Energy Economy
Saeed Rasekhi; Sara Ghanbartabar
Abstract
The utilization of natural resources, particularly energy, is essential for economic well-being. However, the increasing consumption of economic resources raises concerns about sustainable development. This study aimed to investigate the dynamic decoupling of economic growth, energy consumption, and ...
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The utilization of natural resources, particularly energy, is essential for economic well-being. However, the increasing consumption of economic resources raises concerns about sustainable development. This study aimed to investigate the dynamic decoupling of economic growth, energy consumption, and pollution in Iran from 2000 to 2020, employing the method proposed by Tapio (2005) and factor analysis on three levels of energy consumption (i.e., primary, final, and useful). The findings revealed that economic growth is often associated with negative decoupling, with this negative decoupling being more pronounced in useful and final energies compared to primary energy. Decomposing energy consumption further confirmed negative decoupling in various energy components. Additionally, the study confirmed weak decoupling between energy consumption and pollution (CO2 emissions), with stronger negative decoupling observed at lower energy levels. Furthermore, the decoupling of economic growth and pollution closely mirrors the decoupling of economic growth and energy consumption. The negative decoupling can be attributed to the inefficiency in energy consumption, limited access to new technologies, and the lack of appropriate structures due to the absence of a specific strategy for sustainable development. The research recommends the prioritization of energy efficiency across different energy levels as well as the investment in infrastructure and energy technology.IntroductionEconomic growth is intricately linked to the consumption of natural resources, with these scarce and costly resources serving as the primary catalyst for the development and acceleration of economic growth process in modern societies (Song et al., 2019; Song et al., 2020; Zhang et al., 2018). Meanwhile, the production and consumption of energy resources are associated with significant social costs and diminished welfare (Feng et al., 2020a; Feng et al., 2020b; Li et al., 2018; Rjoub et al., 2021; Wang et al., 2020). The world grapples with the challenge of balancing economic development and energy consumption (Bradshaw, 2010). Despite the looming threat of global warming, many countries, particularly developing nations, have prioritized economic development over environmental conservation (Shah et al., 2016). Consequently, decoupling energy consumption from economic growth is widely recognized as a significant achievement in the global effort to combat climate change and mitigate adverse environmental effects. The experience of developed countries instill hope for overcoming resource scarcity and growth limitations, as well as fostering green and sustainable economic growth. While relative decoupling has been achieved in numerous countries, absolute decoupling remains challenging and seemingly unattainable (Hickel & Kallis, 2020). In this respect, the present study aimed to scrutinize the decoupling dynamics of economic growth, energy consumption, and pollution in Iran from 2000 to 2020, employing the method proposed by Tapio (2005) as well as factor analysis across three energy levels.Materials and MethodsThe study followed the method proposed by Tapio (2005) in order to calculate the decoupling between energy consumption and economic growth. First, the decoupling elasticity coefficient was calculated as outlined below: (1)e(E) is the elasticity coefficient of decoupling between economic growth and energy consumption. ∆E represents changes in energy consumption during the time period under study. E (t-1) indicates energy consumption in the base year. ∆G refers to changes in GDP per capita during the time period, and G (t-1) indicates the GDP per capita in the base year (Wang & Zhang, 2021). In the method proposed by Tapio (2005), eight decoupling states can be distinguished (Figure 1).Figure 1. Decoupling states The present study conducted a more comprehensive analysis of decoupling by using factor analysis at various energy levels. In this line, the consumption across three energy levels (primary, final, useful) was divided into three distinct effects: activity (production rate), structural (change of economic structure), and intensity (technology effect). The logarithmic mean division method and each of these effects were used as follows: (2) (3) (4) (5)The study also divided economic activities into several categories: agriculture, services, industry, residential, and transportation. This categorization aligns with the most feasible separation based on the available data and statistical classifications within domestic data sources. In Iran’s energy balance, although household, public, and commercial sectors are categorized under one group, these sectors were individually reported, and the residential sector was distinguished from the commercial and public sector (as the service sector).Results and DiscussionFigure 2 presents the decoupling dynamics of Iran’s economic growth, energy