فصلنامه اقتصاد مقداری
سال بیستم شماره 4 (پیاپی 79، زمستان 1402)

Emergence of the new Keynesian School and its dramatic impact on the Dynamic Stochastic General Equilibrium (DSGE) models and integration with concepts such as nominal rigidity and monopoly competition, have made these models a central focus of the monetary economist and central banks. In the framework of this school and using the literature of such models, we built an estimable DSGE model for the Iranian economy. By simulating the effects of the implementation of monetary and foreign exchange policies through the policy instruments, bank interest rate, central banks international reserves and the nominal exchange rate, are measured on the macroeconomic variables, the real trade balance, production gap, inflation rate, real exchange rate and foreign assets.

In order to formulate an appropriate model, first the behavioral equations of economic agents have been specified according to the realities of the Iranian economy. Traditionally, an inter-period utility function and a production and profit function have been considered to explain the behavior of consumers and producers, respectively. These agents want to maximize their benefits (utility – profit) or the goal function. The foreign sector is added to the model as a trade balance (net exports) which is the key function. Policy making is operated via the optimum simple rule and under three alternative currency regimes: Managed Exchange Rate (MER), Floating Exchange Rate (FER) and Pegged Exchange Rate (PER) regime. The monetary authority (central bank) has designed four methods for applying the mentioned policies: inflation target, production target, production and inflation targets and finally inflation, production and real exchange rate targets. The analyzed variables are production gap, country’s trade balance (without oil), inflation rate and real exchange rate.
 policy instruments also include bank interest rate, foreign reserves of the central bank and the rate of change in the nominal exchange rate. After designing and adjusting the model for the Iranian economy and determining the necessary dynamics, the linear equation system was prepared. The effects of monetary and exchange policies on foreign sector variables was analyzed according to the mass of this sector in production and employment and based on model’s dynamic relations. Furthermore, the actions, reactions and influences of these policies on country’s trade balance have been measured in the format of variable fluctuations. The model is simulated by using calibrated real data and Dynare software under MATLAB.

The findings indicate that in all policy rules, the scenario of the intermediate currency system has superiority over other currency systems and causes less fluctuations in model’s endogenous variables comparing to the other alternative currency systems.  

The results show that Managed Exchange Rate (MER) for all four methods is optimum and the loss of central bank is minimized as much as possible and  compared to other systems, it has caused the fluctuations of the external sector variables of Iran's economy to be minimized. Hence, it is necessary for the Central Bank to strictly use the intermediate currency system as the dominant scenario when setting policy packages.

Tax evasion is a major component of underground activities or the irregular sector of the economy, and economists are increasingly seeking to analyze this phenomenon. Given that the tax structure is highly dependent on the governance structure and improvements in governance and corruption control structures lead to public confidence in the government and can reduce the underground economy and tax evasion, examining the relationship between the quality of institutions and good governance with Tax evasion are also important. This study tries to answer this question by examining this relationship during the period 1978-2018, whether improving the quality of institutions in Iran can reduce tax evasion and the underground economy in the country or not? In order to achieve this goal, after identifying the factors causing tax evasion, in the first stage using the method of Multiple Indicators - Multiple Causes (MIMIC) to estimate the time series of relative and absolute size of tax evasion in Iran and investigate the causes and effects using Amos software and with maximum likelihood method. Then, in the second stage, after calculating the time series of the hidden variable of tax evasion, in order to study and empirically analyze the long-term and short-term impact of institutional quality and other related variables (inflation and GDP) on tax evasion in the Iranian economy in Time series, ARDL Bounding test method was used.

As previously mentioned, in the first stage, the method of Multiple Indicators - Multiple Causes (MIMIC) method is employed to estimate the time series of relative and absolute tax evasion in Iran, and to investigate its causes and effects using the AMOS software package and the Maximum Likelihood method. After calculating the time series of tax evasion, the model concerning the relationship between institutional quality and tax evasion in Iran during the study period is formulated as follows:LTE = f (LPR, LGDP, INF)                                                                           (1)
Where: LTE: Logarithm of Tax Evasion (obtained in the first stage)
 LPR: Logarithm of Institutional Quality
 LGDP: Logarithm of Gross Domestic Product
INF: Inflation Rate

