Journal of Economic Modeling Research

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Although many factors in economic growth and development are scientific, but the global impact and energy consumption have a prominent role in the economy according to the evidence. In the meantime, we should not ignore the consequences of environmental destruction. In the present study, the effect of uncertainty of globalization and energy consumption on CO2 gas emission has been investigated with the help of fuzzy regression model with symmetric and asymmetric coefficient for the time period of 1369-1400. According to the average scale of the phased vessel model, the three boundaries and the bottom are calculated for each of the investigated changes under different uncertainty conditions using the particle swarm algorithm. Examining the effect of the limits related to the uncertainty of globalization and energy consumption on the amount of CO2 gas emissions indicates that as the degree of membership approaches 0.1 to the degree of membership 0.9, first, the amount of CO2 gas emissions up to be Membership increased by 0.4 and then decreased in a downward trend of CO2 emissions. This impressive trend is also true for the middle and lower limits. From this, it can be stated that the effect of the uncertainty of energy consumption on the amount of CO2 emissions is similar to an inverted U. It is noteworthy that the trend of energy consumption compared to globalization increases the amount of CO2 emissions, so it can be said that the amount of CO2 emissions is not the result of the refugee hypothesis.

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In Islamic and conventional banks, there may always be differences in efficiency, cost gap ratio and credit risk; Therefore, the purpose of this study was to investigate the relationship between credit risk, cost gap ratio and efficiency of banks in selected Islamic and conventional countries. For this purpose, credit risk, efficiency and cost gap ratio were calculated for 50 Islamic banks and 50 non-Islamic (conventional) banks during the years 2013-2019 and regard, the results of the t-test showed that the credit risk, inefficiency and cost gap ratio are higher in Islamic banks than conventional banks. Also, the results of the Granger causality test showed that there is a bidirectional causality relationship between inefficiency and credit risk. But this relationship is a little weak. There is no causal relationship between credit risk and cost gap ratio, and there is a strong two-way causality relationship between inefficiency and cost gap ratio. The results in Islamic banks are almost similar to all banks. However, in Islamic banks, credit risk is not the Grangerian cause of inefficiency. Also, the significance level of other causal relationships is much higher. For conventional banks, there is no causal relationship between inefficiency and credit risk. There is no causal relationship between credit risk and cost gap ratio, and there is a two-way causality relationship between inefficiency and cost gap ratio. In addition, the results of variance analysis indicate that the cost gap and inefficiency have a close relationship with each other and their effectiveness is high. Credit risk also has a more or less effect on inefficiency during future periods. In Islamic banks, the effects of inefficiency and cost gap on credit risk are slightly higher. But the inefficiency of the cost gap has a high effectiveness. In conventional banks, credit risk has the same effectiveness as Islamic banks, but its effectiveness is somewhat less. Also, inefficiency has less effects than the cost gap. The cost gap, like Islamic banks, has a high effectiveness of inefficiency, and this effectiveness decreases over time.
 

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This study explores how monetary and fiscal policies influence certain macroeconomic variables through a multi-sector stochastic dynamic general equilibrium (DSGE) model that includes input-output (IO) analysis. The focus is on the industrial sector, taking into account the specific conditions for Iran. The research uses quarterly data from Spring 2006 to Spring 2023 and references the 2016 input-output table provided by the Central Bank. In the nonlinear model, the original 89 activities from the input-output table have been simplified to 9, which includes the industrial sector and eight other sectors. Model parameters are estimated based on previous studies of the Iranian economy and data from the input-output table. The model's effectiveness is assessed by comparing simulation results with real-world data, which shows a strong correlation. The simulations indicate that increases in the money supply result in only a small rise in both total and industrial output. This leads to a slight decrease in total employment, while employment in the industrial sector experiences a minor increase. Similarly, increases in government spending show tiny improvements in overall and industrial output, accompanied by a slight drop in total employment and a small rise in the industrial sector. The findings suggest that the effects of monetary and fiscal policy shocks on output and employment, when accounting for input-output relationships and dividing the economy into nine sectors, better reflect the realities of the Iranian economy. Given the minimal influence of these policies on boosting production and economic growth, it is essential for them to be targeted and supported by additional measures and strategies.
 