consumption, and carbon dioxide emissions during 2000–2020. The figure is divided into two parts focused on various energy levels for different components: the first part depicts the decoupling of economic growth and energy consumption, while the second part shows the decoupling of energy consumption from carbon dioxide emissions. As show in Figure 2, the decoupling of economic growth and carbon dioxide follows a pattern similar to and influenced by the decoupling process between economic growth and fossil energy consumption. The decoupling of economic growth and fossil energy consumption aligns with changes in decoupling at different energy levels (primary, final, and useful), reflecting the significant share of fossil energy in Iran’s overall energy consumption. Figure 2 also highlights the weak decoupling between fossil energy consumption and carbon dioxide, which can be attributed to the nature of fossil fuel pollution. Consequently, the decoupling of economic growth from carbon dioxide is influenced by fossil energy consumption.The first part of Figure 2 reveals various forms of negative decoupling (expansive negative, weak negative, and strong negative) concerning economic growth and energy consumption. Correspondingly, the second part indicates a generally weak decoupling for different energy levels and carbon dioxide emissions. Within the energy consumption components, the intensity component exhibits strong decoupling, though it fluctuates, sometimes displaying positive decoupling (weak, recessive, and strong) and occasionally negative decoupling (expansive and strong negative)—which can be caused by the drop in technology. This finding aligns with the second part of Figure 2, where the decoupling of the intensity component and carbon dioxide experiences fluctuations. Notably, the structural component in the first part of Figure 2 exhibits the strongest negative decoupling from economic growth, signifying a change in Iran’s economic structure that has exacerbated the decoupling between energy consumption and economic growth. However, the decoupling of the structural component and carbon dioxide, as depicted in the second part of Figure 2, remains within the range of weak but fluctuating decoupling.Finally, the first part of Figure 2 indicates that economic growth is often associated with negative decoupling (expansive and strong negative) from total energy consumption. Despite weak decoupling in initial periods and subsequent fluctuations, the last two years show strong decoupling between total energy consumption and carbon dioxide. Overall, Figure 2 illustrates a fluctuating trend in the decoupling of economic growth and energy consumption over time, predominantly featuring negative decoupling, which corresponds to the decoupling trend between energy consumption and carbon dioxide. Among the components of energy consumption, the intensity component exhibits strong negative decoupling, while the structural component displays weak decoupling, both characterized by fluctuating patterns. This fluctuation may stem from the absence of a specific plan and strategy to decouple economic growth, energy consumption, and carbon dioxide.Figure 2. Decoupling of economic growth, energy consumption, and carbon dioxide emission in Iran during 2000–2020 Expansive negative decoupling decoupling ExpansiveWeak decouplingStrong decouplingRecessive decoupling Recessive coupling Weak negative decoupling Strong negative decouplingConclusionUsing the method proposed by Tapio (2005) and factor analysis across three energy levels, the present study investigated the dynamics of decoupling economic growth, energy consumption, and pollution in Iran during 2000–2020. The findings underscored challenges faced by the policy aimed at reducing energy consumption, which is primarily due to the dependency of Iran’s economy on energy. Specifically, the research showed the dependency of Iran’s economy on energy on energy consumption across all three levels: primary energy, final energy, and useful energy. Moreover, the results highlighted a low degree of energy efficiency, particularly at higher energy levels (secondary and useful). Considering the relation between environmental pressure and restrictions on economic growth, there is a pressing need to address energy intensity and energy efficiency to strike a balance between economic growth and energy consumption. The observed negative decoupling in structural, intensity, and activity effects suggests a lack of a specific strategy in Iran’s economy concerning the decoupling and balance between energy consumption and economic development. In light of these findings, it is imperative to focus on enhancing energy consumption efficiency across diverse energy levels. Additionally, the study recommends prioritizing more effective decoupling in sustainable development policies concerning energy consumption, economic growth, and pollution.
Energy Economy
Seyyed Mohammad Ghaem Zabihi; Fatemeh Akbari; Narges Salehnia
Abstract
The relationship between economic, financial, political risks and per capita carbon emission (CO2) is considered as one of the major global challenges. The effect of these three factors on carbon emissions is very important. Therefore, the current research seeks to investigate the role of economic, financial, ...
