Geopolitical Events Research Articles

Assessment of the energy-saving and environment effects of China's gasoline vehicle withdrawal under the impact of geopolitical risks

With the increasing number of geopolitical events, energy and economy have been affected in all regions of the world. Uncertain geopolitical risks have led to the instability of the energy supply chain, thus affecting the future planning of fuel vehicles. Accordingly, the environmental effects of “Banning gasoline vehicle sales policy” (BGVSP) will also be affected by geopolitical risks. Therefore, using life-cycle assessment and the Lotka–Volterra model, this study evaluated the environmental effects of BGVSP in terms of energy consumption, carbon emissions, human toxic potential (HTP), global warming potential (GWP), acidification potential (AP), air quality potential (AQP), and photochemical ozone creation potential (POCP). We further analyzed the effects of differences in policy timing on the energy-conservation and emission-reduction benefits of BGVSP under multiple scenarios. The results show that the implementation of BGVSP in 2025 reduces the energy consumption, carbon emissions, GWP and POCP of the Chinese passenger vehicle market by 17.2%, 18.6%, 17.9% and 46.2%, respectively. However, it may also enhance HTP, AQP, and AP impact by 5.3%, 5.6%, and 18.2%, respectively. Meanwhile, lightweight automobile development could also help reduce energy consumption and carbon emissions in the passenger vehicle market. In this situation, the environmental effects of BGVSP implementation are superimposed. Moreover, the emission-reduction effect of new-energy vehicles is linked to the energy structure in terms of the whole life cycle; thus, the environmental effect of BGVSP in the context of energy cleaning is “super additive”. Regarding environmental effects, 2030 would be the optimal time for China to implement BGVSP as it transitions to clean energy.

The Russian-Ukrainian Conflict and its Implications for EU Energy Security

The Russian-Ukrainian Conflict and its Implications for EU Energy Security

Frames and sentiments of the Twitter communication by German Chancellor Scholz during the Russian invasion of Ukraine

Abstract In a complex information environment, Russia’s invasion of Ukraine presents a major challenge to the communication of political leaders throughout the world. The objective of this article is to analyse the frames and sentiments used by German chancellor Olaf Scholz, employing a novel data set of his Twitter communication (N = 612) during the Russian invasion of Ukraine between 24 February 2022 and 24 February 2023. A combination of computational text analysis approaches with natural language processing (NLP) techniques was used, including the Valence Aware Dictionary and the sentiment Reasoner (VADER) model for sentiment analysis and Latent Dirichlet Allocation (LDA) for topic modelling. This research investigates the prevalent frames and emotions in the chancellor’s communication, providing valuable insights into the German government’s stance and strategic communication during this critical geopolitical event. The results of the study revealed that the chancellor used the frames ‘effects of the Ukraine invasion’, ‘climate & environment’, ‘solidarity’ and ‘Russian aggression’ and communicated with positive sentiments. By examining the chancellor’s Twitter communication, this study contributes to the understanding of political communication in the digital era, particularly in the context of international crises, and offers implications for policymakers, scholars and the broader public.

RETRACTED: Geopolitical oil price uncertainty transmission into core inflation: Evidence from two of the biggest global players

This research argues that inflation indirectly correlates with geopolitics through the oil markets. The argument is that uncertainties generated by geopolitics are often transmitted into core inflation through oil prices, and we provide empirical evidence to support this by establishing an uncertainty-oil-macroeconomy nexus for the biggest oil importing countries, the U.S. and China. The study specifically examines whether there are indirect contributions of geopolitical oil price uncertainty to inflation that appear in core inflation, excluding the more volatile food and energy prices. It employs a non-parametric quantile causality technique for analyzing how geopolitical oil price uncertainty and core inflation interact in both countries and conducts rolling windows-based non-parametric quantile causality analysis for robustness. The full-time non-parametric quantile causality results show that geopolitical oil price risk strongly affects core inflation both in mean and variance, especially in the mid-quantiles, and that its effect is greater in variance relative to mean for both countries. The rolling windows-based outcomes indicate that geopolitical oil price risk exerts an increasing influence on core inflation during important geopolitical events such as the Euro crisis, Brexit, presidential elections, trade wars, and COVID-19, and these impacts differ not only between countries, but also according to whether causality is mean or variance. Finally, the significance of the findings is discussed.