After comparing the fit criteria and estimated results of the estimated models, a model was selected as the final model and basis for tax evasion calculations in which energy consumption growth, money demand growth and GDP growth as effects and inflation, unemployment rate, export-to-GDP ratio, official exchange rate, per capita income, capital asset acquisition ratio (construction cost) to GDP, and import tax ratio to total imports are considered as causes of tax evasion. This model is in a better position than other estimated models in terms of significance of coefficients of factors and effects of tax evasion. In this model, inflation, tax burden, per capita income and official exchange rate have a positive and significant effect on tax evasion, and economic openness index, government size and unemployment rate have a negative effect on tax evasion. It should be noted that in the selected model, the greatest effect of tax evasion is on the growth of money demand. Also, among the variables of causes, the most impact is related to per capita income. The results of estimating the second-stage model also indicate that the impact of institutional quality is significantly negative both in the short run and in the long run.

The results of calculating the relative size of tax evasion show that although the trend of tax evasion fluctuates in the desired period, but in general it has had an increasing trend over a period of 38 years, so that from 6.12% of official GDP in In 1978, it increased to its highest amount in 2000 (24.46% of GDP) and finally in 2016, it reached 11.33%. Also, the results of calculating the absolute size of tax evasion show that its amount increased from 63664 billion rials in 1978 to its highest amount in 2000 (290250 billion rials) and in 2018 equal to 89095 billion rials.
Based on the results, the sign of the coefficient for the institutional quality variable is negative and significant in both the short run and the long run. This indicates that improvements in institutional quality in Iran during the study period decrease growth of underground economy and tax evasion. Specifically, a one percent improvement in institutional quality in the long run leads to a 0.62 percent reduction in tax evasion.
Furthermore, the findings indicate that an increase in inflation in the long run increase tax evasion in the country. Conversely, an increase in gross domestic product (GDP) serves as a factor in preventing further growth of the underground economy and tax evasion.

In the field of the impact of monetary policy on inflation, much research has been done, in most of which structural failure has not been studied and the regression method with a fixed parameter has been used and reached different results. Lucas (1976) argues that any change in policy regime can lead to structural failures in inflation dynamics, and that any policy analysis that does not take these failures into account will naturally have little validity. Therefore, it is important to examine whether the volume of liquidity has a different effect on inflation over time and using new regression model methods with variable time parameters can lead to more accurate policy analysis and thus more accurate economic decisions.

Given the importance of the relationship between liquidity and inflation in monetary policy, it is important to examine whether the volume of liquidity has a different effect on inflation over time and using new regression model methods with variable time parameters can lead to more accurate policy analysis and thus more accurate economic decisions.
Using a regression model with time varying parameter (TVP) and the Kalman filter approach the present study examines the reaction of the inflation rate over time to the influential variables such as the inflation rate of the previous period, the expected inflation rate, the imported inflation rate, the production gap and especially the volume of liquidity in the  period under study in which the application of time-varying parametric technique is considered as an innovation of this research and gives us more accurate results. 

Examining the changes in the growth rate of liquidity, inflation rate and GDP growth rate shows that in most years, the growth rate of liquidity has a positive effect on the inflation rate of the next period. But in some years, despite the increase in the growth rate of liquidity, the inflation rate of the next period has decreased. Also, in some other years, despite the decrease in the growth rate of liquidity, the inflation rate of the next period has increased. It can be said that in short term, inflation in Iran is not just a monetary phenomenon. Also, due to the fact that in some years the inflation rate was relatively high, but in the next period, the growth rate of liquidity increased or in some other years, the GDP growth rate was relatively low, but in the next period, the liquidity growth rate decreased. It can be said that the changes in the growth rate of liquidity in Iran were not commensurate with the changes in inflation rates and economic growth rates and this shows that monetary policy has been wrong. 

In present study, the results of estimating the regression model as a variable time parameter and examining the trend of coefficients of explanatory variables over time in this study show that these coefficients have not been constant during the period under study and have changed over time due to external shocks such as revolution, war, oil price shocks, applied economic policies, structural changes, international political stances and economic sanctions. That is, in addition to the volume of liquidity, other variables such as delayed inflation rate, expected inflation rate, imported inflation rate and GDP gap also have a variable effect on inflation rate over time.

