Modelling the effect of monetary policies of central bank on macroeco-nomic indicators in Iran using system dynamics and fuzzy multi-criteria decision-making techniques
محورهای موضوعی : Financial AccountingMehdi Memarpour 1 , Ashkan Hafezalkotob 2 , Mohammad Khalilzadeh 3 , Abbas Saghaei 4 , Roya Soltani 5
1 - Department of Industrial Engineering, Science and Research Branch, Is-lamic Azad University, Tehran, Iran
2 - College of Industrial engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
3 - Department of Industrial Engineering, Science and Research Branch, Is-lamic Azad University, Tehran, Iran
4 - Department of Industrial Engineering, Science and Research Branch, Is-lamic Azad University, Tehran, Iran
5 - Department of industrial Engineering, Faculty of Engineering, KHATAM University, Tehran, Iran
کلید واژه: fuzzy multi-criteria decision-making techniques, Monetary Policies, System Dynamics, macroeconomic indicators,
چکیده مقاله :
The most important policymaker entity in the bank-centered economy of Iran is central bank of Islamic Republic of Iran which has always been trying to manage and improve macroeconomic indicators by applying monetary policies. However, investigation of Iran's economy after four decades shows that this country has always suffered from double-digit inflation rates and 15000-fold liquidity throughout this period, while GDP of Iran has grown only by two times during this period. This paper tries to evaluate the effect of monetary policies of central bank on macroeconomic indicators by analytical-descriptive and library method via combining system dynamics and fuzzy multi-criteria decision-making using Vensim and Super Decision software. Monetary policy instruments in this re-search include foreign exchange rate, deposits interest rate, facilities interest rate, required reserve ratio, and open market operations. Further, the macroeconomic indicators include inflation, liquidity, national foreign exchange value, and eco-nomic growth. The results indicated that the most important macroeconomic indi-cators in the country according to economic experts are "national foreign ex-change value" and "inflation". The most important tool for monetary policies of central bank is "foreign exchange rate". Indeed, in order to improve the economic misery index, this bank should take measures to improve the national foreign exchange value, then manage inflation and liquidity, and eventually adjust the banking interest rate
The most important policymaker entity in the bank-centered economy of Iran is central bank of Islamic Republic of Iran which has always been trying to manage and improve macroeconomic indicators by applying monetary policies. However, investigation of Iran's economy after four decades shows that this country has always suffered from double-digit inflation rates and 15000-fold liquidity throughout this period, while GDP of Iran has grown only by two times during this period. This paper tries to evaluate the effect of monetary policies of central bank on macroeconomic indicators by analytical-descriptive and library method via combining system dynamics and fuzzy multi-criteria decision-making using Vensim and Super Decision software. Monetary policy instruments in this re-search include foreign exchange rate, deposits interest rate, facilities interest rate, required reserve ratio, and open market operations. Further, the macroeconomic indicators include inflation, liquidity, national foreign exchange value, and eco-nomic growth. The results indicated that the most important macroeconomic indi-cators in the country according to economic experts are "national foreign ex-change value" and "inflation". The most important tool for monetary policies of central bank is "foreign exchange rate". Indeed, in order to improve the economic misery index, this bank should take measures to improve the national foreign exchange value, then manage inflation and liquidity, and eventually adjust the banking interest rate
[1] Atefi, M.R, Radfar, R, Asgharizadeh, E. A System Dynamics Model for Balanced Performance Evalua-tion of A LARG Supply Chain, Industrial Management Perspective, 2022; 4(11): P.253-290. doi:10.52547/JIMP.11.4.253
[2] Hesami Azizi, B., and Mehnatfar, Y., and Jafari, A., Relationship between effective rate of interest rate on facilities and on deposits with emphasis on the role of central bank (In Persian), banking monetary research, 2016; 9(28): 199-222. RePEc: mbr: jmbres: v:9: y:2016: i:28: 199-222
[3] Omrani, M., Determining the interest rate on deposits and facilities of banks, boys quarterly of Islamic jurisprudence studies and principles of law, 2011; 20(1):253 magiran.com/p980434
[4] Tavasoli, R., Tajik, M., Kalantar Mehrjerdi, A., Investigating the effect of monetary policies of central bank on money creation by the banking system. Journal of novel researching management and account-ing, 2016; 16(1): 165-174.
