Issue #3 (Volume 17 2026)

Type of the article: Research Article

Abstract
Vietnam’s revived nuclear power program creates an environmental economics problem because accident externalities, restoration obligations, and delayed compensation can shift costs from operators to affected communities, ecosystems, and public budgets. This study aims to assess the environmental and economic risk allocation and compensation readiness of Vietnam’s post-2025 nuclear liability framework against modern international nuclear liability benchmarks. A doctrinal and comparative method is applied to Law No. 94/2025/QH15, Decree No. 332/2025/ND-CP, Decision No. 768/QD-TTg, the 1997 Vienna Convention, and IAEA materials, using legal and policy data for 2025–2026 updated through April 2026. The results show that Vietnam fully aligns with five of seven benchmark elements and partially aligns with two. The aligned elements perform four economic functions: channeling concentrates claims and insurance demand in one operator; strict liability internalizes prevention and accident costs; seven compensable heads cover death, health injury, property loss, direct economic loss, environmental restoration, environmental-use income loss, preventive measures, and residual economic loss; and 30-year/10-year limitation periods protect latent claims. The monetary architecture requires 150 million SDR of operator financial security for nuclear power plants, 5 million SDR for other installations and transport, a 300 million SDR total compensation floor per incident, and a state top-up for shortfalls. The terrorism defense and missing treaty-based cross-border procedure remain partial gaps. The study concludes that Vietnam has a domestic platform for cost internalization, but full environmental and economic compensation readiness depends on treaty accession, valuation rules for environmental damage, and operational financing of claims.

Acknowledgment
This research is funded by University of Economics and Law, Vietnam National University Ho Chi Minh City, Vietnam.

Type of the article: Research Article

Abstract
The transition toward low-carbon energy systems is increasingly viewed not only as an environmental necessity but also as a driver of innovation, competitiveness, and entrepreneurial development in modern economies. This study investigates how public energy research, development, and demonstration (RD&D) expenditures are associated with annual energy and green start-up counts, as well as with the availability of venture financing for clean-technology entrepreneurship across countries. The empirical analysis is based on a panel dataset covering 23 countries over the period 2000–2023 (470 country-year observations). It applies Poisson and negative binomial fixed-effects models, distributed lag specifications, fixed-effects OLS, and Gamma PML and PPML estimators. The results indicate that public RD&D spending does not have a statistically significant immediate effect on the number of green start-ups, as the Poisson FE estimates for renewable RD&D (0.034) and storage RD&D (0.011) remain insignificant. The venture-funding models show positive, though only weakly significant, coefficients for renewable-energy RD&D, with values of 1.41 for early-stage funding and 1.56 for later-stage funding, suggesting a possible association between public research activity and venture financing. Robustness checks indicate that low-carbon RD&D is positively associated with later-stage venture financing in selected model specifications, with a PPML coefficient of 1.77. The findings suggest that public RD&D is not a standalone driver of annual energy and green start-up counts and may be related to selected venture-financing outcomes, particularly in later-stage funding models, such as the scaling and commercialization of green innovation.

Acknowledgment
This article was prepared based on the results of the project 101127491-EnergyS4UA-ERASMUS-JMO2023-HEI-TCH-RSCH. Views and opinions expressed are, however, those of the authors only and do not necessarily reflect those of the European Union or European Education and Culture Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

Type of the article: Theoretical Article

Abstract
Industrial symbiosis has gained increasing importance as a systemic approach within the circular economy for improving resource efficiency and reducing greenhouse gas emissions. The aim of this study is to develop a theoretical framework explaining how industrial symbiosis networks contribute to greenhouse gas emission reduction within an environmental economics perspective. The study is based on a theoretical analysis and conceptual synthesis of industrial ecology and environmental economics literature.
The results identify three core operational mechanisms – material substitution, energy cascading, and waste valorization – through which industrial symbiosis reduces lifecycle emissions, and structure their relationships within a framework consisting of four interrelated components: industrial symbiosis activities, operational mechanisms, environmental performance outcomes, and environmental economic outcomes. Greenhouse gas emissions expressed in CO2-equivalent terms are conceptualized as the primary environmental performance indicator, while economic indicators such as cost savings, eco-efficiency, and emission abatement cost are integrated to explain how emission reduction aligns with economic efficiency. The framework demonstrates that industrial symbiosis functions as a decentralized coordination mechanism that reduces environmental externalities through system-level resource optimization rather than technological change alone.
The findings contribute to environmental economics theory by clarifying the relationship between industrial cooperation, environmental performance indicators, and economic efficiency, providing a structured basis for future empirical assessment and policy evaluation.

