Iranian Energy Economics

Abstract Among the most important indicators that depend on political-economic-social stability is inflation control; because people's activism has a high tendency towards the stability of inflation; Therefore, gaining political power in societies depends on providing a program to control inflation. The increase in the high inflation rate is associated with macroeconomic instability, increased welfare, unfair distribution of wealth, and a decrease in household purchasing power. Monetarist considers excessive growth of money volume, excess demand in the commodity market, some cost pressure and increase in the price of production inputs, and institutionalists consider structural factors and bottlenecks in various economic and commercial sectors to be the main cause of inflation. Therefore, knowing the factors affecting inflation and providing a solution to control and reduce inflation can lead to socio-economic justice. The components of good governance can also lead to the reduction of inflation through the channel of increasing productivity and improving institutional quality and increasing the effectiveness of monetary and financial policies. This research aims to investigate the factors influencing inflation with an emphasis on good governance in oil exporting countries using the generalized moment method (GMM) in the time period (2011-2021). The obtained results indicate that the inflation break, the difference between GDP growth and liquidity growth had a positive effect and good governance had a negative effect on the inflation rate.

Abstract The implementation of the mechanism of carbon border adjustments or carbon tariffs as a tool to deal with carbon leakage and reducing the competitiveness of production, was implemented by the European Union in October 2023 under the transitional phase and it will be implemented under the definitive phase from January 2026. Some countries, including the United States of America and Japan, have also predicted similar policies. This is while developing and developed countries have committed to take measures to combat climate change and reduce carbon emissions based on the Paris Agreement. This shows the concern of countries applying carbon tariffs because of carbon leakage even after the creation of the Paris Agreement. Considering that the European Union has announced that it will first apply carbon tariffs to energy industries, this study uses the GTAP-E model to investigate the change in the amount of carbon dioxide emissions in Iran's industries as a result of the imposing of carbon tariffs by the European Union, the Japan, the United States of America and all regions on Iran's energy intensive industries. The statistical of the research includes 141 regions and 65 section in the GTAP10 data base that published in 2019. The estimation of the model shows that under all four scenarios, the amount of production and carbon dioxide emissions will decrease in the energy-intensive industries sector and the entire industries of Iran.

Abstract Forecasting electricity demand is one of the most important issues of the electrical energy system. Considering the structural changes in electricity demand and the stylized facts of electricity consumption in different sectors of demand, forecasting the amount of electricity demand will clarify the prospects of changes in the Iran's electric energy system in the medium and long term. By using new approaches, this prediction will have higher reliability. In this research, using the state-space approach and combining it with Markov regime switching, the main sources of uncertainties were included in the model. By using the data of electric energy feed-in the system to supply electricity demand and the average real price of electricity and temperature and the number of customers in the ten-year period of 2013-2022, the parameters of the model were estimated based on the state-space approach and Markov regime switching. State-space approach in the form of time-varying parameters and Markov switching approach in the form of variance fluctuations were included in the model. The results showed that the model based on this integrated approach gives a more accurate prediction than the classical model of electricity demand. The standard error of the estimated equations is reduced to 0.1 (in the competing model, the standard error of the corresponding equation is 0.03, and in the integrated approach, it is 0.002 for peak and 0.004 off-peak periods). The sensitivity of electricity demand to the real price of electricity and temperature changes is decreasing and the demand for marginal costumer is increasing.

Abstract The growing natural gas consumption has made it difficult to supply gas to power plants and large industries in the cold seasons and forces these industries to use polluting fuels. One of the consequences of this situation is air pollution. Due to the inelastic demand of natural gas, command policies cannot prevent the increasing trend of gas consumption. So it is necessary to use incentive policies to manage consumption. Recently, in developed countries, regulatory instruments based on exchange of certificates, such as tradable savings certificates based on the market, have been significantly developed and had positive results. Considering the importance of gas consumption management and with the aim of creating a mechanism for certificates of natural gas exchange, in this research, based on the experiences of the leading countries in this field and the results of consensus of the elites, design a mechanism for the exchange of consumption savings certificates of natural gas. The results of Delphi analysis showed that the mechanism of issuing and exchanging natural gas saving certificates is feasible and this mechanism makes households and business units find motivation to save natural gas consumption. Also, power plants and other large industries can fulfill part of their natural gas needs in the cold season by buying certificates from households in the established market, and in this way they can access clean fuel in the cold seasons of the year.

Abstract This study examined the impacts of economic policy uncertainty and oil price on carbon dioxide emissions as a criterion of environmental quality in seven OPEC member countries from 1990 until 2019. According to the theoretical framework, economic policy uncertainty can directly or indirectly affect the quality of the environment, such as through direct policy adjustment, consumption, and investment channels. In this regard, with the help of panel data, the experimental models of this study were estimated and evaluated by the Fully-modified Ordinary Least Squares (FMOLS) method. The results indicate that the economic policy uncertainty and the oil price variables are statistically significant in both models, and their coefficient is positive. In other words, higher policy-related economic uncertainty and oil price over this period has led to higher carbon dioxide emissions and, thus, lower environmental quality in OPEC member countries. Ultimately, the estimates in the second model confirm an inverse U-shaped relationship between economic growth and the quality of the environment of these countries in the mentioned period, based on the Environmental Kuznets Curve (EKC) hypothesis.

Abstract Energy is a fundamental input in production, and its availability and use are essential for the social, economic, and technological advancement of a nation. Energy consumption and greenhouse gas emissions have been increasing along with rising production, primarily sourced from non-renewable resources. The increase in production and economic development has led to higher greenhouse gas emissions, resulting in climate change, which poses a new challenge for countries. Energy efficiency is the most beneficial way to reduce greenhouse gases and control energy supply. In this regard, one of the responsibilities of governments is to find tools to minimize the national economy's energy efficiency gap by increasing energy efficiency within the economy.

For this purpose, in this study, we used the Shephard energy distance function to define the energy efficiency index and the stochastic frontier analysis technique to estimate the energy efficiency gap in selected oil and gas producing countries from 1990 to 2022. We examined some factors influencing the energy efficiency gap and observed that the energy efficiency gap increased from 6% to 29% during the years under review. Additionally, foreign direct investment and total factor productivity have a negative impact, while urbanization has a positive impact on the energy efficiency gap.

