پژوهش ها و چشم اندازهای اقتصادی

پژوهش ها و چشم اندازهای اقتصادی

بررسی نحوۀ اثرگذاری اجزای منابع نقدینگی در اقتصاد ایران: رهیافت DSGE

نویسندگان
1 استادیار گروه اقتصاد، دانشگاه شهید بهشتی، تهران، ایران
2 دانشجوی دکتری رشتۀ اقتصاد پولی، دانشگاه شهید بهشتی، تهران، ایران
چکیده
کنترل مدیریت‌نشدۀ رشد نقدینگی به‌دلیل پیامدهای منفی آن، همواره مورد توجه سیاست‏گذاران بوده است. هدف مقالۀ حاضر تحلیل و بررسی مکانیسم اثر‏گذاری اجزای منابع نقدینگی بر متغیرهای کلان اقتصادی ایران است. تغییرات نقدینگی منابع مختلفی دارد و ناشی از تغییر در عرضه دارایی‏ های متفاوتی است که اجزای مختلف منابع نقدینگی را تشکیل می‏ دهند و می‏ توانند اثرات متفاوتی بر عملکرد متغیرهای کلان اقتصادی داشته باشند. به این منظور یک الگوی اقتصاد کلان با لحاظ کردن اجزای منابع نقدینگی شامل خالص دارایی‏ های خارجی بانک مرکزی، خالص دارایی‏ های خارجی بانک‏ها و مؤسسات اعتباری غیر‏بانکی، خالص بدهی بخش دولتی به بانک مرکزی، خالص بدهی بخش دولتی به بانک‏ها و مؤسسات اعتباری غیربانکی و بدهی بخش غیر‏دولتی به بانک‏ها و مؤسسات اعتباری طراحی شده است که روابط متغیرهای اقتصادی را در چهارچوب یک مدل تعادل عمومی پویای تصادفی ارائه می ‏دهد. الگوی موردنظر براساس اطلاعات اقتصاد ایران طی دورۀ زمانی 1379-1399 شبیه‏ سازی شده است. واکنش متغیرهای کلان اقتصادی به‌ازای رشدهای یکسان نقدینگی براساس توابع عکس ‏العمل آنی، نشان می‏ دهد اجزای مختلف منابع نقدینگی اثرات متفاوتی بر متغیرهای کلان اقتصادی دارند. این نتایج حامل این پیام سیاستی است که علاوه بر مدیریت نقدینگی، توجه به تحولات اجزای منابع نقدینگی نیز از اهمیت بسیاری در حوزۀ سیاست‏گذاری پولی برخوردار است.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Investigating the effects of the components of liquidity sources in Iran's economy dynamic stochastic general equilibrium approach

نویسندگان English

hossein samsami Mazreeh Akhoond 1
Ahmad Bakhtiyari 2
1 Assistant Professor of Economics, Shahid Beheshti University of Tehran, Tehran, Iran
2 Ph.D Candidate in Economics, Shahid Beheshti University of Tehran, Tehran, Iran
چکیده English

Introduction

The volume of the external money supply is determined by the policymaker, but the amount of money and liquidity will be influenced by the individual's decision to combine their portfolios and the behavior of banks (through lending channels and balance sheets) in the internal money supply. From this perspective, the initial change in external currency (monetary base) causes changes in the supply and demand of all types of assets (such as external and internal money) and their rate of return, and the behavior of individuals and banks determines the optimal composition of the portfolio of assets of individuals and banks and the new and balanced composition of liquidity volume. . Due to differences in the structure of the economy in different countries, the external currency itself can be created from different origins, the exogenous increase of each component of the central bank's asset column (monetary base) causes a change in the relative supply of that asset and its rate of return. Liquidity changes have different sources and are due to changes in the supply of different assets that make up different components of liquidity resources and since the components of liquidity resources are not of the same kind and originate from different processes can have different effects on the performance of macroeconomic variables. The purpose of this article is to analyze and investigate the mechanism of the effect of the components of liquidity resources on the macroeconomic variables of Iran. Changes in liquidity have different sources and are caused by changes in the supply of different assets that form different components of liquidity

sources and can have different effects on the performance of macroeconomic variables. For this purpose, a macroeconomic model by including the components of liquidity resources including net foreign assets of the central bank, net foreign assets of banks and non-bank credit institutions, net debt of the public sector to the central bank, net debt of the public sector to banks and non-bank credit institutions and Non-governmental sector debt is designed to show the relationships of economic variables in the framework of a dynamic stochastic general equilibrium model provides.

