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Electric scooters are increasingly gaining popularity in India owing to rising global crude oil prices and rising levels of vehicular pollution. Most of them are currently powered by expensive in-wheel (IW) permanent magnet (PM) brushless DC motors. Owing to their simplicity, and ruggedness while being cost-effective (since they do not employ PMs), switched reluctance motors (SRMs) are a viable alternative. Despite these benefits, SRMs possess drawbacks such as low torque density and inferior efficiency. Recently, a multi-teeth (MT) SRM with an improved performance was reported. However, the design of MTSRM topologies and their electromagnetic performance have not been explored sufficiently. In this paper, a design formula governing the selection of the number of MT and rotor poles for MTSRMs has been proposed. Using this, a novel four-phase 8/18 IW-MTSRM is derived and proposed for an E-scooter. The characteristics of the proposed SRM are numerically compared with a conventional 8/10 SRM based on magnetic characteristics, efficiencies and steady-state operation for the complete torque-speed range. Results indicate that the proposed 8/18 MTSRM has a higher peak torque capacity, torque density, superior drive cycle efficiency and reduced torque ripple. Further, the FEA model is validated experimentally on a downsized 8/18 MTSRM prototype. [ABSTRACT FROM AUTHOR]

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]

In the evolving landscape of global energy, accurately forecasting oil prices plays a pivotal role in strategizing the transition to green energy. Traditional forecasting methods, though widely used, often fall short in capturing the multifaceted influences on oil price dynamics. This research introduces a multimodal deep learning approach that incorporates both time series oil price data and key economic indicators to enhance forecasting accuracy. By employing a combination of Long Short-Term Memory (LSTM) and Temporal Convolutional Networks (TCN), the model adeptly captures temporal patterns and economic influences. The findings not only demonstrate the model's superior performance over traditional methods but also underscore the profound impact of specific economic indicators on oil prices. [ABSTRACT FROM AUTHOR]

Crude oil prices play a critical role in the global economy, and accurately predicting their future values is of great importance. In this study, we evaluated the performance of three support vector machine (SVM) models - standard SVM, SMO-based SVM, and SGD-based SVM - in predicting crude oil prices based on daily, weekly, and monthly data, aligning with the Industry 4.0 paradigm, to enhance decision-making in the oil and gas sector. The results showed that all three models performed well, with high coefficient of determination R2 values and low MSE values across all versions of the dataset. The SMO and SGD-based models demonstrated particular advantages for larger datasets. Furthermore, SVMs are well-suited for modelling complex financial datasets and can handle non-linear relationships between variables. Our findings suggest that SVMs can provide effective models for predicting crude oil prices, with the SMO-based and SGD-based models showing potential for large datasets. [ABSTRACT FROM AUTHOR]

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie 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.)

Once a cornerstone of the U.S. economy, crude oil production now experiences a paradigm shift, abundant for domestic consumption and export, signaling a lasting global oil price transformation. Despite a surge in U.S. hydrocarbon production and weakening oil prices, imports from Nigeria dramatically dropped from 1.5 million barrels per day in 2006 to 0.2 million in 2013, ceasing entirely by early 2014. Consequently, Nigeria faced a sudden depletion of trade surpluses and reduced foreign reserves. This study delves into the immediate and long-term challenges confronting Nigeria, particularly examining the impact of recent oil and gas price fluctuations on key macroeconomic factors. Findings highlight the balance of payments' high elasticity to oil price shifts and low elasticity to money supply changes with a coefficient of determination of 78.69%. Additionally, the exchange rate shows low elasticity to oil price changes and moderate elasticity to money supply variations with a coefficient of determination of 82.80%. [ABSTRACT FROM AUTHOR]

We examine the comovement between China’s commodity futures and world crude oil prices based on their daily return series. Using a dynamic time-varying approach, we combine the generalized autoregressive score (GAS) model with the copula approach, allowing for asymmetry and tail dependence. Our results demonstrate a significant nonlinear causal impact of world crude oil prices on each of China’s commodities. The comovement between China’s commodity futures and crude oil prices is positive, with varying degrees of significance across different commodity types. Notably, non-ferrous metal and chemical commodity futures are more vulnerable to rising crude oil prices. From a dynamic perspective, we observe continued volatility in the comovement between China’s commodity futures and world crude oil prices in recent years. Moreover, the time-varying dependence between the three non-ferrous metals and crude oil prices is higher than that of other commodities. These findings hold significant implications for global investors, risk managers and policymakers. [ABSTRACT FROM AUTHOR]

