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The objective of the study was to identify the impact of renewable energy on Saudi economy during 2000-2021. Analytical techniques were used to conduct this study. An analysis of the study used a set of variables, in which Renewable energy perceives as independent variable and the dependent variables are GDP per capita, net foreign direct investment, unemployment, fixed capital formation, and net foreign trade. The data of the study were analyzed using the E-views program. According to the study, renewable energy has an impact on certain economic variables and does not have an impact on others. A partial validity is found for the study's central hypothesis. According to our findings, renewable energy contributes significantly to net foreign direct investment, unemployment, and fixed capital formation, but not to GDP per capita, net foreign trade, or fixed capital formation.
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In this study, which is based on daily data, the relationship between BIST electricity index and BIST tourism index was measured between 2012:M9 – 2022:M9 periods. The aim of the study is to measure the relationship between BIST electricity index and BIST tourism index. VAR Granger causality test was applied to determine whether there is any causal relationship between the variables. It has been determined as a result of the analysis that the BIST electricity index has no effect on the BIST tourism index. Two-way ineffectiveness was determined among the variables. In addition, it was obtained as a result of the analysis that the applied correlation relationship was weak between these variables. The results obtained from the study are important in terms of measuring the effects among BIST indices.
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The future to geo-political and geo-economic conundrums is by transforming current economies into inclusive and sustainable societies. In this race for global dominance and hegemony, policy makers must be wary of not forgetting institutional practices of conserving and preserving ecosystems and biospheres with pro-active and proper thinking. Governments that are in power must be sensible to realize that economies will eventually grow when more people join the formal and informal sectors, but the challenge is to have a planet that sustains our needs rather than addressing our greed. Legal systems must work harder in the 21st century to embed proper and critical thinking driven by an ecological conscience to preserve, conserve and protect the environment that sustains us. The technology that is being built and fashioned to drive businesses must submit to stringent ecological standards. With the rapid spread of Covid19, scientists are aware that humanity will be afflicted with more such zoonotic diseases primarily brought on by the global warming and climate change. Third world governments in their search for competing and contributing with the global economy forget the impending dangers of a cataclysmic warmer, hotter and unsustainable planet that will deprive burgeoning populations of food and clean water furthering a health scare. Across the globe, we have witnessed government's response to Covid19 especially in the third world and the loss of lives that could have been prevented. This affliction is bound to endure owing to the inadequate policies that fail to create low-carbon economies or submit to Sustainable Development Goals that could mitigate the debilitating effects of a globally warmer planet. In all of this, the future will be fought not over oil but wars are bound to be fought over water and food and lack of immediate or urgent healthcare support. It is observed painfully, that the people most affected or afflicted with the mostly the marginalized, the poor, the disadvantaged. In this paper, I propose how governments of the day must transform their economies to be sustainable and inclusive, ameliorate global warming, promote healthy agricultural practices, constantly set higher moral standards for a low-carbon economy and build on a healthcare system that is robust and flexible to everyone's needs. The globe after observing many discussions at Copenhagen is now becoming familiar with the reality of a resource-efficient economy and natural capital as an invaluable economic asset. © 2023 Scrivener Publishing LLC. All rights reserved.
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The Intergovernmental panel on Climate Change has sounded its alarm through its special report on the impact of global warming of 1.5oC and called for a strengthened global response to the threat of climate change. Despite that the COVID-19 pandemic has left a devastating effect on the aviation industry, this is forecasted to bounce back and recover within a few years. It is therefore important now to revisit opportunities for a better balance between social, environmental and economic impact of the sector. The European Union has been leading the way in limiting the environmental impacts of aviation. Despite that most of the R&D effort has been focused on the airborne phase, the European Union is legislating so that all aircraft movements on the ground are set to be emission-free by 2050. The paper focuses on engineless aircraft taxiing with the aim to reduce emissions on the ground. We demonstrate that upon landing, an aircraft has enough kinetic energy, which if recovered could power a 5-minute engineless taxiing process. When scaled to a large fleet such as low-cost carriers, this emissions problem can be turned on its head and becomes an opportunity for fuel savings and a reduction in emissions on the ground. The paper also demonstrates that the cost to retrofit such technology can be recovered in a short timeframe and therefore there is an economic incentive to the airline. © 2022 ICAS. All Rights Reserved.