Abstract This study employs a vector autoregression approach with time-varying parameters (TVP-VAR) to investigate the spillover of volatility and risk among the stock markets of 13 OPEC and OPEC+ member countries, alongside Gold, Brent Oil, OPEC Oil, and the Dollar index. Daily data spanning from March 1, 2014, to March 1, 2023, is utilized for analysis. Our findings reveal several key insights. First, the average systemic risk within the network of investigated variables has escalated in the years following the onset of the COVID-19 pandemic. Second, among the investigated countries, the stock markets of Saudi Arabia, Kuwait, UAE, Russia, Malaysia, and Nigeria serve as transmitters of fluctuations within the network, while the stock markets of Bahrain, Kazakhstan, Venezuela, Oman, Iran, Iraq, and Mexico act as receivers of volatilities. Third, significant volatilities in Iran's stock market returns originate from idiosyncratic shocks, with variables such as OPEC oil prices and the stock markets of Bahrain, Iraq, and Kuwait playing pivotal roles in explaining these fluctuations. Fourth, approximately 60% of the volatility in gold returns and the dollar index can be attributed to idiosyncratic risks. Fifth, compared to other OPEC+ member countries, the Saudi stock market's volatility exerts a more substantial influence on the volatilities observed in the global oil, gold, and dollar markets.

Abstract it is of strategic importance to investigate the methods of financing the establishment of petroleum refinery units. Meanwhile, economic sanctions have seriously affected the access to financing methods, especially the financing methods of petroleum refinery projects. For this purpose, this research has identified and ranked the financing methods of petroleum refinery projects according to the current conditions of the country's economic system. In order to identify the types of financing methods for petroleum refinery projects, all available library documents such as books, articles and related research reports were studied. In the next step, with the aim of firstly ensuring the statistics of all methods and secondly extracting the criteria for prioritizing financing methods, interviews were conducted with financing experts in the refinery and petrochemical industry, and the findings were analyzed using thematic analysis method. In the following, after the initial review and refinement of financing methods by the focal group, a questionnaire for prioritizing financing methods was compiled and provided to the experts. Examining the results of prioritization showed that joint venture (JV), build, operate and transfer (BOT), build, lease and transfer (BLT), lines of credit, engineering, procurement, construction and finance (EPCF), exchange of oil and oil products with other goods and equipment and even the project, participation in the net profit (Net Profit Interest) and pre-sale agreements (Off-Take Agreement), eight "main and priority methods", for the financing of suitable petrochemical projects in the current coordinates of Iran's economy

Abstract Finding effective factors on productivity for its impact on economic growth and development is essential for societies, especially countries that are in the process of development. By examining new researches and analyzing the economic conditions and problems of developing countries, we find the importance of the factor of energy consumption, especially non-renewable energies such as oil consumption, and the question of whether more energy (oil) consumption will lead the country towards productivity improvement is crucial for developing a development plan and roadmap. The study investigates the effect of energy consumption (oil) on total factor productivity using the Cobb-Douglas production function and solo growth model, for 10 developing countries including Iran, based on the Human Development Index from1996 to 2022. In this research, using panel data, first through the primary model, which is the generalized Cobb-Douglas function linear model, the total factor productivity was calculated, and then through the secondary model, including the total factor productivity variable, the research hypothesis was investigated.

The results showed that the effect of energy consumption on total factor productivity (TFP) in selected developed countries is negative and meaningless and the effect of urbanization is negative and significant. Also, the effect of energy consumption and urbanization on the productivity of all factors in emerging and developing countries is negative and significant. The desirability of the Watson-R camera statistic and the significance of the overall regression were reviewed and confirmed in each group.

Abstract This qualitative study investigated the impact of utilizing renewable energy sources in football stadiums. The research focused on experts in sustainable development, stadium managers, and technical engineers involved in the Iranian Football Premier League from 2019 to 2020. Data analysis was conducted using qualitative content analysis methods. Research participants were selected through purposeful and snowball sampling methods, ultimately leading to 12 interviews that reached theoretical saturation. The analysis resulted in 44 open codes, which were further categorized into three key concepts: environmental management, improving the social and cultural situation, and enhancing the economic status. These categories encompassed areas such as reducing environmental risks, managing energy resources and pollution, improving social attitudes and welfare services, urban beautification, reducing organizational costs, promoting the stadium's brand, and generating income. Given global environmental crises and the impact of sports on the environment, it is recommended that government officials, policymakers, and sports managers support the utilization of renewable energy sources like solar and wind energy in football stadiums. These actions are necessary for sustainable development and carbon-free sports.

Abstract Abstract:

Due to current sanctions, financing upstream oil industry projects faces significant challenges. To design an effective financing portfolio for these projects, we first identified financing criteria through a literature review. Using the fuzzy Delphi method, we screened and determined six main criteria. The fuzzy DEMATEL technique revealed that among these criteria, repayment structure constraints, currency exchange rate fluctuation risk, external monitoring factors (cause type), and The financing cost factors, the time required to acquire financial resources, and the risk of failing to obtain financial resources are of the effect (dependent) type. Additionally, the time required to acquire financial resources has a greater weight compared to other criteria. Considering the weighted criteria the fuzzy TOPSIS technique showed that issuing forward contracts had the highest priority, while obtaining international bank loans had the lowest priority. The study involved 12 experts from the oil industry and the banking and capital markets, who provided responses to structured questionnaires.

Abstract This study investigates the application of recurrent neural network (RNN) models—specifically RNN, long short-term memory (LSTM), and gated recurrent unit (GRU)—in predicting the stock indices of the Iranian energy industry. Using daily time series data from May 1, 2020, to May 1, 2024, the dataset was divided into a training period (80%) and a testing period (20%). In the first step, the optimal architectures of each model (estimating hyper-parameters) were determined for prediction horizons of 1, 2, 5 (one week), and 20 trading days (one month). Subsequently, prediction errors of the three machine learning models were compared with the linear econometric model (ARIMA) across various forecast horizons. The findings in two areas of cross validations of machine learning models as well as predication error reveal the following insights: First, as the forecast horizon increases, the batch size of optimal prediction decreases for all three machine learning models, and the larger the input training sample size leads to the smaller batch size. Second, in short-term forecast horizons (1, 2, and 5 trading days), machine learning models—particularly LSTM—demonstrate lower prediction errors than ARIMA, while in the 20-trading-day (1-month) forecast horizon, ARIMA's predictive accuracy approaches to the nonlinear machine learning models. Third, forecast accuracy decreases as the horizon lengthens, with accuracy dropping from approximately 98.5% (for a 1-day horizon) to 92.5% (for a 20-day horizon). Finally, selecting the appropriate forecasting method for the stock market indices of energy industries depends on the forecast horizon and data characteristics.

Abstract The purpose of this article is to evaluate the progress of fuel subsidies as well as the budgetary and distributional effects of the possible removal of such subsidies in Iran. In this research, the analysis of the machine learning scenario model, the microsimulation model of the tax benefit for Iran, along with the consumption and subsidy microdata of households since the subsidy reform has been used. The results of the research show that the subsidy for consumption is advanced towards an increase, while the subsidy for gasoline and diesel tends to decrease. The paper's simulations show that removing all fuel subsidies would increase poverty and inequality due to the importance of the domestic gas subsidy to low-income households. Eliminating gasoline and diesel subsidies will not affect poverty and inequality, while helping to reduce government spending. It was also shown that using part of the budget saved from fuel subsidy removal to increase social assistance payments in Iran can be a mechanism to compensate low-income families after fuel subsidy removal.