One of the most important challenges of Iran's economy in recent decades is its excessive reliance on oil revenues. According to the time series of the central bank, during the years after the Islamic revolution and especially the years after the imposed war, on average 80 to 90 percent of the export income, 40 to 50 percent of the government's annual budget and 20 percent of the country's total gross domestic product It is provided from the place of oil export. Based on this, the development of the export of non-oil products with a relative advantage in the world markets is considered an inevitable requirement for the country of Iran. In other words, due to the strong dependence of the country's economy on oil on the one hand and the instability and extreme fluctuations of oil prices in the world markets, as well as due to the dominance of a multilateral monopoly market on it on the other hand, many anomalies that rule this market It is transferred inside and causes economic activities to fluctuate according to the exchange rate (Maghdisi and Ali-Shahi, 2016). According to economic planners and policy makers; The only way to free the country from the single-product economy and dependence on foreign exchange income from the sale of oil, as well as to meet the country's ever-increasing foreign exchange needs, is to develop non-oil exports and access global markets. If the foreign currency demand for imports is met from the foreign exchange earnings of non-oil exports, the country's economy will not need oil export earnings and the direct injection of these oil foreign exchange resources into the domestic economy in the current form. For this reason, the economic policy makers in Iran have paid special attention to the improvement of the non-oil trade balance in the medium-term (economic and social development programs) and long-term (Perspective Document of Iran 1404) programs of the country and mainly emphasized on The monetary and banking sector has been supported by granting facilities with lower interest than non-oil producers and exporters.
Due to the importance of this issue, in this study, the role of currency fluctuations in the impact of monetary policies on Iran's non-oil trade balance has been analyzed seasonally, with an emphasis on regime changes during the period of 1352-1396. In this regard, EGARCH regression has been used to model currency fluctuations and STAR regression has been used to investigate the role of these fluctuations in the impact of monetary policy on the non-oil trade balance.

Following the empirical studies, the following model has been considered to achieve the goals of this study:                                    (1)
where in,
lxtmt: natural logarithm of the ratio of non-oil exports to total imports in year t;
lrexcht: the natural logarithm of the real exchange rate (the product of the free market exchange rate by the global producer price index divided by the producer price index in Iran) in year t;
vrexcht: currency volatility index (conditional variance of variable lrexch_t) in year t;
lmtgdpt: the natural logarithm of the ratio of total liquidity to Iran's nominal GDP in year t;
vrexch*lmtgdpt: the natural logarithm of the ratio of total liquidity to Iran's nominal GDP in the currency volatility index
loilxt: natural logarithm of revenues from oil and gas exports in million dollars in year t;
lopenesst: natural logarithm of trade openness index (ratio of total trade to nominal GDP) in year t;
εt: is the residual of the model in year t.
After estimating exchange rate fluctuations by EGARCH regression in the period of 1352-1996 on a seasonal basis, the STAR model was used to investigate the role of exchange rate fluctuations in the impact of monetary policies on Iran's non-oil trade balance, emphasizing regime changes in the period. The study is estimated. Also, all the data were obtained from the database of the Central Bank of the Islamic Republic of Iran and the World Bank.

The results of STAR model estimation showed that there are two regimes including high and low regime with a threshold value of -4.055 for the trade balance variable in the studied time period. The results related to the low regime (trade balance less than -4.055) show that the variables of trade balance with one break, real exchange rate, currency volatility index with monetary policy, liquidity and trade openness index are respectively 980/ 13, -1.299, -0.462, -1.404 and -2.484 have an effect on the trade balance. In the above regime (trade balance more than 4.055), variables of trade balance with one break, real exchange rate, currency volatility index with monetary policy, liquidity and trade openness index are 25.601, 1.604, 562 respectively. 0.0, 2.177 and 3.158 have an effect on the trade balance. Therefore, in the low regime, the exchange rate fluctuation has a negative effect on the trade balance, and in the low regime, it has a positive effect. This result can be due to the severe exchange rate fluctuations in the post-revolution period, which caused domestic goods to become cheaper compared to foreign goods and increased non-oil exports due to the decrease in the value of the national currency. Although the increase in non-oil exports in the country is mainly in the form of raw materials and agricultural products, and industrial products have a very small share in the country's exports. The dependent variable coefficient with one break in both regimes has a positive effect on the trade balance in the current period, which is consistent with empirical studies. Other variables have negative coefficients in the low regime and positive coefficients in the high regime, which shows that the real exchange rate, liquidity and trade openness had a negative effect on the trade balance in the period before and at the beginning of the revolution until the fourth quarter of 2012. But after 2012, the mentioned variables have had a positive effect on the trade balance. The reason for this can be due to the decreasing trend of the trade balance during the period of the low regime, which could not have a positive role on the trade balance due to the excess of imports and the lack of non-oil exports, the variable of trade openness, as well as the exchange rate and liquidity. But in the above regime, which lasts from the first quarter of 2013 to the fourth quarter of 2016, the trend of the trade balance is increasing in these years. Therefore, the aforementioned factors have also played a positive role in increasing the trade balance, although as it was said, most of the country's non-oil exports are from the raw materials of industrial production and agricultural products, and it cannot be said that the improvement of the trade balance during the high regime period is due to It has been an increase in the export of industrial products. The results obtained from this research are consistent with the results of the studies of Wong and Chong (2016), Gomez and Alvarez (2006). Also, the results of the research of Agbola (2005) and Gilfason and Risagar (1984) are in accordance with the results of this study in the low regime. From the point of view of the effect of liquidity on the trade balance, the results obtained are consistent with the research of Fitras et al. (2014).