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The objectives of this research include: (1) examining and analyzing the effect of capital structure, profitability, dividend payments and inflation on the value of mining companies;(2) examining and analyzing the moderating role of Good Corporate Governance (GCG) on the effect of capital structure, profitability, dividend payment and inflation on the value of mining companies listed on the IDX. The population of this study is all mining sector companies listed on the IDX for the period 2014-2020. The purposive sampling method is used as the sampling technique. The total population is 49 companies and the number of samples that meet the criteria are 44 companies. The research period is 7 years, so the total number of observations is 308 data (pooled data). The Moderated Regression Analysis (MRA) is used as the analysis method. The result is as follow: (1) capital structure has a negative significant effect on firm value;(2) profitability has a positive significant effect on firm value;(3) dividend payment has no significant effect on firm value;(4) inflation has a negative significant effect on firm value;(5) GCG has a moderating effect on the influence of capital structure, profitability and inflation on firm value, with the type of Quasi Moderating, whereas on the influence of dividend payments on firm value, it was the type of Pure Moderating.
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The first two months of war alone turned the Russian clock back decades, undoing thirty years of post-Soviet economic gains and reducing the country to an international pariah state. Three decades after the collapse of the Soviet empire, Russians are being dragged back in time to when Soviet citizens lived isolated from the rest of the world, in a bubble of failed ideology and misinformation. That system fell apart under just the kind of autarky and autocracy that Putin hopes to reimpose. Just as the Soviet system collapsed, Putin is also failing Russia, erasing the gains of the postcommunist period in a feckless attempt to rebuild a doomed empire.
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This study investigates the long- and short-run effects of crude oil price (COP) and economic policy uncertainty (EPU) on China's green bond index (GBI) using the quantile autoregressive distributed lag model. The empirical results show that COP and EPU produce a significant positive and negative influence on GBI in the long-run across most quantiles, respectively, but their short-run counterparts are opposite direction and only significant in higher quantiles. Thus, major contributions are made accordingly and shown in the following aspects. The findings emphasise the importance of understanding how COP and EPU affect China's green bond market for the first time. In addition, both the long- and short-run effects are captured, but long-run shocks primarily drive the green bond market. Finally, time- and quantile-varying analyses are adopted to explain the nexus between COP and EPU to GBI, which considers not only different states of the bond market but also events that occur in different time periods. Some detailed policies, such as a unified and effective green bond market, an early warning mechanism of oil price fluctuation, and prudent economic policy adjustments, are beneficial for stabilising the green finance market.
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PurposeThis paper investigates the influence of the ongoing crisis of Russia's incursion on Ukraine on the risk dynamics of energy futures contracts with high-frequency data on four different futures contracts using risk metrics of value at risk (VaR) and conditional value at risk (CVaR) for the USA market.Design/methodology/approachThe author used different generalised autoregressive conditional heteroscedasticity - Extreme Value Theory (GARCH)-EVT models and compared the performance of each of the competing models. Backtesting evidence shows that VaR and CVaR combined with GARCH-EVT better estimate risk.FindingsThe study results show that combined risk metrics are efficient and adaptive to estimating the risk dynamics and backtesting of the models, revealing that the autoregressive moving average (ARMA) (1,1)-asymmetric power autoregressive conditional heteroscedasticity (APARCH) model performs relatively better than other models.Practical implicationsThe paper has practical implications for different market participants. From the risk manager's and day traders' angles, the market participants can estimate the risk exposure in the energy futures contract and take positions accordingly. The results are important for oil-importing countries due to the developing supply crisis and price escalation, which can brew inflation in the economy.Originality/valueTo the best of the author's knowledge, the paper is the first to throw light on the risk angle of energy futures contracts during the ongoing crisis of the Russia–Ukraine war.
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Purpose: The fluctuation in the price of crude oil on the global market has created a lot of attention to the researchers to investigate its price movement. This study tries to address the problem of predicting crude oil prices in a situation of unusual circumstances. Methodology: In this study, Box Jenkins methodology was used to analyze monthly dynamics of the Brent oil price from January 2002 to February 2022. Data were first differenced to achieve stationarity, and then ACF and residual diagnostics were utilized to choose models that were used for analysis Findings: The performance of various models were evaluated and ARIMA (0, 1, 1) was found to be the best model for forecasting crude oil prices. This study further reveals that despite the corona virus and the Ukraine war having a considerable impact on crude oil prices, such a model is still capable of capturing the underlying volatility in crude oil prices. Originality/Value: Oil demand suddenly decreased as a result of the corona outbreak, but then abruptly increased as a result of the conflict in Ukraine. Therefore, there is a need to update the ARIMA model in order to best predict the price of crude oil in a time of exceptional circumstances. Because of the nature of world oil market, predictions for the medium and long term are often therefore, we have limited the scope of our forecasts in this study to a single year in order to achieve the highest level of accuracy.