[5] Makiyan, S., Samadi, A., Amareh, J., Investigating Cyclical Status of Monetary and Financial Policies in Iran. Quarterly Journal of Quantitative Economics, 2022; 18(4): 67-92. doi: 10.22055/jqe.2020.31264.2157
[6] Meysami, H., and Nadri, K., Open market operations with securities of the government and central bank, Islamic financial research ,2015; 5(1): 119-154.
[7] Hanh Song Thi Pham, Thanh Le & Loan Quynh Thi Nguyen. Monetary Policy and Bank Liquidity Cre-ation: Does Bank Size Matter? International Economic Journal, 2021; 35(2): 205-222, doi:10.1080/ 10168737. 2021.1901762
[8] Yazdani, M., Mohammadi, M., The role of inflation goalsetting in the foreign exchange rate equaliza-tion policy: approach of difference in differences, (in Persian). quarterly of monetary- banking research, 2019; 12(42): 721-744.Handle: RePEc: mbr: jmbres: v:12: y:2020: i:42: 721-744
[9] Montagnoli, A., and Moro, M., The Cost of Banking Crises: New Evidence from Life Satisfaction Data KYKLOS, 2018; 71(2): 279–309. doi:10.1111/kykl.12170
[10] Ghasan H.B., and Krichene. N., Financial Stability of Conventional and Islamic Banks: A Survey. Financial Stability of Conventional and Islamic Banks: A Survey, 2017; 2(1): 1–31.
[11] Askari, H., Krichene, N., Islamic finance: an alternative financial system for stability, equity, and growth, PSL Quarterly Review, 2014; 268(67): 9-54. doi: 10.13133/2037-3643/11984
[12] Otzurk. O, Gerlikhan, S, Kanusaji, I, Ozkan, C, Serin, Z, A. System Dynamic Approach for Determina-tion of Optimal Monetary Policy During the Covid-19 Economic Crisis: A Case of Turkey, Finansal Araştırmalar ve Çalışmalar Dergisi. 2021; 13(24): 223-244. doi: 10.14784/marufacd.879264
[13] Ghaffary fard, M., rezaei, H., rahmati, A., Simulation of the Effect of Monetary Policy on the Produc-tion Upsurge of the Iranian Economy: A System Dynamics Approach. Scientific Journal of System Man-agement Studies, 2021; 1(4): 39-67.
[14] Bakhshi Dastjerdi, R., Taleb Baghebani, M., Mojahedi Moakher, M. M., Ahmadniya, M. S., The sys-tem Dynamics Approach to Money Creation Effect on Inflation in Iran Economy. qjerp. 2019; 27(89): 99-137.
[15] Khairul Bahri, M., Indonesia's Macroeconomic Model using System Dynamics Approach, 2013. doi:10.13140/2.1.4215.6487
[16] Firoozan, T., Pourakbar, M., The Modeling of Liquidity in Iranian Economy by Dynamic System Method. jde. 2015; 1(2) :61-90.
[17] Ghazizadeh, M., and Molaalipour, J., Identifying the effect of foreign exchange rate determination on macroeconomic variables of Iran's economy with system dynamics approach, the 10th international con-ference of industrial engineering, 2013.
