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Copyright of Gazi Journal of Economics & Business is the property of Gazi Journal of Economics & Business 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 study examines the co-movement between geopolitical risk (GPR), energy price, and bitcoin (BTC) in BRICS countries, namely Brazil, Russia, India, China, and South Africa. Previous studies have focused on the impact of GPR on the volatility and risk premium of BTC investment. However, very limited studies have focused on integrating BTC as an extension of the mix of GPR on the co-movement with energy price. The analysis is based on monthly data of GPR index for BRICS countries, brent oil futures, natural gas futures and BTCs covering the period between March 2012 and Jun 2021. We employ the Bayesian graphical structural vector autoregressive model and time-varying parameter vector autoregressions-based dynamic connectedness to investigate the network-dependence structure. This research project provides useful empirical evidence for assessing the impact of both BTC and GPR on energy prices. Nonetheless, it will also be informative about the likelihood of co-movements occurring at different stages. [ABSTRACT FROM AUTHOR]

We use cointegration-based techniques to investigate the relationship between oil prices and the euro effective exchange rate taking also into account the influence of interest rates and stock prices. We find that higher oil prices cause a depreciation in the euro exchange rate (either nominal or real) in the short run. This suggests that during episodes of higher energy prices, the euro area consumer is faced with additional price pressures, as a depreciated euro causes import prices to further rise. Our study also indicates that as stock prices rise in the short and long term, the euro appreciates, while higher oil prices will likely result in overall higher policy rates and lower stock prices. [ABSTRACT FROM AUTHOR]

Carbon dioxide emissions from the transport sector make a significant contribution to global greenhouse gases, and understanding the factors that influence these emissions is beneficial for devising effective emission reduction policies. Oil prices are an important influencing factor since the fuel used in the transport sector is primarily based on oil, and fluctuations in oil prices directly impact the sector's CO2 emissions. Additionally, environmental policies, as a key means of controlling CO2 emissions, can affect the relationship between oil prices and CO2 emissions in the transport sector. Therefore, this study aims to examine the impact of oil prices on CO2 emissions in the transport sector and explore the nonlinear role of environmental policy stringency in this relationship. Based on data from 27 OECD member countries and 6 non-member countries from 1990 to 2019, we used the environmental policy stringency index as a threshold variable to construct a panel threshold regression model. The analysis results indicate a double-threshold effect: when the environmental policy stringency index is low, the impact of oil prices on CO2 emissions in the transport sector is not significant. However, when the index reaches the first threshold, the impact of oil prices significantly increases; upon reaching the second threshold, the effect is further intensified. This paper also analyzes the three subindicators—market-based policies, non-market-based policies, and technology support policies—to clarify the distinct impact mechanisms of different types of environmental policies. Finally, based on the research findings, we propose policy recommendations to achieve carbon dioxide emission reduction targets in the transport sector. [ABSTRACT FROM AUTHOR]

This study aims to investigate the factors influencing inflation in Turkey between 2006:1-2023:11, taking into account the structural changes that occurred during periods of significant economic, political and geopolitical turmoils. For this purpose, we employ the Hacker and Hatemi-J (2006) bootstrap causality test along with the Fourier Toda-Yamamoto bootstrap causality to capture structural changes. Our findings indicate that when structural changes are taken into account, the drivers of inflation are monetary factors such as the money supply and exchange rate. Furthermore, an exogenous factor such as the oil prices is not a determinant of inflation, suggesting that inflation is a domestic factor. Given these findings, the study emphasizes the importance of strong and stable monetary policies in Turkey to control inflation and achieve price stability. [ABSTRACT FROM AUTHOR]

Summary: We provide new evidence that the transmission of oil price shocks to the US economy has changed with the shale oil boom. To show this, we develop a time‐varying parameter factor‐augmented vector autoregressive (FAVAR) model with a large data environment of state‐level, industry, and aggregate US data. The model effectively captures potential spillovers between oil and non‐oil industries, as well as variation over time. Specified in this way, we find that investment, income, industrial production, and (non‐oil) employment in most oil‐producing and some manufacturing‐intensive US states increase following an oil‐specific shock—effects that were not present before the shale oil boom. [ABSTRACT FROM AUTHOR]

This study explores the effect of green bonds, oil prices, and the coronavirus disease 2019 (COVID-19) pandemic on industrial carbon dioxide (CO2) emissions. In this context, this study examines the United States of America (USA), which is the biggest economy in the world, uses weekly data between March 6, 2020 and September 30, 2022, and applies a novel wavelet local multiple correlation (WLMC) approach under time-varying and frequency-varying perspective. The novel empirical findings shows that (i) there is a strong negative (positive) co-movement between industrial CO2 emissions and green bonds in the short-run (long-run); (ii) there is a strong positive (negative) co-movement between industrial CO2 emissions and oil price in the medium-run (long-run); (iii) there is a strong negative (positive) co-movement between industrial CO2 emissions and the COVID-19 pandemic in the medium-run (long-run); (iv) the oil price is the dominant factor, whereas there are changing effect of the variables on each other at different times and frequencies; and (vi) overall, there are long-run asymmetric and dynamic correlations between industrial CO2 emissions and variables. Hence, the empirical results highlight the asymmetric, time-varying, and frequency-varying effects of green bonds, oil prices, and the COVID-19 pandemic on industrial CO2 emissions by presenting fresh and novel evidence. Moreover, the study proposes policy implications for the USA government. [ABSTRACT FROM AUTHOR]