Type of the article: Research Article

Abstract
Central Asian countries face acute air quality challenges, with PM2.5 concentrations in major cities exceeding World Health Organization guidelines several times over, while industrial CO₂ emissions continue to rise alongside economic development. Understanding the empirical linkage between these pollutants is essential for designing integrated environmental policies. The purpose of this study is to assess the impact of industrial CO₂ emissions on PM2.5 air pollution in five Central Asian countries – Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan – using balanced panel data for the period 2000–2020 (N = 105) obtained from the World Bank’s World Development Indicators. Pooled OLS, fixed effects, and random effects estimators were applied, with GDP per capita, urbanization, and energy intensity as control variables. Model selection was based on the Hausman test, and robustness was verified through ten alternative specifications. The random effects model (Hausman χ2 = 0.412, p = 0.521) reveals a statistically significant positive relationship: a one million metric ton increase in industrial CO₂ emissions is associated with a 0.87–0.89 µg/m3 rise in mean annual PM2.5 concentration (p < 0.01). The coefficient remains stable across all robustness checks (0.823–0.923). GDP per capita shows a significant negative effect (−1.92, p < 0.05), supporting the Environmental Kuznets Curve hypothesis, while energy intensity has a positive effect (p < 0.05). Country-specific effects reveal substantial heterogeneity, with Tajikistan exhibiting the highest baseline PM2.5 (+26.25 µg/m3 above Kazakhstan) and Turkmenistan the lowest (+7.49 µg/m3). These findings confirm the co-pollutant hypothesis and justify integrated climate-air quality policies with country-specific strategies.

Acknowledgments
The authors would like to thank the anonymous reviewers for their constructive comments and suggestions that helped improve this manuscript.

Type of the article: Review Article

Abstract
Energy prices are a crucial factor influencing the emissions–income nexus. Hence, this study aims to examine the environmental effects of energy prices within the Environmental Kuznets Curve (EKC) framework through bibliometric analysis and narrative synthesis of empirical studies. For this purpose, 67 Scopus-indexed documents published during 1997–2025 are analyzed. The bibliometric findings reveal that publications have grown at an exponential rate since 2016, peaking at 10 articles in 2023. Bradford’s Law analysis identifies that Environmental Science and Pollution Research is the leading source. Moreover, Lotka’s Law shows that nearly 75% of authors contributed only one or two studies, indicating a diverse research community. Citation analysis further reveals high global citations but limited local citations, suggesting strong external visibility but relatively weak internal connectivity. Thematic analysis identifies carbon dioxide emissions and renewable energy as dominant motor themes, showing increasing scholarly interest in the renewable energy transition due to high energy prices. The empirical synthesis shows that the EKC hypothesis and environmental benefits of high prices are more frequently validated in energy-importing advanced economies. In contrast, studies on energy-exporting economies often fail to validate the EKC hypothesis or report N-shaped EKC patterns, together with adverse environmental effects of energy prices. Overall, the review concludes that the environmental impact of energy prices within the EKC framework varies according to economic development and energy-trade status.

Acknowledgment
The authors extend their appreciation to Prince Sattam bin Abdulaziz University for funding this research work through the project number (PSAU/2025/RV/9). All utilized data for analysis are available at Mendeley Data (Mahmood, 2026).

Type of the article: Research Article

Abstract
This study analyzes the impact of digitalization, green transformation, financial access, and institutional support on agricultural labor productivity in transition economies of Eastern Europe and the Caucasus. Panel data for six countries (2000–2024) were examined using fixed and random effects models, with robustness checks using the Driscoll–Kraay estimator. Results show that digitalization and financial access consistently enhance productivity at the panel level (0.141; p < 0.01), while institutional factors do not show a consistent direct effect once temporal trends are removed (0.050, p > 0.05), though they may strengthen resilience indirectly. In contrast, the Green Index exerts a significant negative effect (–1.848; p < 0.01), reflecting substantial transitional costs of ecological modernization. Country fixed effects reveal heterogeneity: Moldova (+0.1106) shows the highest positive deviation, while Armenia (–0.0365), Azerbaijan (–0.0749), and Kazakhstan (–0.0382) exhibit negative deviations. Ukraine (+0.0176) and Georgia (+0.0028) remain close to the panel mean. Country specific regressions reveal both commonalities and divergences. In Moldova, institutional quality (0.265, p < 0.001), digitalization (0.033, p = 0.026), and green practices (–0.462, p < 0.001) significantly shape productivity, while finance is excluded. In Armenia, institutional quality (0.469, p = 0.001) and green practices (–0.502, p = 0.001) remain significant, but finance enters negatively (–0.855, p = 0.050), and digitalization is excluded. Digitalization and finance are immediate productivity enhancers at the regional level, but their role varies by country. Ecological modernization imposes short term costs and requires compensatory policies.

