This work aims to examines the effect of Chinese outward foreign direct investment (CoFDI), renewable energy, and energy intensity on CO₂ emissions in 46 Belt and Road Initiative (BRI) nations divided into: Panel A, consisting of 16 European countries, and Panel B, comprising 30 Asian and MENA countries. This analysis used data from 2005 to 2018, applying second-generation econometric techniques. The empirical outcomes, obtained using Driscoll–Kraay methods, confirmed the pollution halo effect in Panel A, suggesting that FDI flows in these countries are environmentally friendly. In contrast, the results indicated a positive impact of CoFDI on CO₂e in Panel B, supporting the pollution haven hypothesis that FDI may add to pollution. In addition, the study found an inverted-U-shaped association between per capita income and CO₂e, validating the environmental Kuznets curve (EKC) hypothesis in both panels. The findings also revealed that energy intensity positively affects CO₂e, whereas renewable energy has a significant negative effect in both panels, while the interaction terms of renewable and energy intensity are heterogenous in both panels. Based on these findings, the study recommends policy makers of these countries to attract clean FDI, particularly in renewable sectors, and shift from fossil fuel-based energy to renewable sources to control pollution by enacting energy-saving initiatives via lowering energy intensity.

Green initiatives and digital transitions in Central European countries are catalyzing significant transformations within the region’s socio-economic landscape, embedding contemporary technologies into daily life and commercial activities. Consequently, this fosters improved environmental quality through sustainable practices. This research unravels the complex interplay between renewable energy consumption, digitalization, and financial development in various national contexts, providing key insights into their respective and collective impacts on environmental quality. This study investigates the relationship among environmental quality, digitalization, renewable energy consumption, financial development, and economic growth in Central European countries, analyzing data from 1995 to 2019. An analysis of the panel data reveals a statistically significant positive relationship between economic growth and carbon emissions, and a negative relationship among digitalization, renewable energy consumption, and carbon emissions. In Central European nations, including the Czech Republic, Hungary, Latvia, and Slovakia, digitalization serves a mediating role in the relationship between renewable energy consumption and environmental quality. However, the role of financial development as a mediator between renewable energy consumption and environmental quality manifests varied impacts across different countries. These findings hold the potential to guide policy recommendations for the countries under consideration.

The rapid economic growth observed in Central European countries in the last thirty years has been the result of profound political changes and economic liberalization. This growth is partly connected with reducing carbon dioxide (CO₂) emissions. However, the problem of CO₂ emissions seems to remain unresolved. The aim of this paper is to test whether the Environmental Kuznets Curve (EKC) hypothesis holds true for Central European countries in an annual sample data that covers 1995–2016 in most countries. We examine cointegration by applying the Autoregressive Distributed Lag bound testing. This is the first study examining the relationship between CO₂ emissions and economic growth in individual Central European countries from a long-run perspective, which allows the results to be compared. We confirmed the cointegration, but our estimates confirmed the EKC hypothesis only in Poland. It should also be noted that in all nine countries, energy consumption leads to increased CO₂ emissions. The long-run elasticity ranges between 1.5 in Bulgaria and 2.0 in Croatia. We observed exceptionally low long-run elasticity in Estonia (0.49). Our findings suggest that to solve the environmental degradation problem in Central Europe, it is necessary to individualize the policies implemented in the European Union.

Renewable energy sources are becoming increasingly popular due to their advantages over fossil fuels, their economic benefits, and growing environmental concerns. Researchers are particularly focused on understanding the factors that affect the efficiency of various energy sources. This paper explores the relationship between renewable energy consumption and trade openness from 1990 to 2018 among the top 15 countries that consume the most renewable energy. The study also considers economic growth, natural resources, capital, and financial globalization as additional factors influencing renewable energy use. To analyze the data, the paper utilizes advanced panel data techniques, including the dynamic Seemingly Unrelated Regression (DSUR) and Dimutrescu–Hurlin panel bootstrap causality methods. The findings reveal cross-sectional dependence and slope heterogeneity in the model. The results show that trade openness, economic growth, and capital investment promote renewable energy consumption, while financial globalization tends to reduce it. Additionally, the study finds one-way causality from trade openness, economic growth, natural resources, capital, and financial globalization to renewable energy consumption. These insights can inform the development of renewable energy policies in the countries examined.

We examine the effectiveness of green innovation on CO₂ emissions in the top twelve polluting nations—China, the US, India, Russia, Japan, South Korea, Canada, Mexico, Turkey, Italy, Poland, and the UK—from 1996 to 2020. Using panel data fixed and random effect model and decision tree analysis, we found that industrialization, urbanization, and economic growth increase CO₂ emissions, whereas green energy consumption and governance decrease CO₂ emissions. In the panel data tree-based model, governance is in the second and third positions in the decision tree fixed, and random effect model. Green innovation is not statistically significant despite the expected negative sign. The findings suggest that policymakers should encourage investment in green energy production and governance to combat environmental degradation. Investment in green energy should be escalated to ensure energy efficiency in the long term.

This research aimed to investigate the relationship between climate policy uncertainty (CPU), clean energy (ENERGY), carbon emission allowance prices (CARBON), and Bitcoin returns (BTC) for the period from August 2012 to August 2022. The empirical analysis strategies utilized in this study included the Fourier Bootstrap ARDL long-term coefficient estimator, the Fourier Granger Causality, and the Fourier Toda–Yamamoto Causality methods. Following the confirmation of cointegration among the variables, we observed a positive relationship between BTC and CARBON, a positive relationship between BTC and CPU, and a negative relationship between BTC and ENERGY. In terms of causal associations, we identified one-way causality running from CARBON to BTC, BTC to CPU, and BTC to the ENERGY variable. The study underscores the potential benefits and revenue opportunities for investors seeking diversified investment strategies in light of climate change concerns. Furthermore, it suggests actionable strategies for policymakers, such as implementing carbon taxes and educational campaigns, to foster a transition towards clean energy sources within the cryptocurrency mining sector and thereby mitigate environmental impacts.