AbstractPower is one of the key concepts for understanding world politics and great power's competition in international relations. In this regard, the main question of this paper is what will be the outlook of global power from an energy perspective in the 21st century? Based on the qualitative method and the comparative approach, the hypothesis of the paper is that the hegemonic power's ability to control and secure energy as a strategic commodity will be one of the main components of global power in the future. Considering the changes that have taken place in the 21st century, especially their impact on energy policy, the aim of the article is to examine the perspective of global power. Research findings show that in competition for achieving superiority in world politics, the European Union's dependence on energy constantly makes its position in the global arena more vulnerable. Russia, following the war in Ukraine and the use of energy as a political tool, faces a structural limitation of power in the short term. Moreover, China's position as the largest energy consumer in the hegemonic competition is affected by its energy security concerns. Also, the United States, as a producer and exporter of energy, will try to stabilise its hegemonic position in the competition with competing players, including China and Russia, by shaping new energy geopolitics and controlling the global energy markets.

AbstractThe purpose of this study is to examine and compare the validity of the environmental Kuznets curve and the relationship between carbon dioxide emissions, per capita GDP, fossil fuel consumption, oil prices and foreign direct investment in advanced oil‐importing and oil‐exporting countries from 1970 to 2020. The researchers consider these nations for their dependency on oil resources and their different economic characteristics. The Westerlund (Oxford Bulletin of Economics and Statistics, 2007, 69, 709) co‐integration test shows that the studied variables are co‐integrated in the long run in both panels of the countries. The pooled mean group‐autoregressive distributed lag (PMG‐ARDL) model established by Pesaran et al. (Journal of the American Statistical Association, 1999, 94, 621), which assesses the short‐ and long‐run nexus between the variables of interest, detects statistically significant associations, providing evidence to support the hypothesis of EKC in both groups. Furthermore, foreign direct investment and fossil fuel consumption have long‐term positive effects on CO2 emissions. The main difference between both groups of countries is that oil price has a positive effect on CO2 emissions in oil‐exporting countries, while it has a negative effect on environmental degradation in oil‐importing countries. The study suggests increasing investment in renewable energy infrastructure by encouraging research and development, providing subsidies and tax incentives for renewable energy companies and promoting large‐scale renewable energy projects as they contribute to environmental quality.

AbstractThis paper brings to light the factors that played major role in explaining the trend of the economic growth of a number of oil‐exporting countries during the pandemic period, specifically, during the years 2020–2021 and 2022. The results show that the institutional factors, adaptive restrictions as well as the degree of trade openness and the size of government fiscal intervention were major determinants of the trend of the GDP of the countries in question. Based on the findings, the paper recommends some policy measures and highlights important future challenges that test efforts of globalization.

AbstractTo successfully implement mitigation policies, it is first needed to identify the factors that contribute to carbon emissions. Based on the extended Kaya identity approach, this study investigates the driving factors of energy‐related carbon emissions in Pakistan from 1990 to 2019 using the multiplicative LMDI‐I decomposition technique with no residual term. The decomposition results reveal that the population and affluence contributed significantly to accelerating carbon emissions from energy consumption across all the sub‐periods. The cumulative effect of population size increased to 2.286 times in 2019, far greater than the impact of other factors. The cumulative effect of economic activity per person reached 1.566 in 2019. The impact of fuel quality and energy intensity is relatively minor (as the index value is less than one) most of the time. The cumulative effect of renewable energy penetration has increased from 0.998 in 1990 to 1.034 in 2019 due to the country's less mature renewable energy technologies. Fossil fuel switching is a factor that reduces carbon emissions, as the index value decreased from 0.945 in 1990 to 0.918 in 2019. The results of the study contain helpful information for lowering carbon emissions.

AbstractThe study investigated the potential non‐linear impacts of fluctuations in oil prices on domestic prices in Nigeria. Utilising the non‐linear autoregressive distributed lag (NARDL) model, the study revealed the presence of asymmetry in the behaviour of domestic prices. Both forms of oil price shocks were observed to have a negative influence on domestic prices in the short term, with only positive oil price shocks demonstrating statistical significance. However, in the long run, a distinct pattern emerged where a decrease in oil prices significantly affected domestic prices. Additionally, analysis of VAR impulse response showed a consistently negative reaction of domestic prices to oil price shocks, falling below the steady‐state equilibrium. The study concluded that changes in oil prices, in conjunction with other macroeconomic variables, affected the prices of domestic goods in Nigeria, whether in the short or long term. This underscored the complexity of Nigeria's economic landscape. Consequently, it is advisable to prudently invest excess revenue generated from rising oil prices to mitigate the adverse impacts of negative oil shocks on the economy.