This study aims to document the impact of oil price variations on generating stock returns in Gulf Cooperation Council (GCC) markets during the COVID-19 era. It documents the pandemic era results from January 2020 to October 2022 by employing cointegration, Granger causality, and time-varying coefficient-vector autoregression techniques on daily data. The findings suggest two-way causality between all stock indices and the oil market. Time-dependent relationships were observed during the review period. The findings (based on regression and variance decomposition) indicate that although the reliance of the GCC stock markets was not on oil alone, oil had a significant impact during the study period. It is recommended that investors not consider diversifying portfolios in GCC stocks and oil markets to optimize benefits. The findings are expected to enhance the understanding of academics, market players, regulators, and investors regarding relationships among GCC stocks and oil markets. This study contributes to the literature by documenting the impact of the oil market on stocks during an abnormal period of the COVID-19 pandemic, considering time-varying parameters in a net oil exporting region. [ABSTRACT FROM AUTHOR]

This paper delves into the critical determinants of renewable energy consumption, focusing on the contrasting roles of oil imports and exports. It aims to bridge the knowledge gap by comparing these determinants across both oil-importing and oil-exporting nations, offering a comprehensive and nuanced perspective to inform policy recommendations. Using annual data from 1990 to 2018 sourced from the World Bank database, the study employs panel multiple regression analysis and adopts a fixed effects model to explore two main questions: What drives the use of renewable energy sources? How does a country's oil importer or exporter status affect these factors? The findings reveal a significant but inverse relationship between oil rents and renewable energy consumption (REC) for both types of countries. Additionally, there is a notable negative correlation between GDP growth and REC for both oil-exporting and oil-importing countries. Interestingly, the crude oil average closing price and inflation show an insignificant impact on REC in both contexts. The study also highlights that net energy imports significantly affect REC, with a much stronger inverse relationship in oil-importing countries compared with oil-exporting ones. For oil-importing countries, diversifying energy sources is a crucial investment. Governments should prioritize research and development in renewable energy to spur technological advancements, enhancing efficiency and affordability. Economic growth-promoting policies, such as tax incentives and subsidies for renewable energy businesses, are vital for encouraging sustainable practices. Consistent, long-term policies are essential for providing investor confidence and supporting the transition to renewable energy. For oil-exporting countries, similar strategies are recommended. Additionally, allocating a portion of oil revenues to renewable energy infrastructure and funding research and development in renewable technologies through local universities and startups are crucial steps. This dual approach will not only enhance energy diversification but also foster innovation and sustainability in the energy sector. [ABSTRACT FROM AUTHOR]

This study investigates the return and volatility spillovers between BRICS bonds and oil price volatility in the pre-COVID and during COVID periods by employing the bivariate EGARCH model, cross-quantilogram approach, and wavelet coherence framework. The findings are mixed when comparing the volatility transmissions with various nations and in two periods since variations in return and volatility spillovers between oil prices and bond market returns have co-moved through time. In particular, they increased during the COVID-19 outbreak, which supports the idea that financial market integration intensified during the crisis. Additionally, oil prices have a positive impact on bond markets in Russia and South Africa in both periods, while there are weak and negative relationships in China, India, and Brazil in pre-COVID and pandemic periods. This information has consequences for risk management and portfolio decisions for investors with a substantial position in the BRICS bonds market. [ABSTRACT FROM AUTHOR]

This study investigates the complex relationship between oil price fluctuations and economic growth in Algeria, using time series data from 1973 to 2023. Advanced econometric techniques, including Vector Autoregression (VAR), Impulse Response Functions (IRFs), Variance Decomposition (VD), and the Toda-Yamamoto causality test, were employed to examine both the direct and indirect effects of oil price changes on the country’s growth. The results of the VAR model indicate a strong positive relationship between oil prices and economic growth, emphasizing the critical role of hydrocarbon exports in driving Algeria’s economy. However, this connection is influenced by other macroeconomic factors, such as inflation, exchange rates, and money supply. IRF analysis shows that while oil price increases initially stimulate growth, long-term impacts are moderated by adjustments in monetary policy and exchange rates. The variance decomposition analysis further highlights that oil price volatility significantly influences short-term economic performance, but its effect diminishes over time, suggesting progress in economic diversification, policy adaptation, and the effectiveness of managing oil-related volatility. The Toda-Yamamoto causality test provides additional insights, confirming unidirectional causality from oil prices to growth and highlighting indirect effects through exchange rates and money supply. These findings underscore the importance of continued diversification efforts in oil-dependent economies like Algeria, as well as the need for adaptive monetary and exchange rate policies to ensure both short-term stability and long-term growth. This study contributes to the broader literature on oil price-growth dynamics and offers valuable guidance for policymakers in resource-rich countries.

This study examines the effect of oil price fluctuations on economic growth in Algeria from 1973 to 2023. Using the Autoregressive Distributed Lag (ARDL) model and the Zivot-Andrews (ZA) structural break test for unit roots, the results confirm a long-run relationship between the variables. A 1% increase in oil prices is associated with a significant 1.05% rise in economic growth. However, the model also reveals a delayed negative impact from lagged oil price changes, indicating that price volatility can lead to economic instability. These findings underscore the critical importance of oil price stability for sustainable economic development in Algeria.

