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Fluctuations in crude oil prices exert substantial economic influence, necessitating adept responses and strategic policy formulations to mitigate potential adverse consequences. Kilian has emphasized the heterogeneous nature of oil price shocks, wherein price rises can yield varied effects contingent upon underlying determinants. Consequently, it is imperative for investors, economists, and policymakers to disentangle real price shocks and assess their impact on macroeconomic aggregates. This study employs a two-stage approach grounded in a structural vector autoregressive (SVAR) model, inspired by Kilian's framework, to examine and contrast the repercussions of various crude oil price shocks on the actual Gross Domestic Product (GDP) and Consumer Price Index (CPI) in countries that are either net importers or exporters of oil. Our empirical results reveal that variations in real oil prices are more substantially influenced by shocks due to aggregate demand and precautionary demand, as opposed to shocks originating from the oil supply side. Additionally, aggregate demand shocks lead to significant GDP surges for most oil-importing countries and all oil-exporting countries, while only leading to continuous CPI increases in oil-importing countries. Precautionary demand shocks initially boost GDP in oil-exporting countries but lead to GDP reductions in oil-importing countries. Precautionary demand shocks sustain CPI increases in the oil-importing countries, though with variations in significant durations, but have mixed effects in oil-exporting countries, with significant CPI increases observed in Canada and Norway. Concerning the implications for policymakers and investors, the findings underscore the importance of considering variations in response patterns to crude oil price shocks based on their drivers and the country's status as an oil importer or exporter. [ABSTRACT FROM AUTHOR]

The paper explores the worldwide co-movement between the demand for electric cars and oil prices from January 3rd, 2020, to March 6th, 2023, utilizing wavelet methodology. The main finding shows a strong link between electric car demand and oil prices when oil prices are highly volatile in the short term. When oil prices suddenly drop, people's preference for electric cars decreases in the very short term. However, in the short term, the demand for electric cars is influenced by how much oil prices change and the anticipation of future trends, causing a shift between traditional and electric cars. These results hold true even when considering factors like geopolitical risks, pandemics, the health of the car industry, and the cost of metals used in car batteries. The findings have crucial implications in the socio-economic environment, being very useful to both policy-makers and car market actors. In this light, on the one hand, the outputs can offer support in shaping policies able to reduce fossil fuel dependency and address climate change. On the other hand, this insight aids in correcting the market dynamics across automotive and energy sectors under oil price volatility. Furthermore, these dynamics can affect economic indicators like inflation, trade balances, unemployment, and GDP growth. Not least, transitioning to electric cars can mitigate emissions reduction, improve air quality, diversify energy sources, and enhance energy security. [ABSTRACT FROM AUTHOR]

This study examines whether the effect of oil prices on economic growth is influenced by the level of corruption. I focus on 30 oil-rich economies and employ dynamic heterogeneous panel estimation techniques to address the issue of cross-sectional dependence. Evidence from the study reveals that the impact of oil prices on growth varies with corruption levels. Specifically, the marginal effect of oil prices on growth is positive at low levels of corruption but hampers immediate and long-term growth at high levels of corruption. Essentially, the results indicate that a simultaneous increase in oil prices and corruption impairs growth, whereas increase in oil prices coupled with a reduction in corruption benefits the economy more. Using a disaggregated sample of countries based on their corruption levels, the results suggest that the adverse effect of simultaneous increases in oil prices and corruption is more pronounced in oil-rich countries with higher levels of corruption compared to those with lower levels. The study implies that the level of corruption is a crucial factor in how changes in oil prices impact long-term growth in oil-rich economies. Therefore, for sustainable long-term economic growth, an increase in oil prices must be accompanied by a significant reduction in corruption. [ABSTRACT FROM AUTHOR]

