فصلنامه مدلسازی اقتصادی
سال هفدهم شماره 1 (پیاپی 61، بهار 1402)

The main objective of this study is to investigate the interactive effects of monetary and macroprudential policies on the stability of Iranian banking system. For this purpose, the effects of monetary and macroprudential policies and interactive of these two policies have been evaluated using the annual time series data of 24 private and government banks of Iran during the period of 2007-2019 and using generalized moments method (GMM).The results show that the monetary policies have significantly caused the instability of the banking system, and the macroprudential policies have significantly increased the stability of the banks. Also, empirical findings of the research show that, the interaction of monetary policies and macroprudential has a positive and significant effect on the stability of banks. This result indicates that the implementation of macro reserve policies in Iran has caused the effects of monetary policies to be modified on the instability of banks. Hence, it is necessary for the economic policy makers to consider these interactions when designing monetary and macro prudential policy interventions. In fact, economic policymakers are advised to use macroprudential policies to strengthen the stability of the banking system when implementing expansionary monetary policies.

This paper investigates the situation of foreign trade to compensate for water shortage problems in Iran. Using input-output tables of 2011 and 2016 tables, the changes in virtual water trade balance in this period were investigated. Results indicate that in spite of the positive trade balance in these years, international trade caused virtual water to enter the country. However, both the value of the trade balance of products and the trade balance of virtual water in 2016 decreased compared to 2011. Overall, despite the increase in the import of virtual water due to the decrease in the total backward linkage of final products and the change in the share of exports and imports in the foreign trade balance; changes in the trade balance, the intensity of direct water consumption, the structure of production, and the structure of traded goods, respectively, contributed the most to the reduction of virtual water imports.

In this paper, the effect of formed habits on consumer behavior was investigated by separating the three effects of generation, age and time (year) by generating a quasi-hybrid data set using the Dayton method. For this purpose, in the field of generations, 14 generations were studied from 1305 to 1995. Concerning time (year), this research investigates over 30 years from 1986 to 2020. The age of the subjects in this study ranged from 16 to 72 years. The results of the analysis of generation effects show that consumption expenditures are increasing with younger generations. The results of the study of the effect of time show the increase of households' consumption expenditure during the years 1986 to 2020 and the somewhat constant trend of the years 1995 to 2015. Results of the effects of age on consumption expenditure pattern confirmed the life cycle pattern.

In this paper, the effect of formed habits on consumer behavior was investigated by separating the three effects of generation, age and time (year) by generating a quasi-hybrid data set using the Dayton method. For this purpose, in the field of generations, 14 generations were studied from 1305 to 1995. Concerning time (year), this research investigates over 30 years from 1986 to 2020. The age of the subjects in this study ranged from 16 to 72 years. The results of the analysis of generation effects show that consumption expenditures are increasing with younger generations. The results of the study of the effect of time show the increase of households' consumption expenditure during the years 1986 to 2020 and the somewhat constant trend of the years 1995 to 2015. Results of the effects of age on consumption expenditure pattern confirmed the life cycle pattern.

The main aim of the research was to identify the financial variables that are effective in predicting turnaround of the listed companies in the Tehran Stock Exchange and to predict turnaround by using artificial intelligence method. For this purpose, the information of 173 Distress Companies that came out of distress and turnaround was extracted during 1383 to 1399. Artificial Intelligence approach was used to analyze the data. In this approach, by using Lars and Relief Feature Selection Algorithms, 10 out of 54 financial variables which were effective in turnaround of companies were identified and then, the Learning Algorithm of Support Vector Machine and Decision Tree were used to evaluate the accuracy of the results of the identified variables in predicting turnaround. The results showed that Lars Feature Selection Method and Vector Machine Algorithm Support have better performance in predicting the time to exit from distress as compared to the Relief Feature Selection Method and Decision Tree Algorithm. Also, regardless of feature selection methods, support vector learning machine has a higher predictive power as compared to decision tree.

According to the emphasis of the Ball Committee, the survival rate of any economy is proportional to the resilience rate of its banks, and, when economic crises occur, the resilience of banks is too important. Then the purpose of this research is to investigate the indicators of the development of the banking sector that can affect the resilience of the Iranian banking system. Therefore, with the help of previous research, some factors were identified and the data were collected for 30 banks and credit institutions during the years 2000 to 2020 in the form of unbalanced panels. After that, the level of resilience was calculated with the help of the Volare index, and the type of relationships was evaluated with the help of the dynamic data panel method. The results showed that among the 18 indicators investigated as factors affecting the resilience of the Iranian banking system, only 9 factors are nonlinearly related to resilience. Resilience variables of the previous period, banking efficiency, the ratio of Interest-Free Income to total income, and the ratio of low-cost resources to total resources, have a direct relationship with resilience, and the indicators of bank size, shareholders' equity to debt, the ratio of loans to free resources, the ratio of the cost of doubtful loans to total expenses and the level of risk tolerance, had an indirect relationship. Also, private or public banks had no significant relationship with resilience. In conclusion, the resilience process of Iranian banks from 2000 to 2020 was drawn.