The causal relationship between green finance and geopolitical risk: Implications for environmental management

ESG practices mitigating geopolitical risks: Implications for sustainable environmental management

As climate change and geopolitical conflicts intensify, understanding how geopolitical risks affect companies prioritizing Environmental, Social, and Governance (ESG) practices is crucial. This study investigates the dynamic relationship between global geopolitical risks and the performance of Environmental, Social, and Governance (ESG) and non-ESG companies, particularly their influence on green markets. Utilizing a robust methodological framework, including the dynamic time-varying parameters vector autoregression (TVP-VAR) model, and causal impact modeling, we analyze daily financial data from 2021 to 2024. The results reveal a substantial negative impact of geopolitical risks on non-ESG companies, contrasting with the resilience of ESG-committed counterparts. This suggests that ESG-committed companies demonstrate better resilience against geopolitical risks, emphasizing the protective role of ESG practices amid uncertainties. Additionally, the inclusion of ESG companies in green markets diminishes the severity of the negative impact of geopolitical risks, underlining the transformative role of ESG commitment in shaping investor behavior towards sustainable investments. Our findings offer insights for policymakers and investors navigating geopolitical risks and ESG performance, with a focus on environmental management, and provide guidance for effective risk mitigation and investment policies to enhance environmental sustainability.

Global chessboard: Analyzing how geopolitical risk shapes renewable energy technology investments

The allocation of budgets for renewable energy (RE) technology is significantly influenced by geopolitical risks (GPRs), reflecting the intricate interplay among global political dynamics, social media narratives, and the strategic investment decisions essential for advancing sustainable energy solutions. Against the backdrop of increasing worldwide initiatives to transition to RE sources, it is crucial to understand how GPR affects funding allocations, informing policy decisions, and fostering international collaboration to pursue sustainable energy solutions. Existing work probes the nonlinear effect of GPR on RE technology budgets (RTB) within the top 10 economies characterized by substantial research and development investments in RE (China, USA, Germany, Japan, France, South Korea, India, the United Kingdom, Australia, and Italy). Past research largely focused on panel data techniques to delve the interconnection between GPR and RE technology, overlooking the distinctive characteristics of individual economies. Contrarily, existing investigation implements the "Quantile-on-Quantile" tool to explore this association on an economy-particular basis, enhancing the precision of our analysis and offering both a comprehensive global perspective and nuanced perceptions for entire countries. The findings manifest a significant reduction in funding for RE technology associated with GPR across various quantile levels in the chosen economies. The disparities in results spotlight the necessity for policymakers to perform thorough assessments and carry out competent strategies to address the variations in GPR and RTB.

Shaping a greener future: The role of geopolitical risk, renewable energy and financial development on environmental sustainability using the LCC hypothesis

The recent progress report of Sustainable Development Goals (SDG) 2023 highlighted the extreme reactions of environmental degradation. This report also shows that the current efforts for achieving environmental sustainability (SDG 13) are inadequate and a comprehensive policy agenda is needed. However, the present literature has highlighted several determinants of environmental degradation but the influence of geopolitical risk on environmental quality (EQ) is relatively ignored. To fill this research gap and propose a inclusive policy structure for achieving the sustainable development goals. This study is the earliest attempt that delve into the effects o of geopolitical risk (GPR), financial development (FD), and renewable energy consumption (REC) on load capacity factor (LCF) under the framework of load capacity curve (LCC) hypothesis for selected Asian countries during 1990-2020. In this regard, we use several preliminary sensitivity tests to check the features and reliability of the dataset. Similarly, we use panel quantile regression for investigating long-run relationships. The factual results affirm the existence of the LCC hypothesis in selected Asian countries. Our findings also show that geopolitical risk reduces environmental quality whereas financial development and REC increase environmental quality. Drawing from the empirical findings, this study suggests a holistic policy approach for achieving the targets of SDG 13 (climate change).