Abstract In the process of globalization, the interdependence between countries increases, and changes in economic policies introduce uncertainty shocks to both domestic and foreign economies. In oil-dependent countries, fluctuations in global oil prices significantly impact income and Gross Domestic Product (GDP). This study examines the impact of uncertainty in global economic policies and oil prices on Iraq's economic growth from 2008 to 2022. The research employs the nonlinear Autoregressive Distributed Lag (NARDL) econometric model. The results indicate that an increase in the uncertainty of global economic policies leads to a decrease in Iraq's economic growth in the short term, with this effect persisting in the long term. Conversely, a reduction in the uncertainty of global economic policies leads to an increase in Iraq's economic growth over both timeframes. Regarding oil prices, a reduction in uncertainty in the short term (at the first lag) fosters economic growth; however, at the second lag, it has a negative impact. In the long term, a decrease in oil price uncertainty contributes to an increase in economic growth. An increase in oil price uncertainty does not significantly affect economic growth in the short term; however, in the long term, it leads to a decline in Iraq's economic growth. These findings highlight the asymmetry in the effects of economic policies and oil prices on Iraq’s economic growth.

Abstract Commodity price fluctuations, particularly oil prices, significantly impact the stock markets of commodity-exporting countries. This study investigates the relationship between commodity price changes and stock market returns in selected commodity-oriented countries. The analysis, conducted using the ARDL approach over the period January 2, 2001, to February 16, 2023, reveals that in the long run, oil price changes have a direct and significant positive relationship with the stock market index in all studied countries except Iran. This suggests that rising oil prices generally lead to a rise in the stock market value of these countries. The impact of other commodities, however, varies across the selected countries. Interestingly, the study identifies oil as the most influential commodity affecting their stock markets. These findings highlight the critical importance of understanding the dynamics between commodity prices and stock market returns for both investors and policymakers in commodity-exporting countries. With this knowledge, investors can make informed decisions, while policymakers can develop strategies to enhance the resilience of their stock markets in the face of commodity price fluctuations.

Abstract With the increase in electricity consumption in the country over the last few years, despite the strategic nature of the steel industry in the country, the supply of electricity for steel companies has faced serious problems; In this study, we have first examined the strategies for improving the quality and increasing the production rate of Gol Gohar Steel Company through forming a SWOT matrix. Then, considering that sustainable electricity supply is identified as the key strategy to achieve this goal, using multi-criteria decision-making methods, different power plants are ranked for electricity supply of this company. For this purpose, using two main indicators of maintenance planning, i.e. reliability and availability, the options have been evaluated, and the ranking of power plants has been done using different methods: AHP, EDAS, TOPSIS, and MAUT. Also, for the weighting of criteria, two methods of forming a pairwise comparison matrix (PCM) and Shannon's method have been used. The results indicate that among the three power plants—Kahnouj, Goharan, and Samangan—the power supply from the Samangan power plant will be the most reliable for the Golgohar company. Specifically, in three out of four decision-making methods, the Samangan power plant was identified as the best option, while it ranked second in the remaining method. Additionally, the Kahnouj power plant and the Goharan power plant were identified as the second and third-best options, respectively.

Abstract Reports from the International Renewable Energy Agency (IRENA) predict that the expansion of renewable energy resources at the regional level significantly influences employment, contributing to the creation of direct, indirect, and induced jobs across various sectors. In light of this, the present study examines the impact of renewable energy development on employment in two groups of countries—developing and developed—both possessing renewable energy resources, over the period 2008 to 2022. The analysis employs the Dynamic Ordinary Least Squares (DOLS) method.

The findings reveal that installed renewable energy capacity has a positive effect on employment in both country groups, contributing to increased job opportunities. Furthermore, the study identifies a positive relationship between GDP and employment in both developing and developed countries. In contrast, wages show a negative association with employment across both groups. Finally, the results indicate that gross capital formation positively affects employment in developing countries but has a negative impact in developed countries.

Abstract Today, almost 80% of the world's energy is produced from fossil fuels, which significantly release environmental pollution. Since economic growth in Iran is mostly achieved through fossil fuels, a study was conducted to explain the relationship between Iran's gross domestic product and total energy demand using the framework of the EKC, this study first highlights some points about pollution and energy consumption And then it deals with the sustainable development and EKC, in the experimental model part, ARDL model is estimated as the chosen method by conducting relevant tests, and then in the second part, using dynamic systems, the model is estimated period 2000-2045. The result indicates that Iran is in the first stage of the Kuznets curve and 59% of changes in energy demand are due to changes in GDP. For this purpose, the policy recommendation that can be considered in this article is education and public awareness of the dangers of using fossil fuels and investing in renewable systems, which on the one hand leads to economic growth and leads to the transition from the first stage of the EKC.

Abstract Effect of Oil Shocks on Stock Returns in Iran: Sing Restriction Approach

Considering that the price of oil has changed a lot over the past decades and these changes can have a great impact on the financial markets of a country like Iran, the effect of oil shocks on the return of the Iranian stock market has been emphasized in this study. To measure the impact of oil shocks on financial market returns (in this study, stock market returns) in Iran, the sign-restricted VAR model has been used. The data of the study includes stock returns as a representative of Iran's financial market, Texas oil prices, and exchange rate uncertainty, and the period of the study covers the spring of 2017 to the spring of 2014. The results of the research show that the impact of the oil price shock on stock returns is significant and increasing, and then decreasing and lasting. The impact of exchange rate uncertainty on stock returns is also significant and increases and then decreases.

Keywords: Oil Prcice, Exchange Rate Volatility, Stocke Return, Impuls Respons

JEL Classification: H54,G14,G21,R32

Abstract Abstract

The industrial sector, especially energy-intensive industries, is considered one of the most important polluting sectors. Given that the industrial sector itself includes several production sub-sectors and the pollution caused by them is different, first the amount of carbon dioxide emissions at the level of all two-digit ASIC codes during the years 2004-2022 has been estimated. Then, the industry that emitted the highest amount of carbon dioxide (the industry producing non-metallic mineral products) was considered as a polluting industry, and the factors affecting the carbon dioxide emissions of that industry were identified. The results of the present study, using Bootstrap regression estimation during the period under study, show that the amount of carbon dioxide emissions emitted by the non-metallic mineral industry is a positive function of the amount of energy carrier consumed, physical capital intensity, and human capital intensity, and a negative function of the intensity of human resource skills, industry capital expenditures, and research & development expenditures.