Impact of Geopolitical Risk on Financial Assets: Evidence from Time-Varying Parameter Var

Geopolitical events are expected to affect all countries, asset classes, and sectors. Vietnam is a large open economy, actively participating in a vast network of free trade agreements. Therefore, political conflicts in some regions will have both positive and negative impacts on the Vietnamese economy. Aiming to explore the dependency structure between the geopolitical risk index and stock market returns, this study has evaluated quite in-depth using the TVP-VAR method combining the wavelet coherence phase between February 2012 and April 2022. The results show that geopolitical risk has a heterogeneous effect on the return of financial assets, and the market does not respond to geopolitical tensions in a uniform manner. Our research uncovers new and interesting implications for policymakers and investors involved in the Vietnamese stock market.

The Impact of International Relations Patterns on China’s Energy Security Supply, Demand, and Sustainable Development: An Exploration of Oil Demand and Sustainability Goals

This study explores the impact of international relations on China’s energy security and supply/demand dynamics, specifically focusing on new energy sources and technological advancements. Given China’s status as the world’s largest energy consumer, achieving a balance between energy supply, demand, and sustainable development is crucial. This study quantifies the influence of international relations on the energy market, particularly the uncertainties arising from geopolitical events and international tensions that affect energy supply and prices. The research findings indicate that, in a long-term cointegrated relationship, a 1% change in the geo-political risk (GPR) index leads to a 0.229% change in China’s crude oil imports. Additionally, the impact of China’s GDP growth, carbon emissions, and sustainable energy consumption is −2.176, 0.723, and 0.167, respectively. This study also discusses the reasons behind the differential impact of crude oil prices on the United States and China. Recognizing the interplay between China’s energy security and international relations is vital for effective policy formulation. This study provides valuable insights for policymakers and stakeholders to ensure a sustainable and secure energy future.

Editorial: There's an AI for that

In recent months, the educators and higher education institutions have responded with concern, critique, and hope, to the rise of generative artificial intelligence (AI)’s unregulated and mounting influence. Following the period of emergency remote teaching, and the great ‘snapback’ (Jandrić et al., 2022), yet another new concern has emerged, promising to revolutionise education, or threaten its existence. The gravity of the situation has reverberated across the system, as wizardry of predictive pattern recognition fundamentally threatens the validity of long-held practices of summative assessments including essays, and online quizzes. This latest quandary/crisis shows no sign of abating, as venture capitalist funding and language modelling datasets grow. The technology becomes more deeply integrated into word processing, and cloud-based applications through which much of our academic labour is conducted. Understanding and conceptualising new technology within education has long been a necessity, as we wrestle with wrangling tools into our human interactions. Higher education’s relationship with edtech has always been characterised by a cyclical response to disruptive external influences of evolving technology, whose recent developments are often underpinned by neoliberal values of competition, efficiency, market-based solutions, and the privatisation of software platforms. Recent large language model developments are proving no different, with deregulation and the free market serving as the impetus to design and create such tools. Across higher education, educators scramble to decode the GenAI black box, deciphering hallucinations, confabulations, and smooth outputs indistinguishable from original student work. Policy responses range along a continuum of ban or embrace. New AI literacies are being woven into curricula, as change continues apace. 2023 marks a year of existential crisis precipitated by a global pandemic, followed by geopolitical events and a fatigue from the continual adaptation to a new normal. Even within, we are constantly shaping our educational systems. That pull is in many different directions – to accredit, to certify, to help learners become, to socialise, to emancipate, to measure - to meet very diverse purposes and aims. The politics and power structures inherent in our system further affect our response (Kuhn et al., 2023). While the potential of AI chatbots based on natural language processing models is undeniable, it is crucial to discern the reality from the hype and to better understand how our actions and responses are shaping our educational systems in this evolving domain. This editorial examines this dilemma further, to consider the impact on our scholarship of teaching and learning and how we as a community of researchers and educators respond.

Dynamic risk connectedness of crude oil price and sustainable investment in the United States: evidence from DCC-GARCH.