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Crude oil is, without a doubt, one of the most significant commodities in the modern world. The highly contagious coronavirus, the conflict between Ukraine and Russia, and not to mention the unusual turn of events worldwide have all significantly impacted crude oil prices. Since oil is required for all critical economic activities, such as production and transportation, a forecast for crude oil prices is essential. Using a range of GARCH models at such an intense time, this study attempted to close this gap by forecasting crude oil volatility. To forecast the returns of Brent crude oil prices from January 2002 to February 2022, this study uses a family of GARCH models. In the respective family of models, GJRGARCH (1,1) was the most effective in predicting the volatility of crude oil prices. The GJRGARCH model was chosen since it had a higher likelihood value and a lower information criteria value. A diagnostic check was done to evaluate the produced model further to ensure that the proposed model was good enough for forecasting crude oil volatility. The study suggests employing the GJRGARCH technique to predict future fluctuations in exceptional circumstances..
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PurposeThe purpose of this study is to test the content validity of value-adding indicators derived from a comprehensive review of literature and expert interviews within the context of the nascent corporate real estate management (CREM) practices in Ghana.Design/methodology/approachA questionnaire survey was conducted on a panel of experts to assess the content relevance and clarity of the value-adding indicators. The individual content validity (I-CVI) index as well as the average scale content validity index (S-CVI) were computed. Preliminary interviews were analyzed using summative content analysis.FindingsThe I-CVI for relevance and clarity ranged from 0.33 to 1.00, whereas the average S-CVI was > 0.80. Critical analysis of the results by corrections, eliminations due to lower I-CVI scores and suggestions from the experts resulted in a final list of 50 indicators grouped under 10 domains. The results from the content validity confirm the applicability of the value-adding indicators in literature within the Ghanaian context. The study provides detailed sustainability indicators while introducing a new value-adding parameter that relates to CREM preparedness for pandemics such as the Covid-19.Research limitations/implicationsFurther psychometric assessment such as construct validity, inter- and intra-examiner reliability and internal consistency of the indicators is recommended.Practical implicationsThe indicators developed through the content validation can assist in the design and review of measures for the assessment of added value by corporate real estate managers and researchers.Originality/valueThe paper presents the first attempt to test and develop added value indicators within the context of a developing country by taking a systematic content validation procedure.
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PurposeThis study aims to investigate the safe-haven and hedging properties of Bitcoin against a wide variety of conventional assets before and during the coronavirus disease 2019 (COVID-19) pandemic.Design/methodology/approachThis paper uses a smooth transition regression (STR) to jointly test the hedging properties of Bitcoin in normal conditions and Bitcoin's safe-haven properties in extreme stock market conditions.FindingsHighlighting the results, the authors show that Bitcoin is able to provide safe-haven feature during the COVID-19 pandemic period while Bitcoin serves as a hedge tool in the pre-COVID-19 pandemic period. The findings also show that the prowess of the safe-haven/hedge nature is sensitive to the type of the asset market and the time horizon when switching from daily to weekly frequency data.Originality/valueThis is one of the first studies that conduct a combined analysis of the safe-haven and hedging capabilities of Bitcoin against several asset classes using an STR method. This study uses the longest sample period to yet, allowing researchers to examine Bitcoin's safe-haven and hedging features both before and after the COVID-19 pandemic.
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The recent Russian invasion of Ukraine has had significant effects on the global economy. The purpose of study is to display how Russia's aggression and the international sanctions imposed have affected the European economy, especially the petrol and gas market. Albeit the goal of sanctions was to press and hurt Russia, seems to harm in equal to the European economies mainly through immediate effects on the supply of energy. If the war in Ukraine lasts, estimated that the energy prices will stay high, and the European governments will feel uncertain about the available quantity and adequacy of energy resources.
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The election of Ebrahim Raisi as the new president of Iran in June has been the most significant development in Iran during 2021. It represented the end of an era -the reformist-pragmatist one- and the beginning of a new one controlled by the conservative establishment. This article analyses the domestic and international implications of such transition, including assessing Rouhani's performance and legacy. It also analyses the evolution of the Iranian economy, still marked by the sanctions and the Covid-19 pandemic. Besides, it describes and assesses the evolution of the nuclear negotiations transferred from the outgoing to the new administration.
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Energy prices are generally more volatile than the prices of other commodities. This is because short-term energy demand responds more quickly to the impact of economic growth than to price changes. This paper aims to analyse this phenomenon. Therefore, when an energy shock occurs, an important price change may be necessary to influence the market. Currently such shock has been caused by the COVID-19 pandemic, which has produced the biggest sustained change in demand since World War II. In the medium to long term, energy prices will rise if investment will not be on an upward trend, which seems unlikely given the current environmental protection guidelines adopted by many countries around the world. In our paper we argue that supply and demand shocks and high price volatility are likely to continue to weigh on the energy market and the global economy.