The growing interstate rivalry sweeps more and more areas of international relations, including energy issues. While the ‘traditional’ oil and gas exporters are trying to maintain or even strengthen their current positions, new players in the oil and gas market are trying to challenge the status quo. The changing situation on the oil market due to the ‘price war’ between the United States and OPEC countries serves as a clear manifestation of this trend and encourages the OPEC members to coordinate their policies more closely with external partners. This paper aims to identify the prerequisites and assess the dynamics of cooperation between Russia and the Kingdom of Saudi Arabia (KSA) within the OPEC+ framework. The first section of the paper examines the logic behind the OPEC+ agreement in the context of the development of energy cooperation between the Russian Federation and the KSA before the outbreak of the Ukrainian crisis. The authors note that the new format demonstrated stability within the first years of its existence and generated closer cooperation between the hydrocarbon exporting countries. The second section examines the development of OPEC+ in the face of increased geopolitical pressure from the United States and its allies. The authors conclude that the efforts of Washington and oil importing countries to undermine energy cooperation within the OPEC+ format have not succeeded, on the contrary the international stance of the group members has only strengthened. In conclusion, the authors emphasize that OPEC+ not only contributes to the stability of energy prices, but also brings tangible political benefits to its members. At the same time, according to the authors, the future of this format largely depends on the dynamics of international environment and, particularly, on the scale of the US-Russian confrontation.

Analogous to an experienced mariner choosing a safe harbour depending on the wind direction, we hypothesize safe-haven asset(s) are conditional on the cause of the market fall. Using oil markets as a salient case study, we find that traditional safe-haven assets, such as the US dollar and government bonds, act as safe havens only when oil prices fall due to declines in actual or expected demand. On the other hand, stock markets provide safe-haven protection when oil prices fall due to increases in oil supply. Therefore, our results suggest that papers that seek to identify safe-haven assets in response to declines in a given asset's return need to test for the possibility that the identified assets might not be safe-haven assets in all circumstances. [ABSTRACT FROM AUTHOR]

Abstract Recent theoretical developments in economics distinguish between risk and ambiguity (Knightian uncertainty). Using state-of-the-art methods with intraday stock market data from February 1993 to February 2021, we derive financial ambiguity and empirically examine the effect of shocks to it on the price and volatility of crude oil. We provide evidence that ambiguity carries important information about future oil returns and volatility perceived by investors. We validate these results using Granger causality and in-sample and out-of-sample forecasting tests. Our findings reveal that financial ambiguity is a possible factor that explains future drops in oil prices and their increased variability. Our findings will benefit scholars and investors interested in how financial ambiguity shapes short-term oil prices.

Abstract In 2020, the world experienced several significant events, including the coronavirus (COVID-19) pandemic and the collapse of international crude oil prices. The rapid spread of this pandemic has dramatic impacts on financial markets all over the world, thereby increasing market risk aversion in an unprecedented way since the subprime financial crisis. The decline in stock markets implied volatilities of equity and oil prices, thereby heightening turmoil in global financial markets despite comprehensive and substantial financial reforms. To this end, we investigated the likely effects of this pandemic on the Saudi stock market while controlling for oil prices based on daily data for a period from 1/1/2020 to 19/9/2022. To ascertain the existence of a long-run equilibrium relationship between the variables, we applied autoregressive distributed lag (ARDL) modeling and the error correction model, with this ultimately revealing the existence of strong cointegration in the long run. The ARDL bounds test was found to be robust by combined cointegration tests, thus providing further evidence of a strong relationship in the long run. Granger causality tests also yielded evidence of causality between the variables in both directions. The total COVID-19 confirmed cases and oil prices also caused movements in stock returns in the short run. Our findings have some prominent implications for asset managers and policymakers to improve stock market efficiency and boost global economic activity. Saudi authorities can consequently remove the regulatory and legal obstacles to develop their stock market and better improve the risk management, which will allow to make quick decisions in response to any oil price volatilities. Policymakers should also adopt proactive strategies that can comfort stock investors’ anxieties over the increasing oil price volatilities. Finally, the findings should be treated with some cautions because of the limited sample size and the tests’ statistical inference. Nevertheless, they do open opportunities for further studies to look in more detail at how the COVID-19 pandemic affected, over the short and long run, monetary and fiscal policy coordination, financial stability, and various other macroeconomic indicators in Saudi Arabia.

Recent theoretical developments in economics distinguish between risk and ambiguity (Knightian uncertainty). Using state-of-the-art methods with intraday stock market data from February 1993 to February 2021, we derive financial ambiguity and empirically examine the effect of shocks to it on the price and volatility of crude oil. We provide evidence that ambiguity carries important information about future oil returns and volatility perceived by investors. We validate these results using Granger causality and in-sample and out-of-sample forecasting tests. Our findings reveal that financial ambiguity is a possible factor that explains future drops in oil prices and their increased variability. Our findings will benefit scholars and investors interested in how financial ambiguity shapes short-term oil prices. [ABSTRACT FROM AUTHOR]