Abstract The Ecological Footprint Index measures the human demand for natural resources, which leads to climate change, biodiversity loss, soil degradation, and environmental pollution. This study uses data from 1980 to 2021 and the Threshold Autoregressive (TAR) method to examine the effects of energy consumption, economic growth, globalization, and financial development on the ecological footprint in Iran. The results reveal that the impact of variables on the ecological footprint depends on the initial energy consumption threshold (3.6 exajoules). In both lower and higher regimes of this threshold, energy consumption and globalization positively and significantly contribute to increasing the ecological footprint, with these effects being significantly amplified in the higher regime. Additionally, economic growth significantly impacts the ecological footprint only in the higher regime, indicating the adverse effects of advanced economic development on the environment. Financial development, on the other hand, negatively and significantly affects the ecological footprint in both regimes, demonstrating its potential to reduce environmental pressures. However, this mitigating effect is stronger in the lower regime. Therefore, it is essential to devise effective strategies to reduce fossil fuel consumption and improve energy efficiency during advanced stages of economic growth to alleviate environmental pressures.

Abstract This study investigates the relationship between the Global Economic Policy Uncertainty (GEPU) index and global crude oil prices, employing a combination of classical econometric models—such as VAR, BEKK, and DCC—and advanced machine learning techniques including LSTM, GRU, and XGBoost. The results indicate a bidirectional and predictable relationship between GEPU and oil prices, along with volatility spillovers. However, the immediate and short-term effects of shocks between the two variables are generally weak and often statistically insignificant. The relationship is more evident at the level of volatility correlation, and in the long run, rising oil prices can contribute to increased global economic instability. Bidirectional Granger causality between the two variables is confirmed, yet impulse responses within the VAR framework are largely insignificant. Volatility-based models and wavelet analysis reveal that co-movements in volatility intensify during crisis periods, and volatility spillovers between GEPU and oil prices are substantial. The application of advanced machine learning methods enhances the accuracy of forecasting the long-term and noisy relationships between the variables. The findings underscore the complexity and multidimensional nature of the interaction between global economic policy uncertainty and oil prices.

Abstract Iran has been facing economic sanctions for more than four decades. In general, sanctions affect the environment and sustainable development in several ways. Restrictions on financial flows, transfer of technology, pressure on government budgets, pressure on the environment, and many other issues are among the issues that have put pressure on the environment and prevented the process of sustainable development in Iran. The present study has used the "calculable general equilibrium" method to simulate the effect of sanctions on Iran's economy and is purposefully applied and developmental and descriptive-analytical in nature.

The research model is designed based on the Lafgren standard model according to the characteristics of Iran's economy and in accordance with the purpose of the research, and eight scenarios are applied to the research model. According to the results of the, if the government's goal is to "reduce the budget deficit while reducing the pressure on the environment", the best option is to increase the tax rate. If the government's goal is to "reduce pollution while increasing economic growth and development" but does not take into account the budget deficit, increasing research and development incentives is recommended. If the government's goal is to "grow and develop in the long run and increase the competitiveness of the business community in order to be more resilient to sanctions," the scenario is to increase research and development efficiency throughout the economy. Therefore, the results indicate that the strengthening of research and development in various economic sectors will be significantly important

Abstract Deteriorating condition of facilities and operational units in Iran's oil sector necessitates immediate rehabilitation and modernization initiatives. This urgency is compounded by escalating operational costs and the constraints of domestic resources within the Ministry of Petroleum, highlighting the need for increased private sector investment and involvement. In this context, the implementation of Rehabilitation, Operation, and Transfer (ROT) contracts as a public-private partnership model presents a promising approach to tackle these challenges.

This study seeks to examine the obstacles and advantages linked to the adoption of the ROT framework within Iran's oil industry. Utilizing a qualitative research methodology, the investigation incorporates case studies, with data collected through document analysis and comprehensive interviews. The results indicate notable disparities in how the ROT model is perceived in Iran compared to other nations. To date, only two public-private partnership projects have achieved operational status under the National Iranian Oil Company (NIOC). Despite various challenges, limited experiences with the Build-Operate-Transfer (BOT) model suggest a potential for future public-private collaborations. Moreover, the ROT model's extensive applicability in Iran's oil sector, particularly concerning NIOC projects, is reinforced by its advantages over traditional models. Given that ROT projects require lower capital investment and entail reduced risks associated with product ownership, engineering metrics, and land allocation, they are likely to be preferred over BOT or other conventional contractual arrangements such as design and construction within Iran's oil industry.

Abstract Renewable energies have been proposed as a key solution to deal with climate change and reduce dependence on fossil fuels. The development and expansion of this type of energy has been dependent on various factors, including human capital and green financing. Human capital and green financing are two key factors in the development of renewable energy. Investing in the training and development of specialized human resources and providing sufficient financial resources can help accelerate the transition to renewable energiesand sustainable energy. The current research is the effect of two factors of human capital and green financing on renewable energy in ECO member countries. Therefore, in the period from 2000 to 2024 and based on the Cross Sectional Augmented Autoregressive Distributed Lag (CS-ARDL), the relationship between the research variables has been analyzed. The results show that in Eco, there is a positive and significant relationship between human capital and green financing and renewable energies. Also, the results of this research, in addition to clarifying the issues of sustainable development, provide an insight based on the examination of the complexities of the transition towards the perspective of greener energies, for policy makers and researchers in this field.

Abstract This study uses a Dynamic Computable General Equilibrium (DCGE) model, Iran’s 2011 Social Accounting Matrix (SAM), and 1970–2022 data in R software to examine the impact of uncertainties in hydroelectric energy consumption, urbanization, natural resource rents, industrial output, and per capita income on Iran’s ecological footprint. Five scenarios with 5% increases in each variable were tested via Monte Carlo simulations. Sensitivity analysis showed that a 5% rise in hydroelectric energy consumption (Scenario 1) cut the footprint by 2.124%, underscoring clean energy’s role. Conversely, urbanization (Scenario 2) led to a negligible increase (2.06E-46%), indicating efficient urban planning. Natural resource rents (Scenario 3) most adversely increased the footprint by 3.122% from unregulated exploitation. Industrial output (Scenario 4) rose negligibly (0.002%) due to green tech, while per capita income (Scenario 5) saw a 1.74E-05% increase. The findings stress prioritizing clean energy, regulating resource extraction, and advancing sustainable industry.

Abstract This paper examines the impact of natural resource rents on financial development in selected MENSA (Middle East and North Africa) countries from 2000 to 2022 using an ARAL panel model. The results indicate that, in the short term, rising natural resource rents negatively affect financial development, primarily due to an over-dependence on natural resource revenues and a decline in non-oil sectors. However, in the long term, the adverse effects of these rents are alleviated, suggesting that effective management of natural resource revenues and investment in financial infrastructure can bolster financial development. The research findings reveal that trade openness has a positive and significant influence on financial development. Expanding international trade and attracting foreign investment through access to new technologies enhances the financial performance of MENSA countries. Conversely, increasing urbanization negatively impacts financial development, as the pressure on government finances to address infrastructure and municipal service needs restricts investment opportunities in the financial sector. Overall, effective management of natural resource revenues, enhancement of governance quality, and investment in financial infrastructure mitigate the negative effects of natural resource rents on financial development. Trade openness also contributes positively to financial development, while rising urbanization adversely affects it due to the strain on government finances.