Sustainable investment is widely regarded as an important market-based approach to achieving inclusive green growth. To achieve the inclusive green growth objective, companies providing sustainable products must be profitable enough to attract private capital. Oil price changes can however affect the profitability of such companies. This study assesses volatility transmission between crude oil prices and sustainable investment in the USA. Using the dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH) method, daily data from September 28, 2012, to October 19, 2022, is analyzed. There are several key findings from this analysis. The risk connectedness of crude oil and sustainable investment is found to vary with time. Results further show that the risk connectedness increases in periods of important economic and geopolitical events. The greatest risk connectedness of crude oil and sustainable investment is observed during the outbreak of coronavirus disease (COVID-19). Moreover, the result shows that crude oil is the main risk transmitter, whereas, both the energy efficiency and pollution mitigation indices (i.e., sustainable investment) are risk receivers, and crude oil is constantly dominating sustainable investment. The study findings provide valuable insights for investors and policymakers alike.

Neural Networks-Based Forecasting Platform for EV Battery Commodity Price Prediction

This study explores the impact of green energy-based economies on the growing use of electric vehicle (EV) batteries in transportation and electronic devices. Despite the environmental benefits, concerns have emerged regarding the supply, pricing, and volatility of raw materials used in battery manufacturing, exacerbated by geopolitical events such as the Russian-Ukrainian war. Given the high uncertainty surrounding EV commodity materials, this research aims to develop forecasting tools for predicting the prices of essential lithium-based EV battery commodities, including Lithium, Cobalt, Nickel, Aluminum, and Copper. The study builds on previous research on commodity price forecasting. Using Neural Networks such as LSTM that run using analytics platforms like RapidMiner, a robust and accurate models is able to be produced while require little to no programming ability. This will solve the needs to produce advanced predictions models for making decisions. As the results from the research, the models that are produced are successful in generating good prediction models, in terms of RMSE of 0,03 – 0,09 and relative errors of 4-14%.

Does geopolitical risk affect firms' idiosyncratic volatility? Evidence from China

Using 2663 Chinese A-share listed companies from 2003 to 2019, we investigate the relationship between geopolitical risk (GPR) and firm idiosyncratic volatility through panel fixed effects and attempt to explain the mechanism. The main findings are presented as follows. First, GPR can explain the change of firms' idiosyncratic volatility. Different industry conditions and ownerships have heterogeneous effects on the firms' idiosyncratic volatilities. In addition, the interaction terms of ownership concentration, competitive intensity and operating leverage with GPR are statistically significant, and they interact with GPR to affect firms' idiosyncratic volatility. After we conduct a series of robustness tests using methods such as instrumental variables, we innovatively introduce the South China Sea dispute as an external event and use the DID (Difference-in-difference) model to analyze the impact of geopolitical events on corporate risk-taking, our findings remain valid. Our research contributes to a better understanding of geopolitical risk and firms' idiosyncratic volatility.

Critical metals in uncertainty: How Russia-Ukraine conflict drives their prices?

Critical minerals bring new challenges to energy security in the transition to clean energy, so their supply and prices are a spectacle of global uncertainties. This research investigates the impact of the Russia-Ukraine war on critical metal prices and the extent to which it affects them. The study will also highlight the price trends in the absence of this geopolitical event. The results outline that the Russia-Ukraine conflict drives critical metals prices. The outcomes show rapid divergence from counterfactual predictions, and the critical metals prices are consistently higher than expected without conflict. The curves suggest a reconvening pattern in metals prices around April 2022. The point-wise causal effect displays an estimate of the critical metal prices increased following the conflict. In relative terms, the prices of critical metals, namely cobalt, nickel, lithium, copper, and aluminum, experienced increases of 2%, 36%, 14.97%, 3%, and less than 1%, respectively. In comparison, the price of lead exhibited a decrease of 8%. The highest increase was observed in nickel, followed by lithium, indicating that these two metals are more responsive to such variations. However, it is noteworthy that prices tend to stabilize and return to pre-event levels from May to September, depending on the respective metal's sensitivity. Moreover, outcomes emphasize that global dependencies, lack of resources and investments, and intentional conflict of crucial minerals exporting nations lead to the conflagration.