The relationship between oil prices and clean energy indices is of great importance for investors and financial market participants when considered as a financial investment tool. As the world grapples with environmental challenges and seeks sustainable solutions, understanding the impact of oil prices on the clean energy sector plays a critical role in strategic decision-making processes. Fluctuations in oil prices can directly impact the financial performance of the clean energy sector by affecting the returns and costs of clean energy investments. Investors need insights into the potential asymmetric effects of oil prices on sustainability and clean energy indices; this can shape their portfolio allocations and risk management strategies. As global sustainability concerns and shifts towards clean energy continue to evolve, the complex relationship between traditional energy markets and the expanding clean energy sector remains a subject of study in the literature. The decreasing reliance on conventional energy sources and the accelerated transition to renewable energy sources create significant implications for financial markets. In this transformative process, it is crucial for investors to analyze the short- and long-term impacts of changes in oil prices on the clean energy sector. Understanding the complex relationship between traditional energy markets and the expanding clean energy sector can help investors anticipate future trends and develop sustainable investment strategies. Moreover, understanding the asymmetric effects of oil prices on clean energy investments plays a vital role in achieving global sustainability goals and addressing environmental challenges. In this context, an in-depth analysis of these dynamics will provide valuable insights not only for academic research but also for policymakers and investors. In this article, we examine the complex relationship between oil prices, sustainability, and clean energy indices using a comprehensive dataset spanning from 2014 to 2023. The focus of the analysis is on the West Texas Intermediate (WTI) crude oil futures prices, the Dow Jones Sustainability World Index (DJSWI), and the S&P Global Clean Energy Index (SPGCE). These variables represent critical aspects of the financial system by reflecting the dynamics between traditional energy sources, sustainability initiatives, and the emerging clean energy sector. In this context, the study employs the Nonlinear Autoregressive Distributed Lag (NARDL) method to explore the asymmetric effects of West Texas Intermediate (WTI) prices on the S&P Global Clean Energy Index (SPGCE) and the Dow Jones Sustainability World Index (DJSWI). The NARDL method is advantageous due to its applicability to variables with different levels of stationarity and its effectiveness in handling small sample sizes. The study also incorporates the Dynamic Conditional Correlation (DCC) model to assess the time-varying relationships between the variables. In this context, the study differs from existing literature by examining the asymmetric effects of oil prices on sustainability and clean energy indices using both the NARDL and DCC methods. According to the results from the NARDL model, it was found that positive shocks in WTI prices have a more significant effect on the S&P Global Clean Energy Index (SPGCE) compared to negative shocks. According to the Dynamic Multiplier test, positive and negative shocks to the WTI variable have a weak negative effect on SPGCE from the third to the fifth period, gradually approaching equilibrium thereafter. The results obtained from the DCC model indicate a positive and strong relationship between WTI prices and the S&P Global Clean Energy Index (SPGCE). The positive relationships between WTI prices and clean energy indices, especially during periods of positive shocks in oil prices, suggest potential opportunities for returns. However, awareness of the highlighted dynamic relationships is crucial, and investors should employ diversification strategies to mitigate risks associated with fluctuations in oil prices. Considering the results obtained from the DCC model, investors should actively monitor market dynamics and adjust their investment strategies accordingly. During significant event periods identified in the study, such as the "COVID Era," correlations between assets can change rapidly. Being mindful of these changes can assist investors in making timely and informed decisions. Moreover, given the positive relationship between sustainability indices and oil prices, portfolio managers may consider increasing allocations to sustainable investments. Integrating companies with strong sustainability practices can enhance portfolio resilience and align with global environmental-conscious initiatives. [ABSTRACT FROM AUTHOR]

We investigated the relationship between supply chain disruptions (SCD) and the financial performance (FP) of European automotive companies across emerging and developed nations. Addressing gaps in the literature, it offers a comprehensive, industry-specific analysis using panel data from 73 automotive firms across 21 European countries from 2013 to 2022. We examined the impact of SCD on return on assets (ROA), return on equity (ROE), and stock returns (SR), while controlling for factors such as age, leverage, size, economic growth, inflation, and unemployment. Our findings revealed that disruptions related to industrial materials and iron prices (IRAW) positively influence stock market performance, with a 99.5% increase in SR per 1% rise in IRAW, suggesting increased demand. Conversely, precious metal prices negatively affected all financial metrics, reducing ROE by 17.3% and SR by 55.5% per 1% increase. Heightened shipping costs showed varied impacts on ROA and ROE but contributed to a 12.9% average increase in SR, indicating effective cost transfer to consumers. The pandemic years significantly decreased ROA, ROE, and SR, highlighting challenges faced by the automotive sector. Rising oil prices showed no significant association, underscoring the importance of hedging strategies. The control variable outcomes emphasize the need for detailed evaluation in assessing financial performance. This study's contribution lies in its detailed analysis of specific disruptions within the automotive industry and their distinct impacts on financial performance metrics, providing a nuanced understanding that addresses significant gaps in the existing literature. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of global geopolitical risks and global supply chain pressures on global inflation for the monthly period of 1999M1–2022M12. The investigation is based on a structural vector autoregression model, where the effects of global oil prices and global monetary policy are controlled for. Four alternative measures of inflation are used, including headline, core, food, and energy inflation. The empirical results show that disruptions in global supply chains are the main drivers of global inflation in the long run as the corresponding shocks explain the lion's share of volatilities in headline inflation (by 32%), core inflation (by 30%), and food inflation (by 22%), followed by oil price shocks and policy rate shocks. In comparison, energy inflation is explained the most by oil price shocks (by 55%) followed by supply chain shocks and policy rate shocks. Positive supply chain pressure and oil price shocks have positive and statistically significant effects on headline inflation even after five years, whereas positive policy rate shocks have negative and statistically significant effects on headline inflation in the long run. In contrast, positive shocks to geopolitical risk result in higher headline inflation only up to one year, with insignificant effects in the long run. Several policy implications follow. [ABSTRACT FROM AUTHOR]

