Search Results (406)

This study investigates the relationship between economic growth and energy consumption using the Energy Kuznets Curve (EKC) framework. Spatial econometric models, including the Spatial Panel Lag Model and the Spatial Dynamic Panel Lag IV Model, are employed to capture both spatial and dynamic effects. The results indicate that energy consumption in Thailand is spatially clustered, with energy use tending to spill over into neighboring provinces and concentrating in specific regions. Key factors that positively influence energy consumption include gross provincial product (GPP) per capita, population density, and road density. Regions characterized by favorable climates, sufficient infrastructure, and high levels of economic activity exhibit higher per capita energy consumption. The EKC analysis reveals a U-shape relationship between GPP per capita and energy consumption in the BKK&VIC, CE, EA, WE, and NE regions. As many regions continue to experience rising energy consumption, the findings underscore the importance of Thailand adopting more efficient energy usage strategies in tandem with its economic development. Full article

This study focuses on the impact of China’s digital economy on sustainable modernization from 2011 to 2021, using provincial panel data for empirical analysis. By applying threshold and mediation models, we find that the digital economy promotes modernization through industrial upgrading (with a mediating effect of 38%) and trade openness (coefficient = 0.234). The research reveals “U-shaped” nonlinear threshold effects at specific levels of digital development (2.218), market efficiency (9.212), and technological progress (12.224). Eastern provinces benefit significantly (coefficient ranging from 0.12 to 0.15 ***), while western regions initially experience some inhibition (coefficient = −0.08 *). Industrial digitalization (coefficient = 0.13 ***) and innovation ecosystems (coefficient = 0.09 ***) play crucial roles in driving eco-efficiency and equity, in line with Sustainable Development Goals 9 and 13. Meanwhile, the impacts of infrastructure (coefficient = 0.07) and industrialization (coefficient = 0.085) are delayed. Economic modernization improves (coefficient = 0.37 ***), yet social modernization declines (coefficient = −0.12 *). This study not only enriches economic theory but also extends the environmental Kuznets curve to the digital economy domain. We propose tiered policy recommendations, including the construction of green digital infrastructure, carbon pricing, and rural digital transformation, which are applicable to China and offer valuable references for emerging economies aiming to achieve inclusive low-carbon growth in the digital era. Future research could further explore the differentiated mechanisms of various digital technologies in the modernization process across different regions and how to optimize policy combinations to better balance digital innovation with sustainable development goals. Full article

The depletion of global fish stocks poses a major challenge to sustainable development, particularly in economies where marine resources are critical to livelihoods and food security. In this study, the relationship between economic development and the sustainability of fish stocks is examined using the Environmental Kuznets Curve (EKC). We use panel data from 32 economies between 2002 and 2020 and analyze the fish stock status indicator (EPI_FSS) from the Environmental Performance Index, which captures the proportion of national catches from overfished or collapsed stocks. Using a dynamic panel approach and the generalized method of moments (GMM), we investigate how the human development index (HDI) and other socio-economic factors influence changes in the state of fish stocks. Our results show a statistically significant inverted-U-shaped (∩-shaped) relationship between the HDI and the state of fish stocks, suggesting that the deterioration of fish stocks increases at lower levels of development, but improves beyond a certain threshold. In addition, higher levels of foreign direct investment (FDI), education, and research and development (R&D) spending are associated with better outcomes for fish stocks. These results suggest that while early economic growth may put pressure on marine resources, sustained investment in human capital, innovation, and global integration is critical to promoting long-term marine sustainability. Full article

The relationship between economic progress and environmental quality remains a central focus in global sustainability discourse. This study examines the link between per capita economic growth and CO₂ emissions across 128 countries from 1996 to 2022, controlling for energy consumption, trade volume, and foreign direct investment (FDI) inflows. It also evaluates the role of governance quality—measured by regulatory quality and its volatility—while considering the globalization index as a confounding factor influencing CO₂ emissions. We test the Environmental Kuznets Curve (EKC) hypothesis, which suggests that emissions initially rise with income but decline after reaching a certain economic threshold. Our findings confirm the global presence of the EKC. The analysis further shows that trade openness, governance, and globalization significantly influence FDI inflows, with FDI, in turn, reinforcing institutional quality through improved governance and globalization indicators. However, in countries with weaker governance and regulatory frameworks, FDI tends to promote pollution-intensive industrial growth, lending support to aspects of the Pollution Haven Hypothesis (PHH). We find a significant departure in EKC explained by post-COVID governance and globalization compromises, which induced the environment towards the PHH phenomenon. These results highlight the need for context-specific policy measures that align economic development with environmental constraints. Full article