Abstract This study aimed to design a strategic energy management model based on the Chinese approach. The research was conducted within an interpretivist philosophical framework and adopted an inductive reasoning approach. It is an applied-developmental study in terms of its purpose and is classified as a non-experimental (descriptive) study in terms of data collection methods. A qualitative research design was employed to achieve the research objective. The participant population included university professors and managers from the Electricity and Energy Deputy of the Ministry of Energy. Purposeful sampling was used, and theoretical saturation was reached with 10 participants. Data were collected through semi-structured interviews and a decision matrix-based questionnaire. The validity of the qualitative coding was confirmed using Holsti's method (0.756) and Cohen’s kappa coefficient (0.681). The face validity of the questionnaire was confirmed, and its reliability was supported through an estimated intra-class correlation coefficient (0.815). The interviews were analyzed and coded using thematic analysis in MaxQDA 20 software. In the second phase, Interpretive Structural Modeling (ISM) and MicMac software were used to determine the relationships among the constructs and to design the model. The findings indicated that China’s authoritarian political system and spatial planning framework influence the country’s cultural soft power projection. This cultural projection affects international communication, diplomacy, and the harmonization of domestic and global systems, ultimately leading to strategic energy management. In turn, strategic energy management contributes to environmental preservation and China’s accelerating economic growth.

Abstract The aim of this article is modeling of consumer financial preferences in selecting between gas-powered and gasoline-powered vehicles, without considering infrastructure limitations and drawbacks of CNG vehicles. For this purpose, using quantitative analysis based on present value and economic modeling, the financial benefits of dual-fuel vehicles are assessed under various vehicle price and fuel price scenarios. The results indicate that, given the current price difference between gasoline and CNG, along with vehicle purchase and maintenance costs, consumers do not derive financial advantages from switching to CNG. Furthermore, infrastructure limitations and disadvantages of CNG vehicles, such as refueling station availability and safety concerns, hinder broader acceptance of dual-fuel vehicles. However, if the fuel price differential reaches 70,000 Iranian Rials (IRR) and dual-fuel vehicles are only 250 million IRR more expensive than gasoline-powered vehicles, the acceptance rate for CNG increases to 58.71%. On the other hand, higher acceptance rate of CNG vehicles lead to reduced greenhouse gas emissions and contribute to the country’s trade balance improvement.

Abstract The diversity and complexity of the export portfolio is one of the requirements for upgrading the production structure. But since Iran's economy depends on oil revenues, it has little diversification. Therefore, it is always exposed to adverse external shocks, and it becomes important to study the structure of dependence between oil rents and the non-oil economy. In order to model the dependence, data on oil rents, GDP, services value added, manufacturing value added, merchandise trade, and bank credit from 1970 to2020 were used. Also, due to the dependence of government expenditures on oil revenues, non-linearity, asymmetry in the data and asymmetric distributions, univariate and bivariate Vine copula functions were used. The research results show that in the first tree of the C-Vine model, there is a strong and asymmetric association, especially in the upper tail, between oil rents, GDP, merchandise trade and bank credit. In other words, the impact of a positive shock is greater than a negative shock. In addition, a positive Symmetric correlation was observed between oil rents and the services added value. A stronger correlation at left tail between oil rents and manufacturing value added a greater effect of the negative shock. Therefore, macroeconomic stabilization policies did not succeed in protecting the Iranian economy in the event of oil shocks, and the diversification model did not lead to a flexible structure.

Abstract The energy sector, a central lever for environmental sustainability, needs precise indicators to evaluate how production factors mitigate resource degradation. This study introduces the Exergetic Productivity (ExP) index to quantify the exergy-based utility of capital and labor across industries. We employ an analytical panel-data design covering fourteen industries in nine developed economies from 2000 to 2019, with data compiled from international statistical databases. ExP is derived from the marginal rate of technical substitution between exergy and the other production inputs (labor and capital) implied by a Cobb–Douglas production function, whose coefficients are estimated via panel regression. The results show that in energy-intensive industries, inputs exhibit higher exergetic productivity and thus greater effectiveness in preventing exergy destruction. Over time, this potential has trended downward for capital while remaining broadly stable for labor. These patterns highlight heterogeneity in how industries convert investments and work effort into avoided exergy loss. Overall, the ExP index offers a concise and policy-relevant metric for tracking energy policy performance, prioritizing technological upgrades, and steering sustainable industrial transformation.

Abstract Economic uncertainty influences key economic variables, particularly energy commodity prices, leading to volatility and economic instability. Each energy commodity has unique characteristics affecting its price behavior. This study examines the dynamic relationship between global economic policy uncertainty (GEPU) and energy commodity prices using the LA-VAR model.

Findings indicate that the impact of GEPU on Brent oil, natural gas, and coal prices varies based on the nature of crises and the level of uncertainty. Before the 2008 financial crisis, GEPU significantly influenced oil price changes, but this relationship weakened or reversed afterward. Additionally, price fluctuations in energy commodities contributed to increases in GEPU, particularly during the 2008 crisis and the COVID-19 pandemic—periods when energy prices reached extreme highs and lows.

The study identifies a causal link between energy commodity prices and GEPU during the 2008 financial crisis, while during the COVID-19 pandemic, this link was specifically between Brent crude oil prices and GEPU. These findings suggest that sudden energy price fluctuations, especially in times of crisis, contribute to increased global economic policy uncertainty. Moreover, price increases in energy commodities have a stronger impact on GEPU than price decreases.

Abstract Iran, with its diverse energy reserves, is one of the countries that pays attention to energy production, distribution, and consumption. One of the factors affecting the energy efficiency gap is the country's financial system. The financial system can improve or weaken energy efficiency by providing financial resources and facilitating access to capital required for energy projects. The performance of the financial system, on the one hand, increases energy consumption, which leads to a decrease in energy efficiency, and on the other hand, promotes technology and increases the level of energy efficiency. In this study, the function of the financial system on the energy efficiency gap in Iran during the period 1370-1403 is examined. First, the energy efficiency gap is estimated using the Shepard energy distance function and stochastic frontier analysis, and then we examine the effects of financial systems on the energy efficiency gap in those years using the smooth transition regression (STR) technique. The findings show that the regime change occurred at a threshold value of 3.14 for the financial system variable. The slope of the transition function between the two regimes was 3.21, indicating a smooth transition between the two regimes. The variables of the banking system, stock market, and technological progress in the high and low regimes have an impact on reducing the energy efficiency gap in Iran. Other variables such as the insurance industry, government spending, foreign investment, ,energy structure in the studied period do not have an impact on the energy efficiency gap in Iran.