This paper examines the volatility risk in the KSA stock market (Tadawul), with a specific focus on predicting volatility using the logarithm of the standard deviation of stock market prices (LSCP) as the output variable. To enhance volatility prediction, it proposes the combined use of the dynamic evolving neural fuzzy inference system (DENFIS) and the nonlinear spectral model, maximum overlapping discrete wavelet transform (MODWT). This study utilizes a dataset comprising 4609 observations and investigates the inputs of lag 1 of the close stock price (LCP), the natural logarithm of oil price (Loil), the natural logarithm of cost of living (LCL), and the interbank rate (IB), determined through autocorrelation (AC), partial autocorrelation (PAC), correlation, and Granger causality tests. Regression analysis reveals significant effects of variables on LSCP: LCP has a negative effect, and Loil has a positive effect in the ordinary least square (OLS) model, while LCL and IB have positive effects in the fixed effect model and negative effects in the random effect model. The MODWT-Haar-DENFIS model was developed as we found that the model has the potential to be an effective model for stock market forecasting. The results provide valuable insights for investors and policymakers, aiding in risk management, investment decisions, and the development of measures to mitigate stock market volatility. [ABSTRACT FROM AUTHOR]

This article estimates the pass‐through of different shocks into different U.S. prices that are important for policy makers. The investigation is based on a structural vector autoregression model, where quarterly data are used. The empirical results depict oil price pass‐through, exchange rate pass‐through, import‐price pass‐through, and producer price pass‐through into import prices, producer prices, and consumer prices for the U.S. economy. Policy implications suggest that achieving and sustaining consumer price stability highly depend on monitoring the developments in oil prices, followed by import prices and producer prices. [ABSTRACT FROM AUTHOR]

This study aims to analyze the oil demand of 49 countries which are net energy importers in the 1990-2016 period within the framework of panel data model. Countries are considered in two panels as high and low energy importing countries according to how much energy they import of their consumption. Income and price elasticities of oil demand for 26 high energy importing countries (Panel A) and 23 low energy importing countries (Panel B) were calculated. The results show that income elasticity of oil demand is positive and significant for both panels, and price elasticity is negative and significant again for both panels. In addition, price elasticity was lower than income elasticity for both panels. Another finding is that high energy importing country panel (Panel A) has lower price elasticity (-0.03) than low energy importing country panel (Panel B), (-0.41). Similarly, the income elasticity of the high-energy importing country panel (Panel A) (1.18) was calculated to be high than that of the low-energy importing country panel (Panel B), (1.04). Based on these results, some important policy implications have been proposed. [ABSTRACT FROM AUTHOR]

This paper aims to assess the effects of oil price shocks on the stock markets of the G7 countries. We develop an oil sentiment indicator that measures the volatility of oil prices. We analyze oil shocks on the stock market of the G7 countries, using a structural VAR and Local Projection approach. Our results suggest that oil shocks explain 8% of the US stock market, 10% in Germany, and 7% in the UK. These results point out the possibility of using this sentiment variable for forecasting the stock market's volatility. [ABSTRACT FROM AUTHOR]

Copyright of Uluslararasi Ekonomi ve Yenilik Dergisi is the property of Karadeniz Technical University, Depertmant of Economics 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 study investigates the complex relationship between oil price fluctuations and economic growth in Algeria, using time series data from 1973 to 2023. Advanced econometric techniques, including Vector Autoregression (VAR), Impulse Response Functions (IRFs), Variance Decomposition (VD), and the Toda-Yamamoto causality test, were employed to examine both the direct and indirect effects of oil price changes on the country's growth. The results of the VAR model indicate a strong positive relationship between oil prices and economic growth, emphasizing the critical role of hydrocarbon exports in driving Algeria's economy. However, this connection is influenced by other macroeconomic factors, such as inflation, exchange rates, and money supply. IRF analysis shows that while oil price increases initially stimulate growth, long-term impacts are moderated by adjustments in monetary policy and exchange rates. The variance decomposition analysis further highlights that oil price volatility significantly influences short-term economic performance, but its effect diminishes over time, suggesting progress in economic diversification, policy adaptation, and the effectiveness of managing oil-related volatility. The Toda-Yamamoto causality test provides additional insights, confirming unidirectional causality from oil prices to growth and highlighting indirect effects through exchange rates and money supply. These findings underscore the importance of continued diversification efforts in oil-dependent economies like Algeria, as well as the need for adaptive monetary and exchange rate policies to ensure both short-term stability and long-term growth. This study contributes to the broader literature on oil price-growth dynamics and offers valuable guidance for policymakers in resource-rich countries. [ABSTRACT FROM AUTHOR]

In this paper, we investigate house price shocks on the macroeconomic variables (financial market, inflation, and real sector) of the G7 economies. We use the GVAR to capture the spillover effects from the U.S. housing market and oil prices on these economies from 1991M3–2022M10. We identify the U.S. house price shock using the Structural Generalized Impulse Response Function, house supply and demand variables, and regional divergence. We find that the domestic stock markets and industrial production are the most sensitive to house price shocks. We further compare the importance of house and oil prices on domestic fluctuations. The estimates reinforce the previous findings: U.S. house prices are responsible for a quarter of the domestic volatility of the stock markets and industrial production. In the other macroeconomic segments, the effects of house prices are present, but in lower values. Our results show that house prices provoke more domestic fluctuations than oil prices. Finally, we also found that short and long‐term credit markets, as well as stock markets, transmit the house price shock to industrial production. Consequently, we provide potential channels to comprehend the spillover effect of U.S. house prices on international markets. [ABSTRACT FROM AUTHOR]

