Search Results (121)

For a long time, the explanation of the various determinants of oil price fluctuations and their impact on economic activity has been based on the supply and demand mechanism. However, with various volatile changes in the international situation in recent years, such as threats to public health and an increase in regional conflicts, special attention has been paid to the geopolitical context as an additional driver of oil price fluctuations. This study examines the relationship between oil price changes and GDP growth and other macroeconomic variables from the perspective of the vulnerability of oil-importing and oil-exporting countries to unexpected oil price shocks, driven by tense geopolitical events, in three European countries (Norway, Germany, and Poland). We apply the Structural Vector Autoregressive (SVAR) model and orthogonalized impulse response functions, based on quarterly data, in regard to two samples: the first spans 1995Q1–2019Q4 (pre-2020 sample), with relatively gradual changes in oil prices, and the second spans 1995Q1–2024Q2 (whole sample), with sudden fluctuations in oil prices due to geopolitical developments. A key finding of this research is that vulnerability to unpredictable oil price shocks related to geopolitical tensions is higher than in regard to expected gradual changes in oil prices, both in oil-importing and oil-exporting countries. Different causality patterns and stronger responses in regard to GDP growth during the period, including in regard to tense geopolitical events in comparison to the pre-2020 sample, lead to the belief that economies are not more resilient to oil price shocks as has been suggested by some studies, which referred to periods that were not driven by geopolitical events. Our research also suggests that countries implementing policies to reduce oil dependency and promote investment in alternative energy sources are better equipped to mitigate the adverse effects of oil price shocks. Full article

Indonesia’s dependence on fossil fuel exports, particularly coal and crude oil, presents a dual challenge: sustaining economic growth while addressing rising CO₂ emissions. Despite significant attention to domestic energy consumption, the environmental implications of export activities remain underexplored. This study examines the dynamic relationship between energy exports, crude oil prices, and CO₂ emissions in Indonesia using a Vector Autoregressive (VAR) model with annual data from 2002 to 2022. The analysis incorporates Impulse Response Functions (IRFs) and Forecast Error Variance Decomposition (FEVD) to trace short- and long-term interactions among variables. Findings reveal that coal exports are strongly persistent and positively linked to past emission levels, while oil exports respond negatively to both coal and emission shocks—suggesting internal trade-offs. CO₂ emissions are primarily self-driven yet increasingly influenced by oil export fluctuations over time. Crude oil prices, in contrast, have limited impact on domestic emissions. This study contributes a novel export-based perspective to Indonesia’s emission profile and demonstrates the value of dynamic modeling in policy analysis. Results underscore the importance of integrated strategies that balance trade objectives with climate commitments, offering evidence-based insights for refining Indonesia’s nationally determined contributions (NDCs) and sustainable energy policies. Full article

Globalization and the spread of technological innovations have made world markets and economies increasingly unified and conditioned by international trade, not only for sales markets but above all for the supply of raw materials necessary for the functioning of the production complex of each country. Alongside oil and gold, the main commodities traded include industrial metals, such as aluminum and copper, mineral products such as gas, electrical and electronic components, agricultural products, and precious metals. The conflict between Russia and Ukraine tested the unification of markets, given that these are countries with notable raw materials and are strongly dedicated to exports. This suggests that commodity prices were able to influence the stock markets, especially in the countries most closely linked to the two belligerents in terms of import-export. Given the importance of industrial metals in this period of energy transition, the aim of our study is to analyze whether Industrial Metals volatility affects G7 stock markets. To this end, the BEKK-GARCH model is used. The sample period spans from 3 January 2018 to 17 September 2024. The results show that lagged shocks and volatility significantly and positively influence the current conditional volatility of commodity and stock returns during all periods. In fact, past shocks inversely influence the current volatility of stock indices in periods when external events disrupt financial markets. The results show a non-linear and positive impact of commodity volatility on the implied volatility of the stock markets. The findings suggest that the war significantly affected stock prices and exacerbated volatility, so investors should diversify their portfolios to maximize returns and reduce risk differently in times of crisis, and a lack of diversification of raw materials is a risky factor for investors. Full article

