effectiveness in managing relationships and social responsibilities. | |
Governance pillar score | GOV | Corporate governance metric (0-100) from Refinitiv Eikon ESG, assessing the firm's governance practices and structures. | |
Control variables | Liquidity | LIQ | Ratio of current assets to current liabilities measuring short-term solvency. |
Profitability | PROF | Ratio of earnings before interest and taxes to current liabilities, indicating how effectively a company uses its resources to cover short-term obligations. | |
Leverage | LEV | Ratio of long-term debt to total assets, indicating capital structure. |
3.3 Statistical models
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To achieve this, we use a fixed-effects estimation approach. Based on the Chow test and the Hausman test, we chose to use the fixed-effects estimation approach instead of the randomized and ordinary least squares estimation approaches. We used the Chow test and Hausman test as diagnostic tests to select the main analytical tool, which indicated that fixed-effects estimation is appropriate for this investigation (See Table 3). To ensure the reliability of our investigation, we used the Generalized Method of Moments.The model used is as follows:
Zit = β0 + β1ENV(it) + β2SOCit + β3GOV(it) + β4LIQit + β6 PROF(it) + β6LEVit + ε. It
Where Z represents the level of financial distress, measured by the modified Z score; ENV represents the environmental pillar score; SOC represents the social pillar score; GOV represents the governance pillar score; LIQ represents the liquidity ratio, measured by current assets divided by current liabilities; LEV represents the leverage ratio, measured by long-term debt to total assets; PROF represents the profitability ratio, measured by EBIT to current liabilities. We used Eviews statistical computing software in this study to conduct panel data analysis.
Effects test | Statistic | Prob | Result |
|---|---|---|---|
Chow | 258.105402 | 0.0000 | Fixed > Pooled |
Hausman | 28.900559 | 0.0001 | Fixed > Random |
IV.
Result / Finding (Heading 4)
4.1 Descriptive statistics
Variable | Obs | Mean | Std. Dev | Min | Max |
|---|---|---|---|---|---|
Z | 300 | 5.268 | 2.649 | -8.632 | 15.249 |
ENV | 300 | 58.543 | 24.143 | 0.420 | 94.101 |
SOC | 300 | 58.826 | 23.107 | 3.336 | 96.953 |
GOV | 300 | 51.759 | 22.711 | 10.063 | 95.037 |
LIQ | 300 | 1.419 | 0.837 | 0.061 | 5.046 |
PROF | 300 | 0.397 | 0.443 | -0.349 | 3.501 |
LEV | 300 | 0.252 | 0.166 | 0.183 | 1.651 |
Table 4 presents the descriptive statistics of the relevant factors obtained from our study's sample of 300 firms. As measured by Z-score, financial distress has a mean value of 5.268, with a range from − 8.632 to 15.249, indicating significant variation in the financial health of the sample firms. Negative Z-score values indicate that some companies are in severe financial distress. Regarding ESG, environmental performance (ENV) shows an average of 58.543 with a standard deviation of 24.143, indicating that the sample companies have a moderate commitment to environmental management, with a range of values from 0.420 to 94.101. Social performance (SOC) has a similar average of 58.826, with variations from 3.336 to 96.953, indicating diversity in corporate social responsibility practices.
Meanwhile, governance (GOV) has a slightly lower average of 51.759, ranging from 10,063 to 95,037, indicating considerable variation in corporate governance practices. For the firm's financial characteristics, liquidity (LIQ) shows an average of 1.419 with a standard deviation of 0.837, illustrating its ability to meet its short-term obligations. Profitability (PROF) averages 0.397, ranging from − 0.349 to 3.501, indicating significant variation in the company's ability to generate profits. Leverage (LEV) has an average of 0.252, ranging from 0.183 to 1.651, indicating significant variations in the capital structure of companies, with some companies having debt that exceeds the value of their assets. This statistic shows the diversity in ESG practices and financial conditions among the companies in the sample.
Table 5 shows the results of the Pearson correlation test used to check whether the variables in the sample are multicollinear. The results show that multicollinearity is not a problem, as none of them exceeds 0.70. As a result, multicollinearity in the current analysis is not a problem. In addition, we used the variance inflation factor (VIF) test to test for multicollinearity issues in the data. Since the variance inflation factor (VIF) for each independent variable was less than 10, there is no problem with multicollinearity in the data (See Table 6). However, the heteroscedasticity test has variable values below 0.05, so there is a heteroscedasticity problem (See Table 6). Thus, we use Generalized Least Squares (GLS), which is designed to handle heteroscedasticity by incorporating the error variance structure into the estimation process, making it the Best Linear Unbiased Estimator (BLUE) under these conditions (Politis & Poulis, 2014).