This article investigates the effect of global oil and wheat prices, and local price shocks on the real price of wheat flour in Lebanon. We estimate a structural vector autoregressive model with exogenous variables (SVARX) using Bayesian methods. We then compute the impulse response functions and find that global commodity price shocks play a trivial role. Meanwhile, local gasoline price and wheat flour price‐specific shocks trigger large increases in the Lebanese wheat flour price on impact. Furthermore, since 2020, local gasoline price and wheat flour price‐specific shocks have contributed the most to the historical variation in the Lebanese wheat flour price. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Economic Administrative & Legal Sciences is the property of Arab Journal of Sciences & Research Publishing (AJSRP) 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 study examines the causality relationship between oil price movements and geopolitical risks for a group of 18 geopolitically sensitive countries, using monthly data by implementing all quantiles distributions. Contrary to earlier studies, which have applied the Granger‐causality through the conditional mean regression, this research estimates the association between the variables through Granger causality within quantiles. Evidence of a two‐way causality is found linking the changes in geopolitical risk and fluctuations in oil prices in the case of Thailand, Argentina, Israel, China, Mexico India, Korea, Indonesia, South Africa, Turkey, Philippines, Venezuela, Ukraine, and others. In addition, it is confirmed that oil prices Granger cause geopolitical risks for the countries like Brazil, Malaysia, and Colombia. Furthermore, a one‐way causality direction is found from changes in geopolitical risk to shifts in oil prices in Russia and Saudi Arabia, which are observed as super oil rich states. This study findings highlight the importance of government policies and business strategies that aim at containing the effects of geopolitical risk and the resulting oil price movements. [ABSTRACT FROM AUTHOR]

In 2020, the world experienced several significant events, including the coronavirus (COVID-19) pandemic and the collapse of international crude oil prices. The rapid spread of this pandemic has dramatic impacts on financial markets all over the world, thereby increasing market risk aversion in an unprecedented way since the subprime financial crisis. The decline in stock markets implied volatilities of equity and oil prices, thereby heightening turmoil in global financial markets despite comprehensive and substantial financial reforms. To this end, we investigated the likely effects of this pandemic on the Saudi stock market while controlling for oil prices based on daily data for a period from 1/1/2020 to 19/9/2022. To ascertain the existence of a long-run equilibrium relationship between the variables, we applied autoregressive distributed lag (ARDL) modeling and the error correction model, with this ultimately revealing the existence of strong cointegration in the long run. The ARDL bounds test was found to be robust by combined cointegration tests, thus providing further evidence of a strong relationship in the long run. Granger causality tests also yielded evidence of causality between the variables in both directions. The total COVID-19 confirmed cases and oil prices also caused movements in stock returns in the short run. Our findings have some prominent implications for asset managers and policymakers to improve stock market efficiency and boost global economic activity. Saudi authorities can consequently remove the regulatory and legal obstacles to develop their stock market and better improve the risk management, which will allow to make quick decisions in response to any oil price volatilities. Policymakers should also adopt proactive strategies that can comfort stock investors' anxieties over the increasing oil price volatilities. Finally, the findings should be treated with some cautions because of the limited sample size and the tests' statistical inference. Nevertheless, they do open opportunities for further studies to look in more detail at how the COVID-19 pandemic affected, over the short and long run, monetary and fiscal policy coordination, financial stability, and various other macroeconomic indicators in Saudi Arabia. [ABSTRACT FROM AUTHOR]

Copyright of Kastamonu University Journal of Economics & Administrative Sciences Faculty / Kastamonu Üniversitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi is the property of Kastamonu University 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.)

Exploring the nexus between oil prices and remittances is critical to both remitting and recipient countries. Employing non-linear panel autoregressive distributed lag (NARDL) approach, we examine the relationship for 32 sub-Sahara African countries over the period 1986-2019. The results reveal that: (1) changes in oil prices and remittance inflows are asymmetrically associated only in the short run for the entire sample; (2) when the sample is divided into middle and low-income subgroups, asymmetric effect is confirmed for former subgroup only in the long run, while it is confirmed for latter subgroup only in the short run, (3) in the long run, positive movement in oil prices reduces remittances for the sample and in the middle income subgroup, whereas it increases remittances in the low-income subgroup, (4) Negative oil price movement reduces remittances for the entire sample and the two subgroups; (5) in the short run, a reduction in oil prices increases remittance inflows only for the entire sample and for the low-income subgroup. These results suggest that policymakers in SSA should implement policies that will reduce oil price risks on remittance inflows especially in the long run. [ABSTRACT FROM AUTHOR]

Summary: Predicting carbon and oil prices is recently gaining relevance in the climate change literature. This is due to the fact that conventional energy market analysis and the design of mechanisms for climate change mitigation constitute key variables for artificial carbon markets. Yet, modelling non‐linear effects in time series remains a major challenge for carbon and oil price forecasting. Hence, hybrid models seem to be appealing alternatives for this purpose. This study evaluates the performance of 12 hybrid models, which weigh results from random forest, support vector machine, autoregressive integrated moving average and the non‐linear autoregressive neural network models. The weights are determined by (i) assuming equal weights, (ii) using a neural network to optimise individual weights and (iii) employing deep learning techniques. The findings of our work confirm the salient characteristics of modelling the non‐linear effects of time series and the potential of hybrid models based on neural networks and deep learning in predicting carbon and oil price returns. Furthermore, the best results are obtained from hybrid models that combine machine learning and traditional econometric techniques as inputs, which capture the linear and non‐linear effects of time series. [ABSTRACT FROM AUTHOR]

