Journal of Economic Modeling Research

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Due to the wide trade relationship between the countries of the world and the economic dependence of the countries on the global economy, the boom or record in the great economic powers of the world will quickly affect the economy of other countries.
In recent years, China has become one of the largest economic powers in the world and has been one of Iran's main trading partners for many years and is one of the countries that can have the greatest impact on Iran's economy.
On the other hand, due to the tightening of international sanctions on Iran in recent years, many measures have been taken to expand trade relations with other countries and attract foreign capital, among which the role of China as the main trading partner of Iran is prominent and it is necessary to reduce the shocks caused by To know the changes in China's economic growth and their effect on the macroeconomic indicators of the country.
Accordingly, the present study examines the effect of China's economic growth shocks on Iran's real GDP, inflation rate, and non-oil exports. In this regard, (GVAR) model and seasonal data from 1992 to 2022 for 34 major trading partner countries of Iran have been used.
The results of the study showed that the effect of a positive shock in China's real GDP on Iran's real GDP is positive in the short term, but in the long term, the said shock is negative and in the direction of its reduction. In relation to inflation, the effect of a positive shock to China's real production on Iran's inflation rate has always been positive and negative on Iran's non-oil exports.

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Due to the position of meat products in the food pyramid and its importance in maintaining people's health and that economic sanctions can have a significant effect on meat consumption through the channel of increasing production costs and increasing the price of meat, the purpose of this research is to investigate the existence of failure There is a structure in the preferences of the meat consumption basket of urban households using the parametric approach and the switching regression framework developed by Ohtani and Katayama (1986) in the period of 2001-2013. The results show a structural failure (change) in preferences suddenly in 2017 and after the withdrawal of the United States from the JCPOA. The results show that after the withdrawal of the United States from the JCPOA, the price of chicken meat has decreased and the price of fish has increased, so that chicken meat has changed from an attractive product to an inelastic product. This result shows that consumers have become dependent on chicken meat and are willing to pay more to buy it. In such a situation, it is important to have adequate and optimal monitoring of the price of chicken meat, because people are forced to pay any price for chicken meat, and the changes of this product can cause the consumption basket of urban households to fluctuate greatly. Also, the estimation of income elasticity shows that chicken meat has changed from a necessary commodity to a luxury commodity after the sanctions. Therefore, to support consumers, it will be the right decision to use income tools and policies that lead to increasing the liquidity of urban households.
 

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Today, the importance of the effectiveness of economic growth on inflation is not hidden from anyone. The literature expresses different views about the effect of inflation on economic growth. Some studies have emphasized the existence of a positive relationship, some studies have emphasized the existence of a negative relationship, and some have considered the effect of inflation on economic growth to be neutral. In recent decades, Iranian economy has faced inflationary conditions that can affect economic growth. Macroeconomics uncertainties can also intensify the negative effect of inflation on economic growth. Considering the importance of the issue, in this article, the vulnerability of economic growth to inflation in the conditions of macroeconomic uncertainties is investigated. For this purpose, using time series data during 1370-1401, the dynamics of the effect of inflation on economic growth has been investigated, using the autoregression method with a distribution with an interval. Since inflation at different levels and thresholds can have a different effect on economic growth, the threshold effect of inflation has been investigated using the threshold regression method. Considering the different effect of inflation in macroeconomic uncertainty, the effect of inflation at the level and threshold on economic growth has been investigated once considering macroeconomic uncertainty and another time without considering macroeconomic uncertainty. E-GARCH method has been used to extract macroeconomic uncertainty. In the models examined in the article, uncertainty of exchange rate, uncertainty of liquidity and uncertainty of stock price index were considered. The findings indicate, inflation at the level without macroeconomic uncertainty has a positive effect on economic growth, but taking macroeconomic uncertainty into account, inflation at the level has a negative effect on economic growth. Also, considering macroeconomic uncertainty indicates that the negative effect of inflation on economic growth is intensified.

