The impact of geopolitical risk and policy uncertainty on CO₂ emissions: A CS-ARDL analysis of G7 economies
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Author(s)Nuriddin ShanyazovLink to ORCID Index: https://orcid.org/0009-0000-1691-5289
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Sanaatbek K. SalayevLink to ORCID Index: https://orcid.org/0000-0001-9471-1337
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Samariddin MakhmudovLink to ORCID Index: https://orcid.org/0009-0008-2046-8889
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Ikhtiyor SharipovLink to ORCID Index: https://orcid.org/0000-0001-9736-1731
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Sanabar MatkuliyevaLink to ORCID Index: https://orcid.org/0000-0001-7280-9982
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Javohir BabajanovLink to ORCID Index: https://orcid.org/0009-0000-0827-2383
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Dilshodbek SaidovLink to ORCID Index: https://orcid.org/0009-0005-2721-5807
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DOIhttp://dx.doi.org/10.21511/ee.17(1).2026.03
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Article InfoVolume 17 2026, Issue #1, pp. 25-37
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6 Downloads
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Creative Commons Attribution 4.0 International License
Type of the article: Research Article
Abstract
This study aims to empirically examine the dynamic effects of geopolitical risk, economic policy uncertainty, and climate policy uncertainty on CO₂ emissions in G7 economies, utilizing annual data from 1990 to 2022. To account for cross-sectional dependence and parameter heterogeneity, the analysis employs a cross-sectional autoregressive distributed lag (CS-ARDL) model. Diagnostic tests confirm significant cross-sectional dependence and slope heterogeneity among the variables. All variables are integrated of order one, I (1), confirmed by unit root tests. In contrast, the cointegration test provides a strong indication of a stable long-run relationship among geopolitical risk, policy uncertainty measures, and CO₂ emissions. The outcomes show that a 1% rise in the geopolitical risk index leads to a statistically significant long-run rise of 0.042% in per capita CO₂ emissions. In addition, a 1% increase in economic policy uncertainty and climate policy uncertainty is associated with long-run increases of 0.028% and 0.015%, respectively. These results remain robust across alternative estimators. Overall, the evidence suggests that heightened geopolitical risk and policy-related uncertainties significantly exacerbate environmental degradation in G7 economies, highlighting the necessity for strategies that improve stability, reduce uncertainty, and encourage renewable energy adoption as part of a long-term environmental strategy.
- Keywords
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JEL Classification (Paper profile tab)Q54, F51, E60, C33
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References36
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Tables6
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Figures0
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- Table 1. Definition and source of variables
- Table 2. Cross-sectional dependence and slope homogeneity test results
- Table 3. CIPS panel unit root test results
- Table 4. Westerlund (2007) panel cointegration test results
- Table 5. CS-ARDL long-run and short-run estimation results
- Table 6. Robustness check results (AMG and CCEMG estimators)
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Relationships between human development, economic growth, and environmental condition: The case of South Korea
Zeynab Giyasova 
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Shafa Guliyeva ,
Reyhan Azizova ,
Liliana Smiech ,
Irada Nabiyeva
doi: http://dx.doi.org/10.21511/ee.16(2).2025.06
Environmental Economics Volume 16, 2025 Issue #2 pp. 73-83 Views: 1393 Downloads: 562 TO CITE АНОТАЦІЯThe study examines the long-term relationships between human development, economic growth, and environmental conditions in South Korea from 1996 to 2021. Understanding these interactions is crucial for shaping policies that balance economic progress, social well-being, and environmental sustainability. The analysis employs cointegration techniques, including the Fully Modified Ordinary Least Squares (FMOLS) and Canonical Cointegration Regression (CCR) methods, to estimate long-run relationships among GDP per capita, the Human Development Index (HDI), and carbon dioxide emissions per capita. Empirical findings confirm a stable long-term equilibrium between GDP and HDI, as demonstrated by significant Engle-Granger and Phillips-Ouliaris test statistics (p-values ≤ 0.0245). The results suggest that economic growth consistently enhances human development, while improvements in HDI contribute to sustained economic progress. The relationship between HDI and carbon emissions per capita, however, yields mixed evidence. The Engle-Granger test supports a long-term association (p-values ≤ 0.015), but the Phillips-Ouliaris test does not confirm cointegration (p-values ≥ 0.112). The covariance matrix test indicates that the negative relationship between HDI and carbon emissions per capita is stronger and more variable compared to the more stable inverse association between HDI and GDP per capita. Additionally, Granger causality analysis reveals a significant causal relationship between HDI and GDP per capita, supported by a Chi-square value of 20.627 and a p-value below 0.001. These findings highlight the complexity of integrating environmental considerations into development policies. South Korea’s experience underscores the necessity of a balanced policy framework that ensures sustainable economic growth while advancing human development and mitigating environmental impacts.
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The importance of renewable energy consumption and CO₂ emissions in formulating Sustainable Development Index: An economic-environmental analysis based on the ARDL model
Dilshod Karimboev ,
Yulduz Yaqubova ,
Intizor Matkarimova ,
Majidbek Jabbarov ,
Inomjon Matkarimov ,
Erkinbay Ismailov ,
Anvar Matnazarov
doi: http://dx.doi.org/10.21511/ee.16(2).2025.13
Environmental Economics Volume 16, 2025 Issue #2 pp. 173-185 Views: 793 Downloads: 411 TO CITE АНОТАЦІЯThis study examines the impact of renewable energy consumption, CO₂ emissions, and renewable electricity generation on the Sustainable Development Index in Uzbekistan over the period 1990–2023. Using an autoregressive distributed lag (ARDL) model, the study estimates the short- and long-run relationships between these variables. The Sustainable Development Index is constructed using indicators of primary school enrollment, life expectancy at birth, and female labor force participation using a min-max normalization method. The results indicate a long-run positive impact of renewable energy consumption (β = 0.0552, p < 0.05), underscoring its significant contribution to sustainable development. Conversely, renewable electricity generation has a significant negative impact in the long run (–0.0153, p < 0.01), which may be due to initial high transformation costs and short-term economic adjustments. CO₂ emissions did not have a statistically significant impact on the Sustainable Development Index. The model is robust, with no autocorrelation or heteroscedasticity issues, indicating reliable results. This study underscores the importance of strategic investments in renewable energy and offers valuable insights for policy development, thereby enhancing Uzbekistan’s sustainable development trajectory.