Our paper examines and compares the influence of oil prices, international geopolitical risks, and government expenditures on Saudi Arabia's economic diversification during 1970–2020. We employ the bounds testing approach to cointegration to estimate the parameters of the Autoregressive Distributed Lag model to attain the paper's goal. Our results show that oil prices and international geopolitical risk harm the KSA diversification process in the short run. The destructive effect of oil prices continues in the long run, while the impact of the international geopolitical risk does not persist. On the other hand, government expenditures encourage the diversification attitude in the short and long run. This outcome highlights the capability of the KSA government to stimulate the diversification process. It is a positive sign of the state capitalism doctrine's impact on the KSA economic diversification mechanism. From a policy implication perspective, our paper suggests prioritizing economic diversification clearly on the KSA government's agenda. Simultaneously, strengthening the KSA institutional framework and developing new forms of the social contract are critical to motivating the diversification process. • Do oil prices, geopolitical risk, and government spending affect diversification. • We employ a time series autoregressive distributed lag model. • Oil prices and geopolitical risk discourage economic diversification. • Government expenditures encourage economic diversification. • The impact of oil prices and government expenditures prevails to the long run. [ABSTRACT FROM AUTHOR]

The objective of the paper was to study the effects of the Russian -Ukrainian conflict on Romanian inflation using the energy shock's pass-through effect to inflation in Europe after the invasion. A monthly time series dataset is used for econometric analysis, and the data was collected from EUROSTAT, IMF and BNR databases. Using a Cochrane-Orcutt AR (1) regression with iterated estimates that control for autocorrelated error terms, we measured how variations in the price of coal, gas, and oil affected the harmonized consumer price index (HCPI). Our results suggest that oil price increases will lead to an increase in HIPC in Romania. Gas prices had an inverse relationship with HIPC in the analyzed period. The data however did not suggest a relation between coal price and inflation, in the studied period. The energy shock that occurred in Europe accounted in higher prices for gasoline, heating, and electricity on the short run, but there is no evidence that this inflationary pressure will affect long run household inflation. [ABSTRACT FROM AUTHOR]

Existing research concerning determinants of climate change mitigation technology (CCMT) development mainly focuses on the role of climate policy, environmental awareness, or R&D intensity. What has been rarely noticed is that the oil price, as an indication of primary energy costs, can make countries with high energy intensity lean toward renewable energy consumption and invest more in the innovation activities of CCMT. Employing a panel investigation of 30 economies from 1990 to 2019, We find strong evidence that rising oil prices promote CCMT performance. The positive effect of increased oil prices on CCMT is imposed by lowering energy intensity, increasing renewable energy consumption, and promoting energy-technology R&D. Such an impact is more pronounced for CCMT related to energy generation and efficiency, greenhouse gas emissions, and transportation. To obtain more concrete policy implications, we also explore heterogeneities of this promoting effect across different levels of economic development and oil dependence. • Increased oil prices positively affect CCMT's share in green innovation. • A rise in oil prices spurs CCMT innovation related to energy, greenhouse gases, and transportation. • The effect of oil prices on CCMT's share in green innovation is more notable in oil-importing, high-income, and developed economies. [ABSTRACT FROM AUTHOR]

This research mainly focuses on investigating the role of the interactions between cash flows, oil price uncertainty, and geopolitical risk on corporate cash holdings across 42 countries. We also investigate whether such interactions may differ across firm and country characteristics. The main results show that the interactions between cash flows interacting with oil price uncertainty and geopolitical risk have a positive correlation with corporate cash holdings. Additionally, the nexus between the interactions and corporate cash holdings is more prominent for financially constrained firms, firms located in highly competitive industries, or Asia and Europe. The main policy implication based on our findings is that policymakers should exercise caution and take into account the effect of the uncertainties of oil price movement and geopolitical risk when designing policies related to corporate decision makings. [ABSTRACT FROM AUTHOR]

The study aims to investigate capital market volatility during crises, exploring the relationships between three key financial indicators: oil prices, the VIX index, and gold prices, using monthly data covering the period from January 2013 to May 2023, based on the Granger causality approach and the impulse response function testing empirically the existence of the long-run relationship using Johansen multivariate approach and the estimation of the VAR/VECM model. By analysing their interdependencies, the research sheds light on how these indicators respond to economic turbulence. The study employs robust econometric methods to investigate causal relationships and predictive patterns, providing valuable insights for investors, policymakers, and analysts navigating uncertain financial landscapes. The findings reveal nuanced dynamics, such as the momentum in oil prices, the inverse relationship between oil prices and the VIX index, and a significant Granger causality relationship running from the VIX index to oil and gold prices. Furthermore, based on the impulse response patterns, the shock in the VIX index caused a notable oil price decrease in the second quarter after the shock, followed by oscillations. Gold prices exhibit a minor initial decline after the VIX shock, with no lasting effects. [ABSTRACT FROM AUTHOR]