The results of STAR model estimation showed that there are two regimes including high and low regime with a threshold value of -4.055 for the trade balance variable in the studied time period. The results related to the low regime (trade balance less than -4.055) show that the variables of trade balance with one break, real exchange rate, currency volatility index with monetary policy, liquidity and trade openness index are respectively 980/ 13, -1.299, -0.462, -1.404 and -2.484 have an effect on the trade balance. In the above regime (trade balance more than 4.055), variables of trade balance with one break, real exchange rate, currency volatility index with monetary policy, liquidity and trade openness index are 25.601, 1.604, 562 respectively. 0.0, 2.177 and 3.158 have an effect on the trade balance. Therefore, in the low regime, the exchange rate fluctuation has a negative effect on the trade balance, and in the low regime, it has a positive effect. This result can be due to the severe exchange rate fluctuations in the post-revolution period, which caused domestic goods to become cheaper compared to foreign goods and increased non-oil exports due to the decrease in the value of the national currency. Although the increase in non-oil exports in the country is mainly in the form of raw materials and agricultural products, and industrial products have a very small share in the country's exports. The dependent variable coefficient with one break in both regimes has a positive effect on the trade balance in the current period, which is consistent with empirical studies. Other variables have negative coefficients in the low regime and positive coefficients in the high regime, which shows that the real exchange rate, liquidity and trade openness had a negative effect on the trade balance in the period before and at the beginning of the revolution until the fourth quarter of 2012. But after 2012, the mentioned variables have had a positive effect on the trade balance. The reason for this can be due to the decreasing trend of the trade balance during the period of the low regime, which could not have a positive role on the trade balance due to the excess of imports and the lack of non-oil exports, the variable of trade openness, as well as the exchange rate and liquidity. But in the above regime, which lasts from the first quarter of 2013 to the fourth quarter of 2016, the trend of the trade balance according to figure (2) is increasing in these years. Therefore, the aforementioned factors have also played a positive role in increasing the trade balance, although as it was said, most of the country's non-oil exports are from the raw materials of industrial production and agricultural products, and it cannot be said that the improvement of the trade balance during the high regime period is due to It has been an increase in the export of industrial products. The results obtained from this research are consistent with the results of the studies of Wong and Chong (2016), Gomez and Alvarez (2006). Also, the results of the research of Agbola (2005) and Gilfason and Risagar (1984) are in accordance with the results of this study in the low regime. From the point of view of the effect of liquidity on the trade balance, the results obtained are consistent with the research of Fitras et al. (2014)                                
Based on the above results, it is recommended that the monetary policy makers take into account the currency fluctuations in order to improve the non-oil trade balance through monetary policies. In other words, monetary policies should be used to improve the non-oil trade balance when the currency market is less volatile. Or at least, appropriate currency policies to reduce currency fluctuations along with monetary policy should be considered simultaneously in improving the trade balance. Based on this, if there are severe currency fluctuations, monetary policies in the country cannot improve the non-oil trade balance. This shows that the growth of liquidity in the country regardless of its origin, if the currency market in the country does not reach the necessary stability, it cannot be considered a powerful tool in improving the country's non-oil trade balance. Also, the export of the country should be shifted from the export of raw materials to the export of finished goods and industrial products. Because as the trend of the country's trade balance showed, the trade balance with non-oil exports has been negative in the entire time period studied, and for the trade balance with non-oil exports to be positive, industrial production must increase, which will ultimately bring economic growth and development.