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Sustainability of pension funds indicating the balance between contributions and pension expenses, is one of the fundamental principles governing social security systems. Among the things that affect the contributions and pension expenses of the Iran’s Social Security Organization (ISSO)’s fund is the minimum wage which according to Article 41 of Iran’s labor and social security laws, is determined annually by the Iran’s supreme labor council and, every year, becomes a controversial and disputed issue between labor :union:s, employers and the public authorities. An increase in minimum wage have effects on both the received contributions and pension expenses and, as a result, its final effect on the cash balance of ISSO’s fund has been arguable. Considering the issue importance, this paper studies the effect of an increase in minimum wage on ISSO’s contributions, pension expenses and its cash balance during 1961 to 2022 using an econometric time series model of autoregressive distributed lags (ARDL). The results show that a 10% increase in the minimum wage will increase ISSO’s contributions by 25.6% and its pension expenses by 23%. Therefore, comparing the effects, it can be stated that the ISSO’s cash balance would be increased by 2.6% as a results of a 10% increase in minimum wage. To test the result, one more time, the association between an increase in minimum wage and the ISSO’s excess resources was investigated separately. The results once again confirm that the ISSO cash balance would be improved by 3.3% in association with a 10% increase in minimum wage. In this study, it was also shown that the population of contributors, the population of pensioners, the population support ratio, GDP and dummy variables of sanction and Iran-Iraq war have been influential as well.

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Creating the necessary conditions for growth and development is one of the goals of any economic system, which requires the application of correct economic policies, the identification and application of the components that affect growth, and as a result, the establishment of economic stability that leads to economic development and maintaining interests. It becomes national. Therefore, in order to achieve economic growth and to be on the path of economic development, it is necessary to consider the factors affecting economic growth. Among them, we can point out the control of inflation (growth of liquidity) and the reduction of income inequality. In this regard, examining the impact of monetary policies on these variables (stability, liquidity and inequality) can be effective and useful. Monetary policies are among the most important macroeconomic policies, which are among the main duties of central banks. Therefore, in this research, we investigate the influence of central bank independence on liquidity growth, unequal distribution of income and economic stability using time series data from 1981 to 2014. In the upcoming study, three sections were considered. The first part is the relationship between central bank independence and liquidity growth, the second part is the relationship between central bank independence and income distribution, and the third part is the relationship between central bank independence and economic stability. In each section, the influence of the economic indicators of the central bank's independence on the desired dependent variables was also examined. The calculated index for central bank independence in this study is a composite index. The results of the hypotheses test showed that the independence of the central bank has a positive and significant relationship with the growth of liquidity in Iran and a negative and significant relationship with the unequal distribution of income during the period under review and finally a positive and significant relationship with economic stability in Iran.
 

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Introduction
 Poverty has become one of the major global challenges faced by most Asian countries. Although they have been able to achieve technology and increase productivity in the fields of production in recent decades, a high percentage of their society still lives in poverty. The current concern about the increase in chronic poverty in many countries of the developing world requires a deeper understanding not only of the number of poor people, but also of the nature of poverty. This issue has a widespread and devastating impact on the lives of millions of people around the world and is important because its effects go beyond the economic sphere and extend to the social, political and cultural spheres. Poverty reduction is one of the fundamental economic and social challenges in global societies. Therefore, it is very important to examine the factors affecting poverty reduction One of the ways to reduce poverty is the existence of institutional foundations and institutions. Since the second half of the twentieth century, numerous studies have been conducted on the role of institutional and political approaches in poverty reduction. According to these studies, the existence of strong institutions and institutions attracts investment, improves technology and employment, and consequently increases production and economic growth. Therefore, the existence of institutions is the main factor in the growth and development of countries. The existence of institutions and institutions can explain the differences in welfare, growth and development and economic well-being between countries. By creating a stable structure in the economy and society, institutions reduce risk and uncertainty, and thus reduce transaction costs. In short, understanding the interaction between institutional factors, spatial dynamics and poverty reduction is essential for designing effective policies and interventions. The aim of this study is to answer the question of how institutional factors and economic growth can reduce poverty in selected Asian countries?