Amidst a dynamic energy market landscape, understanding evolving influencing factors is pivotal. Accurate forecasting techniques are indispensable for effective energy resource management. This study focuses on illuminating insights into economic uncertainty and commodity price forecasting. A meticulously curated dataset spanning January 2000 to December 2022 forms the foundation, incorporating diverse economic and financial uncertainty metrics. Through an innovative research framework, we discern influential factors and forecast their trajectories. Three deep learning models—Short-Term Memory, Gated Recurrent Units, and Multilayer Perception Network—are deployed. The Multilayer Perception model emerges as the standout, showcasing exceptional predictive capability rooted in its adeptness at decoding intricate market patterns. This finding holds significance for policymakers, industry experts, and energy economists. The Multilayer Perception model's supremacy offers a robust tool for decision-making in crafting economic policies and navigating volatile markets. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Professional Business Review (JPBReview) is the property of Open Access Publications LLC and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper investigates the predictive relationships among climate policy uncertainty (CPU), oil prices, and renewable energy (RE) stock market returns, particularly highlighting the challenges posed by the varying data frequencies of these variables. The study utilizes a comprehensive dataset comprising monthly CPU, daily oil prices, and RE stock returns, sourced globally. By applying a mixed-frequency causality test (MFCT), the analysis reveals significant predictability across different time horizons, particularly highlighting the strong influence of oil prices on RE stock returns over short-term horizons, while CPU demonstrates a more pronounced effect over medium to long-term horizons. In contrast, the application of the classical Granger causality test on low-frequency (monthly) data indicates an insignificant relationship between CPU and RE stocks, suggesting that traditional models may overlook important predictive dynamics. The analysis was conducted using Matlab code, and the findings provide valuable insights for policymakers in designing effective climate policies and for investors in optimizing portfolio strategies and hedging against risks. [ABSTRACT FROM AUTHOR]

Recent examples of energy price downturns did not alter trade surpluses in commodity exporting countries. Economic theory contends that such developments may indicate that the changes observed in energy prices are perceived as permanent by the market. We perform a trend-cycle decomposition of oil prices and find that permanent shocks account for about 90% of oil price variation. The observed variability of oil prices attributable to permanent shocks may be explained by the increased financialization of oil markets. This finding is in line with the empirical evidence that the current account surplus is generally unaffected by permanent terms-of-trade shocks. [ABSTRACT FROM AUTHOR]

Boosting energy consumption, ensuring energy supply security, and mitigating emissions are critical global concerns, especially during the surge in energy prices, continuous expansion in income level and persistent economic integration with other countries, and climate change. The existing evidence on the determinant of renewable energy is still in its early stages; however, there is currently limited empirical evidence regarding the determinant of renewable energy in Australia. Therefore, this study probed into the effect of the asymmetric effect of economic globalization on renewable energy usage in Australia, which prior studies in the literature have neglected. The study employed carbon emissions, economic growth, and oil price as other regressors. The dataset for the period spanning from 1970 to 2018 was analyzed using the nonlinear autoregressive distributed lag. Evidence from the empirical analysis reported that the positive variation in economic globalization has a positive and significant effect on renewable energy, thus the rise in economic globalization promotes renewable energy. Meanwhile, the negative variation in economic globalization has a neutral impact on renewable energy. Furthermore, economic growth and oil price positively and significantly affect the usage of renewable energy in Australia. Moreover, carbon emissions have a negative and significant effect on renewable energy. Furthermore, the wavelets coherence was also for the robustness test, which reports positive co-movement between all regressors and renewable energy, except for CO2 emissions (negative co-movement). Economic globalization, economic growth, and CO2 emissions drive renewable energy, while renewable energy leads to oil prices in Australia. This study offers significant and crucial suggestions to policymakers in Australia, emphasizing the need to prioritize environmental sustainability and promote economic globalization to foster the growth of the clean and efficient energy sector. [ABSTRACT FROM AUTHOR]

Remittances are regarded as an important source of foreign exchange for the majority of low and middle-income countries, and thus have the potential to impact their aggregate economic activities. The current study investigates the impact of remittance inflows and international oil prices on India's trade balance from 1975 to 2020. We use a non-linear autoregressive and distributed lag model to examine the asymmetric impact of remittance and oil price changes on trade balance. The study discovered that rising remittance inflows have a detrimental long-run impact on the trade balance. It also demonstrates that while a positive oil price shock worsens the trade balance, a negative oil price shock improves it in the long run. As a result, the paper emphasises the need to reduce skilled migration, properly channel remittance revenues, develop financial institutions, and implement more efficient exchange rate policies in order to achieve long-term trade surpluses. [ABSTRACT FROM AUTHOR]