Crude oil is a widely recognized, indispensable global and national economic resource. It is significantly susceptible to the boundless fluctuations attributed to various variables. Despite its capacity to sustain the global economic framework, the embedded uncertainties correlated with the crude oil markets present formidable challenges that investors must diligently navigate. In this research, we propose a hybrid machine learning model based on random forest (RF), gated recurrent unit (GRU), conventional neural network (CNN), extreme gradient boosting (XGBoost), functional partial least squares (FPLS), and stacking. This hybrid model facilitates the decision-making process related to the import and export of crude oil in India. The precision and reliability of the different machine learning models utilized in this study were validated through rigorous evaluation using various error metrics, ensuring a thorough assessment of their forecasting capabilities. The conclusive results revealed that the proposed hybrid ensemble model consistently delivered effective and robust predictions compared to the individual models. 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

This paper constructs a modified hypothesis extraction method (MHEM)–structural decomposition analysis (SDA)–structural path decomposition (SPD) analytical framework and employs the 2018–2022 Chinese input–output tables to discuss sectoral consumption correlations, driving forces of consumption, and the transmission paths of carbon energy (CE), oil and gas energy (OGE) and electric energy (EE). The results of the study indicate that energy-exporting sectors are primarily energy production or conversion industries, while energy-importing sectors are mainly in the construction sector. China’s energy consumption has shown consistent year-on-year growth, with the primary driving force being the intensity of energy consumption and the secondary factor being per capita demand. The consumption of all three types of energy is primarily directed toward domestic consumption and capital formation. Regarding energy consumption transmission paths, the first-order path with the largest overall impact on CE is “electricity, gas, and water supply sector → domestic consumption”, while higher-order paths are primarily subpaths of “electricity, gas, and water supply sector → capital formation”. For OGE, the main supply and transfer path is “coke, refined petroleum, and nuclear fuel sector → domestic consumption”, along with its subpaths. In contrast, EE transmission is more balanced, with a high demand for electricity across all sectors. Full article

Indonesia plays a dominant role in the global refined palm oil (RPO) supply chain. Given the increasing global emphasis on carbon neutrality and sustainable trade, understanding the carbon footprint of Indonesian RPO and its embodied carbon emissions (ECE) in global trade is essential for identifying mitigation opportunities and aligning with international sustainability standards. This study integrates life cycle assessment and trade data to quantify the carbon footprint of RPO products and analyze the spatiotemporal patterns of trade-related ECE. Results show that producing 1 ton of RPO emits 2196.84 kg CO₂e, with wastewater treatment (57.67%) and land use change (32.82%) as the main contributors. From 2010 to 2022, ECE induced by RPO exports rose from 35.79 Mt CO₂e to 54.94 Mt CO₂e (3.64% annual growth). Major ECE importers were India, China, and Pakistan, accounting for 20.36%, 14.29%, and 11.45% of Indonesia’s total trade-related ECE, respectively. Comprehensive sensitivity and uncertainty analyses conducted on key parameters confirmed the robustness of the above results. Based on these robust findings, integrated mitigation strategies targeting both production optimization and sustainable trade mechanisms are proposed to accelerate Indonesia’s RPO industry decarbonization. Full article

This study employs asymmetric quantile regression to investigate the asymmetric impact of WTI crude oil prices and economic policy uncertainty (EPU) on stock market returns from May 2014 to December 2024 in oil-importing (China, India, Germany, Italy, Japan, USA, and South Korea) and oil-exporting (Saudi Arabia, Russia, Iraq, Canada, and the United Arab Emirates) countries. The findings reveal that an increase in oil prices significantly impacts the returns of all countries. For oil-importing countries, an increase in oil prices consistently exhibits a positive impact, with insignificant effects in lower and medium quantiles and significant effects in higher quantiles. Conversely, a decrease in oil prices generally decreases stock market returns across all quantiles. This study offers valuable insights for investors to manage risks and improve the predictability of oil price fluctuations. It also provides strategies and policy implications for capitalists and decision-makers. By addressing contemporary issues and using up-to-date data, the study supports financial institutions and portfolio managers in formulating effective strategies. Full article