The oil price is a dominant factor to affect the economic growth. This study analyzes the influence of oil prices on economic growth of member countries of South Asian Association for Regional Cooperation (SAARC). The dynamic effects of such oil prices are estimated by the mean of Pooled Mean Group Autoregressive Distributed Lag Model (ARDL) and Panel Fully Modified Least Square (FMOLS). The time series data are used for the period of 1995 to 2023. The results concluded oil prices to significantly affect economic growth and in negative. However, fuel imports are found to favor the economic growth. Likewise, labor force and Gross Fixed Capital (GCF) formation have significant and positive effect on economic growth. The findings on ARDL and FMOLS are similar. Noticeable, in case of short run, oil prices effect on economic growth is insignificant. It shows that effect of oil prices on economic growth is recordable in long run. The study concludes oil prices to have significant role towards economic growth. However, negative affectation of oil prices cannot be taken in a way that SAARC member better start losing their dependency on oil but to explore substitute energy sources. [ABSTRACT FROM AUTHOR]

We assess the impact of changes in oil prices on building permit applications in the top oil-producing counties, using monthly data between 2004 and 2021. In the long-run, a positive shock in oil prices increases the number of home permit applications in Lea and McKenzie Counties. Long-run point estimates also reveal that a 10 percent increase in oil prices reduces building plans by 2 and 3.4 percent in Kern and Oklahoma Counties, respectively. In Midland and McKenzie Counties, only long-run changes in oil prices impact home investment decisions while short-run changes have no impact. The inverse relationship between oil prices and permit applications hints that investors may dampen construction plans in lieu of higher costs of raw materials during periods of higher energy prices. Threshold Autoregressive model findings demonstrate that changes in permit applications occur during periods of high oil prices. Our findings imply that the expansionary monetary or fiscal policies that would be required to revive the housing market would need to be regime and region specific. Thus, coordination between regional lending units and investors is important and can boost recoveries from economic downturns. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Financial Politic & Economic Reviews / Finans Politik & Ekonomik Yorumlar is the property of Journal of Financial Politic & Economic Reviews / Finans Politik & Ekomomik Yorumlar 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 aims to investigate the possible explanatory effect of geopolitical risks on the oil price changes from February 1986 to December 2019 by employing the nonlinear bivariate Granger causality test and frequency domain Granger causality test based on the geopolitical risk index. The results suggest that there exists a nonlinear causality from geopolitical risks to crude oil prices. Moreover, geopolitical risks have a short-term impact on oil prices, less than 12 months. Actual geopolitical events have a smaller and less lasting impact on oil prices than pure geopolitical risks. [ABSTRACT FROM AUTHOR]

The depletion of natural gas reserves, combined with rising oil prices, local market inflation, and concerns about pollution, has accelerated the search for alternative energy sources. As a result, research on turbines and internal combustion engines for electricity generation is increasingly focusing on using vaporized ethanol as a fuel substitute. However, the high cost of analyzing the chemical composition of these fuels often leads to an oversight of their impact on combustion characteristics, such as flame behavior, emission profiles, and temperature distribution.This study employs a statistical approach to assess the combustion and emission characteristics of biofuels, aiming to find suitable alternatives to petroleum-based fuels. By integrating considerations of oil price fluctuations and the digital economy's impact, the research proposes a cost-effective method for evaluating the chemical makeup of vaporized fuels and their effects on post-combustion pollution.Experimental data reveal that alternative fuels can offer stable ignition performance and lower pollution levels, contingent on their specific properties. Fuels with high aromatic content and viscosity tend to produce significant CO emissions, while reducing these characteristics may increase CO2 production. The study also highlights the challenge of simultaneously reducing both CO and NOx emissions. Additionally, the findings show that petroleum gasoline, due to its lower volatility, has favorable fire safety properties and generates fewer pollutants.In the context of economic pressures from rising oil prices and inflation, this research underscores the importance of exploring biofuels as viable, sustainable alternatives for the future energy landscape.

ABSTRACT: This study explores the impacts of the exchange rate, consumer confidence, oil prices on the stock returns of the Borsa Istanbul (BIST) manufacturing firms for the timeline aftermath of the Covid-19 pandemic (March 2020 – September 2022). As the manufacturing companies comprise the majority of the stock market of the BIST, the composite index of these industrial companies (XUSIN) is selected as the response variable. Implementing the autoregressive distributed lag (ARDL) bounds-testing methodology on the monthly time series data, the cointegration existence is detected among the series. The empirical results also show that oil price is the most significant determinant among these variables affecting manufacturing companies’ returns for the long-run. When considering oil as a vital production input in industries, the decreases in stock prices resulting from oil price rises (i.e. increases in production costs) are inevitable. However, the significant long-run effects of exchange rates and the consumer confidence index on stock returns of this industry cannot be detected for the Covid-19 period. ÖZ: Bu çalışma Borsa Istanbul (BIST) bünyesinde işlem gören imalat sektöründe yer alan şirketlerin hisse senedi getirileri üzerindeki döviz kurunun, tüketici güveninin ve petrol fiyatlarının etkilerini Covid-19 pandemi dönemi ve sonrası (Mart 2020 – Eylül 2022) için araştırmaktadır. İmalat sektöründeki firmalar, BIST hisse senedi piyasasının büyük bir bölümünü oluşturduğu için bu şirketlerin kompozit endeksi olan BISTSINAI endeksi bağımlı değişken olarak seçilmiştir. Gecikmesi dağıtılmış otoregresif (autoregressive distributed lag - ARDL) sınır testi yönteminin aylık zaman serilerine uygulanması ile değişkenler arasında eşbütünleşme ilişkisi tespit edilmiştir. Ampirik bulgular aynı zamanda uzun dönemde petrol fiyatlarının hisse senedi getirileri üzerinde en çok etkiyi yapan değişken olduğuna işaret etmektedir. İmalat sektöründe petrolün en önemli üretim girdilerinden biri olduğu göz önüne alındığında, petrol fiyatlarında oluşan artış dolayısıyla üretim maliyetlerinde meydana gelen artışın hisse senedi fiyatlarını olumsuz yönde etkilemesi kaçınılmaz olmaktadır. Diğer taraftan, bu sektörün hisse senedi getirileri üzerinde döviz kurunun ve tüketici güveninin uzun dönemli ve istatistiksel olarak anlamlı etkileri bulunamamıştır.