As a pivotal economic province in China, Jiangsu’s efforts in civil building energy conservation are critical to achieving the national “dual carbon” goals. This paper proposes a hybrid model that integrates wavelet transform, support vector regression (SVR), and extreme learning machine (ELM) to predict the civil building energy consumption of Jiangsu Province. Based on data from statistical yearbooks, the historical energy consumption of civil buildings is calculated. Through a grey relational analysis (GRA), the key factors influencing the civil building energy consumption are identified. The wavelet transform technique is then applied to decompose the energy consumption data into a trend component and a fluctuation component. The SVR model predicts the trend component, while the ELM model captures the fluctuation patterns. The final prediction results are generated by combining these two predictions. The results demonstrate that the hybrid model achieves superior performance with a Mean Absolute Percentage Error (MAPE) of merely 1.37%, outperforming both individual prediction methods and alternative hybrid approaches. Furthermore, we develop three prospective scenarios to analyze civil building energy consumption trends from 2023 to 2030. The analysis reveals that the observed patterns align with the Environmental Kuznets Curve (EKC). These findings provide valuable insights for provincial governments in future policy-making and energy planning. Full article

The rapid expansion of plastic waste trade has intensified environmental pressures, accelerating ecosystem degradation and climate change. We examine the long-term impacts of plastic waste imports and domestic waste production on ecological footprints and greenhouse gas emissions across 20 countries representing 70% of global plastic waste trade and 45% of world GDP. Under the Environmental Kuznets Curve (EKC) framework, we explore nonlinear interactions among economic growth, urbanization, and sustainability goals. Using a panel simultaneous equations approach, we apply Pedroni, Kao, and Westerlund cointegration tests and Fully Modified and Dynamic OLS estimators to address endogeneity and heterogeneity. Robustness checks include alternative environmental indicators and the Dumitrescu–Hurlin panel causality test. Results demonstrate a stable long-run equilibrium: plastic waste imports substantially increase ecological footprints and emissions, while progress on sustainable development goals mitigates some damage. The negative GDP squared coefficient supports the EKC hypothesis, indicating that environmental impacts rise initially with growth but decline once income exceeds a threshold. These findings highlight the need for stronger international regulations, enhanced waste management infrastructures, and circular economy strategies. Focused investment in sustainable technologies and global cooperation is essential to lower environmental costs of plastic waste trade. Full article

This study investigates the impacts of financial inclusion, development, and technological innovation on ESG readiness across low-income, lower-middle-income, and upper-middle-income countries from 2004 to 2020. Grounded in an augmented environmental Kuznets curve framework, financial intermediation, and financial literacy theories, the analysis employs a panel data approach. Results from panel and quantile regressions reveal that financial inclusion and financial development positively influence ESG readiness, with stronger effects in less financially developed countries. However, in upper-middle-income countries, excessive credit may increase energy-intensive consumption, moderating sustainability gains. Financial inclusion negatively affects ESG readiness at lower quantiles in low-innovation contexts but enhances it at higher quantiles in high-innovation settings. Financial development consistently supports ESG readiness, which is amplified by technological innovation. Effects are stronger in less financially developed countries, moderated by energy-intensive consumption in upper-middle-income economies. The findings underscore the critical role of technological infrastructure in maximising the sustainability benefits of financial systems, advocating for technology-supported financial inclusion and green financing. This study enriches the sustainable development literature and informs policies for achieving the UN Sustainable Development Goals. Full article

The United Arab Emirates has become increasingly concerned about carbon dioxide emissions due to their impact on climate change and the environment, as it is one of the top ten world oil producers. This reflects its recognition of the need for sustainable development. Therefore, this research aims to study the dynamic impact of economic growth, urbanization, energy consumption, and economic openness on CO₂ emissions, during the period 1975–2022. To capture these effects, a novel dynamic ARDL is employed to separate the impact of each variable separately. The results indicate that the effect of GDP per capita on carbon emissions is negative, as a 1% increase in economic growth leads to a decrease in carbon dioxide emissions by 0.6%. Moreover, the findings confirm that the UAE economy does not apply to the Kuznets curve in developing countries. Furthermore, the impact of energy consumption, urbanization, and trade openness is positive on CO₂ emissions, as a 1% increase in each raises CO₂ by 0.17%, 11.6%, and 1.2%, respectively. These findings are important for decision makers in the environmental field to make decisions to reduce carbon emissions by altering the impact of economic variables and spread awareness towards reducing carbon emissions. Full article