Risk return profile of commodity derivatives: an investors perception

This article provides an overview of the literature on the commodity market, with a particular focus on the risk of commodity investment. The sources of return in the commodity market are examined, as well as the impact of various macroeconomic factors such as interest rates and inflation on the return. The commodity market is an increasingly popular investment opportunity for investors looking to diversify their portfolio. However, investing in commodities is not without risk. The volatility of commodity prices can lead to significant losses for investors, especially those who are not familiar with the market. One of the primary sources of return in the commodity market is through price appreciation. This is driven by supply and demand factors, such as changes in weather patterns, geopolitical events, and changes in consumer tastes. In addition, commodities can also generate returns through passive income, such as through rental income from real estate or dividends from stocks. Interest rates and inflation are two key macroeconomic factors that can have a significant impact on the return of commodity investments. Higher interest rates can lead to lower commodity prices, as investors seek out higher yield investments. Inflation can also impact the return of commodity investments, as it can lead to higher prices for raw materials and other inputs. For wheat, corn, and soybean futures, seasonality of return is an important consideration for investors. The prices of these commodities are often influenced by seasonal factors, such as weather patterns and harvest cycles. Understanding these seasonality patterns can help investors make more informed investment decisions. In conclusion, this study is mostly descriptive in nature, providing an overview of the literature on the commodity market and the risks associated with commodity investment. The impact of various macroeconomic factors, such as interest rates and inflation, on the return of commodity investments is also examined. Finally, the seasonality of return for wheat, corn, and soybean futures is discussed as an important consideration for investors.

The role of eco-innovation, renewable energy consumption, economic risks, globalization, and economic growth in achieving sustainable environment in emerging market economies.

In the last two decades, environmental degradation has been a topic of concern. The rising level of CO2 emissions (CO2E) has adversely affected life in the E7 countries, which comprise of Brazil, China, India, Indonesia, Mexico, Russia, and Turkey. The increased in CO2E is the cause of rising sea levels in the E7 countries. Visibly, E7 nations which are considered as the largest emitters of CO2 are facing the most severe environmental challenges. This study investigates the impact of eco-innovation, economic growth (EG), renewable energy consumption (REC), economic risk (ERI), and globalization on the CO2E, using the Feasible Generalized Lease Squares (FGLS) and Panel Corrected Standard Errors (PCSE) techniques for the period 1995 to 2018. The results indicate an inverted N-shaped relationship between eco-innovation and CO2E. Also, eco-innovation, REC, and economic risk are observed to be significant factors in abating CO2 emissions. On the contrary, globalization and GDP are responsible for rising CO2E in E7 countries. According to empirical estimates, eco-innovation improves the efficiency of carbon emissions, which lowers CO2E. In addition, because they are immune to changes in the price of oil and gas and disruptions brought about by geopolitical events, renewable energy sources can offer countries a more secure energy source than fossil fuels. Alternative energy sources can reasonably cut CO2E while offering a more reliable and secure energy source. Therefore, it is crucial that policies be put in place to cut CO2E by giving priority to environmental innovative policies.

Transmission mechanisms of geopolitical risks to the crude oil market——A pioneering two-stage geopolitical risk analysis approach

As an exogenous risk, geopolitical risk drives oil price volatility indirectly through multiple factors, which are ignored by most studies. This paper establishes a two-stage approach for the first time to analyze the indirect geopolitical risk transmission mechanisms, and applies the time-varying parametric vector autoregressive (TVPVAR) model to illustrate how geopolitical risk affects oil prices via different transmission paths including micro media (supply, demand, inventories, speculative behaviors) and macro media (global economic activities). Oil prices do not always rise in response to geopolitical events, sometimes even varies to the opposite direction, a phenomenon that can be well explained and modeled by the transmission mechanisms we developed. In this paper, we have identified two clear and unique geopolitical transmission paths to enhance energy-related decisions. Aside from the conventional economic phenomenon of geopolitical risks affecting oil prices through supply and demand behaviors, speculative behaviors increase during the period of high geopolitical risk, and the impact of speculative activity on oil prices is prominent. In addition, the most influential path is that geopolitical factors can indirectly impact oil prices by influencing economic fluctuations, which provides powerful and empirical supports for energy-related financial decisions and policy implications.

Investigating the dynamics of crude oil and clean energy markets in times of geopolitical tensions

This study examines how adverse geopolitical events influence the dynamics of crude oil and clean energy markets. A vector smooth transition regression model is implemented to capture the presence of regime shifts due to geopolitical conflicts. The impulse response analyses reveal that the crude oil market is non-responsive to all geopolitical events. A significant spike in oil prices arises only if risks associated with geopolitical tensions surpass a certain threshold level. The green equity market responds differently, showing an adverse reaction during episodes of higher geopolitical uncertainty. Moreover, our empirical results point out a decoupling between traditional and clean energy sectors in times of geopolitical stress. Our findings contrast with the conventional wisdom that a surge in oil prices would foster a shift toward alternative energies. While the observed disconnection would offer better diversification benefits, it is challenging for policymakers to encourage investors to maintain low-carbon portfolios.