Geopolitical risk, financial development, and renewable energy consumption: empirical evidence from selected industrial economies

The rapid rise in climate and ecological challenges have allowed policymakers to introduce stringent environmental policies. In addition, financial limitations may pose challenges for countries looking to green energy investments as energy transition is associated with geopolitical risks that could create uncertainty and dissuade green energy investments. The current study uses PTR and PSTR as econometric strategy to investigate how geopolitical risks and financial development indicators influence energy transition in selected industrial economies. Our findings indicate a non-linear DCPB-RE relationship with a threshold equal to 39.361 in PTR model and 35.605 and 122.35 in PSTR model. Additionally, when the threshold was estimated above, financial development indicators and geopolitical risk positively impacts renewable energy. This confirms that these economies operate within a geopolitical context, with the objective of investing more in clean energy. We report novel policy suggestion to encourage policymakers promoting energy transition and advance the sustainable financing development and ecological sustainability.

Financial development, resource richness, eco-innovation, and sustainable development: Does geopolitical risk matter?

Financial development and geopolitical risks can significantly affect sustainable development. However, the roles of these factors in sustainable development are rarely investigated. Thus, this study takes into account the role of geopolitical risk while exploring the effects of financial development, natural resource rents, and eco-innovation on sustainable development in the Organization for Economic Co-operation and Development (OECD) countries. To this end, yearly data from 1990 to 2019 is analyzed using advanced econometric tests. The Common Correlated Effects Mean Group (CCEMG) results indicate that financial development and eco-innovation are significantly and positively related to sustainable development. Natural resource rents have a detrimental impact on sustainable development which confirms the presence of the resource curse hypothesis in OECD countries. Furthermore, the results revealed that controlling geopolitical risk is useful in fostering sustainable development. Lastly, the panel Granger causality test unveiled one-way causality from financial development, eco-innovation, natural resource rents, and geopolitical risk to sustainable development. Moreover, causalities are found from geopolitical risk to financial development, eco-innovation and natural resources. These findings suggest that OECD countries should prioritize financial development and eco-innovation policies for sustainable development while mitigating the negative effects of natural resource rents. The geopolitical risk can harm sustainable development, so policymakers should promote international cooperation and risk-sharing.

Geopolitical risk and ecological efficiency: A combination approach based on super-efficiency-DEA and extended-STIRPAT models

Increased geopolitical risks are impacting the sustainable development of the ecological environment. To better understand the impact of geopolitical risk on ecological sustainability, this study develops a research framework for the impact of geopolitical risk on ecological efficiency. (i) Measuring ecological efficiency by data envelopment analysis. (ii) Examining the relationship between geopolitical risks and ecological efficiency using the extended STIRPAT. (iii) Heterogeneity analysis and mediation test were used to further explore the impact mechanism of geopolitical risks. The research results show that: (i) There are obvious differences in the ecological efficiency of countries with different income levels. The ecological efficiency of countries with higher income levels is generally higher, while the ecological efficiency of countries with lower income levels is lower. (ii) Geopolitical risks reduce ecological efficiency, which is bad for ecosystem sustainability. (iii) The magnitude of the adverse impact of geopolitical risks on ecological efficiency is different among different income groups. The negative impact of geopolitical risk on eco-efficiency is worse in high-income countries than in low-income countries.

Quantile connectedness between the climate policy and economic uncertainty: Evidence from the G7 countries

In this study, we investigate the transmission mechanism between climate policy uncertainty (CPU) and economic policy uncertainty (EPU) in the G7 countries. To account for different conditions, we use a quantile-based VAR (Q-VAR) model over the period between 2000 and 2021. Our results show high connectedness between the CPU and the EPU of G7 countries, particularly at extreme quantile orders. On the other hand, the spillover effects between climate and economic policy uncertainty differ depending on the distributional levels of the uncertainty indices. The CPU is a net receiver of uncertainty shocks, while for almost all countries, the EPU acts as a net receiver or emitter, depending on the economic situation. During times of high or low economic uncertainty, the EPU of all G7 countries is strongly affected by shocks originating from the CPU. Moreover, the results indicate that the dynamic spillover patterns between EPU and CPU vary over time, responding to different economic events and financial crises. These results call for policymakers and governments to urgently integrate climate considerations into economic planning, fiscal policies, and regulatory frameworks to promote sustainable economic growth and mitigate the impacts of climate change.