In developing countries, economic growth is the main concern of policy makers and economic thinkers. Knowing the tools and factors affecting economic growth is essential and requires deeper investigations. The importance of knowing the effective factors in the growth and development of countries in today's growing world is undeniable. The degree of effectiveness and recognition of these factors can be an important step towards accelerating growth and development. Accelerating economic growth is a tendency in developing countries. Economists are looking for an answer to the main question, what are the reasons for the difference in the economic growth of the countries of the world? In examining the factors affecting economic growth, two groups of causes can be mentioned. The first group is related to direct factors such as the accumulation of human and physical capital, and the second group includes final factors such as institutions, social capital, etc. In relation to political factors, the situation of developing countries is slightly different from their situation and performance regarding economic factors, especially, the internal economic structure of countries is very vulnerable to adverse factors. Political instability, as the most important internal factor, has the closest interaction with the concept of economic security in influencing the performance of macroeconomic variables, including production. The insecurities that arise in the atmosphere of political instability and violent behavior (such as terrorist activities) in developing countries cause the country's inability to successfully attract foreign capital, capital flight and reduction of capital. Investments are made. Among the indicators of political instability, which has been raised as one of the sensitive issues of the international community, especially developing countries, and its effects on the developments of international economic and political relations, is the phenomenon of terrorism. In this context, Asimoglu (2001), believes that with more efficient and better institutions, more investment will be made in the field of physical and human capital, security, improvement in property rights and less deviations in policies. Among the variables affecting growth and investment, security is a key category. Security is a complex concept and due to the existence of constituent quality indicators and its complexity, both theoretically and empirically, it is a source of controversy. Terrorism is a fundamental factor disrupting economic and social security.

The purpose of this research is to investigate the relationship between terrorism and economic growth in selected countries of the Middle East using the panel spatial econometric method during the period of 1980-2019 using the spatial Durbin model (SDM). Statistics and information required for variables of GDP per capita, foreign trade as a percentage of GDP, bank credits granted to the private sector, foreign direct investment as a percentage of GDP and inflation rate from the World Bank website and For the terrorism variable, it has been extracted from the global database of terrorism, separately for 9 selected countries in the Middle East region.

First, in order to check the spatial dependence of the Moran and Jerry C test, the spatial dependence of the countries was confirmed and based on the significance of the Moran test, the research model was estimated in the spatial panel framework. According to the results of the research, terrorist activities show negative and destructive effects on the economic growth of these countries, and this result is consistent with the results of other studies such as Hamida (2018) and Sanafdiari (2017). According to the results of the research, the variables of foreign direct investment, foreign trade, and bank credits have a significant and positive effect on the economic development of the studied countries, of which foreign investment and foreign trade have the greatest impact on economic growth. Also, the inflation rate has a negative and significant effect on the economic growth of the above countries, and these results are consistent with the results of other studies such as Kavah (2007), Khan (2019), Haider et al. (2015) and Sana and Shafi (2018). Be 

Terrorism and the increase in casualties caused by accidents have had a negative effect on economic growth. Terrorism affects economic growth through different channels. The increase in threats and terrorist incidents leads to insecurity in the country of origin and negatively affects the arrival of tourists. Terrorism also negatively affects investment in tourism-related fields by reducing the sense of security and prevents the strengthening of this sector. The direct effect of these terrorist incidents is to create an atmosphere of insecurity on the economy; Because it destroys and diverts productive economic resources. Scarce productive resources that could have been used to produce goods and services in society are now gone. Also, the resources and budgets allocated for other useful sectors of the economy, as a result of terrorist incidents, should now be used to strengthen the country's security. None of these changes, which are necessary to create security, will not create additional wealth for the society and will not raise the level of well-being, and will also negatively affect economic growth. On the other hand, foreign direct investment is one of the main drivers of economic development and its flow has strong effects on the country's economy. Terrorist activities reduce security and reduce investors' trust in countries exposed to terrorist activities, which leads to a decrease in the flow of foreign direct investment.