In this study, the relationship between economic growth and carbon emissions for the period 1968–2022 in Turkey was evaluated within the framework of the EKC (Environmental Kuznets Curve) hypothesis. In addition, the impacts of renewable energy consumption and agricultural value added on carbon emissions were analyzed using the ARDL bounds testing approach. The validity of the results was also tested using the FMOLS and DOLS methods. The findings confirmed the existence of a cointegration relationship between carbon emissions and per capita income, renewable energy consumption, and agricultural value added. Long-term analyses indicate that renewable energy consumption reduces carbon emissions, whereas growth in agricultural value added leads to an increase in emissions. In addition, it has been determined that the EKC hypothesis is valid in both the long and short terms and that increases in per capita income raise emissions up to a certain threshold and have a mitigating effect when this threshold is exceeded. The results of the short-term analysis showed that the effects of renewable energy consumption vary across periods, and that agricultural value added increases emissions in the short term. This study provides empirical evidence for Turkey by incorporating sectoral variables within the EKC framework and offers meaningful insights for policymakers regarding the environmental impacts of agricultural value added and renewable energy use in the context of a developing country. Accordingly, fiscal policy instruments such as green taxation, carbon credit trading mechanisms, and financial and agricultural subsidies should be more effectively utilized in Turkey to support structural transformation in agriculture and promote the use of clean energy, in line with the findings that suggest the need for targeted agricultural and energy policies aligned with Turkey’s SDG commitments. Full article

This study examines the symmetric and asymmetric impacts of international trade on consumption-based carbon emissions (CBEs) in the People’s Republic of China (PRC) and the United States of America (USA) from 1990 to 2018. The analysis uses autoregressive distributed lag (ARDL) and non-linear ARDL (NARDL) methodologies to capture short- and long-run trade emissions dynamics, with economic growth, oil prices, financial development and industry value addition as control variables. The findings reveal that exports reduce CBEs, while imports increase them, across both economies in the long and short run. The asymmetric analysis highlights that a fall in exports increases CBEs in the USA but reduces them in the PRC due to differences in supply chain flexibility. The PRC demonstrates larger coefficients for trade variables, reflecting its reliance on energy-intensive imports and rapid trade growth. The error correction term shows that the PRC takes 2.64 times longer than the USA to return to equilibrium after short-run shocks, reflecting systemic rigidity. These findings challenge the Environmental Kuznets Curve (EKC) hypothesis, showing that economic growth intensifies CBEs. Robustness checks confirm the results, highlighting the need for tailored policies, including carbon border adjustments, renewable energy integration and CBE-based accounting frameworks. Full article

The readiness of businesses to address global climate change is pivotal for achieving sustainable development. However, the dynamics of business development remain underexplored, thereby limiting the depth and scope of research in this area. To this aim, the study examines the relationship between CO₂ emissions and new business density (NBD) in the top 14 countries with the highest NBD (Hong Kong, Cyprus, New Zealand, Estonia, Malta, United Kingdom, Australia, Botswana, Iceland, Latvia, Mauritius, Norway, Sweden, and Georgia) from 2006 to 2020, within the framework of Schumpeter’s theory and the environmental Kuznets curve (EKC) hypothesis, incorporating control variables such as renewable energy consumption (REC) and population size. To estimate the relationships between variables, we employ the novel Method of Moments Quantile Regression (MMQR) approach. The findings suggest that higher NBD is associated with increased CO₂ emissions. The results support the EKC hypothesis, positing an inverted U-shaped relationship between economic growth and environmental degradation, and highlight the mitigating effects of REC and population growth on CO₂ emissions. These findings emphasize the need for countries to align labor legislation with sustainable development objectives and to promote strategies grounded in environmental principles, green economic practices, and eco-friendly technologies. Full article