Methodology

The model presented in this research is a small open economy consisting of six sectors of households, firms, foreign sectors, banks and credit institutions, government and central bank within the framework of dynamic stochastic general equilibrium model of new Keynesians with respect to nominal and real frictions. By optimizing the objective functions of each of the above brokers, the result of the obtained economic relations is a system of nonlinear differential equations under rational expectations that are currently not empirically solvable, especially in larger patterns. But we can use approximation technique to calculate the model solution in the approximate range functionally. In this research, the set of equations is linear logarithmic using the Ahlik method (1999). In the next step, the input values of the pattern and calibration of parameters and variables have been done using the Iranian economy data during the period 2000-2020. Then, using the Dynar software, the system of equations based on the Bunchard-Kahn method is solved. The results of the statistical tests and moments indicate that the proposed model is suitable for simulating Iran's economy.

Results and Discussion

In order to evaluate the different effects of liquidity resources on economic variables, the reaction of these variables to liquidity component shocks based on instantaneous reaction functions has been investigated. The findings of the research show that the net assets of the banking system through balance of payments and net debt to the banking system through the channel of the state financial balance, if the source of liquidity is created, increases the variables of production, consumption and investment and causes mild growth or decrease of inflation and exchange rate variables. However, if the source of the liquidity creation of non-governmental debts is from the channel of facilitation, it has a decreasing effect on the variables of production, consumption and investment, and only increases inflation and exchange rate. The two sources of the net assets of the banking system and the net of government liabilities to the banking system, contrary to the source of non-governmental sector debt due to the creation of added value in the economy, have more productive effects and investment and less inflationary effects, hence, macroeconomic stability will bring.

Conclusion

The reaction of macroeconomic variables for the same liquidity growth based on instantaneous reaction functions shows that different components of liquidity sources have different effects on macroeconomic variables. These results carry the policy message that, in addition to liquidity management, attention to the developments in liquidity resources components is also important in the field of monetary policy. Considering that liquidity has increased by about 5% in all five components of liquidity components, the effects and implications of the five components of liquidity creation sources can be examined. Comparative results indicate that for the specific growth of liquidity, the increases caused by the net assets of the banking system and the net of public sector liabilities to the banking system have more productive and investment effects and less inflationary effects, hence macroeconomic stability. Therefore, it is recommended that the monetary transition policy as much as possible prevent the increase in non-governmental sector debt which leads to increased liquidity.