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The relationship between economic, financial, political risks and per capita carbon emission (CO2) is considered as one of the major global challenges. The effect of these three factors on carbon emissions is very important. Therefore, the current research seeks to investigate the role of economic, financial, and political risk in reducing per capita carbon emissions (CO2) by using the very new and fresh approach of quantile-on-quantile regression (QQR) modeling in the annual period from 1990 to 2018. The statistical relationship between the variables mentioned in Eviews12 and Matlab2022 software platform has been investigated for Iran. The results show that the economic risk variable in all quantiles (0.5 to 0.95) had a positive effect on carbon emissions per capita in all quantiles (0.5 to 0.95), and this positive relationship was relatively stronger in the quantiles (0.3 to 0.95), of the economic risk variable. the financial risk variable in all quantiles (0.5 to 0.95) had a positive effect on carbon emissions per capita in all quantiles (0.5 to 0.95), and this positive relationship was relatively weak in all quantiles (0.5 to 0.95) of the financial risk variable, as well as Politics risk has a positive effect on carbon emissions per capita in all quantiles (0.5 to 0.95) and this positive relationship is relatively weak in all quantiles (0.5 to 0.95) of the Politics risk variable. Thus, the need to pay attention to Iran's economic, financial, and political stability to improve the environment's quality and reduce carbon emission (CO2) is very important.1.IntroductionThe most significant global threat in the 21st century is climate change and global warming, primarily driven by carbon dioxide (CO2) emissions (Akadiri et al., 2021; Oladipopo et al., 2021). The rapid development of modern industrial societies worldwide in recent years has led to a gradual rise in the consumption of fossil fuels, including coal, oil, and natural gas. The increased consumption has resulted in the substantial emission of CO2 (Danish et al., 2019; Dong et al., 2018; Zhao et al., 2021). In recent years, there has been an enhanced awareness among governments and international organizations worldwide regarding the impact of climate change on the economy, society, and the environment (Gambier et al., 2022). The heightened awareness has prompted the adoption of environmental protection policies (Roncroni et al., 2021). However, the implementation of these policies requires significant expenditures. Consequently, the role of financial stability in addressing the risks associated with climate change and reducing greenhouse gas (GHG) emissions has gained increasing importance (Sun et al., 2022). Research indicates that a stable financial environment is conducive to stimulating production and investment, albeit with a potential increase in energy consumption and CO2 emissions (Solimana et al., 2017).Global warming and CO2 emissions are closely intertwined with economic and political risks (Adoms et al., 2018). Global uncertainties have increased the volatility of economic and political policies on a global scale. Any form of uncertainty, be it social, political, economic, or war-related, invariably impacts economic activities (Blatman & Miguel, 2010; Guidolin & La Ferrara, 2010). Economic (in)stability plays a crucial role in shaping the environment in which companies operate, influencing the decision-making processes of economic entities. Similarly, political instability can significantly impact investors’ decision-making. Moreover, political risk is on the rise in nearly all countries, exerting pressure on military budgets at the expense of construction budgets. This situation leads to a reduction in overall production within the country, and the decreased production results in a further decline in energy consumption, and ultimately leading to a decrease in carbon emissions (Ahmad et al., 2022). Employing a novel methodology known as quantile-on-quantile regression (QQR), the present research aimed to explore the impact of economic, financial, and political risks on per capita carbon emissions in Iran during 1990–2018. Regarding the methodology and the specific focus, no similar research has been conducted in Iran. Therefore, the current study stands out for its innovation in terms of subject matter, methodology, and the targeted context, potentially yielding significant findings.2. Materials and MethodsThe QQR approach is a novel method for analyzing bivariate equations. Introduced by Sim and Zhu (2015), it combines ordinary regression and nonparametric estimation, providing more comprehensive insights compared to traditional estimation methods. QQR examines the intricate relationship between the lower and upper quantiles of the data series, which yields a more realistic analytical perspective than conventional methods (Yu et al., 2022). This study used the QQR approach to investigate the relationship between economic, financial, and political risks and per capita carbon emissions. In this line, the econometric model was formulated as in Equation (1): (1) In Equation (1), CO2t denotes per capita carbon emissions in year t. ERt represents economic risk in year t. FRt is financial risk in year t. PRt indicates political risk in year t, and 𝜀𝑡 is a component of the model error.Several methods were used to analyze the data, including the descriptive analysis, assessment of variable reliability, the diagnostic test (esp., the disruption components autocorrelation test), the correlation test, Johansen’s co-accumulation, and finally the quantile-by-quantile model estimation.3. Results and DiscussionUtilizing the innovative econometric approach of quantile-on-quantile regression (QQR), the research explored the statistical relationship between economic, financial, and political risk variables and per capita carbon emissions in Iran during 1990–2018. The findings revealed that the economic risk variable had a positive effect on carbon emissions per capita across all quantiles (0.5 to 0.95), with this positive relationship being relatively stronger in the 0.3–0.95 quantiles of the economic risk variable. Similarly, the financial risk variable had a positive effect on carbon emissions per capita in all quantiles (0.5 to 0.95), although this positive relationship is relatively weak across all quantiles of the financial risk variable. Likewise, political risk positively influenced carbon emissions per capita in all quantiles (0.5 to 0.95), with this positive relationship being relatively weak across all quantiles of the political risk variable. The research results align with the findings of Zhang and Chiu (2020), Abbasi and Riaz (2016), Mehmet et al. (2018), and Zaidi et al. (2019).4.ConclusionThe present study aimed to examine the correlation between economic, financial, political risks, and per capita carbon emissions in Iran during 1990–2018. The findings emphasize the significance of maintaining economic, financial, and political stability in Iran as it is crucial for enhancing the quality of the environment and mitigating carbon emissions.