[18] Taheri, F., Setayesh, M., janani, M., hematfar, M., Designing the Optimal Model of Banking Assets and Liabilities Management based on System Dynamics Approach. Advances in Mathematical Finance and Applications, 2021; 3(1): 133-141. doi: 10.22034/amfa.2021.1928525.1587
[19] Yeh, T.M., Huang, Y.L., Factors in determining wind farm location: Integrating GQM, fuzzy DEMATEL, and ANP. Renewable Energy, 2014; 66(1):159-169. doi: 10.1016/j.renene.2013.12.003
[20] Hsieh, T.Y., Lu, S.T., and Tzeng, G.H., Fuzzy MCDM approach for planning and design tenders selec-tion in public office buildings. International journal of project management, 2004; 22(7):573-584. doi:10.1016/ j.ijproman.2004.01.002
[21] Habibi, A., Izdiar, S., Sarafrazi, A, Fuzzy Multi-Criteria Decision Making, 2014, Katibeh Gil Publica-tions (In Persian).
[22] Mohanty, R. P., Agarwal, R., Choudhury, A. K., & Tiwari, M. K. A fuzzy ANP-based approach to R&D project selection: a case study. International Journal of Production Research, 2005; 43(24): 5199-5216. doi:10.1080/00207540500219031
[23] Safaei ghadikolaei a.h., tabibi m., hajiabadi f., Compound method approach of fuzzy anp- dematel for making preference of green supplier performance assessment criteria (case study: iran heavy diesel com-pany). Management research in iran (modares human sciences). 2013; 17(3):129-149.
[24] Yousefi nejad attari m., bagheri m.r., neishabouri jami e. A decision making model for outsourcing of manufacturing activities by anp and dematel under fuzzy environment. International journal of industrial engineering and production research (ijie) (english). 2012; 23(3):163-174.
[25] Hashemi, F., Hosseini, S., Hozhabr Kiani, K., Farzin, M., Investigating the Relationship between Infla-tion and Exchange Rate by Considering the Foreign Exchange Market Pressure Index and the Degree of Intervention of the Central Bank. The Journal of Economic Studies and Policies, 2020; 7(2): 239-266. doi: 10.22096/esp.2021.128880.1353
[26] Salatin, P., Ghalamzan, K., Ghafari, N., The Impact of Financial Markets on the Misery Index: An Integrated Data Approach, Quarterly Journal of Financial Economics, 2016; 10(35): 131-146. 20.1001. 1.25383833.1395.10.35.6.4
[27] Saatichoubar, F., Mohebbi, M., Zeraat kish, Y., Negahdari, E., Application of Panel Regression Model in Examining the Effect of Monetary Policy on Bank Profitability, Advances in Mathematical Finance and Applications, 2022; 6(4): 117-128. doi: 10.22034/amfa.2022.1952584.1700
[28] Baghestani, A.A, Rahimi,R, Baghestany, A.A., Rahomi, R., Investigating the Relationship Between Interest Rates and Liquidity in Tejarat Bank, Journal of Computational Economics, 2022; 1(1): 131-145. magiran.com/p2426579
[29] Memarpour, M., Hafezalkotob, A., Khalilzadeh, M., Saghaei, A., Soltani, R., A Data-Driven Design of the Optimal Investment Portfolio for the Industry in a two-level Game using the Markowitz Model by Me-ta-Heuristic Algorithms: Economic Analysis of Condition Monitoring System. Scientia Iranica, 2022; 11(2): 99-112. doi: 10.24200/sci.2022.55048.4047.
[30] Hosein Ahmadi, M., Erfani, A., Investigating the Optimal Behavior of Policymakers in Determining Bank Interest Rates in the Iranian Economy, Quarterly Journal of Applied Theories of Economics, 2021; 7(4): 1-26. doi: 10.22034/ecoj.2021.12261
[31] khani, F., Jafari Samimi, A., tehranchian, A., ehsani, M., The Effects of Money Market on Gold Mar-ket with a Systemic Dynamics Approach. Economical Modeling, 2021; 15(54): 1-19. doi: 10.30495/ eco. 2021. 1926550.2501
[32] Naghdi, Y., Efati Baran, F., Determining the Optimal Interest Rate and Its Effects on Iran's Economy: An Application of Optimal Control Theories. Economic Modelling. 2019; 45(1): 73-92.