Oil is one of the significant energy resources for the majority of the world’s states, so many of them monitor and analyze the price of black gold. Currently, there are such organizations of oil exporting countries as OPEC and OPEC+, which for a long time continue to influence not only the world market of this energy resource but also the events taking place in the economic and political spheres of the world. These organizations’ actions have a direct impact on market conditions, policy making, oil price, and the volume of its supply on the market in world trade. The collective responsibility of the member countries for a significant portion of global oil production makes the decisions and actions of OPEC and OPEC+ extremely important for the global oil industry and the economy as a whole. All the above-mentioned points to the relevance of the topic of the study, the objectives of which are to analyze the history of the emergence of the oil exporting countries’ organizations, the dynamics of their development during the history of their existence, as well as to assess the degree of their influence on the oil industry and the global economy as a whole.

Abstract This paper investigates the predictive relationships among climate policy uncertainty (CPU), oil prices, and renewable energy (RE) stock market returns, particularly highlighting the challenges posed by the varying data frequencies of these variables. The study utilizes a comprehensive dataset comprising monthly CPU, daily oil prices, and RE stock returns, sourced globally. By applying a mixed-frequency causality test (MFCT), the analysis reveals significant predictability across different time horizons, particularly highlighting the strong influence of oil prices on RE stock returns over short-term horizons, while CPU demonstrates a more pronounced effect over medium to long-term horizons. In contrast, the application of the classical Granger causality test on low-frequency (monthly) data indicates an insignificant relationship between CPU and RE stocks, suggesting that traditional models may overlook important predictive dynamics. The analysis was conducted using Matlab code, and the findings provide valuable insights for policymakers in designing effective climate policies and for investors in optimizing portfolio strategies and hedging against risks.

The present study undertakes a comprehensive assessment of two predictive models, namely Long Short-Term Memory (LSTM) and Multi-layer Perceptron (MLP), with a specific emphasis on their effectiveness in predicting oil prices, particularly those of the Petroleum Exporting Countries (OPEC). In this study, three fundamental statistical measures are utilized: The Symmetric Mean Absolute Percentage Error (SMAPE), the Mean Squared Error (MSE), and the Mean Absolute Percentage Error (MAPE). The results demonstrate that the LSTM model regularly surpasses the MLP model in the three benchmarks. In particular, the LSTM model demonstrates lower values for SMAPE, MSE, and MAPE, indicating higher prediction accuracy. The decreased error scores linked to the LSTM model highlight its improved capacity for precise oil price prediction in comparison to the MLP model. These results signify a notable progress in the use of machine learning techniques for predicting OPEC oil prices. Moreover, this study provides invaluable perspectives for OPEC management, policymakers, and organizations focused on oil price fluctuations, therefore contributing to the wider endeavour of enhancing the stability and economic sustainability of the oil pricing system in OPEC countries. The consequences of the study include the promotion of a pricing system that facilitates the achievement of economic and social development goals in these countries.

Abstract This research explores economic growth dynamics in five ASEAN countries (1980–2020), analyzing the short and long-term impact of financial development (FD), oil prices, investment (INV), and inflation on GDP growth. Panel ARDL analysis reveals a transient positive link between FD and long-term GDP growth, necessitating a holistic approach for short-term stability. Similarly, oil prices exhibit long-term volatility, urging diversification strategies. In contrast, consistent and significant relationships exist between INV and GDP growth in both time frames, underscoring investment's pivotal role. The study emphasizes managing inflation for sustained growth, offering vital insights for policymakers, economists, and analysts in fostering ASEAN's economic stability.

