Nooshin Karimi Alavijeh, Mohammad Taher Ahmadi Shadmehri, Fatemeh Dehdar, Samane Zangoei and Nazia Nazeer
While science has researched the impact of air pollution on human health, the economic dimension of it has been less researched so far. Renewable energy consumption is an…
Abstract
Purpose
While science has researched the impact of air pollution on human health, the economic dimension of it has been less researched so far. Renewable energy consumption is an important factor in determining the level of life expectancy and reducing health expenditure. Thus, this study aims to investigate the impact of renewable energy, carbon emissions, health expenditure and urbanization on life expectancy in G-7 countries over the period of 2000–2019.
Design/methodology/approach
This study has adopted a novel Method of Moments Quantile Regression (MMQR). Furthermore, as a robustness check for MMQR, the fully modified ordinary least square, dynamic ordinary least squares and fixed effect ordinary least square estimators have been used.
Findings
The results indicated that renewable energy consumption, health expenditure and urbanization lead to an increase in life expectancy across all quantiles (5th to 95th), whereas higher carbon dioxide emissions reduce life expectancy at birth across all the quantiles (5th to 95th).
Practical implications
The empirical findings conclude that governments should recognize their potential in renewable energy sources and devise policies such as tax-related regulations, or relevant incentives to encourage further investments in this field.
Originality/value
This paper in comparison to the other research studies used MMQR to investigate the impact of factors affecting life expectancy. Also, to the best of the authors’ knowledge, so far no study has investigated the impact of renewable energy on life expectancy in G-7 countries.
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Emad Kazemzadeh, Mohammad Taher Ahmadi Shadmehri, Taghi Ebrahimi Salari, Narges Salehnia and Alireza Pooya
The purpose of this study is to examine oil price shocks on US shale oil supply and energy security during the period 2000q1–2020q4.
Abstract
Purpose
The purpose of this study is to examine oil price shocks on US shale oil supply and energy security during the period 2000q1–2020q4.
Design/methodology/approach
In this study, the Shannon–Wiener index was used to calculate energy security, and then a structural vector autoregression (VAR) was applied to measure the effect of oil price shocks.
Findings
The results of the variance decomposition indicate that oil prices account for about 20% of changes in US shale oil production, while it explains only about 3% of changes in energy security. Finally, historical decomposition confirms the results of impulse response functions.
Originality/value
The novelty of this study is that so far, no study has examined the effect of oil price shock on shale oil production and energy security in the USA using the structural VAR model. This study also used the latest Shannon–Wiener index as a measure of energy security in the USA. The reason for selecting this index is that, in addition to considering the share of the total consumption of each primary energy, the share of energy imports from each country as well as the political risk of energy exporting countries to the USA are also included.
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Emad Kazemzadeh, Mohammad Taher Ahmadi Shadmehri, Taghi Ebrahimi Salari, Narges Salehnia and Alireza Pooya
One of the most important ways to pay attention to sustainable economic development is to invest in green technology and alter the energy consumption structure (ECS) in countries…
Abstract
Purpose
One of the most important ways to pay attention to sustainable economic development is to invest in green technology and alter the energy consumption structure (ECS) in countries. Changing the ECS can be important in two ways: first, it increases the diversity of energy consumption and reduces energy dependence on other countries. Second, the use of highly polluted nonrenewable energy sources (such as oil and coal) is reduced, leading to the transfer of energy to natural gas with less carbon emissions or renewable energy. To this end, the authors examined the asymmetric effects of eco-innovation on the US ECS from 1980 to 2019. This paper aims to address this issue.
Design/methodology/approach
In this research, the nonlinear autoregressive distributed lag (ARDL) (NARDL) model is used and the results are compared with the linear ARDL model.
Findings
The ARDL results also confirm the positive effects of oil prices and GDP per capita in the long run. On the other hand, short-term and long-term Wald test results confirm the nonlinear effects of eco-innovation (LPATENT) on US ECS. These results indicate that 1% positive shock in LPATENTˆ+ increases the ECS by 0.179, while 1% negative fluctuations (LPATENTˆ-) leads to a decrease (−0.085) in the ECS. However, the ARDL results, in general, show the positive effects of LPATENT on the ECS in long run. Evidence suggests that ignoring nonlinear effects can lead to inaccurate results. Policy suggestions for environmental technology innovation are presented in the results.
Originality/value
This research has innovations in various aspects so that the previous studies in this field have examined the effects of environmental innovation on renewable or nonrenewable energy consumption, and so far no study has been done on the ECS. In this research, the Shannon–Wiener index has been used to calculate the ECS.
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Emad Kazemzadeh, Mohammad Taher Ahmadi Shadmehri, Taghi Ebrahimi Salari, Narges Salehnia and Alireza Pooya
The USA is one of the largest oil producers in the world. For this purpose, the authors model and predict the US conventional and unconventional oil production during the period…
Abstract
Purpose
The USA is one of the largest oil producers in the world. For this purpose, the authors model and predict the US conventional and unconventional oil production during the period 2000–2030.
Design/methodology/approach
In this research, the system dynamics (SD) model has been used. In this model, economic, technical, geopolitical, learning-by-doing and environmental (social costs of carbon) issues are considered.
Findings
The results of the simulation, after successfully passing the validation test, show that the US unconventional oil production rate under the optimistic scenario (high oil prices) in 2030 is about 12.62 million barrels/day (mb/day), under the medium oil price scenario is about 11.4 mb/day and under the pessimistic scenario (low oil price) is about 10.18 mb/day. The results of US conventional oil production forecasting under these three scenarios (high, medium and low oil prices) show oil production of 4.62, 4.26 and 3.91 mb/day, respectively.
Originality/value
The contribution of this study is important in several respects: First, by modeling SD that technical, economic, proven reserves and technology factors are considered, this paper models US conventional and unconventional oil production separately. In this modeling, nonlinear relationships and feedback loops are presented to better understand the relationships between variables. Second, given the importance of environmental issues, the modeling of social costs of CO2 emissions per barrel of oil is also presented and considered as a part of oil production costs. Third, conventional and unconventional US oil production by 2030 is forecast separately, the results of this study could help policymakers to develop unconventional oil and plan for energy self-sufficiency.