This study aims to examine the magnitude of the influence of non-oil and gas exports on the increase in Foreign Direct Investment (FDI) in Indonesia from 2004-2022, which is influenced by changes in credit interest and the rise and fall of fuel prices. This study uses linear regression analysis techniques with the SPSS-22 and Eviews-10 programs to process secondary data types promptly from sources from the Central Statistics Agency and Bank Indonesia in the period 2004-2022 with a total of 19 observations. Explanatory research design with hypothesis testing, using a descriptive quantitative approach model. The data used in this study is time-ordered from 2004-2022 with Linear Regression analysis techniques. The partial hypothesis is obtained using the statistical T and F tests for simultaneous model hypothesis testing. The findings of this study explain that credit interest, fuel prices, and non-oil and gas exports simultaneously significantly affect FDI in Indonesia. The subsequent results showed that Interest on loans partially had a negative and significant effect on FDI. Meanwhile, fuel prices positively and significantly affect FDI in Indonesia. This research contributes to Indonesian policymakers in finding sources of FDI from non-oil export, particularly credit interest and fuel prices. [ABSTRACT FROM AUTHOR]

Background: The share market is acknowledged as a pivotafsubset of the larger financial market for trading financial assets, which is believed to be a catalyst for economic growth in the economy. However, various fundamental economic dynamics, especially the oil price and exchange rate, affect the overall behavior of returns to investors in the stock market. Nigeria has crude oil as its major export commodity in the international market, and in view of the recent global economic downturn that is linked to the COVID-19 pandemic, the petroleum cost has been plummeting along with the worsening exchange rate. Objective: This investigation explored the effects of fluctuations in oil prices and currency exchange rates on stock market yields in Nigeria. Method: Monthly information on crude oil cost, naira/dollar conversion rate, and the overall share index of Nigerian Stock Exchange (NSE) were acquired from the US Energy Information Administration encompassing the timeframe from January 2000 to September 2020 and estimated through the ARDL model. Results: We found that (i) The ARDL boundary examination indicated a sustained association among the variables examined in the investigation. (ii) A 1% escalation in oil prices would probably induce a 15.5% rise in stock returns in the short term and a 23.7% increase in the long term. (iii) A 1% devaluation of the naira/dollar exchange rate would reduce short-term stock market returns by 0.16%, whereas in the long term, an inconsequential adverse impact of the exchange rate on stock market returns was identified. Originality: Noteworthy for its unique contribution, this study stands out as one of the few empirical examinations exploring the tripartite relationship among stock market returns, prices of crude oil, and currency exchange rates in Nigeria. Using high-frequency data, the study effectively captures both the short-run and long-run effects of oil price changes and exchange rate fluctuations on stock market returns. [ABSTRACT FROM AUTHOR]

E10 is still the largest market for blending of ethanol in transportation fuels in the U.S. This paper analyzes the relationship between the input costs of transportation fuel blends (crude oil, wholesale gasoline) and the transportation fuel prices (E10) that U.S. consumers pay at the pump both in the short run and in the long run. The article employs a generalized spatial random-effects autoregressive-distributed lag model for E10 price using U.S. regional data. We estimate the short run elasticity of E10 price with respect to crude oil price as 0.28, and the long run elasticity as 0.42. In both the short run and the long run, the elasticities of E10 with respect to wholesale gasoline price are higher than the elasticities with respect to crude oil price; at 0.59 and 0.83. We find that the federal policy of E15 approval increased E10 prices. We do not find significant impacts of income or population on E10 prices. [ABSTRACT FROM AUTHOR]

The primary contribution of the current article is to use the SVAR methodology to study the dynamic responses of China's trade balance with its three largest partners – the U.S., Japan, and Korea – to shocks of oil supply, global demand, and oil-specific demand, controlling for world trade policy uncertainty. We discover that the transmission of oil price shocks relies on the type of shock and different trading partners. Thus, China would need to consider the various oil shock components as the key factors determining the dynamics of the bilateral trade flows with its major partners. We also reveal that world trade policy uncertainty plays an important role in fluctuating China's trade flows with the U.S., but not with Japan and Korea. When examining China–U.S. trade, therefore, it is important to take into consideration the uncertainty surrounding trade policies. Failure to do so may result in model misspecification in econometric models, which could lead to misleading conclusions. [ABSTRACT FROM AUTHOR]

Climate policy uncertainty needs to be considered urgently in view of the fact that climate policy is affecting energy and agricultural markets. This paper uses quantile connectedness to examine the dynamic spillover among climate policy uncertainty (CPU), crude oil prices (COP) and agricultural product prices (APP), further revealing the impact of climate policy on markets in both normal and extreme markets. The results show that there is a higher connectedness level at extreme quantile. Uncertain climate policy activities and major events affect system connectedness. Further analysis shows that, compared with the isolated role in the normal market (median quantile), CPUs in the extreme market (lower and upper quantile) become continuous shock receivers in the system. The risk spillover mainly focused on soybeans and corn, and COP increased the risk of spillover especially after the epidemic. By revealing the transmission mechanism of the price correlation between oil and agricultural products under the CPU framework, this can fully explain the linkage between them. In general, the stability of the oil market and agricultural product market is crucial to the formulation of climate policy. These conclusions provide significant enlightenment for policy-makers and investors coping with the high level of CPU. [ABSTRACT FROM AUTHOR]