Faced with a significant devaluation of its currency and a surge in food prices, the Nigerian government prohibited the use of foreign currency for food imports. This essentially blocked the importation of numerous food items under the guise of stimulating the domestic output of these staples. Consequently, food prices in Nigeria increased despite a global decline in food prices, and the incidence and severity of food insecurity escalated. This study examines the changes in the types and severity of coping mechanisms for food insecurity resulting from the food price shock caused by the oil price crash, currency devaluation, and restrictions on foreign exchange. Nigeria's General Household Survey Panel data from 2012 and 2015, during periods of high oil prices, is compared with data from 2018 when oil prices had remained low, the currency had been devalued, and the treasury had been depleted. Alongside detailed descriptive statistics, logistic and hurdle regressions are employed for statistical analysis. Findings indicate a rise in the percentage of Nigerian households grappling with food insecurity from 2015 to 2018. During this period, 68.7% of households resorted to at least one coping mechanism, 31.8% adopted six or more coping strategies, and 43.2% resorted to severe coping strategies. The issue stems not primarily from natural disasters or conflicts but from a failure in macroeconomic and agricultural economic policies. Our findings confirm that these policies come at great cost, particularly to female‐headed households, single‐parent households, households headed by elderly people, and other vulnerable populations, pushing them deeper into food insecurity. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between the international oil market and the West Texas Intermediate (WTI)—Western Canadian Select (WCS) price differential. Monthly data were collected for January 2005 to September 2023 from the U.S. Energy Information Administration, the Federal Reserve Bank of Dallas, the Canada Energy Regulator, and the Government of Alberta. The paper finds that a negative oil supply shock increases the differential with a delay. On the other hand, a positive oil-specific demand shock increases the WTI-WCS differential with a delay, while a positive aggregate demand shock increases the differential persistently. Overall, the three shocks in the international oil market account for 61% of the variability in the price differential in the long run. The aggregate demand shock is the most substantial factor in explaining the variation in the WTI-WCS differential in the long run. This indicates that the global oil market demand has an asymmetric effect on WTI and WCS prices. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic had profound impacts on the global economy, initially triggering a severe economic downturn due to widespread lockdowns. This outbreak generated various economic shocks, a major one being the oil price crash. A brief understanding of how this pandemic is affecting the financial markets, empirical analysis is done on three financial markets. Three stock exchange markets are selected from emerging markets in South Asia (Pakistan, China, and India). The world crude oil market is selected as a reference, to how it transmits volatility to South Asian stock markets in pandemic time. We use a bivariate BEKK-GARCH model for examining the volatility spillover from November 19, 2019, to March 31, 2021. All markets show negative coefficients with the oil market, indicating that the previous day's shocks in oil prices reduce today's stock market volatility, with significant values for India and Pakistan. China has a negative coefficient while the rest of the two markets show a positive and significant coefficient means past volatilities in the stock market decrease today's oil market volatility, likely indicating a reactive or adaptive market behavior to stock volatility. Generally, oil price changes have a significant impact on these markets, with both immediate effects (via ARCH terms) and persistent effects (via GARCH terms). The paper's key contribution is its in-depth look at how oil price volatility impacts stock markets in South Asia, particularly during the uncertainty of the COVID-19 pandemic. By highlighting these dynamic connections, it offers practical guidance for policymakers to better manage economic risks and for investors to make smarter decisions when diversifying their portfolios in today's interconnected global markets. [ABSTRACT FROM AUTHOR]

Copyright of Afyon Kocatepe University Journal of Science & Engineering / Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi is the property of Afyon Kocatepe University, Faculty of Science & Literature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fluctuations in domestic food prices raise significant concerns about food and national security in developing countries. Previous studies established the link between oil prices and rising food prices, but the influence of economic structure and global economic uncertainties received less attention. Using monthly data from 2000:01 to 2023:11 and the cross-sectional dependence autoregressive distributed lag model, we examined the effect of oil prices and economic policy uncertainty (EPU) on domestic food prices in 41 developing countries based on aggregate and disaggregate analyses. The empirical findings indicate that, while oil prices and EPU comove with food prices in the short run, oil price drives domestic food prices in the long run in oil-importing countries. This is valid for high-income oil-importing countries and low-income oil-exporting countries where both short- and long-run effects are ascertained. In addition to global oil prices, EPU is another channel which explains the dynamics of domestic food prices in developing countries. Therefore, the link between oil prices, EPU and food prices in developing countries is explained by the countries' economic structures, timing/period under consideration and the transmission channels associated with global uncertainties. We proffer some policy suggestions based on the empirical findings. [ABSTRACT FROM AUTHOR]

