Iranian Energy Economics

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 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 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 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 The National Development Fund was established as a development fund with the aim of providing intergenerational benefits, preventing the spread of fluctuations in oil revenues to the economy, and also supporting the country's development plans. Despite this, until now, there has not been a detailed evaluation of how the allocation of resources of this fund affects macroeconomic variables. However, by studying and examining the successful global models of such funds, in addition to the limited impact of this fund on the macro-economic variables in Iran, there are also flaws in the way its resources are allocated. Based on this, the main goal of this research is to design a dynamic stochastic general equilibrium model to evaluate the impact of the allocation of National Development Fund resources on macroeconomic variables with the Bayesian estimation approach using quarterly data for the period 2011-2021. The results of the simulation show that if the National Development Fund spends part of its resources on direct and indirect investment, although at the beginning of the period its effects are the same as before (only facilities), but after that the level of production, capital and investment will increase, which will lead to higher economic growth. Also, the results obtained from the minimum variance portfolio method show that among the existing methods, buying shares of capital market companies directly and investing in various types of investment funds, can bring higher returns than the current method (facilities) for the Fund at a certain level of risk.
Introduction
Countries rich in natural resources often struggle with resource mismanagement, institutional inefficiency, and economic volatility. Iran, despite significant oil revenues, has faced low economic growth and macroeconomic instability. The NDF was created to mitigate these challenges by saving oil revenues and promoting productive investment. This research explores how the structure and allocation of NDF resources affect macroeconomic variables and seeks to identify optimal strategies for maximizing its impact.
Methods and Materials
The study employs a DSGE model based on Real Business Cycle (RBC) and New Keynesian foundations, integrating sectors such as households, firms, government, central bank, and the NDF. Bayesian estimation techniques were used to calibrate model parameters using quarterly macroeconomic data. Multiple policy scenarios were simulated, including pure loan-based allocation and mixed investment strategies, to examine their effects on output, inflation, employment, and capital accumulation.
Results and Discussion
Simulation results show that switching from a loan-only strategy to a mixed investment approach enhances capital accumulation, investment, and output growth. While the short-term effects (approximately the first year) of both approaches are similar, the investment-inclusive approach yields superior long-run results. Portfolio optimization through the MVP model recommends allocating 43.4% to equities, 49.6% to mutual funds, and 7% to real estate, maximizing returns under acceptable risk levels.
Conclusion
The findings emphasize that diversifying the NDF’s financial instruments beyond traditional loans enhances both fund profitability and macroeconomic stability. Strategic allocation toward capital markets and investment vehicles leads to sustainable growth and improved intergenerational equity. Future policies should integrate a balanced portfolio approach to optimize the Fund’s economic contribution.
Acknowledgments
The author extends sincere gratitude to Dr. Mehdi Sarem for his invaluable support in model development, and to the editorial board of the Journal of Energy Economics of Iran for their constructive feedback and publication support.
 

Abstract The purpose of this study is to compare the economic efficiency of Iran's petroleum contracts, buyback contracts, and production-sharing contracts. This study also determined the optimum path for production and drilling operations in the Yadavaran oil field which has special importance because it is a joint field with Iraq. It was estimated using real field data and the SQP algorithm by MATLAB software. First, the objective function, the constraints of each contract model, and the cost function are defined and expressed based on field data. For the objective function, the oil price is determined based on the reference price scenario and based on the forecast of the US Energy Information Administration (EIA). Cao et al (2009) 's cost function model is also modified by using historical field data (first development phase data) to be applied to the study field. The results show that the most efficient oil contract is the Iran petroleum contract, with a low floor for capital costs and no limit to the number of drilled wells. it was proved that the buyback contract with the ceiling of capital costs incompatible with the recovery coefficient has recorded the lowest efficiency. Also, the Iran petroleum contract can be a good alternative to the buyback contract, because it can well solve the problems of the buyback contract, especially for joint oil fields where the priority of the objective function of the maximum cumulative production over the objective function of the maximum present value of the total profit is more desirable.

Abstract Reducing greenhouse gas emissions is one of the most important goals of the world’s energy and environmental policies. Even though fossil fuels are one of the most important factors in creating pollution, their role in the structure of production and economic growth cannot be ignored. Nowadays, to measure economic growth, economists do not consider only the amount of production of goods and services, but also consider the structure of production of goods and services in terms of technical knowledge (technology level) used in them. Accordingly, in recent decades, the index of economic complexity has been proposed, and by calculating it the possibility of knowing the development of countries’ levels is provided. The purpose of this study is to investigate the effect of the economic complexity index on greenhouse gas emissions in some oil exporting countries in the period from 1995 to 2019 using the panel smooth transition regression (PSTR) model. The results of the linearity test confirm the existence of a nonlinear relationship between the considered variables. Also, considering a transfer function with a threshold parameter that expresses a two-regime model is sufficient to specify the nonlinear relationship between the model variables. The slope parameter (transition speed) equals 3/1964. The test results indicate that in both regimes (first and second), the economic complexity index has a negative effect on the amount of greenhouse gas emissions