This paper analyzes the dynamics of CO2 emissions over the last decade for a large group of 25 European countries, an issue that is at the center of the ecological transition project involving various commitments (COP21, COP26, G20 meetings, etc.). To this end, our model measures the repercussions of energy price shocks (oil, gas, coal) for carbon emissions, as well as changes in industrial production and sustainable development in the context of the coronavirus pandemic. Using annual data for 23 EU countries, together with Russia and the UK, our findings show that CO2 emissions reacted significantly to oil and coal price shocks and vary with industrial production cycles. We quantified this reaction while computing the related elasticities. Further, while a significant reduction in CO2 emissions was observed during the COVID-19 pandemic, the stepping up of investment in sustainable development and renewable energy consumption also had a negative impact on CO2 emissions. This suggests that the key driver to reducing the risk of climate change and lowering high carbon dioxide (CO2) emissions involves significant commitment to sustainable development. [ABSTRACT FROM AUTHOR]

This paper examines the nonlinear relationships between oil and inflation for twelve major global economies in the presence of important macroeconomic variables. Using the nonparametric quantile causality approach, we show strong evidence of causality-in-variance from inflation to changes in oil prices for all economies across different quantiles with the exception of Australia. On the other hand, evidence of a causality-in-mean from oil to inflation is identified for Australia, Canada, Greece, the UK, and the US and a causality-in-variance in the same direction for almost all economies, exhibiting a hump-shaped pattern across the quantiles. Results for partial and multivariate wavelet approaches show that the macroeconomic factors drive and accentuate the oil-inflation co-movements under all frequencies and over time. These results have significant implications for investors and policy makers. • We examine nonlinear relationships between oil and inflation for twelve major global economies. • Our work also considers important macroeconomic variables. • Evidence of causality-in-variance from inflation to changes in oil prices for all economies except Australia. • Evidence of a causality-in-mean and variance from oil to inflation for Australia, Canada, Greece, the UK, and the US. • Macroeconomic factors drive the oil-inflation co-movements across frequencies. [ABSTRACT FROM AUTHOR]

The share of renewable energy consumption in total electricity consumption is analysed for a sample of forty-nine countries worldwide from 1985 to 2017. The analysis follows a two-step approach. First, the club convergence model was used to find the convergent countries. Second, a panel vector autoregression (PVAR) model estimation was used to analyse the convergent countries. Club convergence analysis confirms that forty-two countries are convergent in renewable energy consumption in total electricity consumption. The subgroup convergence tests confirm the existence of seven subgroups and one non-convergent group. Of these eight groups, the first seven are convergent among their group members, but the eighth group (Norway, Switzerland, Trinidad and Tobago) is non-convergent. The PVAR revealed a dense Granger causal relationship among the variables share of renewable electricity consumption, fossil consumption, GDP, trade openness, economic complexity, financial development, and oil prices. In their interventions, policymakers should be aware that the share of renewable energy consumption in total electricity consumption is very interdependent. [ABSTRACT FROM AUTHOR]

Unlike previous studies, the current study uses oil price and inflationary shocks to assess the feasibility of actualizing the ECOWAS Vision 2020, which is aimed at creating a monetary union. With the help of the Blanchard and Quah (BQ) decomposition for a sample from 1975:05 to 2018:08, two sets of models are estimated: models for inflationary shocks and models for oil price shocks. It is found that although the vision is a mirage, the creation of a common currency can serve as a shock absorber against the negative spillovers of global and regional inflationary shocks. The study also finds that oil price shocks lead to appreciation of the currency for the oil exporting country Nigeria, while Nigeria, the Gambia and Ghana stand out in their responses to oil price shocks. The study recommends that these countries cannot be part of the Vision and that more coordination among ECOWAS members is needed before this Vision can be actualised. [ABSTRACT FROM AUTHOR]

Multi-source data is widely used in the field of energy future prices forecasting, the improvement of forecast ability and data screening are becoming the focus of current research. In this paper, two tree-based models (namely, Random Forest and XGBoost model) are employed to predict China's crude oil future prices. The empirical analysis confirms that Random Forest and XGBoost model have superior prediction performances than benchmark and the XGBoost model performs best. An important finding is that there is a time gap between investor information search and processing because the prediction performance within the time lags is obviously superior than that of the current period. [ABSTRACT FROM AUTHOR]