 Method
 In this research, the research method is of the spatial analytical and econometric type. The data of this study were collected from the World Bank and the Macro Trends website. In estimating the spatial panel data model, it is necessary to mention a few points. First, the spatial effects in the calculations are factors that are related to the location of the variables. The first factor is the spatial dependence or autocorrelation between the observations of the sample data at different points and the second factor is the spatial structure or heterogeneity created by the model relations for moving on the plane. The coordinates change with the sample data. To detect the spatiality of the data, it is necessary to perform spatial detection tests. In this research, a weight matrix was formed for countries that have geographical connections. The weight matrix is ​​of the adjacency type. The adjacency or neighborhood matrix was formed for the 15 countries studied. In this way, the value of one is considered for neighboring or neighboring countries and the value of zero for non-adjacent countries. Therefore, the adjacency matrix is ​​a symmetric 15x15 matrix with a main diameter of zero and elements outside the main diameter of zero and one. Stata software is used to estimate the model. In panel data with spatial characteristics, fixed and random effects can be considered for the model and the best model was selected from SAR, SDM, SAC, SEM and GSPRE models using the spatial Hausman test, of which the spatial autocorrelation (SAC) model was selected.
Conclusion
 Based on the spatial effect of the disturbance components or dependent variables, the results of the spatial autocorrelation model (SAC) show that economic growth and the quality of institutional factors have a positive effect on poverty reduction. Also, increasing domestic investment also helps to reduce poverty. The spatial effects of poverty show that increasing poverty in a country can also cause poverty in neighboring countries. In general, economic growth can increase welfare and create new opportunities. Policies that support economic growth, such as financial development and economic stability, provide a favorable environment for poor households to increase their production and income. The research results show that institutional development and better quality of institutions (such as corruption control, government stability and democracy) have a positive effect on poverty reduction. Better institutional quality improves resource distribution and poverty reduction in the long run. Strong and reliable institutions can increase investment attraction and facilitate international trade. It also confirms the positive effect of domestic investment on poverty reduction. Increased investment increases production, income and welfare and reduces unemployment. Spillover effects of domestic investment can facilitate the transfer of knowledge and technology.
 

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Objective: The aim of this research is to investigate the dynamic and nonlinear dependence between housing market fluctuations and the returns of construction companies on the Tehran Stock Exchange. Materials and Methods: The data used include construction service returns, land price returns, inflation, exchange rate returns, stock index returns, industrial production returns, and rental returns in the period 1991 to 2023 using T-GARCH, Copula-GARCH, and DCC-GARCH. Results: The results indicate the existence of strong and nonlinear dependencies between the returns of construction services and housing market variables, especially the returns of land prices and rents. The T-GARCH model showed a high fit (R-squared=0.969) and confirmed that past shocks have a significant impact on current fluctuations. The Copula-GARCH model confirmed the nonlinear dependencies with an average correlation coefficient of 0.31, while the rolling correlation analysis in the DCC-GARCH model indicated dynamic changes in dependencies in different economic periods. The Kendall-Tao correlations in boom (0.928) and recession (0.923) periods also showed a small but significant difference in the intensity of dependencies. The sensitivity analysis showed that changes in industrial production have a significant impact on the returns of construction services. Conclusion: These findings are useful for investors and policymakers in risk management and setting economic policies in the Iranian housing market.

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The aim of this paper was to estimate the effects of unconventional monetary policy shocks using Narrative sign restrictions method as a novel method, imposing sign restriction on the impulse responses of real interest rate, GDP, GDP price deflator, nonborrowed reserves as well as Total Reserves in response to monetary policy shocks in Iran. Using Narrative sign restrictions model for the period 1983-2020 enables considering the effects of aforementioned five variables as well as identifying the effect of monetary policy shocks on these variables. Narrative sign restrictions constrain signs based on narrative information. According to the liquidity effect, results of the impulse responses function highlights decreasing real interest rate causes increasing in aggregate demand and GDP. With Narrative sign restrictions, real interest rate shocks also have significant impact on GDP through increasing it. To this aim, according to results and also with regard to the importance of unconventional monetary policy in response to crisis, this policy can be applied for resolving stagflation and this supplement policy can be applied besides other policies of Central Bank.
 

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Food security, as an indicator of macroeconomic stability, is the fundamental foundation of countries' economic security and one of the most important prerequisites for sustainable development.
On the other hand, food production and distribution are energy-intensive, and energy is essential for achieving food security.
In this regard, the main objective of this study is to examine the impact of energy security on food security in a selected group of Middle Eastern countries. The results using spatial econometrics in the period 2000-2023 showed that access to electricity as an indicator of energy security has a positive and significant impact on food security in the selected group of Middle Eastern countries. With a one percent increase in access to electricity, on average, assuming other conditions are constant, food security increased by 0.1384 units in the selected group of Middle Eastern countries. The direct and indirect effects of energy are also positive, meaning that increased access to electricity has not only improved food security in the selected group of Middle Eastern countries, but its spillover effects have also moderately improved food security in neighboring countries.
 