Comparing the EU and Chinese carbon trading market operations and their spillover effects

A carbon trading market (CTM) policy for trading carbon dioxide emission rights as a commodity was created to reduce greenhouse gas emissions. CTMs operate differently in different countries and regions, and their interactions deserve an in-depth study. This study focused on the world's largest CTM, the European Union (EU), and the CTM of China, largest carbon-emitting country. First, we evaluate the liquidity and volatility of the two CTMs. Subsequently, the VAR model is used to explore the mean spillover effect between the two markets and the BEKK-GARCH model is used to explore the volatility spillover effect between the two markets. The study concludes that: (1) The liquidity of China's CTM is better than that of the EU's CTM. (2) Both the EU and Chinese CTMs are unstable, but the volatility of the Chinese CTM is lower than that of the EU CTM. (3) Price changes in the EU and Hubei CTMs have a mutual influence. (4) There are interactions between the market fluctuations of the EU CTM and the Shanghai CTM and those of the EU CTM and the Hubei CTM. The results of this study have implications for the construction and development of CTMs in the EU and China.

The responsiveness of renewable energy production to geopolitical risks, oil market instability and economic policy uncertainty: Evidence from United States

This paper aims to investigate the responsiveness of renewable energy production (REP) to fluctuations in geopolitical risks, oil prices and economic policy uncertainty (EPU). It applies a cross-quantilogram framework to examine monthly data of the US economy for the period of 1986-2022. The findings illustrate the asymmetric effect of historical geopolitical risk (GPRH) on REP under long memory. The findings also hold after different subcategories of GPRH, including geopolitical threats and geopolitical acts, are considered. A positive shock in GPRH has the most decisive positive impact on REP when the policies are driven by both energy security and environmental commitments. A positive shock in GPRH can negatively impact REP when policies are driven by energy security causes only. EPU exerts strong negative effects on REP in bearish and bullish states of the market under medium and long memory across different measures of EPU. Dynamic connectedness analysis applying TVP-VAR method between pairwise variables indicates that net REP is a volatility receiver to the changes in GPRH, its subcomponents, oil prices and different measures of EPU.

The impact of energy imports on green innovation in the context of the Russia-Ukraine war

This research paper examines the implications of energy imports on green innovation within the context of the Russia-Ukraine war. It utilizes panel data spanning EU countries from 1999 to 2022. Initially, the study explores the influence of natural gas and oil imports on the advancement of green innovation. Specifically, it reveals that the importation of natural gas facilitates progress in this area, whereas the importation of oil can impede such advancement. Following the Russia-Ukraine war, the role of gas imports in fostering green innovation within EU countries has grown, simultaneously exacerbating the adverse effects of oil imports on green innovation. Secondly, by employing a panel threshold model, the study identifies that higher energy prices make natural gas and oil imports unfavorable for the progress of green innovation in EU nations. Thirdly, an analysis of heterogeneity demonstrates that, as a result of the Russia-Ukraine war, natural gas imports have a more significant detrimental effect on the development of green innovation in EU nations with a natural gas dependency ranging from 10% to 90%. In the case of oil imports, EU nations with a dependence on Russian oil exceeding 50% experience a more pronounced negative impact on the development of green innovation. Fourthly, a mechanistic study elucidates that natural gas imports indirectly stimulate green innovation through the mechanism of energy transition, while oil imports hinder the development of green innovation by exacerbating carbon emissions. The empirical findings of this paper carry substantial policy implications for EU nations, urging the acceleration of energy transition in response to the impact of the Russia-Ukraine war on green innovation. Moreover, these findings have broader implications for global environmental management and the collective endeavor to combat climate change.