This research explores economic growth dynamics in five ASEAN countries (1980–2020), analyzing the short and long-term impact of financial development (FD), oil prices, investment (INV), and inflation on GDP growth. Panel ARDL analysis reveals a transient positive link between FD and long-term GDP growth, necessitating a holistic approach for short-term stability. Similarly, oil prices exhibit long-term volatility, urging diversification strategies. In contrast, consistent and significant relationships exist between INV and GDP growth in both time frames, underscoring investment's pivotal role. The study emphasizes managing inflation for sustained growth, offering vital insights for policymakers, economists, and analysts in fostering ASEAN's economic stability. [ABSTRACT FROM AUTHOR]

As one of the leading oil producers in the world, Nigeria's economy is profoundly influenced by fluctuations in global oil prices, affecting the government capacity to allocate resources on national healthcare system and its ability to ensure healthy lives and promote wellbeing for all, as outlined in Sustainable Development Goal 3 (SDG-3). On this backdrop, this study has undertaken a comprehensive examination of both linear and non-linear relationship between oil price shocks and sustainable development in Nigeria, a country heavily reliant on oil revenue from 1970 to 2022 in Nigeria. Using linear Autoregressive Distributed Lag (ARDL) and nonlinear Autoregressive Distributed Lag (NARDL) models, the findings show that increasing crude oil price shock has a substantially large adverse impact on SDG-3 in the short run while decreasing crude oil price has unobserved effect in both short and longrun when asymmetries were considered. Based on the findings of this study, Nigerian policymakers should expedite efforts to diversify its economy away from oil dependency. This diversification should focus on promoting sectors with growth potentials, creating jobs, and generating stable revenues to support healthcare and sustainable development initiatives. The study highlights other actionable insights and policies to navigate the challenges posed by oil price volatility while advancing the noble aspirations of SDG 3 for the people of Nigeria. [ABSTRACT FROM AUTHOR]

Purpose — The research investigation was centered on the potential for herding behavior in the Amman Stock Exchange. The major goal of the current investigation is to identify any herding behavior that may occur, including behavior caused by liquidity and global factor drivers (such as oil prices and Fed fund rates). Method — The study employed the quantitative research method. The sample consists of 50 observations from 171 companies, and the data were collected from monthly records spanning January 2019 to March 2023. The Generalized Method of Moments (GMM) and a deductive approach were utilized in the quantitative methodology of this study. Result — At this stage, employing a CSSD regression analysis makes it possible to observe evidence of herding behavior in the left tail. The study also found no evidence suggesting that stock market liquidity affects herding behavior in the right tail during periods of both high and low liquidity. However, it did find evidence indicating that liquidity affects herding behavior in the left tail. The Amman capital market has demonstrated that herding behavior is not significantly influenced by global factors. Practical implications — This study suggests that the Amman Stock Exchange should make information accessible to all investors to encourage them to take an active role in making their own investment decisions. [ABSTRACT FROM AUTHOR]

Copyright of China Mining Magazine is the property of China Mining Magazine Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Combating climate change and reducing CO2 emissions are essential for achieving the Sustainable Development Goals within a sustainable development framework. Various factors, such as institutional quality, affect environmental quality, and quantifying this linkage can lead to appropriate policy-making aimed at reducing pollution. The present study provides a comprehensive analysis of the impact of institutional quality on CO2 emissions in the Middle East and North Africa (MENA) region at both the aggregate (institutional quality) and disaggregate levels (corruption control, government effectiveness, political stability, violence and terrorism, regulatory quality, rule of law, voice, and accountability). This study analyzes data from 1996 to 2018 using Driscoll-Kraay and Newey-West standard error approaches to assess the impact of various factors on environmental quality. The findings reveal that GDP, non-renewable energy consumption, and trade activities have a significant negative effect on the environment. In contrast, oil prices, renewable energy, and foreign direct investment (FDI) help reduce CO2 emissions in the long run. Institutional quality and its other five indices, except for political stability and the absence of violence/terrorism, are found to contribute to the reduction of CO2 emissions in the region. Furthermore, the Dumitrescu and Hurlin Granger non-causality model reveals bidirectional causal relationships between GDP, renewable and non-renewable energies, trade, FDI, and institutional quality with CO2 emissions. Reducing emissions in the MENA region can be achieved by promoting green economic growth, developing renewable energy and energy efficiency industries, investing in low-carbon infrastructure, and directing FDI toward sustainable projects.