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The economic growth rate indicates changes in the level of economic activity and a country's ability to produce goods and services, which can be used as a measure to evaluate a country's economic performance and compare it with other countries. In the case of financial development, the ratio of financial assets to non-financial assets increases, which can have an impact on increasing economic growth.The purpose of this research is to investigate the impact of oil revenues on the economic growth of Persian Gulf countries with an emphasis on the financial development channel. The countries under study include: Iran, Qatar, Kuwait, Saudi Arabia, Iraq, Bahrain, and the United Arab Emirates, and the research period was from 2003 to 2023. For this purpose, a two-regime threshold panel regression model was used. The findings show that the effect of oil revenues on economic growth through the financial development where the level of financial deepening is less than the threshold level channel is positive and significant for the first regime, So that before reaching the threshold, one percent in oil revenues increases economic growth by 9.87 percent. For the second regime, that the dependence financial development channel on oil revenues is higher than the threshold level. It is not meaningful. Also, the control variables of trade openness, gross investment, inflation, government consumption expenditure have had a positive and significant impact on the economic growth of the mentioned countries.
 

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Objective: This research analyzes the spillover of fluctuations on the performance indicators of the metal industries, with an emphasis on the Covid-19 crisis in the period 1390 to 1402 (2011 to 2023).
Materials and Methods For this purpose, the quantile autoregressive panel model has been used, which allows the analysis of nonlinear relationships and quantile-based dependencies between companies. This model examines volatility spillovers in different market conditions (including crisis periods) by focusing on different quantiles (0.25, 0.5, and 0.75).
Results Analyses show that economic fluctuations have particularly affected the financial performance of metal companies, reducing their profitability and liquidity. Also, companies that have been able to respond quickly to market changes and maintain their reputation have performed better.
Conclusion: This research emphasizes the importance of risk management and optimizing financial resources in the face of crises and can be considered as a resource for analysts and managers of the metal industries to improve resilience and performance in crisis situations.
Originality: During the COVID-19 health crisis, the metal industry faced serious challenges due to severe economic fluctuations and disruptions in the supply chain. This study shows that the volatility caused by the Covid-19 crisis has had significant impacts on return on assets, financial constraints, and sales rates in these industries.

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Employment is one of the most important issues that any country faces. Employment plays a vital role not only for individuals but also for the economy as a whole, and provides a deep understanding of the labor market conditions of an economy. In this regard, the minimum wage is an important factor that affects the labor market. The literature on the minimum wage uses two labor market models. The standard competitive model, which predicts that the minimum wage will have negative employment effects. In other words, under conditions of perfect competition, economic theory suggests that a higher minimum wage will lead to job losses, and noncompetitive labor market models, which predict that the minimum wage will have positive employment effects. However, it is generally unclear whether minimum wages have a positive or negative effect on employment, or are ineffective. Therefore, the aim of this study is to examine the effects of the real minimum wage on employment in Iran, within the framework of a multiple regression model and OLS estimation during the period 1379-1400. The results of the regression analysis show that the increase in the real minimum wage has a significant negative effect on employment, so that with a one-unit increase in the real minimum wage, employment decreases by about 0.37 units. Therefore, taking the above into account, it is suggested that the increase in the minimum wage should be made as proportionate as possible to the Labor productivity in the economy

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The present study aims to model and investigate the impact of money market variables on stock market performance (capital market). Money market variables can directly or indirectly affect stock market performance. This research examines the influence of interest rates, exchange rates, inflation rates, liquidity, and legal reserve rates on the stock price index. Additionally, another objective of this study is to investigate the effect of economic policy uncertainty on the relationship between monetary variables and the aggregate stock price index, and how monetary variables are guided and their impact on the stock market. The research period spans ten years, from 1392 to 1401. The hypothesis testing results, using seasonal time series data and the Autoregressive Distributed Lag (ARDL) model, indicated that the effect of money supply and exchange rate on the aggregate stock price index is positive and significant. However, the effects of the interest rate and legal reserve rate are not significant. Furthermore, based on an index for economic policy certainty, this research demonstrates that the relationship between the interbank interest rate, money supply, legal reserve rate, and exchange rate with the aggregate price index is influenced by economic policy uncertainty.