Challenges to environmental governance arising from the Russo-Ukrainian conflict: Evidence from carbon emissions

The destruction of ecosystems, increase in carbon emissions, and volatility of energy prices following the outbreak of the Russo-Ukrainian conflict constitute a complex situation that environmental managers must cope with. In response, this study aims to explore the impact of the Russo-Ukrainian conflict on carbon emissions in the European Union (EU) and associated heterogeneity factors. This study utilized stacked data from 2021 to 2022 on daily carbon emissions and used the differences-in-differences (DID) model as its methodological framework. This study also provides additional analyses for the United States (US), the United Kingdom (UK), and Russia. The full-blown Russo-Ukrainian conflict led to a significant increase in carbon emissions in the EU, averaging 0.092 MtCO2. Further investigations showed that the conflict led to a significant increase in energy prices and that changes in the prices of different energy sources had a heterogeneous effect on carbon emissions. Specifically, an increase in natural gas prices drove a rise in carbon emissions, whereas an increase in oil prices led to a decrease in carbon emissions in the EU. Third, the conflict also affected countries outside the EU, including the US and the UK, which experienced significant increases in carbon emissions in contrast to Russia, which underwent a decline. Finally, the study identified four sectors - international aviation, industry, power, and residential - as the primary contributors to elevated carbon emissions in the EU. This study provides a novel perspective for exploring the interplay between conflicts and carbon emissions and offers valuable insights into shaping effective environmental management policies and measures.

Exploring role of green financing in blockchain markets for climate change mitigation in China

This study explores the potential of green finance as a strategic method to addressing climate change mitigation in China's blockchain industry. This research methodically analyzes a large dataset collected from many sources across the period between 1999 and 2020. Using a mixed approach of quantitative research and qualitative case studies, this study delves into the tangled web of relationships between alternative finance sources for green initiatives and the use of blockchain technology to promote more environmentally friendly business practices. The results provide light on how green finance and blockchain technologies might work together to boost China's climate change mitigation efforts, revealing fresh insights into the possible synergies and obstacles that erupt from this intersection. In response to the worsening climate problem, there is a pressing need for unconventional methods of financing that can lead holistic sustainable growth. Concurrently, blockchain technology's disruptive potential reverberates across numerous sectors. However, research on blockchain's potential for combating climate change, especially in conjunction with green funding systems, is still in its infancy. Intrinsic interest has motivated this study, which provides a new viewpoint on paths that might transform climate change mitigation in China by mapping the unexplored territory at the intersection of the green finance and blockchain sectors. This research hopes that by examining this interface, it will shed light on the hidden opportunities presented by the combination of green financing and blockchain innovation, allowing for more well-informed and effective decisions to be made in support of environmentally sustainable futures.

Does geopolitical risk hinder sustainable development goals? Evidence from a panel analysis

This paper is likely the first attempt to empirically investigate the direct effect of geopolitical risk on sustainable development goals (SDGs). We employ a newly developed SDG index along with its 17 sub-indices from the United Nations to capture various aspects of sustainable development. On a panel sample covering 41 countries from 2015 to 2021, we find that elevated geopolitical tensions can hinder the progress towards achieving sustainable development goals. This result is robust to various model specifications and estimation approaches. Further analyses show that the two dimensions affected are Decent Work and Economic Growth (SDG8) and Climate Action (SDG13). Heterogeneity test finds that the negative effect of geopolitical risks is only present in countries highly dependent on natural resources. More importantly, improvements in institutional quality could partially offset the detrimental effect of geopolitical risks on sustainable development goals. Therefore, this study provides important implications for policymakers in devising measures to maintain the progress to achieve SDGs in the era of rising global uncertainties.

Can minimizing risk exposures help in inhibiting carbon footprints? The environmental repercussions of international trade and clean energy

Since bettering environmental conditions has acquired significant interest globally, discovering factors that may facilitate the establishment of environmental sustainability is currently of foremost importance. Hence, this study considers a sample of 33 members of the Organization for Economic Cooperation and Development and checks whether reducing exposure to different forms of country risks, in the presence of international trade and clean energy consumption, can reduce their respective carbon footprint levels. Utilizing annual data from 2000 to 2018 and employing methods that handle problems related to dependence across cross-sectional units and heterogeneity of slope coefficients, the findings endorse that (a) reducing financial and political risks abate carbon footprints, (b) economic risk exposure does not influence carbon footprints, (c) international trade exerts carbon footprint-boosting effects, and (d) undergoing unclean to clean energy transition curbs carbon footprints. Accordingly, the concerned governments should these findings into account while conceptualizing green environmental policies in the future.