Variables | Z | ENV | SOC | GOV | LIQ | PROF | LEV |
|---|---|---|---|---|---|---|---|
Z | 1.000 | ||||||
ENV | 0.296 | 1.000 | |||||
SOC | 0.284 | 0.673 | 1.000 | ||||
GOV | -0.093 | 0.355 | 0.164 | 1.000 | |||
LIQ | 0.620 | 0.196 | 0.232 | -0.078 | 1.000 | ||
PROF | 0.642 | 0.265 | 0.259 | 0.019 | 0.553 | 1.000 | |
LEV | -0.180 | 0.108 | 0.093 | -0.064 | -0.044 | -0.079 | 1.000 |
Collinearity VIF test | Heteroskedasticity Breusch-Pagan | |
|---|---|---|
Independent variable | ||
ENV | 2.134 | 0.0003 |
SOC | 1.887 | 0.2258 |
GOV | 1.201 | 0.0926 |
Control variables | ||
LIQ | 1.484 | 0.8887 |
PROF | 1.511 | 0.3272 |
LEV | 1.042 | 0.0280 |
4.2 Regression analysis
In Table 7, the results of the GLS model show that ENV is not statistically significant with a coefficient of -0.0022, which indicates that a one-unit change in ENV leads to a -0.0022 change in the likelihood of financial distress as measured by Z-score. Thus, a one-unit increase in the environmental pillar score leads to a -0.0022-unit decrease in the financial distress score of the energy sector sample companies. A higher Z-score implies lower financial risk, meaning that a higher ENV increases the risk of financial distress in the sample firms. This result does not support H1. SOC has a positive and statistically significant relationship with Z-score, while it has a positive and statistically insignificant relationship with Z-score. This means that SOC and GOV are negatively associated with financial distress, supporting H2 and H3.
Variables | Coefficient | Std. Error | t-Statistic | Prob. |
|---|---|---|---|---|
ENV | -0.0022 | 0.0020 | -1.0926 | 0.2756 |
SOC | 0.0062 | 0.0022 | 2.7736 | 0.0059 |
GOV | 0.0005 | 0.0019 | 0.2466 | 0.8054 |
LIQ | 1.3001 | 0.0695 | 18.7100 | 0.0000 |
PROF | 1.9221 | 0.0772 | 24.9141 | 0.0000 |
LEV | -2.3624 | 0.4675 | -5.0528 | 0.0000 |
4.3 Additional Analysis-Robust analysis
Many corporate finance academics recognize the endogeneity problem in panel data. The generalized method of moments (GMM) is an estimation technique that removes endogeneity (Lin et al., 2019). Dynamic GMM includes a one-year lag of the dependent variable as an independent variable to capture adjustment dynamics and correct for endogeneity. Table 8 summarizes the GMM regression results. The Sargent test tests the instrument's validity (Roodman, 2009). The insignificant value of the Sargan test indicates that the instruments used in the equation are appropriate. The Arellano-Bond test is used to determine consistent estimation, i.e., there is no autocorrelation between the residuals and the endogenous variables, which is indicated by the second-order first difference. An insignificant AR(2) value indicates no autocorrelation problem. The Wald test determines the joint significance of the calculated coefficients for all variables. The probability value (0.0000) indicates that the research model is significant and statistically meaningful. Based on the GMM test results, this research model is free from endogeneity.
Variable | Z-score |
|---|---|
Z-score (-1) | 0.0759 (0.0274) |
ENV | -0.0256 (0.0055) |
SOC | 0.0484 (0.0092) |
GOV | − 0.0176 (0.0039) |
LIQ | 2.1949 (0.2780) |
PROF | 2.2267 (0.2463) |
LEV | 0.2406 (0.5214) |
Wald statistic | 712.7716 |
AR (1) | 0.0000 |
AR (2) | 0.0917 |
Sargent Test | 0.9211 |
V.
Discussion
The finding of a negative relationship between the environmental pillar and Z-score implies that environmental activities increase the risk of financial distress. However, the statistically insignificant result between the environmental pillar and Z-score is inconsistent with the findings of (Pålsson and Beijer, 2021). This could be because while environmentally responsible firms may exhibit lower resilience and risk, they also face higher costs that could lead to financial distress if not managed properly (Hoang et al., 2020), as described in legitimacy theory, where pressure to meet social expectations related to the energy transition creates a short-term financial burden for energy companies in developing countries. The study by Xing et al. (2025) shows that firms involved in environmental violations are more likely to experience financial distress. This is due to increased funding constraints and decreased internal control quality, thus exacerbating financial distress. While environmental responsibility may have a short-term negative impact on profitability, it is essential for long-term sustainability and reducing the risk of stranded assets. The trend of unrelenting investment in fossil fuel infrastructure of energy sector companies in the Asia Pacific region triggers the risk of financial distress due to increasing stranded assets. Therefore, the sector should focus on environmental innovation to improve environmental and financial performance, as innovations in reducing carbon emissions and improving energy efficiency can reduce the negative financial impact of environmental initiatives (Wedari et al., 2023) and can prevent the risk of financial distress.