Acknowledgments
The authors acknowledge the financial support received for the implementation of the project “Accelerating the Digital and Green Transformation of Agri-Food SMEs in Moldova and Armenia”, funded by the National Agency for Research and Development of the Republic of Moldova (NARD) (Project No. 26.80013.0807.05ARM) and the Higher Education and Science Committee of the Ministry of Education, Science, Culture and Sports of the Republic of Armenia (Project No. 26NARD-1D007).

Type of the article: Research Article

Abstract
This study examines the dynamic relationships among environmental quality, economic growth, and trade across a sample of Asia-Pacific economies during the period 2000–2024. While previous studies have extensively investigated the links between economic growth, trade, and environmental degradation, relatively limited attention has been devoted to examining these variables simultaneously within a dynamic multivariate framework. To address this gap, the study employs a Vector Autoregression (VAR) approach to analyze the interdependencies among economic and environmental indicators. Environmental quality is represented by CO2 emissions, land-use change, biocapacity, and ecological footprint, while economic activity and trade are measured using GDP and trade indicators. The empirical results reveal significant dynamic relationships among economic growth, trade, and environmental variables. The estimated coefficients indicate substantial persistence across several economic and environmental indicators, suggesting important temporal dependencies within the system. The impulse response analysis further shows that shocks originating from environmental variables generate measurable responses in economic indicators, while economic disturbances are also associated with subsequent changes in environmental conditions. In addition, the stability analysis indicates that the estimated VAR system satisfies the stability condition over the sample period. The findings suggest that economic growth, trade activity, and environmental quality evolve within an interconnected dynamic framework. These results contribute to the literature on environmental–economic interactions and highlight the importance of incorporating environmental considerations into broader economic and trade policy discussions aimed at supporting long-term sustainable development.

Acknowledgment
The funding for this research was provided by Universitas Hasanuddin. We would like to express our sincere gratitude to the university for their generous support, which made this study possible.

Type of the article: Research Article

Abstract
This study aims to assess a macroeconomic methodological approach for evaluating the impact of investment activity, energy efficiency, energy costs, and renewable energy development on CO₂ emissions in Ukraine, using the model’s insights for a conceptual extrapolation to the residential sector with subsequent policy scaling to the municipal building stock. The methodological basis is a top-down approach using econometric modeling (OLS) for 2002–2021, which represents the pre-war period in Ukraine. All estimations are based on aggregated macroeconomic proxy indicators and not on direct residential or municipal emissions measurement data due to a lack of reliable information. The results demonstrate that macroeconomic energy efficiency is the most powerful driver of decarbonization. An analysis of the residential sector indicates that higher household financial burdens associated with higher utility expenditures are statistically connected with lower CO₂ emissions, which may reflect demand-side adjustments in energy consumption, including price-driven savings. However, other factors, such as energy inefficiency or energy poverty, may also add to this relationship. In contrast, traditional investment activity still contributes to growing carbon footprints, with CO₂ emissions rising by 136 kg per 1% increase in gross capital formation as a share of GDP. At the same time, the estimated coefficients for global oil prices and the share of renewable energy exhibit the expected negative signs, suggesting economically meaningful long-term decarbonization tendencies. However, these relationships do not reach conventional statistical significance and should therefore be interpreted as directional trends rather than statistically confirmed effects.

Acknowledgments
This paper is funded by the Ministry of Education and Science of Ukraine within the projects “Comprehensive vertically integrated intelligent system for monitoring and regulating energy supply in municipal sector buildings” (No. 0126U000867) and “Drivers and barriers to human capital transformation for a circular and green economy” (No. 0126U001080).