The standardization of catch per unit effort (CPUE) is essential for accurate stock assessment in fisheries management. This study focuses on CPUE standardization for red snow crab (Chionoecetes japonicus) in South Korea, incorporating both spatiotemporal and socioeconomic factors into a generalized additive model (GAM) framework. Using fishery-dependent data from 2009 to 2023, we analyzed the influence of variables such as the proportion of live catch, oil prices, global export prices, and the COVID-19 pandemic on CPUE trends. To quantify the contribution of each variable, a stepwise exclusion analysis was conducted. The results show that excluding socioeconomic variables leads to a more stable CPUE trajectory, indicating that nominal CPUE fluctuations are partially driven by economic conditions rather than changes in biological abundance. These findings highlight the importance of accounting for external drivers, particularly socioeconomic factors when standardizing CPUE. By doing so, the year effect extracted from the model can more accurately reflect relative stock abundance. The approach presented here offers a practical solution for improving CPUE estimates in data-limited fisheries and supports adaptive, evidence-based fisheries management. Full article

The development of an energy transition policy that ensures a rational combination of the requirements of sustainable development and the country’s priorities is a key factor determining the success of its development. The complexity and importance of this task increase in the case of countries in which oil and natural gas export revenues play a key role in the formation of the budget and development of the country. In this paper, the solution to this problem is studied using the example of Azerbaijan. Considering that the task requires addressing the uncertainty and limitations of available information and statistical data, we used an approach based on the use of fuzzy scenarios and expert information. Scenarios have been described using linguistic variables and the formalism of Z-numbers. Z-numbers allow us to simultaneously formalize uncertainty and reliability in the information. Solving the problem involves integrating approximate methods of Z-reasoning and multi-criteria decision-making. This approach considers economic, social, environmental, and technological criteria and allows for the generation, analysis, and evaluation of transition scenarios. The results obtained demonstrate the effectiveness of the proposed methodology for constructing energy transition scenarios for countries producing and exporting oil and gas. The solution suggests a moderate increase in natural gas and hydropower production, along with a significant rise in solar and wind energy production. The results highlight the effectiveness of a rational combination of traditional and renewable energy sources during the transition period. The rule base developed in this article can be adapted to account for the priorities and constraints of a specific oil- and gas-producing and -exporting country, and the fuzzy scenarios approach can be successfully applied to address the transition challenge. Full article

Since private cars and vans accounted for more than 25% of global oil consumption and about 10% of energy-related CO₂ emissions in 2022, increasing the share of electric vehicle (EV) ownership is considered an important solution for reducing CO₂ emissions. At the same time, reducing emissions entails certain economic losses for those countries whose exports are largely covered by the oil trade. The explosive growth of the EV segment over the past 15 years has given rise to overly optimistic forecasts for global EV penetration by 2050. One of the major obstacles to such a development scenario is the limited availability of resources, especially critical materials. This paper proposes a mathematical model to predict the global EV fleet based on the limited availability of critical materials such as lithium, one of the key elements for battery production. The proposed model has three distinctive features. First, it shows that the classical logistic function, due to the specificity of its structure, cannot correctly describe market saturation in the case of using resources with limited serves. Second, even the use of a special multiplier that describes the market saturation process taking into account the depletion (finiteness) of the used resource does not obtain satisfactory economic results because of the “high speed” depletion of this resource. Third, the analytical solution of the final model indicates the point in time at which changes in saturation rate occur. The latter situation allows us to determine the tracking of market saturation, which is more similar to the process that is actually occurring. We believe that this model can also be validated to estimate the production of wind turbines that use rare earth elements such as neodymium and dysprosium (for the production of powerful and permanent magnets for wind turbines). These results also suggest the need for oil-exporting countries to technologically diversify their economies to minimize losses in the transition to a low-carbon economy. Full article