The finding of a significant and positive relationship between the social pillar and Z-score is consistent with the findings of (Pålsson and Beijer, 2021). This indicates that positive corporate social responsibility performance significantly reduces financial distress. Social responsibility practices can produce a more stable and supportive business environment, making it less prone to financial instability (Al-Hadi et al., 2019). Energy sector companies can strengthen relationships with stakeholders and invest in sustainable projects such as renewable energy technology to improve corporate reputation and stakeholder trust. Although there is a risk of financial distress in this sector in the Asia Pacific region due to stranded assets, this can be minimized by aligning ESG initiatives with the company's core business strategy to ensure its contribution to long-term financial stability and resilience. Thus, energy sector companies should gradually invest in technologies that improve environmental sustainability and operational efficiency, which can indirectly support social initiatives (Martto et al., 2023). This will reduce the risk of excessive stranded assets as companies focus on sustainable businesses.
The finding of an insignificant and positive relationship between governance pillars and the risk of financial distress is consistent with the findings (Pålsson & Beijer, 2021). This indicates that positive corporate governance performance reduces financial distress. However, the relationship is not statistically significant, so energy sector companies in the Asia Pacific region can improve their governance practices by increasing the expertise of board members to have relevant skills and experience that can improve decision-making and oversight. Furthermore, encouraging board independence and gender diversity can positively impact governance quality, which in turn can reduce financial distress (Wu et al., 2023). Compliance with global climate policies is important. There is a global climate policy to accelerate the transition to renewable energy, so boards should direct companies in this sector to invest in sustainability projects. Aligning capital allocation with long-term sustainability goals is necessary to prevent resource misallocation contributing to carbon bubbles and stranded assets (Riedl, 2022). In addition, boards can advocate for a strong regulatory framework that supports the transition to sustainable energy and provides clear guidelines to reduce the risk of stranded assets (Peel et al., 2019).
VI.
Conclusion and Recommendation
6.1 Conclusion
This study examines the effect of environmental, social, and governance pillar performance on the financial distress of energy companies. Using a sample of 30 energy companies in the Asia Pacific region over 2014–2023, a panel data approach with fixed effects estimation and a Generalized Method of Moments (GMM) is applied for robustness checks. The findings show that the environmental pillar (ENV) positively impacts financial distress, indicating that environmental activities increase the risk of financial distress. This finding can be explained through legitimacy theory, where pressure to meet social expectations related to the energy transition creates a short-term financial burden for energy companies in developing countries.
In contrast, the social pillar (SOC) and governance pillar (GOV) have a negative impact on financial distress, indicating that higher activities of the two pillars can reduce the risk of financial distress, which aligns with stakeholder theory and emphasizes the importance of building constructive relationships with various stakeholders. These results enrich the literature by demonstrating how legitimacy and stakeholder support mediate between ESG performance and financial distress, providing practical implications for energy companies in developing countries to adopt a phased approach in implementing environmental initiatives while prioritizing social and governance aspects in building financial resilience.
A
This study investigates the influence of Environmental, Social, and Governance (ESG) pillar performance on the financial distress risk of energy companies in developing Asia-Pacific countries. Drawing on panel data from 30 firms over the 2014–2023 period, the analysis employs a fixed effects estimation model, complemented by Generalized Method of Moments (GMM) for robustness. The findings reveal that the environmental pillar (ENV) is positively associated with financial distress, suggesting that environmental initiatives—while aligned with global decarbonization goals—may impose short-term financial burdens on energy firms, particularly in emerging markets. This outcome aligns with legitimacy theory, which posits that firms under societal pressure may incur additional costs to maintain legitimacy in the face of climate transition expectations.Conversely, both the social (SOC) and governance (GOV) pillars exhibit negative relationships with financial distress, indicating that firms actively engaging in socially responsible practices and implementing strong governance structures are more financially resilient. These findings are consistent with stakeholder theory, emphasizing the importance of maintaining constructive and credible relationships with key stakeholders to enhance firm stability.