Type of the article: Research Article

Abstract
Municipal waste-to-energy is often assessed through technical efficiency, energy output, or regulatory compliance. Yet, these indicators do not show whether plants create positive social welfare after operating costs and environmental damages are monetized. This study examines how operational performance, emissions intensity, and stricter environmental valuation shape the net social benefit of German municipal waste-to-energy plants from 2017 to 2023. Germany serves as a benchmark case because its mature waste-to-energy sector, European emissions regulation, and public environmental and energy-market reporting enable transparent public-record welfare assessment. The study constructs a plant-year analytical dataset for 70 facilities from publicly accessible administrative, environmental, market, and technical records, with net social benefit treated as a constructed welfare-accounting measure based on observed records, documented public proxies, and explicit valuation assumptions. It uses plant- and year-fixed-effects models, valuation sensitivity tests, and an optimization-based decision-support layer. The descriptive evidence shows substantial welfare heterogeneity, with a mean traceable-baseline net social benefit of 17.9 euros per metric ton under the central valuation case and lower mean welfare under higher shadow prices. The fixed-effects results do not provide statistical support for the hypothesized operational drivers in the public-data panel: energy recovery, emissions intensity, availability, oxygen instability, and the interaction between emissions intensity and the shadow price index are not statistically significant. The study contributes by integrating cost accounting, externality valuation, and operational performance into a transparent public-record welfare metric for policy appraisal.

Type of the article: Research Article

Abstract
This study explores potential factors associated with renewable energy consumption in Azerbaijan by examining the relationships among economic growth, human development, per capita CO₂ emissions, and urban population growth. The analysis applies an exploratory machine learning framework based on the XGBoost algorithm combined with SHapley Additive exPlanations (SHAP) to examine possible nonlinear associations and evaluate the relative contribution of selected socioeconomic and environmental variables. Correlation analysis indicates a negative relationship between renewable energy consumption and CO₂ emissions (−0.55), while human development and economic growth exhibit generally positive associations with renewable energy use, suggesting a possible role of socioeconomic development in the energy transition process. The exploratory model produced performance indicators of R² = 0.81, RMSE = 1.18, and MAE = 1.04, suggesting that the model captures variation within the available sample; however, given the limited dataset, these results should not be interpreted as evidence of strong or robust predictive performance. SHAP-based interpretation suggests that human development and environmental pressure may represent relatively important variables within the model framework, while the effects of economic growth and urbanization appear comparatively moderate and context-dependent. Overall, the study provides preliminary exploratory evidence regarding possible nonlinear patterns linking socioeconomic development, environmental conditions, and renewable energy consumption in Azerbaijan, offering directions for future research using larger datasets and complementary empirical approaches.

Type of the article: Research Article

Abstract
The growing attention to sustainability is driving the development of green finance studies. However, the distribution of such research remains geographically uneven, particularly in developing countries. As one of the major contributors to global emissions, Indonesia plays a critical role within the broader discourse of green finance, both as a national context and as part of cross-country analyses. Therefore, a comprehensive understanding of green finance research related to Indonesia is essential, especially given the Indonesian government’s commitment to reducing greenhouse gas emissions. This study aims to conduct a bibliometric analysis to map the development of green finance literature related to Indonesia over the period 2015–2025. Using 194 Scopus-indexed publications, the results reveal a substantial increase in research output over the last four years. Indonesia recorded the highest publication output, with authors affiliated to institutions in China and Malaysia occupying important positions within the international co-authorship network. Keyword co-occurrence analysis identified four major thematic clusters: (1) Green financial systems, (2) Economic growth and environmental sustainability, (3) Green finance in energy transition, and (4) Climate finance and environmental governance. This study provides a more accurate representation of the scientific landscape of green finance literature involving Indonesia. It highlights key research trends, identifies emerging themes, and offers insights into future research directions and policy implications, particularly in contexts where Indonesia is positioned within both national and cross-country discussions of green finance.

Type of the article: Research Article

Abstract
This study investigates the impact of green human resource management (GHRM) practices on corporate sustainability (CS) and the mediating role of renewable energy adoption (REA) in Saudi enterprises progressing toward a sustainable economy. Data were collected in 2025 through a structured online questionnaire distributed to 386 employees and managers in Riyadh, Saudi Arabia. The study used exploratory and confirmatory factor analyses to identify and validate the measurement structure, and structural equation modeling (SEM) using AMOS to test the proposed relationships. The findings indicate that GHRM practices have a positive and statistically significant total effect on CS (β = 0.166, p = 0.004) both directly and indirectly through REA, highlighting that REA partially mediates this relationship. The association between GHRM and REA is statistically significant yet relatively weak (β = 0.096, p = 0.049), suggesting the mediation should be interpreted as modest rather than substantial. However, REA demonstrated a strong positive effect on CS (β = 0.710, p <= 0.001). Although GHRM explains only 1.5% of the variance in REA, REA accounted for 53% of the variance in CS, indicating that REA supports meaningful but partial mediation between GHRM and CS. The study concludes that these findings reflect associations among respondents’ perceptions and should not be interpreted as evidence of objective organizational sustainability performance. However, the relatively weak association between GHRM and REA suggests that REA is driven by a wide range of organizational, technological, financial, and policy-related factors beyond HRM practices.