Brazil is a resource-rich economy that relies heavily on the exports of several important commodities. The variability of commodity prices affects both the economy and the stock market. This study investigates the relationship between commodity price shocks and stock returns in Brazil using a structural vector autoregressive (SVAR) model. This study uses monthly data on prices of five major export commodities, stock returns, and several control variables, covering the period from January 2010 to December 2022. To account for the Brazilian economic crisis between 2014 and 2016, we have analyzed the effects of commodity prices on stock prices in three different time periods, namely, before the economic crisis (January 2010–March 2014), during the economic crisis (April 2014–December 2016), and after the economic crisis (January 2017–December 2022). The empirical results of this study provide evidence to conclude that stock returns increase following a positive global commodity price shock or a positive exchange rate shock. The effects are more noticeable during the economic crisis in Brazil. The results also show that the volatility of Brazilian stock returns is mostly explained by global oil prices and exchange rate movements in the long run. Full article

Our investigation, bolstered by the robust gravity trade model and panel data econometric technique, underscores the pivotal factors that influence trade interactions between Saudi Arabia and the BRICS nations—Brazil, Russia, India, China, and South Africa. The study, spanning from 1998 to 2023, delves into key economic metrics such as the gross domestic product, exchange rate fluctuations, inflationary trends, political conditions, and trade deals. We employ a range of econometric strategies, including pooled Ordinary Least Squares (OLS) and fixed effects models, to reveal that the GDP of BRICS states consistently and significantly impacts trade volumes. Specifically, a 1% increase in the GDP of partner countries correlates with a 0.37% rise in trade volume within the pooled OLS model. This effect amplifies to 1.43% when adjusting for temporal and country-specific factors in the fixed effects, underscoring the importance of accommodating unobserved heterogeneity, which refers to the unmeasured factors that can influence the relationship between GDP and trade volume. The political stability of BRICS nations mitigates transactional risks and promotes more stable trade relationships, thereby enhancing trade flows. Fluctuations in exchange rates exert positive and significant effects. This indicates that a more robust Saudi Riyal, an essential policy instrument, can enhance trade by increasing the competitiveness of Saudi exports. This study demonstrates that economic magnitude, political stability, and exchange rates affect Saudi Arabia’s trade with BRICS nations. These results bolster the Kingdom’s Vision 2030 objectives for economic diversification. This research advocates for stable political climates and strategic trade agreements to enhance trade relations. This study asserts that this approach will guarantee sustainable growth and diminish the Kingdom’s reliance on oil exports, instilling optimism in the Saudi economy. Full article

Transport drives economies. This statement covers complex and multifaceted economic, environmental, and political issues. The literature mainly describes the unidirectional impact of transport on the economy, and far less often bilateral or reverse impacts. This is the context in which this study was conducted. The question of whether the economy (GDP and exports and imports) and energy prices (crude oil and diesel) have an impact on road and rail transport in Poland was examined. The research was based on correlation methodology and VAR modelling for the January 2010–March 2024 period (quarterly data). It was found that there is no sufficiently strong basis to speak of an inverse relationship, i.e., that the economy is the cause of transport. This confirms the majority of studies, but it has been shown that this relationship occurs in the current period. And this statement means that both road transport, which is developing, and rail transport, which is declining in Poland, are able to serve the economy on a continuous basis. Moreover, rail transport is positively affected by changes in fuel prices, but the basic energy resource used in rail transport is not fuel but electricity. Therefore, as fuel prices rise, investment in rail transport or combined transport can have positive economic and environmental effects in the future. Full article

This paper explores the transmission of volatility from Brent oil price evolution to the stock returns of 7 MENA countries, encompassing three importers and four exporters, after excluding four initial countries using the ARCH test. Employing the GARCH-BEKK estimation method, we detect this transmission from January 2008 to September 2022. The results reveal significant volatility persistence across six stock markets with three importer countries and three exporters. These findings align with Shiller’s theory, indicating high volatility in financial markets. Tunisia’s stock market shows sensitivity to oil market developments, while the Omani market demonstrates volatility transfer from Brent oil prices. However, Morocco’s market exhibits resilience, with no significant transmission from international oil prices. Exporting countries, except the UAE, display significant and positive coefficients, indicating volatility transmission. The study suggests further research into underlying mechanisms and recommends policymakers and investors implement strategies to mitigate volatility effects. Advanced modeling and behavioral insights can enhance risk management strategies. Full article