This study examines how the rise in energy prices following the Russian invasion of Ukraine (which began on February 24, 2022) has spread to other sectors using the monthly input–output model (56 sectors in 44 countries). The estimated results demonstrate that if prices increase by 20% exclusively in Russia's mining and quarrying (M&Q) sector, there will be almost no global effect. However, if prices increase by 20% in every M&Q sector around the world, global prices (the weighted average across all sectors) will rise by 3.15%, damaging 6.83% of monthly GDP at the pre-invasion level as a surplus loss ($551,080 million per month). Because oil prices rose for almost five months from February 28 to August 3, 2022, the world suffered five times this damage, or 2.85% of annual GDP ($2.7 trillion). This scenario is roughly equivalent to a price change of 5 times in the Russian M&Q sector alone. • Two scenarios for +20% energy prices (fossil fuel) in Russian or global mining sector. • Input–output analysis in 56 sectors/44 countries to seek price rise and surplus loss. • If energy prices increase by 20% only in Russia, global overall prices rise 0.13%. • If increased 20% globally, overall prices rise 3.15% and surplus loses 6.83% of GDP. • To rise global energy price by 20%, the Russian energy price alone must be +5 times. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has caused turmoil in every aspect of life and may be prevalent for years. Therefore, this study aimed to determine whether the pandemic reflects oil prices in China. We utilized a model to simulate and examine the energy, economic, and environmental effects of COVID-19, which affects a wide range of industries and households. The impact of the pandemic is considered in terms of customer expectations and factor input changes. Based on these changes, we find that factor input changes are the primary cause of the economic recession. We further find a parallel relationship between CO2 emissions and economic downturn. In addition, a reduction in transportation has significantly influenced the Gross Domestic product (GDP), which plunged during the pandemic period by 0.49%. Transportation negatively influences industrial production, railway sector, and air transportation by 10.17%, 1.76%, and 1.53%, respectively. Based on these findings, this study proposes important policy implications. [ABSTRACT FROM AUTHOR]

The 12th Sustainable Development Goals (SDGs) highlighted the importance of ensuring sustainable consumption and production patterns. Researchers have found that energy subsidies may encourage overconsumption, misuse, and moral hazard problems. Hence, there is a need to rationalize inefficient energy subsidies. Consequently, the Malaysian government has been implementing a subsidy reformation program to improve energy efficiency and reduce fiscal burdens. This study aims to identify and compare the impacts of energy subsidies and oil prices on energy consumption across the agricultural, industrial and service sectors in Malaysia. It is critical for policymakers to better understand the role of energy subsidies in influencing energy consumption, especially the magnitude to which energy subsidies influence energy consumption, in order to structure a subsidy reform strategy which effectively addresses the energy overconsumption issue. In this study, a time series dataset covering the years of 1978 through 2018 is analyzed. The ARDL approach and Granger causality test were employed to determine meaningful statistical evidence and revealed four important findings. Firstly, energy subsidies have a positive relationship with energy consumption. Secondly, oil prices have a negative relationship with energy consumption and energy subsidies significantly interact with oil prices to affect energy consumption. This significant positive moderating effect suggests that energy subsidies may counteract the negative impact of oil prices on energy consumption. Thirdly, output has the greatest (positive) impact on energy consumption. And finally, energy subsidies drive higher outputs in the agricultural sector. [ABSTRACT FROM AUTHOR]

Energy markets began to tighten in 2021 because of a variety of factors, including the extraordinarily rapid economic rebound following the pandemic. But the situation escalated dramatically into a full-blown global energy crisis following Russia's invasion of Ukraine in February 2022. The price of natural gas reached record highs, and as a result so did electricity in some markets. Oil prices hit their highest level since 2008. [ABSTRACT FROM AUTHOR]

Copyright of Revista Facultad de Ciencias Economicas: Investigacion y Reflexion is the property of Revista Facultad de Ciencias Economicas 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.)

Purpose: This paper aims to investigate how oil price uncertainty affects real gross domestic product (GDP) and industrial production in eight Central and Eastern European countries (CEEC). Design/methodology/approach: In the research process, the authors use the Bayesian method of inference for the two applied methodologies – Markov switching generalized autoregressive conditional heteroscedasticity (GARCH) model and quantile regression. Findings: The results clearly indicate that oil price uncertainty has a low effect on output in moderate market conditions in the selected countries. On the other hand, in the phases of contraction and expansion, which are portrayed by the tail quantiles, the authors find negative and positive Bayesian quantile parameters, which are relatively high in magnitude. This implies that in periods of deep economic crises, an increase in the oil price uncertainty reduces output, amplifying in this way recession pressures in the economy. Contrary, when the economy is in expansion, oil price uncertainty has no influence on the output. The probable reason lies in the fact that the negative effect of oil volatility is not strong enough in the expansion phase to overpower all other positive developments which characterize a growing economy. Also, evidence suggests that increased oil uncertainty has a more negative effect on industrial production than on real GDP, whereas industrial share in GDP plays an important role in how strong some CEECs are impacted by oil uncertainty. Originality/value: This paper is the first one that investigates the spillover effect from oil uncertainty to output in CEEC. [ABSTRACT FROM AUTHOR]