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Tax compliance is one of the most significant issues in the field of economic management, contributing to financial transparency, economic justice, and the enhancement of government revenue sources. In OECD member countries, tax policies between 1990 and 2022 have been designed to improve tax compliance and strengthen the sustainability of tax revenues. This study examines the determinants of tax compliance in these countries using the Generalized Method of Moments (GMM) for panel data analysis. The results indicate a nonlinear and significant effect of the tax rate and its squared term on tax compliance, suggesting that while a positive relationship exists between the tax rate and compliance up to an optimal threshold, excessive increases in tax rates may reduce compliance. Furthermore, the employment index has a positive and significant effect on tax compliance, highlighting the importance of job creation in expanding the tax base. In contrast, the corruption index has a negative and significant effect on compliance, emphasizing the need to reduce corruption and increase transparency within the tax system. Per capita GDP also exhibits a negative effect on tax compliance, which can be attributed to structural changes in the economy and the fiscal policies of the countries studied. Nevertheless, the ratio of tax revenue to GDP in OECD countries has remained relatively stable and slightly increasing, reflecting the role of reforms and transparency in sustaining their tax systems. The findings of this study can inform the design of effective policies to enhance tax compliance in Iran, including determining optimal tax rates, strengthening employment policies, improving transparency, and reducing corruption within the tax administration.

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Backward-looking approaches to loss recognition are among the main causes of banking crisis. This study, emphasizing the calculation of expected credit portfolio losses, focuses on the implications of credit risk models for banking stability. Given data limitations in Iran, a synthetic dataset consistent with IFRS 9 was generated from existing data. The dataset consists of a credit portfolio with 1,000 loans that were assigned credit ratings based on the empirical frequency distribution, probabilities of default estimated using the beta-binomial distribution, and loan exposures simulated through the truncated Pareto distribution. The generation of standardized synthetic data from available information was based on Monte Carlo simulation with one million iterations. The results indicate that the Vasicek model yields more conservative estimates of expected loss compared with Mixture models, yet its outcomes are more sensitive to changes in default correlation. Credit risk analysts face a trade-off between conservatism and stability. Regulatory focus on setting correlation thresholds can more effectively reduce the likelihood of banking crises and enhance the resilience of the banking system.

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Natural gas is currently the most important energy carrier in Iran’s production and consumption mix, and its share is expected to increase in the coming years. Any imbalance in the supply and demand of this key energy source can have significant effects on the value added across various economic sectors. The main objective of this study is to analyze the impact of natural gas imbalances on sectoral value added and Iran’s gross domestic product (GDP), using an updated input–output model based on 2023 data. Four scenarios are considered: (1) no prioritization of sectors under imbalance conditions; (2) prioritization based on social and political considerations; (3) no prioritization along with the absence of consumption management policies; and (4) a combination of social-political prioritization with lack of consumption control policies. The results indicate that sectors such as “chemical products manufacturing,” “natural gas production and distribution,” and “electricity generation and distribution” suffer the most significant declines in value added, output, and employment due to their direct and indirect dependence on natural gas. In contrast, sectors like “motor vehicle manufacturing” and “poultry farming,” which are minimally dependent on gas, experience relatively lower economic losses. Moreover, under the second scenario (12% imbalance without affecting final demand), GDP in 2041 is projected to decline by about 3% more compared to the third scenario (21% imbalance with uniform impact across all sectors).

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Objective:Artificial Intelligence (AI), as an emerging and transformative technology, is still in its early stages of development, and many aspects—particularly its economic and social dimensions—remain underexplored. Given the critical importance of eliminating absolute poverty as the first of the United Nations Sustainable Development Goals (SDGs), the present study aims to investigate the effects of investment in artificial intelligence on poverty and identify the main channels through which this impact occurs in countries leading in AI technologies.
Materials and Methods: This study empirically employs panel data from 20 selected countries during the period 2017–2023 using the generalized method of moments (GMM). The main variables include investment in AI technologies as the explanatory variable, and both income-based and multidimensional poverty indicators as dependent variables. Additionally, the study analyzes the effects of control variables including economic growth, income inequality, health index, and human capital.
Results: Empirical results indicate that investment in AI technologies significantly reduces both income-based and multidimensional poverty. AI contributes to poverty alleviation by enhancing economic growth, improving agricultural productivity, enabling financial inclusion, facilitating access to educational and healthcare services, and increasing the precision of targeted subsidies. Furthermore, economic growth and improvements in health indices reduce poverty, whereas increased income inequality exacerbates poverty.
Conclusion:The study emphasizes the importance of investing in legal and technological infrastructure to effectively leverage the potential of artificial intelligence for poverty reduction. Accordingly, policymakers in developing countries, including Iran, could benefit from developing supportive policies and strengthening necessary infrastructure to harness AI capabilities for poverty alleviation and economic well-being.
Originality:This research is among the first comprehensive empirical studies to examine the impacts of investment in artificial intelligence on both income-based and multidimensional poverty, identifying key channels of impact within countries leading in AI technology. The findings provide valuable insights for formulating technology-driven anti-poverty policies.
 