Acknowledgment
The authors extend their appreciation to Prince Sattam Bin Abdulaziz University for funding this research work through the project number (PSAU/2025/02/34108).

Type of the article: Research Article

Abstract
Climate disasters increasingly damage infrastructure financed through public-private partnerships (PPPs), yet little is known about how such shocks reshape PPP markets. This paper aims to determine how climate disasters and national adaptation readiness affect PPP activity and design in developing and emerging economies. The analysis uses a balanced panel of 129 economies (2000–2024) with 8,213 PPP financial closures from the World Bank PPI Database merged with the Notre Dame Global Adaptation Initiative index, the EM-DAT international disaster database, and World Bank governance and development indicators, and estimates two-way fixed-effects linear and Poisson pseudo-maximum-likelihood models, with damage and GDP in current US dollars. Neither average damage nor major disasters (damage of at least 1% of GDP) show a robust association with the number of closures; post-event coefficients are negative but mostly insignificant, no pre-event decline is detected, and placebo event dates yield estimates of similar size. A positive coefficient at catastrophic levels (at least 5% of GDP) rests on a single episode and is not read as a reconstruction surge. Project composition does respond. After major disasters, the number of non-renewable closures falls by about 38% (p < 0.001), and by more where readiness is low, while renewable closures are unchanged. A one-standard-deviation improvement in regulatory quality is associated with a 12.6-percentage-point higher probability of a PPP closure (p < 0.01) and roughly 131% larger investment (p < 0.001). Case profiles of Armenia, Kazakhstan, and Ukraine reflect the same dominance of institutions. Regulatory strengthening and standby pipelines that keep conventional deals alive through disaster windows are the main levers for disaster-proofing PPP programs.

Acknowledgments
This study was conducted within the framework of the research project “Digitalization of the Public-Private Partnership System as a Driver of the State’s Economic Security in the War and Post-War Periods” (state registration No. 0126U000543), funded by the Ministry of Education and Science of Ukraine.

Type of the article: Research Article

Abstract
Environmental protection accounts for a small share of public budgets, which makes its determinants a practical policy question. Digital administration is expected to improve public resource allocation, and environmental protection is an information-intensive function where that expectation should be visible. This study measures the association between digital government development and the share of public expenditure allocated to environmental protection, compares it with the other nine budget functions, and describes Latvia, Ukraine, and Armenia as illustrations of divergent expenditure trajectories under broadly comparable digital government development. The analysis covers 592 country-year observations for 68 economies, including 13 post-Soviet economies, over 2004 to 2024, combining the United Nations E-Government Development Index with IMF Government Finance Statistics in a two-way fixed effects design with wild cluster bootstrap inference. Digital government development is not associated with the environmental share (β = –0.002, p = 0.997), and environmental protection records the smallest standardized effect among the ten functions, indistinguishable from zero, compared with 0.451 for social protection. European Union membership is associated with a higher environmental share (β = 0.331, p = 0.004), although the estimate is identified from four changes of membership status. A stronger association inside the post-Soviet subsample does not survive a specification that allows every coefficient to differ by group. The study therefore finds no evidence that higher digital government development alone is systematically associated with a larger environmental share of public budgets.

Acknowledgments
The contribution of Liudmyla Zakharkina to this study was carried out within the framework of the research project “GovTech for Ukraine: A Digital, Secure, Transparent, and Equitable State in Times of War and Post-War Reconstruction” (state registration No. 0126U000544), funded by the Ministry of Education and Science of Ukraine.