Abstract Energy subsidies in Iran have always accounted for a significant portion of the gross national income over the years better distributing income, and establishing social justice. In the present study, first, to obtain a quantitative index of the distribution of gasoline subsidies, the Gini coefficient (between 0 and 1) and the concentration index (between -1 and +1) are extracted regarding the inequality of gasoline consumption distribution between household income deciles in the country using household income-expenditure data. In order to examine the effectiveness of gasoline price reform in 2019 compared to previous and subsequent years, the extraction of the above indices was repeated for the years 2018 to 2024. All the results obtained from the calculations of the Gini coefficient and the concentration index indicate the existence of severe inequality in gasoline consumption in favor of the wealthier households, in such a way that the Gini coefficient fluctuated between 0.66 and 0.68 and the concentration index for the weighted deciles of the provincial gross expenditure between +0.32 and +0.37, which indicates the severity and stability of the inequality of distribution in gasoline consumption and subsidy, despite the political developments during the period. Finally, the factors affecting the gasoline consumption of households in Iran were estimated in the form of four regression models. The model showed that factors such as the household's place of residence (urban or rural), gender, occupational group and educational group of the household head, number of private cars, etc. had an effect on household gasoline consumption.

Abstract In Iran, an average of about 40 million cubic meters of oil-associated gas is flared daily, and the country will rank second in the world in this field in 2023. Since 2014, one of the goals of the National Oil Company has been to collect oil-associated gases by transferring NGL units to the private sector. The aim of this research is to evaluate the financial and economic aspects of the Hoveyzeh Persian Gulf Oil-Associated Gas Refining Project by modifying the oil-associated gas pricing formula, considering the social discount rate, and selling carbon emission certificates. For this purpose, the cost-benefit analysis method has been used in this research. To modify the oil-associated gas pricing formula, first the amount of carbon dioxide emissions in the event of not collecting oil-associated gas was calculated and then it was valued based on the market price of Iranian carbon dioxide. Then, the value of unreleased carbon dioxide was factored into the oil-associated gas pricing formula. The results show that gas processing with oil is not justifiable from the private sector perspective and the net present value of the project is -598.59 million dollars. However, by modifying the pricing formula and issuing carbon certificates, the internal rate of return (IRR) increases by 11.58% and the net present value of the project reaches 1908.63 million dollars, which indicates the economic justification of the project from the perspective of society.

Abstract In oil contracts involving exploration activities, the determination of a field’s commerciality is a critical and complex issue that significantly influences the decision to advance to development and production stages. This study provides a comprehensive legal and economic analysis of field commerciality and proposes a refined framework for drafting oil contracts. Employing a descriptive-analytical and comparative methodology, the research draws on documentary sources and examines contracts from multiple countries. The study first delineates the technical, legal, and economic aspects of commerciality. It then revises the conventional Net Present Value (NPV) model by incorporating two often overlooked parameters: the intrinsic value of un-extracted subsurface resources and the environmental impacts of the project as hidden costs. The research further emphasizes the necessity of establishing clear, quantifiable criteria for assessing commerciality, clarifying the authority responsible for its determination, and introduces innovative contractual provisions such as the possibility of renegotiation at the conclusion of the appraisal period. Findings suggest that precise and quantitative commerciality criteria can mitigate contractual disputes and safeguard the host country’s interests against investment risks.

Abstract In recent years, the development of eco-innovation has been recognized as one of the main drivers of reducing the non-renewable energy consumption, the importance of which is undeniable for combating climate change and promoting environmental sustainability. Research evidence shows that green innovations can change energy consumption pattern and lead to a reduction in the demand for fossil fuels by improving energy efficiency and utilizing renewable resources. Therefore, examining the effects of these innovations on energy consumption is not only necessary for developing energy management strategies, but it can also help identify the challenges and opportunities on the path to a green economy. However, this issue has not been addressed in the previous literature. Accordingly, the present study aims to investigate the asymmetric role of eco-innovation in the non-renewable energy consumption in Iran during the period 1975–2022. The findings, based on the Nonlinear Autoregressive Distributed Lag (NARDL) model, show that the effect of eco-innovation (EI) in the research model is asymmetrical, such that positive changes in eco-innovation lead to a decrease, while negative changes lead to an increase in the non-renewable energy consumption (NRE). In addition, the results indicate that human capital (HC), industrialization (IND), and foreign direct investment (FDI) have a negative effect, whereas economic growth (EG), trade openness (TO), urbanization (URB), and the dummy variable to the Islamic Revolution of Iran (DU) have a positive and significant effect on the non-renewable energy consumption.

Abstract Flaring is a phenomenon that exists in most oil-producing countries and refers to the gases associated with oil that are produced during oil extraction and are not collected or utilized for various reasons. The present study examines the impact of flaring, along with other explanatory variables, on Iran's per capita GDP during the period 1366-1402 using the ARDL method. The results of the model estimation, while confirming the existence of a cointegration relationship between the variables, show that in the long term, the impact of flaring on GDP per capita is positive and significant (with a coefficient of 0.58). A review of foreign studies in this field reveals differences in findings, with some studies showing a positive coefficient and some showing a negative coefficient. The present study shows a positive coefficient for flaring in Iran. The positive coefficient may be surprising at first glance, but it is theoretically justifiable (which is explained in the theoretical foundations section of the paper). Furthermore, in an oil economy like Iran, given that there is a positive correlation between oil production and GDP, and since flaring is a side effect of oil production, this positive relationship is to be expected. At the same time, it can be stated that the increase in revenues resulting from the high volume of oil production is sufficiently compensating for the expected decrease in revenues (due to flaring).

Abstract The industrial sector, as the largest consumer of fossil energy and a vital pillar of economic development, plays a crucial role in influencing economic growth and environmental changes. The present study aims to dynamically analyze the relationship between the uncertainty of energy consumption and carbon dioxide emissions in the industrial sector and Iran’s economic growth, while considering uncertainties in the available data and economic variables. Using data from the Central Bank of Iran and the Energy Balance Sheets, and applying a fuzzy modeling approach over the period 1991–2021, the study estimates the impact of industrial energy consumption, population, labor force, capital stock, industrial CO₂ emissions, and trade openness on economic growth. The main novelty of this study lies in integrating variable uncertainties into the dynamic analysis of the relationship between energy consumption, CO₂ emissions, and economic growth. The findings reveal that labor force, capital stock, and industrial CO₂ emissions exert the most significant impacts on per capita GDP, with coefficients of 2.74, 2.022, and 2.32, respectively. Moreover, energy consumption shows a significantly positive effect on economic growth with a coefficient of 4.19e-15, while, at the lower bound with a membership degree of 0.9, industrial CO₂ emissions negatively affect economic growth with a coefficient of –0.82. Based on the results, it is recommended that carbon taxation policies and incentives for renewable energy adoption be implemented as strategies to reduce environmental uncertainties and promote sustainable economic growth.