AbstractThe interaction of global uncertainty and geopolitical risks with energy price fluctuations has remained a critical global issue. This interaction can impact several regions' macroeconomic performance and welfare by making fundamental energy price forecasting more difficult, which may lead to exuberant behaviour. To help producers, consumers, and regulators make informed decisions in the face of volatile and uncertain energy markets, it is critical to highlight how these uncertainties influence price exuberance. In this light, this study examines the impact of global uncertainty and geopolitical risks on international energy price exuberance using monthly data from January 1990 to October 2022. The study employs supremum augmented Dickey–Fuller (SADF) and generalised augmented Dickey–Fuller (GSADF) tests to identify energy price exuberance. Firstly, consistent with exuberant behaviour, the tests identify seven episodes of explosive behaviour in the international energy prices within the sample. Secondly, this study applies the Logit model to estimate the impact of global uncertainty and geopolitical risks on price exuberance. The estimates suggest that the heightening of global uncertainty may deflate the price exuberance. This study also observes that adverse geopolitical risks (threats and acts) in the world and Ukraine amplify the likelihood of price exuberance in the market. However, adverse geopolitical risk (GPR) in Russia negatively impacted the formation of price exuberance. This finding implies that policymakers can use global uncertainty and geopolitical risks as early warning indicators of probable price exuberance in the international energy market. The findings also indicate the need for a buffer system and safe passage for the flow of energy supply in a geopolitical conflict or a major global event. The study further shows the need for a coordinated effort in innovation, research, and development to enhance energy efficiency and minimise reliance on fossil fuels, which these uncertainties may not significantly influence.

AbstractMigration of both skilled labour force can alter economic conditions and environmental sustainability of both host and home countries. Therefore, this study aims to explore the effect of skilled labour force migration on economic growth, energy demand and environmental sustainability of home and host countries. This objective is realised by constructing a multiregional computable general equilibrium model for developed and developing countries. Furthermore, developing countries are subcategorized into four groups such as high income, upper middle‐income, lower middle‐income and low‐income countries. The results of policy simulations indicate that skilled labour migration can reduce the gross domestic product, welfare, energy consumption and carbon emissions in home countries, and the reverse is true for the host countries. Whereas the inflow of remittances to home counties can enhance their economic growth, energy consumption, and CO2 emissions, while reverse trend of remittances outflow is observed in host countries. Similarly, reverse migration can increase economic increase in developing countries along with increasing energy demand and carbon emissions. The study urges for developed countries for utilise skilled immigrants in environment friendly manufacturing industries.

AbstractPrecise electricity forecasting is a pertinent challenge in effectively controlling the supply and demand of power. This is due to the inherent volatility of electricity, which cannot be stored and must be utilised promptly. Thus, this study develops a framework integrating canonical cointegrating regressions (CCR), time series artificial neural network (ANN) and a multilayer perceptron ANN model for analysing and projecting India's gross electricity consumption to 2030. Annual data for the years 1961–2020 have been collected for variables like gross domestic product (GDP), population, inflation GDP deflator (annual %), annual average temperature and electricity consumption. The study was conducted in three phases. In the first phase of the study, the CCR method was used to check the significance of the selected variables. In the second phase, the projected values of independent variables (GDP, population, inflation GDP deflator [annual %] and annual average temperature) were predicted using the time series ANN model. Finally, a multilayer perceptron ANN model with independent variables was used to forecast the gross electricity consumption in India by 2030. The result shows that the electricity consumption in India will increase by around 50% in the next 10 years, reaching over 1800 TWh in 2030. The proposed approach can be utilised to effectively implement energy policies, as an accurate prediction of energy consumption can help capture future demand.

AbstractThe contributions of human capital to improvement in socio‐economic outcomes have generated significant interest in its determinants. On one hand, there is the orthodox view which states that energy consumption does not promote human capital development. In contrast, the heterodoxies argue that energy consumption is an essential driver of human capital development. Thus, we explore the asymmetric effects of energy consumption on human capital development for 22 African countries from 2000 to 2018 within the framework of panel non‐linear ARDL (NARDL). The long‐run results indicate that energy consumption is vital for human capital development. Specifically, in the long‐run, positive and negative shocks to energy consumption significantly improve human development. In addition, we find that economic growth, government effectiveness and foreign direct investment improve human capital only in the long‐run, while carbon dioxide emission retards it in both the long‐ and short‐runs. We found similar results for oil and non‐oil producing countries, ECOWAS, SADC, CEN‐SAD and COMESA countries.

AbstractThe article explores the non‐linear relationship between oil prices, inflation, and GDP in eight African countries that import oil from other nations. The study uses various econometric techniques, including symmetric and asymmetric dynamic panel ARDL models, mean group, and pooled mean group approaches, to examine quarterly data from 1983 Q2 to 2020 Q4. The analysis looks at both short‐term and long‐term variations to measure the positive and negative effects of oil prices and inflation on GDP. The findings reveal that the variables are related, but there are significant non‐linearities in the long run. While both rising oil prices and inflation have a positive impact on GDP in most instances, lower oil prices and inflation might have a neutral or negative impact.