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The main purpose of this study is to investigate the effect of factors affecting the ecological footprint with an emphasis on the role of energy consumption intensity in Iran using the Vector Autoregression Model with Variable Parameters Over Time (TVP-VAR). The ecological footprint reflects the environmental constraints of communities and the extent to which the environment is destroyed by exceeding these limitations. Due to the increasing intensity of energy consumption, Iran is faced with a significant ecological footprint in its economic activities, which requires the root causes of the factors affecting it. Other research variables include the degree of urbanization, human development, financial development, trade openness, and GDP per capita in the period from 1990 to 2021. The results show that increasing the intensity of energy consumption causes a positive and significant increase over time on the ecological footprint. The effect of other research variables on the ecological footprint was also in accordance with theoretical expectations. These findings emphasize that the type and source of energy consumed, as well as the production processes, play an important role in this relationship. Also, the analyses show that environmental sustainability decreases with increasing energy consumption and the ecological footprint of

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The fundamental aim of this study is to investigate the structural dependence between the cryptocurrency and the stock market index. In this study, the total index of Tehran Stock Exchange has been used as a representative of the developing stock market and the index (S&P500) has been used as a representative of the developed stock market. using daily data during the period from 8 August 2015 to 21 February 2023. The results show that there is no structural dependence between the return Bitcoin and Iran stock market , either in the short term or in the long term. In other words, the changes domain in return of Bitcoin during the low and high ranges on the return of the mentioned index are insignificant. The results indicates that the cryptocurrency market is separated from the main class of financial and economic assets and hence offers various benefits to investors. Also, in the long term, for the return of Bitcoin cryptocurrency and the S&P500 stock index, Clayton's copula function was chosen in the first place as the appropriate model to explain the correlation. There is no correlation between the returns of Bitcoin and the s&p500 stock index in the short term. The findings of this study indicate the important role of cryptocurrencies in investors' portfolios as they act as a diversified option for investors and confirm that cryptocurrencies are a new investment asset class. Furthermore, it analyzes the upside and downside risk spillovers between stock markets and the cryptocurrency market by quantifying market risk measures, namely the conditional VaR (CoVaR) and the delta CoVaR (ΔCoVaR). The results indicate that Bitcoin, Ethereum and Ripple cannot be considered a strong hedge during the time of crisis. The speculative nature of cryptocurrencies and risks embedded in Bitcoin, Ethereum, and Ripple increases the risk flow to stock markets during a crisis, thus rendering the hedging costlier.  increases the risk flow to stock markets during a crisis, thus rendering the hedging costlier.
 

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Predicting financial asset volatility is highly important because this information can help investors make more informed decisions regarding buying and selling. Accurate predictions can also reduce financial risks and identify profitable opportunities. Ultimately, the ability to forecast market changes improves portfolio management strategies and minimizes unexpected losses for investors. This study examines and predicts Bitcoin price volatility by using innovative data analysis models. The Heterogeneous Autoregressive (HAR) model and its variants were selected as the primary tools for modeling volatility because of their high capability to analyze volatility data across different time scales. Given the unique characteristics of cryptocurrency markets and rapid, unpredictable price fluctuations, the use of models that can simultaneously capture both short- and long-term volatility is of significant importance. In this study, high-frequency historical Bitcoin price data from 2018 to 2022, covering 60-minute, daily, weekly, and monthly intervals, were analyzed using the HAR, HARJ, HARQ, and HARQJ models. The results indicate that heterogeneous models have strong predictive power for Bitcoin price volatility, and incorporating jump factors into these models further improves their forecasting accuracy.
Predicting financial asset volatility is highly important because this information can help investors make more informed decisions regarding buying and selling. Accurate predictions can also reduce financial risks and identify profitable opportunities. Ultimately, the ability to forecast market changes improves portfolio management strategies and minimizes unexpected losses for investors. This study examines and predicts Bitcoin price volatility by using innovative data analysis models. The Heterogeneous Autoregressive (HAR) model and its variants were selected as the primary tools for modeling volatility because of their high capability to analyze volatility data across different time scales. Given the unique characteristics of cryptocurrency markets and rapid, unpredictable price fluctuations, the use of models that can simultaneously capture both short- and long-term volatility is of significant importance. In this study, high-frequency historical Bitcoin price data from 2018 to 2022, covering 60-minute, daily, weekly, and monthly intervals, were analyzed using the HAR, HARJ, HARQ, and HARQJ models. The results indicate that heterogeneous models have strong predictive power for Bitcoin price volatility, and incorporating jump factors into these models further improves their forecasting accuracy.
 

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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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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