Unlike conventional banking, whose the main goal is to maximize profits based on the loans granted, Islamic banks operate based on the laws and rules of Islamic jurisprudence, in which the use of interest is prohibited. It was precisely due to this characteristic of Islamic banking that many experts were hesitant about its continued existence when the first Islamic bank was established in 1963 and predicted that interest-free banking would not last long. Despite these doubts, Islamic banks are now the fastest growing and developing financial industry in the world.
The basic question here is whether Islamic banking can meet the monetary and banking needs of the economy despite conventional banking? Do Islamic banks have the necessary stability and efficiency? In general, factors such as the ceiling of granted loans, rate of return on assets, rate of return on shares, value of bank assets,diferent types of bank expenses and various other factors can cause differences in the efficiency and performance of banks. Answering to these questions requires investigating the performance of Islamic banking compared to conventional banking.
In order to investigate the performance of Islamic banking compared to conventional banking, we used four different approaches: Data Envelopment Analysis (DEA), Stochastic Frontier Analysis (SFA), Markowitz Model, and Capital Asset Pricing Model (CAPM). DEA approach is one of the non-parametric methods based on mathematical methods and linear programming to measure the efficiency of decision-making units. In contrast, SFA is a parametric method based on econometrics and production function estimation to evaulate the efficiency of decision making units. Then we used the Markowitz model to obtain the optimal rate of return of banking stocks and unsystematic risk, as well as CAPM to find the optimal rate of return of banking stocks and systematic risk.

In order to evaluate the technical efficiency of banks based on DEA and SFA methods, the input and output variables of each model have been introduced, which include three input variables and three output variables in DEA method and three input variables with an output variable in SFA method. In the next stage, the following steps were taken to perform the Markowitz model optimization process:Some classes of the assets that are considered to be invested must be selected and according to the limitations of the Markowitz model and considerations related to the selection of variables, and collection of the research statistical sample, during developing the appropriate mathematical and statistical model, the optimization process is performed.
Expected returns are estimated for each class of assets.
The risk of each class of assets is estimated.
The process of optimization and graphical structure are performed to find the efficient frontier, based on which, the set of efficient and profitable assets is determined.
By implementing the mentioned steps and using the time series data related to the rate of return on shares of each of the banks from 2012 to 2020, the average and standard deviation related to the rate of return on the assets of each of the banks in both Islamic and conventional banking systems was measured and then the efficient frontier curve was extracted for Islamic and conventional banks. Finally, to apply the CAPM and calculate the systematic risk of banks, the value of bank shares was used for this purpose. Due to the statistical limitations in this field where the necessary data was not available for all 40 investigated banks, and on the other hand it was necessary to use the monthly return rates of these data, therefore subject to the DEA and SFA results, 5 banks from the Islamic banking system and 5 banks from the conventional banking system were selected. Then, according to the data of the monthly stock returns of each of these 10 banks since the second month of 2012 through the end of 2020 with 107 observations, the performance of both banking systems based on the CAPM and estimating the systematic risk rate for each bank was compared. For this purpose, we considered the regression model as Where  is the rate of return for asset i during period t,  is the rate of return for the market portfolio M during t,  (also called excess return) is the difference between estimated return and expected return,  is the beta coefficient and 𝜀 is the error term. To estimate above regression for the selected banks, we used the monthly return rates of the MSCI global index as , since the beginning of 2012 through the end of 2020  and the monthly stock return rates as   for each of the banks. First, this regression was performed for the portfolio of Islamic banks and conventional banks, and then we repeated it for each selected bank, and accordingly, the beta coefficients related to the stock portfolio of conventional and Islamic banks, as well as each of the selected banks, were calculated.

The average efficiency of Islamic banks in data DEA and SFA models was evaluated as 74% and 56.15% respectively, and for conventional banks as 69.5% and 48.13% respectively. By implementing the Markowitz model during the period 2012-2020, the average and standard deviation of Islamic banks' stock returns were calculated as 0.76% and 4.09% respectively, and for conventional banks as 0.68% and 6.35% respectively. Next, by developing ten optimization problems, ten pairs of optimal stock returns and their corresponding risk rates were calculated for each of the two Islamic and conventional banking systems, and accordingly, the efficient frontier curve for each of these two systems was extracted. The average correlation coefficients of stock return rates for two Islamic and conventional banking systems were calculated as 40.4% and 44.1%, respectively, which indicates the  lower amount for the Islamic banking system compared to conventional one. Finally, so as to implement the CAPM for measuring the beta coefficient for Islamic and conventional portfolios, firstly this regression was estimated for the portfolios of Islamic banks and conventional banks. The results are compiled in Table No. (1).