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This present study is the first attempt to analyze the synergy between primary energy consumption, economic growth, natural resources, quality of government, financial development, and gross capital formation in the panel data of 30 developing countries from 1990 to 2017. For this purpose, the study employed pooled regression, fixed effects, random effects, and the heterogeneous panel Dumitrescu-Hurlin causation procedure. Our findings confirm that primary energy consumption, gross capital formation, financial development, and quality of government positively impact economic growth. The heterogeneous panel causality test confirms the feedback effect hypothesis in the connection between primary energy consumption and other factors including economic growth. These results offer new insights into policy implications for the developing countries being studied. [Display omitted] • The relationship between primary energy consumption and economic growth in a multivariate framework is investigated. • The panel data consisting of 30 developing countries for the period of 1990–2017 is employed. • Regression analysis and panel Dumitrescu-Hurlin causation methods are utilized. • Primary energy consumption increased economic growth and economic growth increased energy consumption. • Bidirectional causality exists between primary energy consumption and GDP. [ABSTRACT FROM AUTHOR]

Based on China's 30 provinces penal data, from 1990 to 2017, this paper uses the quantile regression model to estimate the impact of fossil energy abundance and clean energy abundance on economic growth and carbon dioxide (CO 2) emissions. The findings show that fossil energy abundance exerts a greater impact on economic growth in the intermediate quantile provinces such as Hebei, Jilin, Liaoning, and Shandong because these provinces have larger petroleum processing and coal gas production industries. The CO 2 emissions in the upper 90th quantile provinces such as Liaoning, Shanxi, and Shandong, receive the biggest impact from fossil energy abundance because these provinces consume more coal and oil. However, the impacts of renewable energy abundance on economic growth in the 50th-75th, upper 90th, and 75th-90th quantile groups are greater, since their renewable energy industry is growing faster. The influence of renewable energy abundance on CO 2 emissions in all quantile groups is positive, meaning it does not play a prominent role in mitigating CO 2 emissions. Therefore, each quantile province should formulate specific policies to promote the growth of renewable energy and actively develop strategic emerging industries. • Fossil energy contributes more to economic growth in the middle-level quantiles. • The impact of fossil energy on emissions in the upper 90th quantiles is the strongest. • Renewable energy abundance does not play a prominent role in reducing emissions. [ABSTRACT FROM AUTHOR]

Pakistan has been confronting economic challenges for two decades due to many factors such as the electricity crisis, among others. It is therefore essential to identify such factors that may play a constructive role in economic growth. In doing so, this study investigates the determinants of economic growth in Pakistan from 1972 to 2018. The dynamic autoregressive distributed lag (ARDL) simulations approach is applied to analyze positive and negative changes in energy consumption, industrial growth, urbanization, and carbon emissions on economic growth in Pakistan. The frequency-domain causality (FDC) test is utilized to check long-, medium-, and short-run relationships. Our empirical evidence reveals that electricity consumption and industrial value-added have a short- and long-run impact on economic growth. However, carbon emissions and urbanization have positive effects on economic growth in the short run. Consequently, we conclude that energy consumption, industrial growth, urbanization, and CO 2 emissions positively impact economic growth in Pakistan. The FDC also confirms the long-, medium-, and short-run causality hypothesis. The study suggests a requirement to integrate better electricity generation and management with the planning of economic policies. The government is advised to invest more in renewable energy to protect the environment from degradation, ban the import of low-efficiency electrical appliances, and evaluate the refugee reception policy. • The study examines the determinants of economic growth in Pakistan from 1972 to 2018. • This study employs a newly developed, dynamic ARDL simulation model. • The study also applied the frequency-domain causality (FDC) test. • Empirical results show long and short-run significant impacts on economic growth. • However, the FDC evidence revealed the short, medium, and long-run relationship. [ABSTRACT FROM AUTHOR]

The effect of the overweight epidemic on energy consumption and environmental degradation was investigated for a panel of thirty-one countries from Europe from 1990 to 2016. The quantile via moments approach was used and revealed that the overweight epidemic increases the consumption of energy and carbon dioxide (CO2) emissions. It does this in two ways. First, overweight increases the consumption of processed foods from multinational food corporations, fast-food chains and multinational supermarket chains. This process impacts the multinational food corporations and farm production positively to attend to the demand for processed foods. This increase impacts the consumption of energy from non-renewable energy sources. Second, overweight reduces physical activities as well as outdoor activities, which increases the intensive use of home appliances and motorised transportation and consequently stimulates the consumption of energy and thus CO2 emissions rise. • The overweight epidemic in 31 European countries increases the consumption of energy. • The overweight increases the use of home appliances and motorised transportation. • The decrease of physical activities by overweight increase the consumption of energy. • The increase in consumption of fossil fuels is caused by the overweight epidemic. • The urbanisation, globalisation, and economic growth causes overweith epidemic. [ABSTRACT FROM AUTHOR]