Type of the article: Research Article

Abstract
Decarbonization has become a challenge for European manufacturing, particularly after Russia’s full-scale invasion of Ukraine, amid rising energy costs and tensions between environmental transition and industrial competitiveness. This study assesses whether market-based climate-policy stringency is non-linearly associated with European machinery production, whether this relationship differed during 2022–2023, and whether it varies with electricity-market stress and 2020–2021 baseline energy-use characteristics. The analysis uses a 2017–2023 panel of 24 European countries; the principal C28 models cover 20 countries and 140 observations. Two-way fixed-effects models combine quadratic specifications, post-2022 interactions, electricity-price moderation, baseline energy-use moderators, and wild-cluster bootstrap inference. The contemporaneous C28 industrial-production specification shows statistically significant concavity: the quadratic MBI coefficient is −0.019 (bootstrap p = 0.047), with a model-implied turning point of approximately 4.7. The upper-bound marginal effect is −0.0984 (p < 0.001), whereas the positive lower-bound effect of 0.0768 is not statistically significant (p = 0.120). This pattern is not reproduced when MBI is lagged or when real C28 GVA levels or growth are used as alternative outcomes. Neither the post-2022 interactions (F = 0.611, p = 0.553) nor the electricity-price interactions (F = 2.193, p = 0.139) are jointly significant. The natural-gas triple interaction is positive but statistically inconclusive under wild-cluster bootstrap inference (β = 0.242, p = 0.057), while the alternative energy-use moderators are insignificant. The findings support contemporaneous concavity in short-run C28 industrial production and an adverse association at high MBI levels, but not a general non-linear relationship across broader measures of machinery-sector performance.

Acknowledgment
Tetiana Vasylieva contributed to this article within the framework of the MSCA4Ukraine project 06030419, which is funded by the European Union. Views and opinions expressed are, however, those of the authors only and do not necessarily reflect those of the European Union, the European Research Executive Agency, or the MSCA4Ukraine Consortium. Neither the European Union, the European Research Executive Agency, nor the MSCA4Ukraine Consortium, nor any individual member institution of the MSCA4Ukraine Consortium can be held responsible for them.

Type of the article: Research Article

Abstract
Amid escalating climate challenges, examining how financial innovation affects sustainable growth in Sub-Saharan Africa (SSA) while informing stronger environmental and financial policy design is a critical priority in environmental management. This study investigates the impact of green finance on green growth in SSA, emphasizing the moderating role of FinTech. Using panel data for 35 countries from 2000 to 2021, it applies the System-GMM estimator to address endogeneity. The results show that green finance significantly promotes green growth at the 1% level. FinTech also plays a critical role, both directly and by enhancing the effectiveness of green finance. Specifically, 1% increase in green finance and FinTech is associated with 5.63 % and 7.62 % gains in green growth, respectively, while their interaction yields an additional 0.22 % increase. The findings highlight the importance of policies that expand green finance through robust regulatory frameworks, innovative financial instruments, carbon pricing mechanisms, and the development of voluntary carbon markets. Leveraging FinTech can further support green investment by improving financial inclusion, lowering transaction costs, and increasing transparency. Strengthening human capital, particularly through environmental education, is essential to support sustainable practices. Besides, greater financial openness can attract foreign investment into green sectors. These measures can help policymakers foster sustainable growth, enhance climate resilience, and advance long-term environmental objectives in the region.

Type of the article: Research Article

Abstract
This paper investigates the impact of oil, coal, renewable energy consumption, CO₂ emissions in the ASEAN-5 countries for the period from 1971 to 2020 utilizing the panel ARDL and MMQR models. The panel autoregressive distributed lag (ARDL) model estimates average short- and long-run effects, whereas the method of moments quantile regression (MMQR), a panel quantile technique, estimates how these effects vary across the distribution of emissions. The MMQR results shed light on the impacts of variables on CO₂ emissions estimated at different emission levels. The results show that oil, coal consumption, and GDP are significant factors influencing CO₂ emissions. Conversely, renewable energy sources contribute significantly to reductions in CO₂ emissions. Also, the results reveal that trade activities have a significant impact on emissions in countries exhibiting high emission levels. In particular, the effects of GDP and renewable energy become stronger at higher quantiles, whereas those of oil and coal remain relatively stable. Furthermore, the panel causality tests reveal bidirectional causality between CO₂ emissions and oil consumption and economic growth. The results also support unidirectional causality from coal consumption to emissions, and causality from emissions to renewable energy. The results indicate the need for comprehensive efforts across various policy areas to reduce emissions and address climate change. Reducing coal and oil dependence should be a priority for all ASEAN-5 countries, while faster renewable deployment matters most for high emitters.

Acknowledgment
Esra Balli would like to acknowledge the financial support provided by the Council of Higher Education (YÖK) through the Academic Development Program (AKAP).