This is study investigates inter-connectedness of Russia-Ukraine conflict with wheat prices in Pakistan through oil prices, exchange rate, economic policy uncertainty. This objective is realized by employing cross-quantilogram, rolling window multiple correlation, and TVP-Var approaches on weekly data from 7 to 1–2021 to 9–3–2023. The estimated results of cross-quantilogram, rolling window multiple correlation reveal significant positive co-movement between Russian and Ukraine conflict and wheat prices. The major variables responsible for the spillover effect are oil prices, depreciation of exchange rate, and economic policy uncertainty. The finding urges to stabilize exchange rate and economic policy uncertainty along with finding alternative cheap energy sources.

Over the last decade, a significant concern in the energy market has been the decline in the USA’s oil imports and fall in energy prices. In this context, we investigate the impact of the shale revolution in the USA on oil prices and examine its potential replicability in other shale-rich countries. Employing the Auto Regressive Distributive Lag Model (ARDL), the influence of the shale energy boom on WTI oil prices has been quantified, using monthly time series data from 2008 to 2019. The results reveal that shale oil output has no effect on oil prices in the short run. However, we found a significant negative impact on oil prices in the long run, as shale development enhances the global energy supply. Additionally, we found that the shale rich countries lack the infrastructure, financing, and have limited property rights, which hampers their chances of replicating the success of shale development in USA. We recommend that countries trying to develop shale resources invest in factors that led to the shale revolution in the USA. Additionally, as low oil prices will reduce future investment in shale oil and gas exploration, the US government should offer adequate incentives for private firms to remain competitive in the energy sector and continue enjoying the benefits of the shale revolution.

AbstractThe performance of bank stocks exhibits a country’s overall financial health and signals economic growth. Therefore, understanding the interaction of macroeconomic factors on bank stock returns is crucial for the valuation of financial assets, especially in a highly volatile stock market. Although macroeconomic factors and their impact on bank stock returns have been extensively investigated, there is still a dearth of comprehensive review articles in this domain. To address this lacuna, we conducted a systematic review to identify the macroeconomic determinants driving bank stock returns. Through a systematic search, 64 articles were identified from two electronic databases for literature synthesis based on inclusion and exclusion criteria from 1980–2023. The review posits valuable insights into the macroeconomic factors that influence bank stock returns, the nuances of the variables’ effects and the methodologies employed in these studies. The key macroeconomic factors identified include interest and exchange rate sensitivity, which has been studied extensively; however, the impact of monetary policies, gold prices and oil prices needs further investigation. Subsequently, the study documents various bank-specific characteristics that influence the relationship between macroeconomic factors and bank stock returns.

AbstractOver the past three decades, Somalia’s economic landscape has witnessed a noticeable dependence on imported goods. The exchange rate was unregulated owing to the collapse of the country’s central bank. This unregulated environment has introduced significant volatility in exchange rates, profoundly impacting consumer prices and fostering a prevalent shift towards the utilization of the US dollar in economic transactions. Hence, this undertaking delves into the asymmetric effects of exchange rates on consumer prices in the presence of dollarization in Somalia from 1995 to 2019. Employing both linear and nonlinear autoregressive distributed lag (NARDL) cointegration methodologies, we explore the short-run and long-run dynamics between exchange rates and consumer price levels. The long-run empirical results from the NARDL demonstrate asymmetrical cointegration between the unregulated exchange rate and inflation in Somalia. Both appreciation and depreciation of exchange rates exert differing impacts on consumer prices, with depreciation exhibiting a more pronounced effect. In addition, the evidence suggests that the exchange rate pass-through is incomplete in Somalia regarding its inelastic coefficient. Oil prices exhibit a substantial and statistically significant association with inflation, both in the long-run and short-run, while GDP remains inconsequential. In the short-run, the most remarkable outcome indicates that dollarization significantly contributes to mitigating inflationary pressures. Based on our empirical insights, the central bank should enhance regulatory oversight of the foreign exchange market by strictly controlling and prohibiting the issuance of counterfeit banknotes to achieve price stability.

The purpose of this article is to investigate the new driving forces behind China's green energy and further assess the impact of green energy on climate change. The existing literature has used linear methods to investigate green energy, ignoring the non-linear relationships between economic variables. The nonparametric models can accurately simulate nonlinear relationships between economic variables. This paper constructs a nonparametric additive model and uses it to explore green energy. The empirical results show that the impact of green finance on green energy is more prominent in the later stage (a U-shaped impact). Fiscal decentralization also exerts a positive U-shaped impact, meaning that expanding local fiscal autonomy has contributed to green energy growth in the later stage. Similarly, the impact of oil prices and foreign direct investment demonstrates a positive U-shaped pattern. However, the nonlinear impact of environmental pressure displays an inverted U-shaped pattern. Furthermore, this article explores the impact of green energy on climate change and its impact mechanisms. The results exhibit green energy generates a positive U-shaped impact on climate change, meaning that the role of green energy in mitigating climate change gradually becomes prominent over time. Mechanism analysis exhibits that industrial structure and energy structure both produce a nonlinear influence on climate change. [ABSTRACT FROM AUTHOR]