In this paper, the autoregressive distributive lag (ARDL) model is used to examine the impact of global crude oil price on manufacturing output in India and the behaviour of consumer price index. Error correction model, co-integration and multivariate GARCH model models are used for the analysis. ARDL analysis shows a significant relation between consumer price index (CPI) and manufacturing index (MI). Also, a significant inverse relation is established between crude oil price with MI and a positive relation between MI and CPI. Despite an inconsistent short run relation between petrol price with CPI, rising fuel price shows dampening impact on manufacturing output in the long run.

This paper analyzes the relationship between food and oil prices in Nigeria before and during the COVID-19 pandemic, using monthly data from January 2018 to December 2021. The ARDL and NARDL models are applied to estimate the symmetry and asymmetric relationship that exists in food price behavior. The NARDL confirms the presence of asymmetries, and the bound test affirms the co-integration and long-run relationship among the variables. In the long run, there is a significant positive relation between oil price increases and food prices, but the long-run impact of oil price reductions on food prices is not significant. In the short run, only increases in oil prices exert a significant influence on food prices, while decreases in oil prices do not. Furthermore, the COVID-19 period exerts a positive and significant impact on food prices, while COVID-19 cases do not influence food prices in Nigeria.

This paper argues that energy efficiency is a potent shield against oil price uncertainty in an increasingly interconnected world fraught with geopolitical tensions. By reducing dependence on oil, enhancing economic resilience, and improving energy security, energy efficiency measures offer multifaceted benefits for both national economies and global stability. Specifically, a wavelet coherence analysis is conducted to study the response of global energy efficiency to geopolitical oil price uncertainty. Quantile-on-quantile and quantile regressions are additionally employed to separate the impacts of various geopolitical oil price risk quantiles on the quantiles of energy efficiency. These methods are utilized in the examination of global time-series data covering the timeframe 2004:Q1–2020:Q4. The wavelet coherence outcomes indicate a positive correlation between geopolitical oil price uncertainty and energy efficiency, particularly during the energy crisis of the 2000s and the COVID-19 pandemic. The results also reveal that geopolitical oil price uncertainty leads to energy efficiency, indicating that an upsurge in geopolitical oil price uncertainty causes energy efficiency to increase. Moreover, the results from quantile-on-quantile and quantile regressions affirm the predominantly positive effects of geopolitical oil price uncertainty on global energy efficiency. Our conclusion therefore is that through strategic investments, innovative policies, and international collaborations relating to energy efficiency, nations can fortify themselves against the destabilizing effects of geopolitical conflicts on energy markets. This would ensure a more sustainable and secure energy future for all. [ABSTRACT FROM AUTHOR]

We conduct a comparison of three portfolio investment strategies in the US stock market following the implementation of Regulation Fair Disclosure in October 2000. The strategies analyzed are analyst‐recommended, recommendation changes, and momentum portfolios. Across various time periods, company sizes, and industry sectors, the momentum portfolio consistently outperforms the other strategies. Portfolios based on analyst recommendations exhibit poor performance in industries such as consumer staples and materials, which are strongly correlated with oil prices. These industries are susceptible to external demand and supply‐side price shocks that are not adequately captured by analyst recommendations. The findings highlight firstly, the efficacy of the momentum strategy and the limitations of relying solely on analysts' recommendations, particularly in oil‐dependent sectors; and secondly, the varying dynamics and performance of different investment strategies for investors seeking to optimize their investment decisions across different sectors and market conditions. [ABSTRACT FROM AUTHOR]

This study analyzed the heterogeneity and nonlinear effects of financial development, governance, real exchange rate and oil price on tourism in OIC countries. We used annual panel data of 50 Islamic countries from 1996 to 2021 and apply panel quantile regression as well as fixed and random effect technique. The empirical results illustrated that across quantiles, financial development contributed to the tourism performance in all models under review. We also observed that the impact of governance indicators on tourism demand were positive and statistically significant. The estimated asymmetric model affirmed the positive effect with the weak significant power of oil price on tourism at across quantiles (except 10th), while exchange rate was negatively associated with tourism demand. Furthermore, the results of slope equality test indicated that, in many models, the relationship between tourism demand and explanatory variables was clearly heterogeneous. Finally, the asymmetric effects at different quantiles for more coefficients based on the quantile plot were confirmed. [ABSTRACT FROM AUTHOR]