Energy Economy
Ali Faridzad; Shamsi Ghasemi; Mehdi Ahrari
Abstract
A review of empirical studies in the field of insurance of upstream oil and gas projects suggests that domestic insurance companies and insurance consortiums in Iran rely on the experience of reinsurance companies to determine premiums and risk conditions. Given the economic sanctions and restrictions ...
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A review of empirical studies in the field of insurance of upstream oil and gas projects suggests that domestic insurance companies and insurance consortiums in Iran rely on the experience of reinsurance companies to determine premiums and risk conditions. Given the economic sanctions and restrictions on determining precise premiums and conditions for direct insurance and reinsurance of oil assets, it is necessary to establish a method to determine premiums even under normal circumstances that can be referred to international reinsurers. To address this need, the present study adopted an empirical method that uses risk-based valuation and the monetary value at risk (VaR), which covers a wide range of relevant oil and energy insurance aspects. The results showed that the research method can determine the premium of oil assets following international standards, taking into account expert opinions and other domestic considerations.IntroductionOil and gas continue to be among the primary sources of energy globally, hence a crucial and fundamental part of the world economy. The various sectors within this vast field offer significant capacities and resources at a large scale, including research, equipment, and resources for exploration, development, and utilization, as well as the derivatives in the real sector processes. In addition, transportation, exchanges, transactions, physical markets, and stock exchanges also play a significant role in this industry. The world economy is thus highly dependent, both directly and indirectly, on the oil and gas industry. It is evident that the global oil and gas industry involves a vast amount of capital and risk, which is more complex and extensive than one may imagine. The industry interacts with numerous sectors of the economy, with extensive links that exceed beyond a single field. Considering the relatively small share of oil and energy insurance in the portfolio of the insurance industry, there are various factors that prevent the entry of insurance services into this area on a significant scale. One significant obstacle is the lack of scientific studies on determining the value at risk for oil assets, which is a crucial factor in determining the volume and size of insurance premiums for insurable oil and gas assets. Using the valuation and estimation of monetary VaR of oil assets, the present study aimed to develop a method for insurance companies to determine the insurance premium of oil and gas assets. An example was provided to demonstrate the applicability of the proposed method in practice. Materials and MethodsTo conduct a risk-based valuation, the study employed Smith’s method as well as the method proposed by Knapp and Heij in order to estimate the value at risk for oil assets.The NPV for the valuation model of exploration and development risk will be as follows (Smith, 2004): (1)Where CF0 is the drilling cost, is the probability of a failed well and {CF1, CF2... CFr} are the expected cash flows in case of success of the well and (i) is the discount rate.According to Knapp and Heij (2017), identifying risk factors, which are variables that pose a risk for an oil asset, is crucial in estimating the value at risk. The risk factors are evaluated based on their probability of occurrence.The monetary VaR is estimated based on the insurable value of a physical asset, which is typically the replacement cost or the actual cash value of the asset covered by standard insurance policies.To estimate the value at risk, two probabilities are combined, which are determined based on the total insurable value (TIV). For instance, if there are five risk groups denoted as j (j=1,...,5), vj represents the sum of the insurable value for each type. TIV is defined as the total of all five groups, as follows: Furthermore, Pinc represents the probability of an event occurring within a year. Pj is the conditional probability of damage in group j occurring in relation to a particular event. Then monetary VaR is then defined as follows: (2)It is important to note that TIV is derived from the method proposed by Smith (2004), which can be used to assess the value of the entire property or its individual parts and components.The insurance rate and premium can be estimated on the basis of the model of exploration and development risk, along with the future discount rate. This estimation includes the initial cost (drilling or installation cost) CF0 and is given by the following equation:NPV, in Relation (1), is replaced by the future value (FV) or the total insurable value (TIV) of the oil asset.CFt = CF0: NPV is equivalent to book value or price determined by official experts or official pricing authorities.PDH: Probability of occurrence of major risks, which is considered equivalent to catastrophic risks leading to total damage.i: It represents risk insurance premium, which is equivalent to the probability of the occurrence of conventional risks that each oil asset faces according to its specific conditions.Now Relation (1) will be changed to Relation (3): (3)Now monetary VaR is calculated as follows: (4)In equation (4), V is TIV, which is equivalent to FV calculated based on Relation (2).Results and DiscussionThe study used the information on the insurance policy of HP-2000 drilling rig of North Drilling Company. Table 1 Information on the HP-2000 drilling rigThe value of the drilling rigReinsurance premium rateMarket premium rateInsurance