Does geopolitical risk matter in carbon and crude oil markets from a multi-timescale perspective?

The ongoing Russia-Ukraine conflict serves as a prime illustration of geopolitical risk, manifesting implications beyond global energy price surges and regional energy deficits; it also resonates within the carbon trading market. This study delves into the non-linear and asymmetric impacts of geopolitical risk on oil-carbon linkages spanning 2013 to 2022. Commencing with an exploration of dynamic correlations within the carbon and crude oil markets, our findings indicate that market movements in carbon or crude oil are subject not only to their respective historical volatility trends but also to reciprocal influences from the alternate market, highlighting the existence of asymmetric spillovers between the carbon and crude oil markets. Subsequently, a threshold vector error correction model (TVECM) sheds light on the long-term transmission dynamics of geopolitical risk to oil-carbon linkages. It is concluded that the oil-carbon linkages have a limited impact on geopolitical risk and are subject to shocks from geopolitical risk. Finally, the maximum overlap discrete wavelet transform (MODWT) method unveils heterogeneity across temporal scales: in the short term, geopolitical risk fluctuations are influenced by oil-carbon linkages, and in the middle and long run it becomes independent. Such insights furnish investors with an enriched comprehension of the interplay between crude oil and carbon markets amid geopolitical disturbances, while also offering policymakers a foundation upon which to sculpt informed responses to geopolitical risk.

Is geopolitics a new risk to environmental policy in the European union?

Geopolitical risks and environmental policy have become increasingly important in the European Union (EU), which is committed to tackling climate change and protecting the environment. However, geopolitical risks can undermine its environmental policy objectives. Thus, the study evaluates the relationship between geopolitical risks and environmental policy in nineteen EU countries from 1994 to 2020 through panel bootstrap Granger causality. The results show that geopolitical risks significantly influence environmental policy in Denmark, Estonia, Finland, France, Germany, Luxembourg, and Romania. On the other hand, the findings reveal that environmental policy causes geopolitical risks only in Latvia, while there is no relationship in the remaining countries. Therefore, policymakers must develop resilience to geopolitical risks, promote renewable energy, strengthen environmental regulations, and address social and economic implications to reduce environmental policy vulnerability to geopolitical risks.

Does target country's climate risk matter in cross-border M&A? The evidence in the presence of geopolitical risk

The impact of climate risk on the payment method in cross-border M&A remains largely unknown in the literature. Using a large sample of UK outbound cross-border M&A deals in 73 target countries from 2008 to 2020, we find that a UK acquirer is more likely to employ an all-cash offer to signal its confidence in a target's value if the target country faces a higher level of climate risk. This finding is consistent with the confidence signalling theory. Our results also suggest that acquirers are less likely to target vulnerable industries if target countries' climate risk is high. In addition, we document that the presence of geopolitical risk would weaken the association between payment method and climate risk. Our findings are robust to the use of an instrumental variable approach and alternative measures of climate risk.

Natural gas spot price prediction research under the background of Russia-Ukraine conflict - based on FS-GA-SVR hybrid model

The ongoing Russia-Ukraine conflict has led to significant upheaval in the worldwide natural gas sector. Accurate natural gas price forecasting, as an essential tool for mitigating market uncertainty, plays a crucial role in commodity trading and regulatory decision-making. This study aims to develop a hybrid forecasting model, the FS-GA-SVR model, which integrates feature selection (FS), genetic algorithm (GA), and support vector regression (SVR) to investigate Henry Hub natural gas price prediction amidst the Russia-Ukraine conflict. The results show that: (1) The feature selection automates model input variable selection, decreasing the time required while improving the model's accuracy. (2) The use of genetic algorithm for selecting support vector regression hyperparameters significantly improves the accuracy of natural gas price predictions. The algorithm leads to a decrease of approximately 70% in measurement indicators. (3) During the Russia-Ukraine conflict, the FS-GA-SVR hybrid model demonstrates more consistent and accurate predictions for natural gas spot prices than the base SVR model. This study serves as a valuable theoretical reference for energy policymakers and natural gas market investors worldwide, supporting their ability to anticipate fluctuations in natural gas prices.