Under the Paris Agreement, each participant country established its Nationally Determined Contribution aiming at reducing its C O 2 emissions. This makes the trade-off between the electricity capacity expansion planning to meet the increase of demand and the reduction of greenhouse gas emissions a challenge, specially for developing countries, which require a higher rate of economic growth. To consider this trade-off, and identify the feasibility of the targets of the electricity expansion planning, a multiperiod optimization model is proposed considering the seasonality of supply and demand and the peak period demand. The goal is to minimize the total cost, satisfying demand constraints, the maximum C O 2 emission constraints and the power expansion supply restrictions for each source. An analysis of the Brazilian electricity matrix for the years 2020–2033 is performed considering two scenarios for the growth of the demand and two scenarios for the C O 2 target emissions The numerical simulations indicate that the present Brazilian electricity expansion planning seems adequate to meet the Nationally Determined Contribution only under a mild economic growth rate scenario. A higher economic growth rate would require a stronger economic policy related to the power expansions of the renewable sources. • A multiperiod optimization model is developed to plan the electricity matrix. • Constraints are the electricity demand, greenhouse emissions and power expansion. • The model is applied for the electricity planning in Brazil for the years 2020–2033. • Feasibility of achieving the goals established in the Paris Agreement is analyzed. [ABSTRACT FROM AUTHOR]

Solving the resource and environmental constraints faced by China benefits from studies on the decoupling relationship between the power industry's CO 2 emissions and economic development. This study provides new ideas for economic development by measuring the decoupling index of CO 2 emissions within the power industry from 1985 to 2017 based on the Tapio decoupling model. Next, this study determines the key influencing factors of the decoupling index in the long- and short-term based on the autoregressive distributed lag model. The results show that: (1) In the past 30 years, the relationship between CO 2 emissions and economic development has exhibited synchronization within the power industry; the base for the decoupling state is expansive negative decoupling and weak decoupling, and the strong decoupling state has existed for only five years. (2) The estimation results for the long-term effect indicate that coal-fired power generation efficiency and terminal energy intensity can effectively reduce the decoupling index with a coefficient of 3.0422 and 2.4822, respectively. (3) The estimation results for the short-term effect imply that decreasing terminal energy intensity reduces the decoupling index the most followed by energy consumption, and the two show coefficients of 9.5986 and 2.6404, respectively. Based on this conclusion, the study provides some recommendations for policy design, collaborative emissions reduction, and low-carbon energy construction in China's power industry. ● Interaction between CO 2 emissions in power industry and economic growth in China. ● Topia decomposition analysis, ARDL, and ECM are employed. ● Decoupling consist of expansive negative decoupling and weak decoupling. ● Strong decoupling only exists for 5 years. ● The key influencing factors of the decoupling index in the long-term and short-term is distinguished. [ABSTRACT FROM AUTHOR]

This study aims to investigate nexus among China's real output, energy consumption, and carbon emissions from 1971 to 2014. We use a nonlinear autoregressive distributed lag model to examine asymmetric transfer effects among the variables. The findings indicate that the asymmetry effect exists in the relationship among the variables in both the long and short term. Positive and negative shocks of energy consumption and carbon emissions have shown different effects on real output in sign and magnitude. Furthermore, energy consumption and carbon emissions have shown different patterns of influence on real output. In the long run, the decrease in carbon emissions has no significant impact on real output, while the decrease in energy consumption will lead to an increase in real output. In the short run, the negative shock in energy consumption in the previous periods is positively linked to real output, it means the decrease in energy consumption will lead to a decrease in real output. If the government proposes energy-conservation policies, the economic growth will be hampered in the short term but promoted in the long term. The results of this study have clear and important implications for devising energy-conservation and emission-reduction policies in China. • We empirically investigate the asymmetric nexus among real output, carbon emissions and energy consumption in China. • The bounds tests suggest presence of long-run cointegration relationship among the variables. • Asymmetry effect is found in the variable's nexus in both long-run and short-run. • Energy consumption and carbon emissions have shown different patterns of influence on the real output. • Government should be very cautious to set energy-conservation and emission-reduction policies in China. [ABSTRACT FROM AUTHOR]

High energy-consuming heavy industry is one of the main sources of China's carbon dioxide (CO 2) emissions. Based on 2005–2017 panel data of China's 30 provinces, this paper uses a quantile regression model to investigate CO 2 emissions in the heavy industry. The empirical results show that economic growth exerts a stronger influence on the heavy industry's CO 2 emissions in the 25th-50th quantile provinces, due to the difference in the fixed asset investment and heavy industrial output. The impact of urbanization on CO 2 emissions in the 10th-25th quantile provinces is lower than that in other quantile provinces because these provinces have the least number of college graduates. Energy efficiency has a smaller impact on CO 2 emissions in the upper 90th quantile province, owing to the difference in R&D personnel investment and the number of patents granted. Similarly, environmental regulations have minimal impact on CO 2 emissions in the upper 90th quantile province, since the growth rate of industrial pollution treatment investment in these provinces is the lowest. However, the impact of energy consumption structure on CO 2 emissions in the 10th-25th and 25th-50th quantile provinces is the highest, because of the provincial differences in coal consumption. • Energy efficiency has a minimal promotion effect on CO 2 emission reduction in the upper 90th quantile province. • Economic growth has a greater pulling action on CO 2 emissions in the 25th-50th quantiles. • Urbanization helps reduce CO 2 emissions, and its contribution to emission reduction in the 10th-25th quantiles is minimal. [ABSTRACT FROM AUTHOR]