premium12000.0040.00283.4(billion rials) (million rials)* Source: issued insurance policyThe future value of the drilling rig for one year is described in the following table:Table 2 The future value of the drilling rigNPV iFV12000.00220.0032400(billion rials) (billion rials)* Source: research resultsThe monetary VaR based on the future value at risk (FV), which is equivalent TIV, for the insured drilling rig is as follows according to Relation (2):Table 3 The monetary VaR of the drilling rigFV=TIV MVR24000.00220.84.3(billion rials) (million rials)* Source: research resultCatastrophe risk (Pinc) and the 5-fold decomposed risks of the oil rig are determined based on expert opinion, which will be the basis of monetary VaR estimation.The premium values and the rate calculated based on the monetary VaR were compared to the premium values in both cases of reinsurance and market (Table 4). Premium rate is obtained by dividing premium, which in the proposed methods is equal to Monetary VaR (MVR), by oil rig price.Table 4 Comparison of the insurance premium rate based on the MVR method with the reinsurance and market rateMVR rateReinsurance rateMarket rate0.00350.0040.0028* Source: research resultsConclusionThe present study highlighted the characteristics and significance of the oil, gas, and petrochemical industry within the global economy, emphasizing the extensive interactions of this industry with various sectors of the economy, particularly in the field of insurance.The study used a distinctively innovative methodology which combines Smith’s (2004) risk valuation of oil assets with Knapp and Heij’s (2012; 2017) monetary VaR approach to determine the insurance premium rate. The proposed research method allows for the determination of an insurance premium rate that is equivalent to international reinsurance rates, based on the factual, environmental, and market conditions. The study offers insurance and oil engineering experts the possibility of calculating an appropriate insurance premium rate for an oil project based on the identified risks using empirical and technical knowledge, as considered in the proposed method.
Energy Economy
Davood Daneshjafari; Mohammadmahdi Hajian; Javad Jafarzadeh
Abstract
In long-term gas contracts, there is usually a risk for the seller that the buyer will refuse to take delivery. For this reason, the condition of obligation to take or pay in such contracts has become common. Commitment condition is a condition that obliges the buyer in the gas sales contract to pay ...
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In long-term gas contracts, there is usually a risk for the seller that the buyer will refuse to take delivery. For this reason, the condition of obligation to take or pay in such contracts has become common. Commitment condition is a condition that obliges the buyer in the gas sales contract to pay the seller a part of the contract price, which is determined as a percentage of the total amount, even if he does not receive the agreed gas volume. The research question is whether this condition has economic efficiency? Will a long-term balance between buyer and seller be an option for this condition in the contract or not? To answer these question, first, with the concept of evolutionary game theory, we have shown a picture of contracts before the existence of this condition and after its formation. Then, by setting the normal form of the game and using Python software, we have repeated this game thousand times, the results show that accepting the condition of commitment to take or pay will be stable evolutionary equilibrium. From this perspective, the inclusion of such a condition in the contract creates economic efficiency, and the policy recommendation in this regard would be for policy makers to prefer a lower definite income to a higher probable income by including such a condition.
Energy Economy
Aida Vaghef; Zahra Abdolmohammadi
Abstract
In oil-exporting countries, it is important to have a clear evaluation of the oil sector at the national and regional levels. In input-output literature, the traditional and extraction methods are often used to analyze the status of economic sectors. These methods have two major shortcomings: double-counting ...
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In oil-exporting countries, it is important to have a clear evaluation of the oil sector at the national and regional levels. In input-output literature, the traditional and extraction methods are often used to analyze the status of economic sectors. These methods have two major shortcomings: double-counting of linkages and having a flaw to show the changes in income of the labor. In this paper, to overcome these shortcomings and to provide a more realistic picture of the status of the oil sector at national and regional levels, a comparative comparison has been used between Iran and Canada focusing on their two major oil-exporting provinces, Khuzestan and Alberta. For this purpose, the production-to-production approach based on the Sraffa-Pasinetti-Leontief theoretical model which its main concept is the induced effect of value-added will be used. The results show that the oil sector creates 0.0435 and 0.0372 units of induced value-added in Iran and Khuzestan. In Canada and Alberta the corresponding figures are 0.3173 and 0.4382. Therefore, this sector has more interdependency with the other sectors in both national and regional levels in Canada (as a well-developed country) than Iran (as a developing country). However, services and industry sectors absorbed more decomposed induced value-added of the oil sector in comparison to other sectors. Therefore, national and regional policies should be implemented to have diversified products and prepare the requirement of having the most of interdependency prerequisites between the sectors.