This research contributes to the ESG and financial distress literature by demonstrating how legitimacy and stakeholder engagement mechanisms jointly mediate ESG’s effect on firm vulnerability. In practical terms, the study highlights the importance for energy firms in developing countries to adopt a phased, balanced ESG strategy—prioritizing social and governance dimensions as immediate levers for financial stability, while gradually integrating environmental initiatives in alignment with institutional and economic readiness.
6.2 Implication
This study offers critical implications for policymakers, sustainability-oriented investors, and corporate leaders navigating the energy transition in developing economies. Policymakers can leverage these findings to design more robust ESG regulations and reporting standards. By institutionalizing ESG disclosures, they can enhance risk governance, increase transparency, and foster a more stable financial environment within a sector inherently exposed to environmental and transition-related vulnerabilities.
For investors, particularly those with a sustainability mandate, the results highlight the value of incorporating ESG metrics into investment analysis. High ESG performers are shown to be less prone to financial distress, signaling stronger long-term viability and lower risk exposure—an insight particularly relevant in volatile energy markets.
Corporate leaders can utilize these insights to position ESG practices not merely as compliance tools, but as strategic mechanisms for mitigating stranded asset risks and enhancing financial resilience. As the findings suggest a negative correlation between ESG performance and financial distress, firms that proactively decarbonize and strengthen their social and governance pillars may better withstand climate-induced market disruptions.
Beyond financial considerations, ESG adoption enables energy firms in developing countries to transform their operational models toward sustainable, future-proof business structures. Superior ESG performance can drive more efficient resource use, reduce emissions, and contribute to broader environmental stewardship. This transformation is especially significant in the context of achieving Sustainable Development Goals (SDGs), including climate action (Goal 13) and responsible consumption and production (Goal 12), where the energy sector plays a pivotal role.
6.3 Limitations and Recommendations
This study acknowledges several limitations that open valuable avenues for future research. First, the scope is restricted to the energy sector in developing countries within the Asia-Pacific region. Future studies may expand the sectoral coverage to include other carbon-intensive industries—such as transportation, manufacturing, or agriculture—and adopt a comparative perspective by examining firms from both developed and less developed economies. Such expansion would enrich our understanding of ESG–financial distress dynamics across different regulatory and economic contexts. Second, the current analysis primarily employs accounting-based indicators to assess financial distress. To capture market sentiment and investor perceptions, future research could incorporate market-based risk metrics, such as credit default swap (CDS) spreads, stock return volatility, or Altman's Z-score in market-adjusted form. Third, this study relies on ESG scores from a single data provider, Refinitiv Eikon. Given the methodological divergence among ESG rating agencies, subsequent research could compare findings across alternative ESG datasets—including Bloomberg, MSCI, or Sustainalytics—to assess the robustness and consistency of ESG–financial distress relationships under varying scoring frameworks. Addressing these limitations not only strengthens empirical generalizability but also contributes to a more nuanced and comparative understanding of how ESG performance shapes financial resilience—particularly within the broader discourse on sustainability, risk governance, and global decarbonization goals.
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Funding statement
The author(s) declare that this research was conducted without any financial support from funding agencies in the public, commercial, or not-for-profit sectors. No external funding was received for the design, implementation, analysis, or publication of this study.
data available statement
The data that support the findings of this study were obtained from the Refinitiv Eikon database. Access to Refinitiv Eikon is subscription-based and restricted to authorized academic institutions. The authors accessed the database through Telkom University’s institutional license, which provides Refinitiv Eikon access for faculty members and students via the university library. Accordingly, the data are not publicly available but can be accessed by eligible researchers through institutional subscriptions to Refinitiv.
Clinical Trial Number
Not applicable – this study is not a clinical trial.
Consent to Publish
Not applicable
Consent to Participate
Not applicable
Ethics Declaration
Not applicable
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Author Contribution
F.T.K., A.Z., and D.P.P. conceptualized the study and developed the theoretical framework. F.T.K led the writing of the manuscript and coordinated the research process. A.Z. collected and processed the data, while D.F.S and T.H. conducted the statistical analysis and robustness checks. All authors contributed to the literature review, interpretation of results, and final revisions. All authors reviewed and approved the final manuscript.
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Data Availability
The data that support the findings of this study were obtained from the Refinitiv Eikon database. Access to Refinitiv Eikon is subscription-based and restricted to authorized academic institutions. The authors accessed the database through Telkom University’s institutional license, which provides Refinitiv Eikon access for faculty members and students via the university library. Accordingly, the data are not publicly available but can be accessed by eligible researchers through institutional subscriptions to Refinitiv.
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