Factors influencing the low-carbon transition: Evidence from the EU economies

Decarbonization, Energy Transition, and Economic Resilience: West African Policy Directions towards Net-Zero and Sustainable Development

Designing effective climate policy: Sectoral approaches to energy-related carbon reduction strategies

Aggregate emission reductions can conceal a redistribution of climate-policy burdens across sectors. This study reanalyses published EU27 Kaya indices and sectoral emission shares for 1990-2022 to ask whether economic-environmental decoupling has been accompanied by a shift toward harder-to-abate activities. The extension introduces five complementary indicators: log-change contribution accounting, mitigation-to-growth leverage, decoupling elasticity, a sectoral reallocation index, and concentration and entropy measures. Per-capita GDP increased by 44.6%, while the combined effects of lower energy and carbon intensity outweighed the scale effect by a factor of 2.50. Per-capita CO₂ emissions consequently fell by 42.5%. At the same time, 20 percentage points of the emissions distribution were reallocated among sectors. Transport, residential, and agriculture/waste increased their combined share from 31% to 51%, while the Herfindahl-Hirschman Index fell from 0.289 to 0.237, indicating a more dispersed and institutionally complex mitigation burden. The findings show that successful aggregate decoupling does not eliminate sectoral lock-in. EU climate policy must preserve power-sector momentum while strengthening coordinated, sector-specific instruments for mobility, buildings, industry, and non-CO₂ agricultural emissions.

Does Globalization Accelerate or Mitigate Greenhouse Gas Emissions? Evidence from Energy Transition and Technological Innovation in Central Asia

Greenhouse gas (GHG) emissions have emerged as a critical challenge to sustainable development in Central Asia, where rapid economic transformation, rising energy demand, and increasing globalization have intensified environmental pressures. This study investigates the determinants of GHG emission growth in Kazakhstan, Kyrgyzstan, Tajikistan, and Uzbekistan over the period 2000–2024 within the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework. Specifically, the analysis examines the effects of economic growth, energy intensity, renewable energy consumption, technological innovation, urbanization, and globalization on annual GHG emission growth. To ensure robust inference in the presence of cross-sectional dependence and heteroskedasticity, the empirical analysis employs Driscoll–Kraay standard errors (DKSE), Panel-Corrected Standard Errors (PCSE), and Feasible Generalized Least Squares (FGLS). Furthermore, the Method of Moments Quantile Regression (MMQR) is applied to examine distributional heterogeneity by assessing whether the effects of the explanatory variables vary across the lower, median, and upper quantiles of the conditional distribution of GHG emission growth. The empirical findings reveal that energy intensity is the dominant driver of GHG emission growth across all estimation techniques, whereas renewable energy adoption and technological innovation significantly mitigate environmental degradation by reducing emissions growth. The MMQR results further demonstrate that the estimated effects of the explanatory variables vary across the conditional distribution of GHG emission growth. In particular, the mitigating effect of globalization becomes more pronounced toward the upper quantiles of the conditional distribution, indicating that its environmental consequences differ across the distribution of GHG emission growth rather than across predefined groups of countries. By contrast, the effects of economic growth and urbanization exhibit greater heterogeneity across the conditional distribution, while the effects of energy intensity, renewable energy, and technological innovation remain broadly consistent in direction. These findings underscore the importance of improving energy efficiency, accelerating the deployment of renewable energy technologies, strengthening innovation capacity, and promoting environmentally sustainable economic integration to achieve long-term climate objectives in Central Asia. By providing comprehensive evidence based on complementary mean-based estimators and distribution-sensitive quantile analysis, this study contributes to the growing literature on the determinants of GHG emissions in emerging economies and offers important policy implications for balancing economic development with climate change mitigation and environmental sustainability.

The role of governments in emission cuts: evidence from emerging and advanced economies 1

Improving people’s livelihood to address climate change: the constraint effects of regional competition and inequality

Achieving the twin goals of carbon peaking and carbon neutrality is a transformative decision made by the Chinese government in response to global climate change. Fiscal policy, as a direct tool for the government to perform its public governance functions, plays a crucial role in promoting carbon emission reduction (CER). Accordingly, this paper theoretically explores how livelihood fiscal expenditure (LFE) affects urban carbon emissions (CE) and proposes research hypotheses. Then, using panel data from 281 cities in China from 2008 to 2020, this study constructs relevant econometric models are constructed for empirical testing. The findings indicate that LFE exerts a significant CER effect. After accounting for endogeneity, policy interventions, and other factors, this result remains robust. Mechanism analysis reveals that the green technology effect of industrial intelligence and the factor spillover effect under market integration are intrinsic drivers of CER. In the heterogeneity analysis, this study divides the sample based on differences in development stage, resource endowment, city size, and mayoral age, yielding several interesting conclusions. Additionally, the results show that regional competition and inequality significantly constrain the CER effect of LFE.

Environmental Kuznets Curve dynamics in oil-rich economies

The Gulf Cooperation Council (GCC) economies, among the world’s largest per-capita carbon emitters, face a pressing policy dilemma of environmental sustainability. The conventional mean-based studies often mask heterogeneous effects across the emissions distribution and yield inconclusive results for resource-rich, energy-intensive settings such as the GCC. This gap limits the design of targeted decarbonization strategies aligned with national visions (e.g., Saudi Vision 2030 and UAE Net Zero 2050). Hence, this study revisits the Environmental Kuznets Curve (EKC) hypothesis for the six GCC countries over 2000–2024 using annual panel data. This study applies quantile regression to capture distribution-specific impacts of economic growth, trade openness, energy use, and urban population on carbon emissions. Results are validated through Dumitrescu-Hurlin causality tests and robustness checks. Findings consistently reject the EKC: economic growth exerts a monotonic positive effect on carbon emissions with no turning point. Energy efficiency and renewable adoption mitigate emissions, while trade openness and technological diffusion also exert reducing effects. In contrast, urbanization significantly amplifies emissions, highlighting demographic pressures. The results underscore that environmental improvements in the GCC require deliberate structural shifts in energy diversification, urban planning, and trade policies rather than growth alone. These context-specific insights advance the environmental economics literature and offer actionable guidance for sustainable development in resource-dependent economies.