Cryptocurrencies and the threat versus the act event of geopolitical risk

We examine the reactions of the cryptocurrency market to two events that occurred during the escalation of the Russia–Ukraine war in February 2022. Using hourly data, we find that the escalation exerted a negative influence on both liquidity and returns. Interestingly, the actual escalation triggered a more pronounced drop than the threat of escalation shortly before. This contrasts with the stock market, where threats of geopolitical events are found to have a greater impact. Post-escalation, we observe indications of increased demand for cryptocurrencies, potentially as a means to circumvent Western sanctions imposed on Russia or to provide aid to Ukraine.

Quantifying the value of energy security: How Russia's invasion of Ukraine exploded Europe's fossil fuel costs

What is the value of energy security? Fossil fuels are subject to interruptions or major price swings based on wars or other geopolitical events. Here, we analyze multiple dimensions of energy security, and quantify the energy security risks of geopolitical volatility in a specific case: we estimate how much Russia's invasion of Ukraine increased Europe's fossil fuel costs above normal. For the excess market costs, we count only the fuel costs beyond our estimates of the counterfactual costs. We find that Europe spent an extra €517–831 billion in excess market costs due to higher prices in the period October 1, 2021, to December 31, 2022, with a best estimate of €643 billion. European governments also announced an additional €908 billion of fiscal spending on energy-related infrastructure and policies. These two categories of costs are not fully commensurable, but the total fossil costs appear over €1 trillion. We then compare these costs to two reference points: Europe's direct material aid to Ukraine in 2022 and the costs of more rapidly decarbonizing Europe's energy system.

Equity market connectedness across regimes of geopolitical risks: Historical evidence and theory

We use a threshold VAR model to capture the connectedness of the equity returns of the G7 in a regime-contingent manner as defined by low- and high-geopolitical risks (GPR). We find that connectedness is statistically stronger when GPR is at its higher rather than lower regime, but more importantly, this observation can be associated with the threat of adverse geopolitical events, rather than with their actual realization. To explain our empirical observations we employ a model of international trade in assets and international relative asset prices. We introduce uncertainty in future dividend payments combined with agents' ambiguity aversion to changes in the expected dividends. This allows us to model a geopolitical threat as a shock that affects the level of ambiguity about future dividends. At the same time, a geopolitical act is defined as a shock to the current period endowment of a given country, with limited effects on asset prices and returns. Our obtained results have important portfolio allocation implications for investors.

Legalization of Ethics in Sports and Disciplinary Liability for “Disrepute”

The norms of ethics in sport have practically merged with the disciplinary norms of sports federations. However, the apparent identity of ethical duties and disciplinary duties has not resolved the existing problems of law enforcement. Ethical norms enshrined in the acts of sports federations must meet certain standards of law. In this case, we are referring to the general principles of legal certainty and proportionality, as well as some other related principles. These principles are the first and main guarantees for the subject of sport in case of a breach of an ethical obligation. They are used at different stages of disciplinary liability. Legal certainty protects against unclear ethical norms and unpredictable consequences of their use by sports federations. Proportionality obliges the measure of disciplinary responsibility not to exceed the necessary negative effect of coercion. The ethical obligation to abstain from disrepute is widespread in the acts of federations. The practice of non-disrepute has been intensified by geopolitical events of 2022. The examples of the practice on non-disrepute do not allow us to state that legal certainty and proportionality really protect in any situation from improper disciplinary liability. The tendency has appeared to understand the reputation of sports and sports federations through the prism of the public positions of a particular federation. Confrontation with such positions automatically creates the risk of disciplinary liability. Similarly, the test for real harm to reputation is ignored unlike potential harm or harm existing only in subjective judgements.

Renewable energy deployment and geopolitical conflicts

This paper investigates whether geopolitical conflicts play a critical role in stimulating countries to shift toward clean energy solutions. We use the panel regime-switching models, which allow us to capture the nonlinear dynamics of the energy transition. Our results for a panel of developed and emerging countries reveal that the geopolitical context does not impact the renewable-income nexus; however, we find that adverse geopolitical events would impact the diffusion of alternative energy sources depending on the level of economic development. Rising geopolitical conflicts would encourage high-income nations to switch toward low-carbon energy sources. Considering the increasing number of regional conflicts, less developed countries must urgently develop their economies away from traditional energy sources and enhance the contribution of the renewable sector.