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Due to the outbreak of Covid-19, crude oil demand fell significantly. The West Texas Intermediate (WTI) crude oil price turned negative for the first time in its history. Given the importance of crude oil as a natural resource and its intrinsic tie to the economy, the price fall may significantly impact crude oil participants. Even though the pandemic has become a new norm globally, crude oil price movements will assuredly remain a concern for crude oil participants. This study uses MATLAB software to model various conditional mean and variance models to address the impact of Covid-19 on WTI and Brent crude oil prices, forecasting returns and measuring potential Value at Risk and Expected Shortfall. Daily crude oil prices of WTI and Brent are obtained from the U.S. Energy Information Administration (EIA) and cover from 4 January 2010 to 30 July 2021. The study period is divided into two periods to study the impact of Covid19 on crude oil prices. The conditional mean and variance models are evaluated by the Box-Jenkins methodology. This study found that both WTI and Brent returns do not follow a normal distribution, and the GJR(1,1) with student-t distribution outperformed the GARCH and EGARCH models. The best fit model of WTI is MA(1)-GJR(1,1), while the best fit model of Brent is MA(2)-GJR(1,1). The results reveal the impact of Covid-19 on crude oil prices and show a higher standard deviation during Covid-19 than before Covid-19. The high GARCH value indicates that the volatility is highly persistent and clustering. The forecast results reveal that the volatility of WTI and Brent crude oil prices will continue to rise in the future. Risk determination for both WTI and Brent was conducted, and the potential losses of WTI are found to be greater than that of Brent.
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The main goal of this study is to evaluate the impact of population mobility on electricity generation in Russian cities in the conditions of the spread of COVID-19, and identify hotspots. Furthermore, the evaluation is also conducted using hybrid fuzzy decision-making modelling. In this context, q-ROF DEMATEL and TOPSIS methods are taken into consideration. Additionally, a comparative evaluation is also performed with the help of Intuitionistic and Pythagorean fuzzy sets. The results are quite similar that allows to conclude that the findings are reliable and coherent. The study proves the hypothesis that human behavior changed during the COVID-19 pandemic, and electricity consumption is declining in major cities around the world. The biggest fall in energy generation was in Moscow and Yekaterinburg. In St. Petersburg and Nizhny Novgorod, the fall in energy generation is no so crucial because these cities have low building density. The study uses Long Short-Term Memory models with many different parameters. The Q-Rung Orthopair Fuzzy Sets model forecasts new COVID-19 using ten parameters. This study identifies factors influencing the spread of COVID-19 based on the theory of "broken windows" and outlines directions in limiting population mobility, which can form the basis of state policy. According to the analysis the air temperature is the variable that most affects this process.
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In recent decades passenger transportation journeys experienced a decline and this decline may due to various causes such as cost of transportation, low economic growth, exchange rate volatility, unemployment and petrol price. [...]to the best knowledge of the author, no study was conducted to determine the relationship between the aforementioned variables. [...]the main objective of the current study is to analyse the impact of the exchange rate, petrol price and unemployment rate on road passenger journeys in the South African transportation sector. [...]to minimize either monetary budget or physical and mental burden, irrespective of having their cars, people prefer to use public transport (Guo & Wilson, 2011;Onderwater & Kishoon, 2017). South African road transport depend on the imported fuel and the price of the latter within the domestic market is determined by the exchange rate. [...]the exchange rate is another economic variable that impacts road transpo0rt demand (Havenga et al., 2014).
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Purpose>Disturbances in terms of major crises such as pandemics, fluctuations in demand and oil price, energy consumption and supply chain can significantly impair the maintenance programs effectiveness and efficiency. Hence, there is an urgent need for an agile asset performance management (AAPM) framework.Design/methodology/approach>This paper's main objective is to design a comprehensive framework for an AAPM system that sustains the desired asset performance by reacting efficiently, quickly and intelligently to the changes in the operating context parameters and asset health conditions. Such a framework is adaptive to changes in scenarios and aims to systematise the decision support process, considering different objectives.Findings>The development of the proposed framework has led to identifying an innovative way of seamless integration between crucial reliability and asset management tools. Also, the methodology implementation is expected to promote the practical use of its reliability tools and enable asset stakeholders to break silo working for clear communication around asset performance.Originality/value>The implementation of the AAPM framework follows a new approach developed during this research and coined by the authors as the “8S approach.”
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The macroeconomic evolution since the beginning of 2022, worldwide, but also at regional and national level, marks major imbalances, caused by several factors, among which the vulnerability of the energy system as a whole is a major one. Demand and supply in all forms of energy, both in terms of production and distribution, have unsustainable gaps, which implies the need the need for public authorities to intervene through the design and implementation of appropriate strategies to address the challenges of the transition in energy resources and, at the same time, to remove the effects of the crisis of the energy system, a crisis that is felt in the vast majority of the states of the world.