During the twentieth and twenty-first centuries, the oil industry has been pivotal in influencing all countries' geopolitical, economic, and human development strategies. Until recently, the debate was about peak oil and what would happen after oil finished. However, due to technological advances and hydraulic fracturing, shale oil formations have become economically viable due to the United States' desire to achieve energy security to make a qualitative shift in the oil industry and the geopolitics of oil. Therefore, this paper deals with an economic model that illustrates the impact of oil price fluctuations to the shale oil and gas companies by analyzing the main determinants of continuity of shale oil and gas companies in production if global oil prices decline or rise. In addition, the study will investigate the effects of OPEC+ policy and Covid-19 on the future of shale oil industry. The study will discuss some future scenarios for global energy trends and predict what the shale industry will look like in the future. The study concluded the shale industry faces an internal destructive process (within the industry itself) and external (Renewable energy, OPEC and Covid-19). The stability of oil prices is a critical factor that promotes the shale industry's recovery. However, shale industry is expected to continue with low productivity growth rates and continuing government support for it. [ABSTRACT FROM AUTHOR]

This study examines the Bitcoin price by taking into account global factors, including the Chicago Board Options Exchange's Market Volatility Index (VIX), the US dollar index, the gold price, the oil price, and Bitcoin price volatility. The analysis is conducted using the structural vector autoregression (SVAR) model. The variance decomposition findings revealed that the influence of the VIX on the Bitcoin price was initially restricted, but progressively intensified over time. Among the indicators, Bitcoin price volatility had the highest explanatory share in both daily and weekly data analysis. The impulse response functions demonstrated a statistically significant inverse relationship between the VIX and the Bitcoin price. Furthermore, the analysis revealed that the Bitcoin price was mostly impacted by its own volatility. This implies that investing in Bitcoin requires a certain level of risk‐taking. [ABSTRACT FROM AUTHOR]

This study examined factors including oil prices, foreign exchange rates, consumer price index, gross domestic product, and foreign direct investment on stock return. This study used secondary data as a basis for research by obtaining information for 30 companies registered at IDX Value 30. This research uses panel regression to show the effect of each independent variable on stock return. According to the result, IDX Value 30 stock return is significantly positively impacted by gross domestic product, consumer price index, and foreign direct investment. Meanwhile, foreign exchange rates and oil prices negatively affect the stock return. [ABSTRACT FROM AUTHOR]

It has been widely documented that the relationship between crude oil prices and the value of US dollar changes over time (Beckmann et al. in Energy Econ 88:104772, 2020). However, the underlying economic driver for the time-varying relationship is not clear. Based on the competitive storage theory, we provide theoretical evidence that greater inelasticity of market demand for crude oil induced by low inventories is expected to lead to higher responsiveness of crude oil prices to exchange rate changes. We empirically test this hypothesis using the threshold vector autoregressive (TVAR) model and show that crude oil prices respond to shocks to the US dollar exchange rates in an asymmetric manner. Changes in the US dollar exchange rates have greater and more significant influence on crude oil prices in the low-inventory regime than in the high-inventory regime. [ABSTRACT FROM AUTHOR]

ABSTRACT Faced with a significant devaluation of its currency and a surge in food prices, the Nigerian government prohibited the use of foreign currency for food imports. This essentially blocked the importation of numerous food items under the guise of stimulating the domestic output of these staples. Consequently, food prices in Nigeria increased despite a global decline in food prices, and the incidence and severity of food insecurity escalated. This study examines the changes in the types and severity of coping mechanisms for food insecurity resulting from the food price shock caused by the oil price crash, currency devaluation, and restrictions on foreign exchange. Nigeria's General Household Survey Panel data from 2012 and 2015, during periods of high oil prices, is compared with data from 2018 when oil prices had remained low, the currency had been devalued, and the treasury had been depleted. Alongside detailed descriptive statistics, logistic and hurdle regressions are employed for statistical analysis. Findings indicate a rise in the percentage of Nigerian households grappling with food insecurity from 2015 to 2018. During this period, 68.7% of households resorted to at least one coping mechanism, 31.8% adopted six or more coping strategies, and 43.2% resorted to severe coping strategies. The issue stems not primarily from natural disasters or conflicts but from a failure in macroeconomic and agricultural economic policies. Our findings confirm that these policies come at great cost, particularly to female‐headed households, single‐parent households, households headed by elderly people, and other vulnerable populations, pushing them deeper into food insecurity.