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Objective: Despite their important role in Iran's welfare and economic system, pension funds have faced financial instability and serious threats in recent years due to financial challenges, especially the cash balance deficit. The aim of this study is to answer the hypothetical question of how much capital and assets is required at minimum to cover the deficit and liabilities of these pension funds.
Methodology: In this research which is a case study for one of the Iranian pension funds, by using two methods of futurology and the Value at Risk (VaR) models, an attempt has been made to estimate the minimum required capital for the financial sustainability of pilot pension fund.
Findings: The results show that in the scenario writing method, the minimum capital required to cover the deficit of this pilot pension fund in four scenarios based on the bond rate, ideal, optimistic and realistic, is on average more than 517 trillion tomans of assets for the year 1402. In the Value at Risk (VaR) method with different parametric (ARIMA-GARCH models) and non-parametric (Monte Carlo and bootstrap simulation) approaches, it was determined that this pilot pension fund needs on average more than 550 trillion tomans of assets for the year 1402 in order to cover its deficit with investment income. The results of this article considering the size of pension funds can be easily generalized to other funds and, thus, can be useful in adopting reform policies for financial sustainability in general.

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Introduction
The growing energy imbalances in the country, which are caused by the higher growth rate of demand and consumption than supply and production, have made the need for planning to solve energy problems more evident than ever before. Undoubtedly, the continuation of the increasing trend of energy imbalances in the country's key carriers will cause economic, social and security effects and consequences. On the other hand, according to economic theories, trade liberalization increases efficiency, economies of scale, improves competition, improves the productivity of production factors and increases trade flows, and ultimately leads to economic growth. On the other hand, the Shanghai Cooperation Organization has great capacities in the energy sector (with about a quarter of the world's population, it controls 23% of oil, 55% of natural gas and 35% of the world's coal). Undoubtedly, the accession of observer countries, especially Iran, will increase the potential and capacities of this organization. Therefore, in this study, the impact of trade tariff reduction between Iran and the Shanghai Cooperation Organization on the balance of various energy types in Iran was scenario-based.

Method
No study has analyzed the impact of trade liberalization policy between the Shanghai Cooperation Organization member countries on the energy balance in Iran, and this study addresses this issue by using the computable general equilibrium (CGE) model. Also, among the computable general equilibrium models, the multi-regional general equilibrium model is specifically designed for analyzing world trade and can conduct research and studies on the international flow of goods and services and factors of production in a dynamic and static manner. Using a multi-regional general equilibrium model instead of a single-regional general equilibrium model has several advantages. One of the strengths of these models is their ability to help understand the relationship between sectors, countries, and factors of production on a global scale. Among the multi-regional general equilibrium models, the Energy-Based World Trade Analysis Project model provides diverse possibilities for world trade and energy-related research.
This study examines the impact of reducing trade tariffs between Iran and the Shanghai Cooperation Organization under scenarios of -25%, -50% and -100% on the balance of various energy sources in Iran, including crude oil and petroleum products, natural gas, coal and electricity. For this purpose, the necessary data were extracted from the Global Trade Analysis Project for Energy-Based (GTAP-E) version 10 database, which includes the Social Accounting Matrix (SAM) of 141 countries or regions and 65 sectors. Finally, the data were analyzed using MATLAB software.

Results and Discussion
The results showed that reducing trade tariffs between Iran and other member countries of the Shanghai Cooperation Organization, on the one hand, due to the ease of exporting energy carriers (especially crude oil and petroleum products) and on the other hand, due to the increased use of fossil energy exploration, production, and distribution technologies (especially crude oil and petroleum products, natural gas, and coal), leads to a decrease in fossil energy consumption and an increase in the net balance of fossil energy in Iran. In addition, the reduction of trade tariffs between Iran and other member states of the Shanghai Cooperation Organization, due to the possibility of increasing imports of goods and equipment that consume less energy needed in various domestic, industrial (light and heavy industries), transportation and agricultural sectors (tractors, combines, etc.), as well as increasing cooperation in the development of renewable energy technologies, will lead to an increase in the consumption of renewable energies and a decrease in the consumption of the energy carriers under consideration (especially electricity), and ultimately an increase in their net energy balance in Iran.