کلیدواژه‌ها English

Dynamic stochastic general equilibrium(DSGE)
Monetary Policies
Money Transfer mechanism
sources of liquidity
Abderezak, A. (2005). Oil price shocks - Money supply causality: Some evidence from Algeria. The Journal of North African Studies, 10(2),173-181.
Agénor, P. R., Alper, K., & da Silva, L. A. P. (2014). Sudden floods, macro prudential regulation and stability in an open economy. Journal of International Money and Finance, 48(part A), 68-100.
Alaei,R., & Bakhtiyari, S. (2019).Threshold effect of the monetary base on inflation: the approach of non-linear auto-regressive soft transmission models. Economic Strategy Quarterly,25(7), 109-141.(In Persian)
Bhatia, J.R. (1971), Factors Influencing Changes in Money Supply in BCEAO Countries, International Monetary Journal. 18(2),389-398.
Bernanke, B. S, & Blinder, A. S. (1988). Credit, Money and Aggregate Demand. The American Economic Review, 78(2), 435-439.
Burriel, P., Fernandez, V., Verde, J., & Rubio-Ramirez, J. F. (2010). MEDEA: a DSGE model for the Spanish economy. SERIEs, 1, 175-243.-Calvo, G. A. (1983). Staggered prices in a utility-maximizing framework, Journal of monetary Economics. 12(3), 383-398.
Caporale, G. M., Ali, F. M. & Spagnolo, N. (2014). Oil Price Uncertainty and Sectoral Stock Returns in China: A Time-Varying Approach. China Economic Review, 34, 311–340.
Cecchett, S. G. (1995). Distinguishing Theories of Monetary Transmission Mechanism. Economic Research Federal Reserve Bank of St. Louis, 77(3), 83-97.
Christiano, L., Eichembaum, M., & Evans, C. (2005). Nominal rigidities and the dynamic effects to a shock of monetary policy, Journal of Political Economy, 113(1), 1-45.
Demirbas, A., Al-Sasi, B., & Nizami, A. (2017). Recent Volatility in the Price of Crude Oil. Energy Sources, Part B: Economics, Planning, and Policy, 12, 408–414.
Durán, N. M, & Hernández, I.P.(2018). Is there any relationship between the monetary base and the interest rate of the US Federal Reserve? Contaduría y Administración, Accounting and Management, 63, 1 -18
Elder, J. (2018). Oil Price Volatility: Industrial Production and Special Aggregates. Macroeconomic Dynamics, 22(3), 640-653.
Gali, J. (2008).Monetary Policy, Inflation and BusineesCycle: An introduction to the New Keynesian Framework, PRINCETON university Press, 79-93.
Ge Xinyu., Li Xiao. L., & L. Zheng. (2020). the Transmission of Financial Shocks in an Estimated DSGE Model with Housing and Banking. Economic Modelling, 89, 215-231.
Hadian, M., & Dargahi, H.(2021). Macroeconomic effects of current and development expenditures of the government in Iran: DSGE approach. Quarterly magazine of applied economic theories, 8(1), 241-272.
Jalali Naeini, A., & Zamanzade, H.(2016).Investigating the different effects of liquidity components on production and price: vector error correction approach with Namana exogenous variables, Monetary and Banking Research Quarterly, 27, 1-27(in Persian)
Kapuściński, M. & Pietryka, I. (2019). The impact of the excess reserves of the banking sector on interest rates and money supply in Poland . Narodowy Bank Polski, Working Paper ,Economic Research Department, 300, 1-48.
Lashgari, M. (2014). Money, Currency and Banking. Tehran, Payame Noor Publications, First Edition.(In Persian)
Koop, Gary & Dimitris, K.(2010). Bayesian Multivariate Time Series Methods for Empirical Macroeconomics. Foundations and Trends in Econometrics, 3(4), 267-358.
Komijani, A., & Alinejad, M. F. (2012). Evaluating the Effectiveness of Monetary Transmission Channels Production and Inflation besides Analyzing their Relative in Iran’s Economy. Scientific and research quarterly of planning and budget, 17, 39-63. (in Persian)
Liu, Z., Waggoner, D.F. & Zha, T. (2011). Sources of Macroeconomic Fluctuations A Regime Switching DSGE Approach. Quantitative Economics, 2(2), 251–301.
McCallum, B., & Nelson, E. (2000). Monetary policy for an open economy: an alternative framework with optimizing agents and sticky prices, Oxford Review of Economic Policy. 16(4), 74-91.
Mohammadi Pour, A., Salmanpour Zonouz, A., & Fakhrhosseini, S, F.(2019). The Effect of Shocks in Monetary Base and Government Oil Revenues on the
Iranian Economy Using Dynamic Stochastic General Equilibrium Model. Quarterly Journal of Economic Growth and Development Research, 10, 93-112 (in Persian)
Moshiri, S., & Vasheghani, M. (2010). Investigating the Monetary Transfer Mechanism and its Timing in Iran’s Economy. Economic Modeling Quarterly, 4, 1-32. (in Persian)
Pesaran, M. H., (1998). Economic Trends and Macroeconomic Policies in Post-revolutionary Iran. Economy and money magazine,82,42-45. (in Persian)
Ravenna, F., & Walsh, C. E. (2006). Optimal monetary policy with the cost channel, Journal of Monetary Economics. 53(2), 199-216.
Sarno L. & Taylor.M. (2001). Offial Intervention in the Foreign Exchange Market: Is It Effective &, If So, How Does Work?. Journal of Economic Literature ,39(3),839. 868.
Sharifi Ranani, H., & Komijani, A., &Shahrestani, H. (2010). Investigating the Mechanism of Money Transfer in Iran: Approach Vector Auto Regressive Structural. Money and Economics Quarterly, 2. (in Persian)
Snowdan B. & Van H. (1997). A Macroecnomics Reader. One eddition
Stracca, L. (2007), Should we take inside money seriously? European Central Bank Working paper series, 841, 1-43.
Tavakolian, H & Sarem, M. (2016). DSGE modeling in Dynare software (modelling, solution and estimation based on Iranian economy). Tehran: Research Institute of Money and Banking. (in Persian)
Uhlig, H. (2001). A Toolkit for analyzing nonlinear dynamic rational expectations models easily, Computational Methods for the Study of Dynamic Economic, 30-61.
Yadollahzadeh Tabari, N. (2013). How do monetary policy tools work? An investigation on monetary transmission mechanism in Iran. Management Science Letters, 3(4), 1167-1174
Walsh, C. E. (2010). Monetary theory and policy. MIT press.third eddition.
Iacoviello, M. (2015). Financial business cycles. Review of Economic Dynamics, 18(1), 140-163.
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