مینو امینی میلانی

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).

The main purpose of this article was to analyze the state of the banking system in terms of the main influencing factors and specifically the interbank interest rate on the profitability of commercial banks. Therefore, after studying the theoretical foundations and literature review of this field, the background of the research was examined with the knowledge of previous experiences. The current research is applied research that aims to help improve the structure and performance of commercial banks by using the research results. To do this, a descriptive-analytical method is used. Also, library methods and the databases of the Securities and Exchange Organization and the Time Series Bank of the Central Bank of the Islamic Republic of Iran have been used to collect the required data. The statistical sample of this research consists of 17 state, private, and privatized commercial banks. In addition, in this article, to analyze the data analysis, the econometric methodology of estimating the model of simultaneous equations is used. According to the research findings, the interbank interest rate has a direct and negative effect and the coefficients obtained from the model estimation are significant. It is worth mentioning that factors such as bank size, bank concentration index, and ownership ratio also have a significant effect on the profitability of commercial banks under study. Also, the results show that macroeconomic variables such as annual inflation rate and economic growth rate have a negligible effect on the exogenous variables of the model.

Exchange rate is one of the important economic variables that are affected by various factors. Since the exchange rate in any country is considered one of the basic indicators in determining the degree of international competition and explaining the internal situation of that country's economy, with the aim of investigating the role of economic sanctions imposed on the exchange rate in Iran, this research was carried out. According to empirical studies, several visible and invisible factors have affected the exchange rate in the country; Factors that sometimes can not all be considered in one economic model; therefore, even with conventional methods, it is not possible to comment with certainty on the extent to which some of these factors affect the exchange rate. Based on this argument, in order to use an appropriate method, in order to investigate the effect of financial and commercial sanctions imposed on Iran along with other variables affecting the exchange rate in the period after the Islamic Revolution (1978-2020) from a fuzzy approach is used. The results show that severe economic sanctions with a high and strong fuzzy coefficient have had a positive and significant effect on the exchange rate in Iran. Also, liquidity, budget deficit, balance of payments, inflation and adaptive exchange rate expectations, respectively, after the severe sanctions, have had the greatest impact on increasing the exchange rate in recent years. The fuzzy coefficients obtained for the variables of oil revenues, the degree of openness of the economy, economic growth and interest rate on account of domestic investment deposit, indicate the negative effect of these variables on the exchange rate in Iran in this period.

The main goal of this research is to investigate the performance of the Islamic banking system compared to the conventional banking system in terms of efficiency criteria by two parametric and non-parametric approaches. For this purpose, two approaches of data envelopment analysis and stochastic frontier analysis were used. The results of the investigation, in terms of both approaches, indicate that Islamic banks are more efficient than banks operating in the conventional system according to the studied input and output variables. The average efficiency of Islamic banks in DEA and SFA models evaluated as 74 and 56.15 percent, respectively, and for conventional banks as 69.5 and 43.18 percent, respectively. The average efficiency of all banks was 71.8% in DEA and 37.8% in SFA. The results also indicated that Iranian banks performed weaker than other Islamic banks in terms of granting the loans, but better than conventional banks. Also, public banks in Iran perform better than private banks in terms of granting loans. Also, the findings of this research showed that the risk of stock returns related to selected Islamic banks is lower compared to conventional banks, both in terms of systematic risk and unsystematic risk.

The main objective of this study is to assess the economic impacts of sanctions against Iran. This analysis was performed using the computable general equilibrium (CGE) model with a focus on exports, imports, production, and price levels. After calibrating the CGE model and measuring the values of exogenous parameters and variables, the study assessed the economic impacts of sanctions on Iran’s economy using the 2016 input-output table (IOT) and other statistical information based on scenario building. The results obtained using GAMS 34 and through two scenarios revealed that the import sanctions have had more severe economic impacts on Iran’s economy than the export sanctions, reducing economic growth by 6.72 and 9.87% and increasing the general level of production costs by 23.6 and 29.46% in the first and second scenarios, respectively. The export sanctions also led to an economic growth by 2.05 and 4.55% and increased the general level of production costs by 2.03 and 4.5% in the first and second scenarios, respectively. It is noteworthy that the general level of prices reduced in the export sanctions, which is consistent with the theoretical analysis.

Iran's economy has been facing the problem of inflation for more than half a century. According to empirical studies, various visible and invisible political, economic, cultural, etc. factors have been effective in increasing the inflation rate; Factors that sometimes cannot all be considered in one economic model. Therefore, it is not possible to comment with certainty on the extent to which some factors affect the inflation rate with conventional methods. Based on this argument, in order to use an appropriate method in this study, from the fuzzy approach to investigate the severity of the impact of economic sanctions imposed on Iran along with other variables affecting inflation, in the period after the Islamic Revolution (1978-2020), Used. The results show that severe economic sanctions against Iran with a strong fuzzy coefficient, have a positive and significant effect on inflation in Iran. Also, liquidity, people's adaptive expectations, budget deficit and exchange rate fluctuations, respectively, after the severe sanctions, have had the greatest impact on increasing inflation. The obtained fuzzy coefficients of oil revenues and economic growth (excluding oil) indicate the negative effect of these two variables on the inflation rate in Iran.

Unemployment has been one of the major problems in Iran's economy over the past decades, and job creation has been one of the main concerns of policy makers over the years. The main purpose of this article is to evaluate employment policies in Iran during 1976-2016. During this period, government has implemented generating projects, granting cheap credits, tax and insurance exemption and encouraging investment in areas with high unemployment rates and attracted foreign investment in the form of development programs. In this paper, labor demand is considered equivalent to job creation so we have estimated the dynamic function of labor demand using the ARDL technique. The results showed that business environment, GDP, labor productivity, government spending, corporate income tax, non-public sector credit balances, capital saving and foreign direct investment had a significant relationship with employment in the period under review. But there was no significant relationship between real wage and employment.