Copyright of Contaduría y Administración is the property of Facultad de Contaduria y Administracion-Universidad Nacional Autonoma de Mexico 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 hedge and safe-haven properties of green bonds (GBs) performing as a safeguard against oil price shocks and uncertainty, in comparison to the corresponding roles of gold, the 3-month European government bills, and the U.S. 3-Month T. bills. Oil price shocks are disentangled into oil supply, oil demand, and oil risk shocks based on the recent methodology of Ready (2018), generated in a framework that includes gold, oil shocks, and oil uncertainty (OVX). The ability of GBs to protect against oil price shocks and oil uncertainty is examined using the GARCH and quantile regression (QR) models. The results show that GBs are more appropriate than gold and conventional bonds (CBs) as hedging and safe haven tools against oil price shocks and oil uncertainty. Besides, the ability of GBs to protect against oil price shocks and uncertainty depends on whether the oil shocks are supply, demand, or risk shocks. Furthermore, we find that GBs serve as a strong hedge and/or a safe haven against structural oil shocks generally under bearish GBs market conditions. The European government bills and the US T. bills play the role of weak hedge and a safe haven asset against oil uncertainty and oil shocks. This role varies across quantiles (bear and bull market conditions). Relevant risk management implications are discussed. [ABSTRACT FROM AUTHOR]

Since 2020, two major crisis impacted the global environment: the COVID-19 pandemic and the Russia-Ukraine war. Both had a major impact on international trade and on the evolution of oil prices which has a direct effect on the logistics industry. The scope of our paper is to investigate the effects of oil price evolution on logistics activities, especially transport. Costs of shipment represent an important component of final prices for consumer products and they can influence the general rate of inflation. This is a major concern among government officials in all countries, as high inflation rates can have negative effects on national economies. Our paper is focused on analyzing price trends on each mode of transport, but also prices for integrated logistics services. The results of our analysis offer insight on the logistic market trends and can be useful to professionals from companies, but also for academics interested in this field and consumers worldwide concerned about prices going up. [ABSTRACT FROM AUTHOR]

The contribution of the present article is to explicitly consider the role of supply and demand shocks in the global oil market when analyzing the nexus between oil price fluctuations and macroeconomic activities – growth, inflation, and exchange rate – in an emerging economy, specifically Indonesia. For doing this, a structural vector autoregressive (SVAR) methodology is applied to monthly observations for 1998 through 2019. We show that the timing, magnitude, and even direction of the response of Indonesia's macroeconomy are likely to vary depending on the type of shock. We believe that this discovery provides important implications for empirical modeling and policy analysis. [ABSTRACT FROM AUTHOR]

Based on the TVP-VAR (time-varying parameter vector autoregressive) based extended joint connectedness methodology, this study analyzes the joint connectedness among BRICS's (Brazil, Russia, India, China, and South Africa) geopolitical risks and the US macro economy (interest rates, consumer price index, crude oil prices, stock prices, and gross domestic production) for return and volatility. Evidence suggests that shocks from geopolitical risks have a considerable impact on emerging economies. Emerging economies are closely linked to developed economies in today's globalized world. Hence, the geopolitical risk of BRICS countries may further impact developed economies. In this study, we performed a cross-sectional analysis of the relationships between geopolitical risks in BRICS nations and a developed economy (e.g., US macroeconomic indicators). Our results were significant in at least two ways. First, geopolitical risks in China and Russia considerably impact the return and volatility system. In contrast, geopolitical risks in China have fewer impacts on the US macro economy than in Russia, Brazil, and India. Second, the value of total joint connectedness during the COVID-19 period was greater than during the 2007–2008 global financial crisis. Third, the consumer price index, crude oil prices, and stock prices receive greater connectedness from the others. The results suggest that policymakers and investors should not pay excessive attention to geopolitical risk in China. Moreover, because the oil and stock markets are highly interdependent, risk spikes for investors who hold both oil and stock when facing high geopolitical risk. We recommend that investors reduce their simultaneous holdings of both assets in times of high geopolitical risk and consider alternative safe haven assets. [ABSTRACT FROM AUTHOR]

In this paper, we used the Baidu feed index to quantify the valuable information from the search engine, and proposed a China's crude oil futures price forecasting model with feed index. The empirical analysis confirms that the feed index, which characterizes the investor attention of participants in China's crude oil futures market, provides valuable information for internet concerns and investor sentiment, and has significant impact on China's crude oil futures price forecasting. We found that the time lag between the search query results and the crude oil futures price changes, which mostly lies within the shorter time range. The forecasting model with the search engine data would produce forecasts with superior performance. [ABSTRACT FROM AUTHOR]

In this paper, a new crude oil price forecasting model using data embedding and Convolutional Neural Network has been proposed to predict more accurate crude oil price movement. It uses the time delayed embedding technique to transform the data into two-dimensional phase space. The Convolutional Neural Network model is used to extract the main data characteristics more effectively, taking advantage of the hierarchical feature extraction and modeling capability of CNN model. Empirical evaluation of the performance of the proposed TDE-CNN model has been conducted using daily price observations in West Taxes Intermediate market. Experiment results confirm that the TDE-CNN forecasting model produces forecasts with the improved forecasting accuracy. [ABSTRACT FROM AUTHOR]

This paper examines the impact of oil price and economic policy uncertainty on China's tourism market. We point out the shortcomings of previous works considering only one factor, and prove the necessity of considering both factors at the same time. The results show that the impacts of oil price and economic policy uncertainty on China's tourism market overlap significantly, their net impact is mainly concentrated in the medium-term and long-term, respectively, and it can explain the significant variation found in China's tourism stock indexes when they are considered simultaneously. Furthermore, among subsectors, hotels are more sensitive to economic policy uncertainty, and scenic spots are most affected by oil price. [ABSTRACT FROM AUTHOR]