Income inequality has emerged as a defining challenge of our time, particularly in advanced economies, where the gap between rich and poor has reached unprecedented levels. This study analyzes income inequality trends from 2000 to 2023 across developed countries (the United States, the United Kingdom, Germany, and France) and developing nations using World Bank Gini coefficient data. We employ comprehensive visualization techniques, Pareto distribution analysis, and ARIMA time-series forecasting models to evaluate the effectiveness of the Kuznets curve as a predictor of income inequality. Our analysis reveals significant deviations from the traditional inverse U-shaped Kuznets curve across all examined countries, with persistent volatility rather than the predicted decline in inequality. Forecasts using ARIMA and neural networks indicate continued fluctuations in inequality through 2030, with the U.S. and Germany showing upward trends while France and the UK demonstrate relative stability. These findings challenge the conventional Kuznets hypothesis and demonstrate that contemporary inequality patterns are influenced by factors beyond economic development, including technological change, globalization, and policy choices. This research contributes to the literature by providing empirical evidence that the Kuznets curve has limited predictive power in modern economies, informing policymakers about the need for targeted interventions to address persistent inequality rather than relying on economic growth alone. Full article

This study investigates the environmental effects of agricultural trade, renewable energy use, and economic growth in a panel of 14 selected countries for the period 2000–2021. Per capita CO₂ emissions are modeled as the dependent variable using a second-generation panel data method, the Augmented Mean Group (AMG) estimator, which accounts for cross-sectional dependence and slope heterogeneity. The analysis reveals that the share of renewable energy in total energy consumption significantly reduces carbon emissions, emphasizing the role of green energy policies in environmental improvement. In contrast, economic growth is found to increase emissions, indicating the validity of only the initial phase of the Environmental Kuznets Curve (EKC) hypothesis. Additionally, agricultural imports—and in certain cases, exports—exert upward pressure on emissions, likely due to logistics and production-related externalities embedded in the trade process. Group-specific results highlight distinct dynamics across countries: while renewable energy adoption plays a stronger role in emission mitigation in developing economies, trade composition and production technology drive environmental outcomes in developed ones. The findings underscore the need to redesign trade and energy strategies with explicit consideration of environmental externalities to align with long-term sustainability objectives. Full article

Understanding the historical peak situation and the rules for CO₂ emissions from buildings helps to formulate reasonable building mitigation strategies, accelerating the achievement of the Chinese government’s carbon peak goal. As developed regions, cities in the Guangdong–Hong Kong–Macao Great Bay Area (GBA) provide valuable reference cases. This study quantified the historical building CO₂ emissions of GBA cities and analyzed the contribution of driving factors using the Kaya identity and logarithmic mean Divisia index. Furthermore, we assessed the historical peak situation using the MK trend test method and discussed the reasons behind the inter-city difference in the peak situation shown by the environmental Kuznets curve. The results indicate that the building-related CO₂ emissions of the GBA will slowly increase to 96.90 Mt CO₂ by 2020 and that P&C buildings accounted for a larger proportion of emissions. Emission factors and population made the largest positive and negative contributions, respectively, to this total. At the city level, Guangzhou, Shenzhen, and Hong Kong ranked as the top three sources of building CO₂ emissions. Hong Kong peaked, Dongguan and Macao plateaued, and other cities maintained either slow or quick growth. CO₂ emissions unit area, per capita building CO₂ emissions, and building CO₂ emissions reached a peak in that order. This study provides a valuable reference for formulating a city-level path showing building CO₂ emissions peaks. Full article

This study investigates the impact of income redistribution on carbon emissions across 154 countries from 1995 to 2023, with a particular focus on carbon inequality. Using a dynamic panel approach with two-step System GMM estimations, the analysis considers three dependent variables: average per capita emissions, top 1% per capita emissions, and the ratio of top 1% per capita emissions to national average per capita emissions. Results show that income redistribution (measured in both absolute and relative terms) significantly reduces average per capita emissions in the short term. However, redistribution has no mitigating effect on the carbon emissions of the top 1%; in some models, it is even associated with increases in elite emissions and a widening of carbon inequality. These findings suggest that while redistribution may contribute to national emission reductions, it is insufficient to curb the carbon-intensive lifestyles of the wealthiest. The analysis confirms the Environmental Kuznets Curve (EKC) hypothesis and underscores the need for complementary policy tools to more effectively address the emissions of high-emitting individuals. Overall, this study contributes to the literature by linking income redistribution with emission disparities across income groups and highlights the importance of considering distributional dynamics in climate policy design. Full article