Facilitate or Inhibit: Corporate Environmental Performance and Financing Costs

The proposed carbon peak and carbon neutralization goals have ushered China into an era of emissions reduction and a climate-oriented economy. With the proposed double carbon goal, China has formulated many environmental protection and green credit policies. This paper aims to assess the impact of corporate environmental performance (CEP) on financing costs, using a panel dataset of companies in China's heavily polluting industries from 2010 to 2019. We employed fixed-effect models, moderating-effect models, and panel quantile regression (PQR) to analyze the impact, underlying mechanisms, and asymmetric features of CEP on financing costs. Our results indicate that CEP has an inhibitory effect on financing costs, with political connections strengthening this effect and GEA weakening it. Moreover, the impact exhibits asymmetry at different levels of financing costs, wherein lower financing costs see a greater weakening effect from CEP. Improved CEP helps to optimize the financing performance of companies and reduce financing costs. Therefore, policy makers and regulatory authorities should work to unblock financing channels for companies, encourage environmental investment, and remain flexible in implementing environmental policies.

Risk-return profile of environmentally friendly assets: Evidence from the NASDAQ OMX green economy index family

The COVID-19 pandemic, geopolitical risks and net-zero targets have created not only pressures but incentives for energy investors. The renewable energy has become the largest energy sector and provided significant investment opportunities. However, companies operating in this sector are highly risky due to economic and political barriers. Therefore, it is of crucial importance for investors to properly assess the risk-return dynamics of these investments. This paper examines the risk-return characteristics of clean energy equities at a disaggregate level using a battery of performance metrics. The main results provide evidence of significant heterogeneity across clean energy sub-sectors; for instance, fuel cell and solar stocks display higher downside risks than the others, while the developer/operator equities are the least risky. The findings further provide evidence of higher risk-adjusted returns during the coronavirus pandemic; as an example, energy management companies appear to provide the highest risk-adjusted returns in the wake of the COVID-19. Comparing the performance with traditional sectors, clean energy stocks outperform certain sectors, including dirty assets. These findings offer important implications for investors, portfolio managers, and policy makers.

Risk measurement and application of the international carbon market in the era of global conflict: A data-driven study using FCM

The accurate measurement and effective estimation of carbon market risk are crucial for practitioners and policymakers to mobilize resources toward the transition to a climate-resilient economy, particularly in a new era of global conflict. However, existing studies that have explored factors contributing to carbon market risk primarily relied on experience or subjective judgment in selecting risk-related factors. Such approaches undermine the estimation accuracy while making it difficult to ascertain causal inferences related to the risk spillover. To fill the gap, we adopted a data-driven factor analysis strategy by introducing the Fuzzy Cognitive Maps (FCM) model to establish a carbon market network and identify risk-related factors. We then evaluate the carbon market's risk level and spillover effects using combined econometric methods and explore their application in portfolio management. We report three main findings. First, based on our sample of 3217 observations between 2008 and 2022, five factors influencing carbon market risk emerged from the FCM, including OIL, COAL, SP500ENERGY, SPCLEANENERGY, and GPR. Second, we find a notable rise in risk spillover from GPR to EUA during the Russia-Ukraine conflict and an escalation of total cross-market spillover during extreme events. Third, our study presents new evidence on the hedging effect for EUA of the SP500ENERGY before the Russia-Ukraine conflict and of the SPCLEANENERGY during the conflict. Finally, implications are discussed for policymakers and investors.