Agricultural expansion is a primary driver of biodiversity decline in forested regions of the tropics. Consequently, it is important to understand the conservation value of remnant forests in production landscapes. In a tropical landscape dominated by oil palm (Elaeis guineensis), we characterized faunal communities across eight taxa occurring within riparian forest buffers, which are legally protected alongside rivers, and compared them to nearby recovering logged forest. Buffer width was the main predictor of species richness and abundance, with widths of 40–100 m on each side of the river supporting broadly equivalent levels of biodiversity as compared to logged forest. However, width responses varied markedly among taxa, and buffers often lacked forest‐dependent species. Much wider buffers than are currently mandated are needed to safeguard most species. The largest biodiversity gains are achieved by increasing relatively narrow buffers. To provide optimal conservation outcomes in tropical production landscapes, we encourage policy makers to prescribe width requirements for key taxa and different landscape contexts. [ABSTRACT FROM AUTHOR]

This paper examines the quantile relationships between the Saudi Riyal (SAR) exchange rate pressure, Credit default swap (CDS) spreads, total reserve assets, and oil prices. Using the available monthly data ranging from 2008 to 2018 and employing the error correction model, the results show a negative and significant relationship between the long-run coefficient of the SAR exchange rate pressure and the long run coefficients of both the CDS and the oil price. However, the long run coefficient of the foreign reserves is statistically insignificant, thus indicating that the exchange rate pressure, CDS spread and oil price variables are cointegrated. As for the short-run coefficients, we find that the lag SAR pressure affects the current pressure. Moreover, the short-run coefficient of the foreign reserves affects negatively the SAR pressure. Moreover, using the quantile ARDL (QARDL) model, we find a significant relationship particularly in the extreme quantiles, regardless of the level or the log level series. Under the long-run coefficients, the positive (negative) relationship characterizes the nexus of the reserves-pressure and the CDS-pressure (oil-pressure) on the SAR. As for the short-run coefficients, we find that an increase in the lag SAR pressures contributes to the current pressure across all quantiles, whereas an increase in the reserves reduces the pressure in the extreme quantiles. These results have important implications for policy makers. [ABSTRACT FROM AUTHOR]

Primary energy sources are realized through Romania's internal production as well as through imports. The current evolution of the world economy, European and, of course, in Romania, has determinedthe es of the heating of energy prices. In this context, the authors aim to analyse, on the basis of data provided by the National Institute of Statistics, Eurostat and the European Union, the price situation on the oil, natural gas and other renewable sources that exist, such as hydroelectric, wind, solar, nuclear and imported electricity. In the current context, the complex crisis that the economy of the world's states is going through (the health crisis, the economic and financial crisis, the crisis of energy sources, the food crisis, the crisis determined by the unclear state of world security) determines a much more careful thinking. The crises that I have mentioned have imposed restrictive measures on the part of countries with resources in the fields of oil, natural gas, coal, which affect in the short, medium and long term the economic development of all the countries of the world. Using these data with care, using the statistical indicators that characterize these developments (indicators of primary energy resources, indicators of the dynamics of primary energy resources capitalization, structure of primary energy resources, etc.), together with logical analysis, the authors try to highlight the current state in the field of primary energy resources and to suggest possibilities of evolution in the next period. This situation is completed with some analyses that the authors have carried out using some statistical-econometric models that give numerical content to the analysis to which we have referred. [ABSTRACT FROM AUTHOR]

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Iraq is one of the rentier economies as it suffers from changes in crude oil prices because there is no sovereign fund that maintains the wealth of the national economy, because most rentier countries rely on financing their budgets on oil revenues mainly and often exposed those revenues to fluctuations as a result of changes in oil prices in the international market, so the, The research found that oil is a depleted wealth and at the same time is the wealth of generations must be preserved from waste by using its revenues in a way that helps the optimal allocation of resources as the main sector to achieve development in the Iraqi economy, and preferably there are precautions to absorb the negative effects of oil price shocks in the world oil markets through the diversification of total exports that are the gross domestic product of the Iraqi economy and the diversification of public revenues and the establishment of a sovereign wealth fund in Iraq. [ABSTRACT FROM AUTHOR]

In response to shareholder interest in greater transparency, oil industry participants issued reassuring forecasts about the role of fossil-fuels by 2040. While differing in energy demand analysis, these forecasts had similar, status-quo predictions on energy intensity and fossil fuels' share of total energy. The forecasts, however, failed to consider the effects of their own alternative energy projects as well as four key contributors to oil market instability; (1) responses to global warming, (2) mandates to write off noneconomic reserves, (3) oligopolistic oil pricing, and (4) technological change. All of these instabilities converged in 2020, causing industry forecasts to be outdated. [ABSTRACT FROM AUTHOR]