Purpose – This study intends to scrutinize the relationship between oil and gold prices on Indonesia’s Islamic stock market before and during the war between Russia and Ukraine, and compare the nature of sharia and conventional stock during the period of study. Methodology – This study uses daily price data of oil price, gold, Islamic index, and LQ45 index. The period spans from 2020 to 2022, which is split into two sub-periods: pre-war and during the war period. Structural vector autoregression (SVAR) was used for data analysis. Findings – This study provided three main findings. First, the Islamic index was found to be more exogenous than conventional stock, implying the safe haven properties of Islamic stock. Second, oil prices have a negative and significant impact on both conventional and Islamic stocks. However, Islamic stocks are less affected by oil price shocks than conventional stocks. Lastly, Gold is a safe haven asset for both Islamic and conventional stocks. Implications – This study is expected to be beneficial for Islamic investors making investment decisions, particularly in the war period, which is still ongoing and more specific for taking advantage of diversification opportunities. Originality – Despite a huge number of studies that investigate the Islamic stock – oil price nexus, this study uncovers the impact of the most recent geopolitical tension during the Russia-Ukraine War.

This paper uses the system dynamics approach to model the changes in oil price prospects in the framework of the shared socio-economic pathways (SSP) climate scenarios proposed by the Intergovernmental Panel on Climate Change (IPCC) until 2100. This theoretical structure connects the primary feedback mechanisms: supply, demand, and price. The determining factors of most tremendous significance in the supply sector are the Organisation of Petroleum Exporting Countries (OPEC) and non-OPEC production levels. The production targets set by OPEC are indicative of its market management policies and are significantly influenced by the actions of its key members. The oil price indicates a cyclical relationship with the oil supply of significant players. The determination of global oil demand in the demand section is based on various climate scenarios presented in the IPCC report. The fluctuation of Brent oil prices over time can be linked to the disparity between supply and demand. According to the model outcomes, the price of oil will be projected to decline to $20 per barrel by the year 2100 if the sustainability policies outlined in the SSP1 framework are implemented. However, in the alternative scenarios of SSP3, characterized by regional competition, and SSP4, characterized by heightened inequality and competition, oil prices are anticipated to rise to $100 per barrel. In the context of the SSP5 scenario, which posits a path of economic and social development reliant on the consumption of fossil fuels, the price of oil displays a declining pattern after a period of relatively higher prices. The peak oil prices within the Intergovernmental Panel on Climate Change (IPCC) scenarios exhibit significant variation based on their Representative Concentration Pathways (RCPs).

Abstract The yield on the 10-year U.S. Treasury Note is among the most cited interest rates by investors, policymakers, and financial institutions. We show that the 10-year Treasury yield’s forward-looking volatility, a VIX-style measure that is a proxy for uncertainty about future interest rates, is a useful state variable capable of predicting the returns and volatility of crude oil prices over the near term. Using monthly data from 2003 to 2020, we document that higher implied volatility in the 10-year U.S. Treasury derivatives market predicts declining oil prices and higher forward-looking volatility in those prices. Our results are robust to different subsamples and various empirical designs.

This editorial discusses the dynamics and prospects of the energy market and energy transition. It emphasizes the global shift towards renewable energy due to government initiatives and technological advancements. However, challenges to the transition process exist, such as the impact of the COVID-19 pandemic on global energy demand and fossil fuel prices. The editorial highlights the varying dynamics of the energy market and transition process at the national and firm levels. The collection of research papers covers topics such as renewable energy subsidies in China, efficiency of hydropower electricity generation, and the impact of oil prices on consumer and producer prices. It also explores behavioral economics and the role of natural gas in achieving urban ecological civilization. The editorial acknowledges the contributions of the authors, reviewers, and journal editors in making this collection possible. [Extracted from the article]