Abstract The global crude oil market, as one of the most significant commodity markets, has always been influenced by geopolitical, economic, and institutional factors. Since its establishment in 1960, OPEC has played a central role in managing supply and stabilizing prices. However, in recent years, it has faced challenges such as the rise of U.S. shale oil production, environmental pressures, and the emergence of new market players. With the formation of the OPEC+ alliance and the increasing production interventions of this group in the global market, analyzing its impact on benchmark crude oil prices has become a strategic issue.This study employs monthly data from 2007 to 2025 and applies a multivariate GARCH model with a BEKK approach to examine the effects of OPEC+ production on benchmark crude oil prices. The results indicate that OPEC+ production policies have significantly reduced price volatility and have effects comparable to the U.S. stock market index, while shale oil production exerts downward pressure on prices and weakens the coalition’s competitive position. Moreover, OPEC+ has remained the dominant market player through leader–follower strategies, although the expansion of shale oil has altered the market’s equilibrium structure.These findings highlight the importance of flexible and resilient policymaking for oil-dependent countries such as Iran, emphasizing the need to withstand price shocks. Future research can focus on analyzing the impacts of these price fluctuations on macroeconomic indicators.

Abstract The exchange rate is one of the most important macroeconomic variables that affects many other economic variables. For this reason, examining the factors determining the exchange rate has always been one of the most important issues in the country's foreign exchange policy. The purpose of this article is to examine the impact of oil prices, economic policy uncertainty, and global geopolitical risk on the exchange rate in Iran during the period 2008-2023.

For this purpose, the autoregressive distribution lag (ARDL) method has been used. The results indicate that the impact of economic policy uncertainty, oil price and global geopolitical risk on the exchange rate variable is symmetric. The impact of geopolitical risk variable on the exchange rate in the long run and the economic policy uncertainty variable on the exchange rate in the short run and long run is positive and significant. While the impact of oil price on the exchange rate is negative in the short run and positive and significant in the long run.

Abstract Energy is one of the most important economic factors in growth and development, which increases its consumption and is harmful to the environment. Therefore, according to the need to use energy, energy is a necessity from energy sources. The use of energy sources from several components that can use it, the importance of which is social capital. In this regard, the current research was conducted with the aim of investigating the impact of social capital on the consumption of renewable energy in OPEC member countries in the period of 2015-2024 and using the method of dynamic joint correlated effects. The results show that social capital has a positive effect on renewable energy consumption in OPEC member countries. In this regard, in order to accelerate the transition towards renewable energy consumption, attention and strengthening of social capital in OPEC member countries should be considered.

Abstract The current research has been compiled and presented by emphasizing the role of production optimization problem as a practical necessity in oil and gas economic studies and discussions that can transform the measured into optimal management decisions. In this study, the optimal path of crude oil production in Ahvaz oil field resulting from the natural gas injection of South Pars phase 13 has been achieved using an optimal meta-heuristic method called particle swarm algorithm in a period of twenty years. Also, in order to simulate the maximum technical and physical conditions of both fields, the concept of the maximum effective discharge rate, and in order to apply the economic dynamics of the global oil and gas market, three price scenarios and two discount rate scenarios have been used. The results of the study show that in case of implementation of programs to increase oil recovery, improve oil recovery, and inject gas at the same time as production from the oil field, During the modeling and simulation period, more than 7.5 billion barrels of additional oil in the extractable volume and 3.5 billion cubic feet of injected gas were re-extracted, and the cumulative production of the oil field was 12.8 billion barrels based on the planned production. Currently, in the revised field development plan, it reaches more than 15.3 billion barrels based on the optimal production path of this study.

Abstract Unauthorized electricity consumption and electricity theft are among the most important forms of non-technical losses in electricity distribution networks. They may appear in consumption data as deviations from normal usage patterns, abnormal load variations, or discrepancies between delivered and recorded energy. In addition to imposing economic losses on power utilities, these phenomena affect grid stability, consumption monitoring, and energy policy. This paper presents a structured review of data-driven approaches for consumption anomaly detection in smart power grids, with an emphasis on unauthorized electricity consumption and the Iranian context. Statistical methods, machine learning, deep learning, federated learning, and hybrid approaches based on smart meter data are reviewed and compared in terms of required data, detection capability, scalability, privacy, implementation cost, and practical limitations. The reviewed studies indicate that hybrid approaches, particularly those combining smart meter data with machine learning and deep learning algorithms, have shown greater potential for reducing detection errors and identifying complex patterns of unauthorized consumption. However, their effective use in Iran depends on the development of smart metering infrastructure, access to reliable data, attention to security and privacy, and the design of corrective policies consistent with energy justice.

Abstract Load forecasting is crucial for planning power plants, meeting electricity demand, and building reliable and efficient energy infrastructure. It is divided into three types: long-term, medium-term, and short-term. Short-term load forecasting (STLF) is particularly important due to the use of distributed energy resources, integration of renewable energy sources, and demand management in smart grids. Various models, such as artificial intelligence, traditional, or hybrid models, are used for this purpose. Accuracy in short-term forecasting is vital for efficient management of electrical systems. Factors like weather, holidays, and temperature affect forecasts, but using large amounts of data can be time-consuming and costly. Therefore, this study uses a simpler model that meets practical needs. Two new models for short-term load forecasting are proposed: one is a hybrid model based on the Mackey-Glass time series with fuzzy logic, and the other is a predictive fuzzy logic model. Both are trained using the Wild Horse Optimization (WHO) algorithm. These models were tested with multi-year data from Iran’s Markazi Province. The models’ performance was evaluated using metrics like Mean Absolute Percentage Error (MAPE) and Mean Square Error (MSE) and compared with three other methods (LSTM, ARIMA, and ANFIS). Results show that the proposed model significantly reduces MAPE and MSE compared to other methods, offering better performance.

Abstract Objective: This study aims to identify and analyze the key drivers and potential future scenarios of supply chain financing in the energy sector of Iran, with the objective of systematically examining the forthcoming challenges and opportunities in this domain.

Method: Initially, 25 driving forces were identified through a comprehensive literature review and expert interviews. Subsequently, expert opinions were collected via an expert evaluation questionnaire and filtered using the Fuzzy Delphi method, resulting in the selection of 9 key drivers. These drivers were then prioritized using prioritization questionnaires analyzed through the Fuzzy WASPAS method, leading to the identification of two primary drivers for scenario development. Finally, based on these drivers and focus group interviews, four future scenarios were formulated. .

Findings: Supply chain resilience and the development of innovative financial instruments were identified as the most critical drivers. Based on these, four future scenarios were developed: Energy Financial Prosperity (the most favorable scenario), Resilience Under Pressure, Lost Opportunities, and Energy Financial Deadlock (the most unfavorable scenario).