An application of QVAR dynamic connectedness between geopolitical risk and renewable energy volatility during the COVID-19 pandemic and Russia-Ukraine conflicts

The article is the first to employ a quantile vector autoregression (QVAR) to identify the connectedness between geopolitical risks and energy volatility from January 1, 2015, to April 03, 2023. This paper is also the first to examine the mediating roles of uncertain events like the COVID-19 pandemic and the Russia-Ukraine conflict on this interlinkage. Dynamic connectedness is 29% in the short term and approximately 6% in the long term. Dynamic net total directional connectedness over a quantile also indicates that connectedness is very intense for both highly positive changes (above the 80% quantile) and negative changes (below the 20% quantile). In the short term, the geopolitical risks remained net receivers of shock, but they turned into net shock transmitters during 2020 in the long term. Clean energy, in the short term, transmits shocks to other markets, and it plays the same role in the long term. Crude oil was a net receiver of shocks during COVID-19 and turned into a net transmitter of shocks in early 2022. Dynamic net pairwise directional connectedness over a quantile suggests that uncertain events like the COVID-19 epidemic or the Russia-Ukraine conflict influence the dynamic interlinkages between geopolitical risks and renewable energy volatility and change their roles in the designed system. These findings are critical since they help authorities develop effective policies to lessen the vulnerabilities of these indicators and minimize how widely the renewable and non-renewable energy market is exposed to risk or uncertainty.

Pollution, political instabilities and electricity price in the cee countries during the war time

Pollution, war and energy crisis are the CEE countries' most important global actual issues. Therefore, this study aims to investigate the impact of political stability and electricity price in 11 CEE countries in the period 2007-2021 to anticipate the effect of these factors on pollution in times of political and energy crisis. The common results based on DOLS/FMOLS and CCEMG estimations indicate that political stability enhances CO2 emissions, while higher electricity prices for non-household consumers reduce pollution. An inverted-U pattern was observed in the relationship between growth and pollution, while renewable energy consumption is the most powerful tool to reduce CO2 emissions. These results are the starting point for policy recommendations.

The influence of shadow economy, environmental policies and geopolitical risk on renewable energy: A comparison of high- and middle-income countries

Given the alarming rate of climate change and environmental degradation, major countries are seeking ways to curtail environmental damage and attain sustainability in the future. In the quest for a green economy, countries are motivated to adopt renewable energy that can assist in resource conservation and efficiency. Accordingly, this study examines the diverse effects of the underground economy, environmental policy strictness, geopolitical risk, gross domestic product, carbon emissions, population, and oil prices on renewable energy for 30 high- and middle-income countries from 1990 to 2018. The empirical outcomes based on quantile regression document significant variations across two country groups. For instance, for high-income countries, the shadow economy has a detrimental effect across all quantiles but it is statistically significant at the top quantiles. Nonetheless, the effect of the shadow economy on renewable energy is detrimental and significant statistically across all quantiles for middle-income countries. In the context of environmental policy stringency, the effect is positive across both country groups, though there is heterogeneity in outcomes. Geopolitical risk has a positive influence on the deployment of renewable energy for high-income countries but negatively impacts renewables for middle-income countries. As far as policy suggestions are concerned, the policymakers of both high- and middle-income countries need to take steps to constrain the growth of the shadow economy by adopting effective policy strategies. Policies need to be implemented for middle income-countries to reduce the unfavorable effect of geopolitical uncertainty. The findings of this study contribute to a better and more precise understanding of factors shaping the role of renewables whereby the energy crisis would be mitigated.

Probabilistic carbon price prediction with quantile temporal convolutional network considering uncertain factors

Accurate carbon price projections can serve as valuable investment guides and risk warnings for carbon trading participants. However, the escalation of uncertain factors has brought numerous new hurdles to existing carbon price forecast methods. In this paper, we develop a novel probabilistic forecast model called quantile temporal convolutional network (QTCN) that can precisely describe the uncertain fluctuation of carbon prices. We also investigate the impact of external factors on carbon market prices, including energy prices, economic status, international carbon markets, environmental conditions, public concerns, and especially uncertain factors. Taking China's Hubei carbon emissions exchange as a study case, we verify that our QTCN outperforms other classical benchmark models in terms of prediction errors and actual trading returns. Our findings suggest that coal prices and EU carbon prices have the most significant effect on Hubei carbon price forecasting, while air quality index appears to be the least important. Besides, we demonstrate the great contribution of geopolitical risk and economic policy uncertainty to carbon price projections. The effect of these uncertainties is more pronounced when the carbon price is at a high quantile level. This research can offer valuable guidelines for carbon market risk management and provide new insight into carbon price formation mechanisms in the era of global conflict.