This study employs the nonlinear autoregressive distributed lag (NARDL) model to investigate the asymmetric effects of international oil prices (oil price uncertainty) and urban residents' income on consumption in China. The empirical results show that the asymmetric effects of oil prices (oil price uncertainty) and urban residents' income on consumption are significant in the both the short- and long-term. Specifically, increasing urban residents' consumption significantly respond to a decline in oil prices while there is no obvious decreased consumption response to a rise in oil prices due to the wealth transfer effect. We also observe that the stimulating effect of falling oil price uncertainty on urban residents' consumption is noticeably stronger than the adverse effect of increasing oil price uncertainty on consumption because of the expectation effect. Finally, we find that the asymmetric effect of income changes on consumption is significant due to the ratchet effect, whereby an income increase has a stronger stimulus effect than the reducing effect of income decline on consumption. [ABSTRACT FROM AUTHOR]

The primary contribution of the present research is to explicitly take into consideration the role that the current outbreak of coronavirus diseases proxied by the COVID-19 index plays when studying the asymmetric impact that oil prices have on the South Korean won (KRW)/US dollar (USD) exchange rate. We discover that the COVID-19 pandemic seems to have been a significant factor in affecting the asymmetric impact of oil prices on the KRW/USD rate in both the short and long run. [ABSTRACT FROM AUTHOR]

The disease burden related to air pollution from traditional solid-fuel cooking practices in low- and middle-income countries impacts millions of people globally. Although the use of liquefied petroleum gas (LPG) fuel for cooking can meaningfully reduce household air pollution concentrations, major barriers, including affordability and accessibility, have limited widespread adoption. Using a randomized controlled trial, our objective was to evaluate the association between the cost and use of LPG among 23 rural Rwandan households. We provided a 2-burner LPG stove with accessories and incorporated a "pay-as-you-go" (PAYG) LPG service model that included fuel delivery. PAYG services remove the large up-front cost of cylinder refills by integrating "smart meter" technology that allows participants to pay in incremental amounts, as needed. We assigned three randomized discounted prices for LPG to each household at ∼4-week intervals over a 12-week period. We modeled the relationship between randomized PAYG LPG price and use (standardized to monthly periods), analyzing effect modification by relative household wealth. A 1000 Rwandan Franc (about 1 USD at the time of the study) increase in LPG price/kg was associated with a 4.1 kg/month decrease in use (95 % confidence interval [CI]: −6.7, −1.6; n = 69 observations). Wealth modified this association; we observed a 9.7 kg/month reduction (95 % CI: −14.8, −4.5) among wealthier households and a 2.5 kg/month reduction (95 % CI: −5.3, 0.3) among lower-wealth households (p-interaction = 0.01). The difference in price sensitivity was driven by higher LPG use among wealthier households at more heavily discounted prices; from an 80 % to 10 % discount, wealthy households used 17.5 to 5.3 kg/month and less wealthy households used 6.2 to 3.1 kg/month. Our pilot-level experimental evidence of PAYG LPG in a rural low-resource setting suggests that further exploration of subsidized pricing varied by household wealth is needed to ensure future policy initiatives can achieve targets without exacerbating inequities. • Cost of and access to cleaner cooking fuels are major barriers to improved health • Use of pay-as-you-go (PAYG) liquefied petroleum gas (LPG) may reduce barriers • We studied price sensitivity by randomizing discounted PAYG costs and measuring use • Relative wealth modified the association between the cost and use of PAYG LPG • Differences were driven by higher use in wealthier households at lower costs [ABSTRACT FROM AUTHOR]

We employ the non-linear autoregressive distributed lag (NARDL) approach to examine if the oil price and public expenditure relationship are dependent on the level of corruption using Nigeria's quarterly data during the 1996-2019 period. The result of the NARDL-bounds test to co-integration demonstrates that there is a long-run relationship between the variables, and we found evidence of long-run asymmetry in this relationship. The estimation results indicate that both positive and negative shocks to oil price have a significant positive effect on public expenditure in the long run, and the impact of oil price on public expenditure depends on the level of corruption. In addition, the marginal effect of oil price on public expenditure varies at different levels of corruption. Other important factors that drive public expenditure in Nigeria, in the long run, include spending on internal security and debt service. Based on these outcomes, we proffer some policy recommendations. [ABSTRACT FROM AUTHOR]

The purpose of this study is to find the impact of macroeconomic (inflation, BI rates, economic growth, world oil prices, and the money supply) on stock return in Indonesia. A sampling of 251 listed companies listed on the Indonesia Stock Exchange (IDX) was carried out using a purposive sampling technique. The data used in this study is panel data, namely cross-section data and time-series data, for the period 2007-2017. While the data analysis technique uses panel data regression and processed by Eviews Software. The results showed that inflation and the Rate does not significantly influence stock returns. While, economic growth, world oil price, and money supply significantly influence stock return. The result of our study gives the implication that macroeconomic variables must be controlled to maintain the stability of stock returns. [ABSTRACT FROM AUTHOR]