Results: To prevent the occurrence of the critical "Energy Financial Deadlock" scenario, it is essential to implement structural reforms, revise legal and regulatory frameworks, strengthen oversight mechanisms, and enhance financial transparency. Other key strategies include developing independent financial institutions, leveraging innovative financial technologies, and utilizing international financial resources. Additionally, improving managerial capabilities and fostering collaboration among stakeholders across the energy supply chain can ensure the resilience and sustainability of the energy financing system.

Abstract Optimal fuel consumption management at petroleum product distribution stations is a major challenge in the oil and energy industry, with direct implications for the national economy and energy security. In this regard, software packages and accounting information systems can provide accurate and timely information and thereby support more effective managerial decision-making. This study aimed to examine the effect of software packages and accounting information systems on fuel consumption management, with the mediating roles of management efficiency, control and monitoring, and planning and optimization at petroleum product distribution stations. The research was applied in terms of purpose and descriptive-survey in terms of method. The statistical population included accounting experts, operations staff, station owners, and members of the relevant professional association; 80 individuals were selected through simple random sampling. Data were collected using a researcher-made questionnaire and analyzed using the partial least squares structural equation modeling (PLS-SEM) approach. The results showed that both software packages and accounting information systems had significant positive effects on fuel consumption management. In addition, accounting information systems had the strongest effect on management efficiency, while software packages had the greatest effect on control and monitoring. The findings indicate that the development of software infrastructure and the implementation of integrated accounting information systems can play an effective role in improving productivity, increasing financial transparency, and enhancing fuel consumption management at petroleum product distribution stations. Accordingly, policymakers and industry stakeholders are advised to prioritize integrated digital systems and invest in human resource training

Abstract   Statistics indicate a continuous growth in gasoline consumption for transportation in Iran. The volume of domestic consumption of gasoline in recent years has exceeded the country’s refining capacity, and a substantial volume has to be imported to meet the increasing demand for fuel. A growing urban population, together with ever increasing popularity of cars and subsidized fuel prices are considered among the most significant factors for this phenomenon. Which, among other problems, has created a substantial burden for the public budget and a  rather serious air pollution in urban communities. Although, rising fuel consumption and its environmental impact could be seen as a common problem in most countries today, it is noteworthy however, that technological progress in urban transportation has presented certain useful alternatives. This study attempts to use advanced econometric methods to postulate a perspective for the long term gasoline consumption in Iran.  Subsequently, it proceeds to examines the economic feasibility of utilizing a more advanced automobiles (i.e. Electro Hybrid cars) as an alternative mean for urban transportation. Findings of the study indicate a rather substantial stream of benefits for the economy, in terms of reduced gasoline consumption, as well as, lower air pollution for urban centers.

Abstract Fiscal regime is one of the main differences between petroleum contracts. Fiscal regimes in oil contracts are divided in two main categories namely Concessionary and Contractual Systems. In contractual systems, the main difference between service and production sharing contracts is the way of compensation of contractor services which could be in cash or in kind. In production sharing contracts the contractor receives a portion of produced oil. One of the main criteria to compare fiscal regimes is government and contractor takes in real values. Comparing the net present value of contractor take shows that PSC could have been more desirable and cost effective in Azadegan, Soroush & Norouz, Forouzan & Esfandyar oil fields than Buy-Back contracts.

Abstract The Upstream Service Contracts in oil and gas industry of Iran have been used as an international contract for the exploration and development of Iran oil & gas fields, aiming to attract investment and establishing relationships with international oil companies (IOCs). These contracts explicitly or implicitly contain several statutory principles which are considered as a basic formation of the contracts. Such principles provide benefits for both national oil company (NOCs) and IOCs plus foreign Investors. Since those principles are considered to be mandatory rules prevailing on petroleum upstream contracts, thus, it would not be possible to derogate from such rules when negotiating and concluding these contracts. This parer is an attempt to investigate and find those principles and provided legal-economic analysis accordingly.

Abstract Iran is one of major oil producers and exporters in the world. Since the crude oil export is a major source of Iran’s income, it indirectly influences the country’s   other economic activities. The aim of this paper is to investigate the effect of oil price changes on major macroeconomic variables including gross domestic product, government capital expenditures, money supply and inflation rate in Iran during 1971-2007 period. A vector Autoregression (VAR) model is estimated for this purpose. Impulse Response Function (IRF), the Forecast Error Variance Decomposition (FEVD) are then utilized to analyze the results. The major findings are as follows: 1-Gross domestic product, government capital expenditures, money supply and inflation rate are positively affected by oil price fluctuations. 2-Forecast  Error Variance Decomposition analysis, indicates that oil price plays a major role in explaining inflation rate and money supply, but it’s role with regard to gross domestic product and government capital expenditures is secondary.  

Abstract Due to the growing demand for electricity it is inevitable to have new power plants. Given the large share of electricity production in thermal power plants, construction of gas burning power plants have particular importance. Because of the high construction cost of the new plants, it is advisable to start with improvement of the efficiency in the existing and plates. One important index in electricity industry, is the efficiency of power plants which concerns all the powerplants in the world. In order to increase it as much as possible, and reduce the loss of energy to a reasonable degree, this paper examined the performance impact of plant life and obtained 0.07 of electricity coefficient for the variable. We also examined other factors related to efficiency. Among the factors influencing efficiency of this type of power plants, the cost of fuel and average plant life and volume of production of electricity were also important. In this study a panel data from 34 gasplants in Iran was used for a period of 4 years (2008-2011). 

Abstract This paper deals with the process of developments in upstream oil and gas contracts during 1979-1991 and 1992-2013. We will understand that any type of conventional contracts had not been concluded during 1979-1991 but in the latter period, three generations of Iranian service contracts named, “Buy-Back Contracts” have been designed and implemented. Due to the necessity of designing new upstream contracts we intend to analyze that which of the conventional upstream contracts are compatible with the current sovereignty laws of oil and gas industry? Regarding the dominant regulations on this sector, what are the concerns and proposal framework of experts about the new contracts? Finally, it seems that the dominant legal requirements on oil and gas upstream sector with the principles of Buy-Back contracts are more convenient than other types of conventional contracts. Of course, the new contracts regarding the current legal capabilities, should be both the ability of answering to concerns of critics as well as suitable  flexibility in terms of oil and gas fields of the country. 

Abstract development of wind power usage in Iran. The economics of energy production from wind and gas power plants are compared. The Levelized Cost of Energy (LCOE) is used as an index to compare the plants’ cost of electricity production. LCOE is a well-known index to measure the economics of a plant once all the factors such as cost of air pollutants and exchange rates are to be considered. We show that by removing subsidies from conventional fuels in Iran, wind power plants are completely cost effective. Due to the opportunity cost of gasoline, power generation from wind can provide the ability to export gasoline. The benefit increases by designing and constructing of infrastructures required to develop the technology inside the country. It is worth mentioning that due to changes in exchange rates, policies should be directed towards developing the wind turbine technology inside the country which in turn provides job opportunities.