بررسی بی ثباتی مالی تحت یک مدل تعادل پویای تصادفی مطالعه موردی اقتصاد ایران

نوع مقاله : علمی

نویسندگان

1 دانشجوی دکتری، گروه اقتصاد، دانشگاه آزاد اسلامی، واحد قزوین، قزوین، ایران

2 استادیار گروه اقتصاد،دانشگاه آزاد اسلامی ، واحد قزوین، قزوین ، ایران

چکیده

در این مقاله با استفاده از مدل تعادل عمومی پویای تصادفی کینزی جدید به بررسی بی­ثباتی مالی با مداخله­گری سیستم بانکی پرداخته می­شود با توجه به اهمیت بخش بانکی در انتقال آثار سیاست اقتصادی سعی شده است که مدل مالی به مدل استاندارد اصلی اضافه شود. علاوه بر این، توابع عکس­العمل آنی بهره­وری، نرخ بهره و ارزش خالص واسطه­های مالی و تأثیر آن بر رفتار عوامل اقتصادی مورد بررسی قرار می­گیرد. برای این منظور از سری زمانی فصلی برای سال­های 1378-1396 استفاده شده است. نتایج نشان می­دهد که یک تکانه مثبت تکنولوژی موجب می­شود بهره­وری عوامل تولید، حجم سرمایه و نیروی کار مورد تقاضای بنگاه­های تولیدی افزایش یابد در نتیجه درآمد خانوار ناشی از اجاره سرمایه و دستمزد نیروی کار  افزایش و همچنین میزان مصرف کالاها و خدمات و پس­انداز در قالب سپرده­ بانکی افزایش ­یابد. از طرفی به دلیل افزایش عرضه کل اقتصاد، میزان تورم در اقتصاد کاهش می­یابد. کاهش تورم و افزایش جذب منابع بانکی، ثبات مالی بانک­ها را افزایش می­دهد. تکانه مثبت نرخ بهره به عنوان یک عامل ایجاد سرکوب مالی، با افزایش هزینه اعتبارات بانکی، میزان دسترسی به اعتبارات و ارزش خالص واسطه­های مالی را کاهش داده و با محدود کردن جذب منابع بانکی  ثبات مالی بانک­ها را کاهش می­دهد.

کلیدواژه‌ها


عنوان مقاله [English]

Financial Instability under a DSGE Modeling Approach: A Case Study of Iran

نویسندگان [English]

  • Afsaneh Ghasemi 1
  • Beitollah Akbari Moghaddam 2
1 PhD student, of Economics, ,Islamic Azad University, Qazvin Branch,,Qazvin, ,Iran
2 Assistant professor, Department of Economics, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
چکیده [English]

We developed a quantitative monetary DSGE model with financial intermediaries that face endogenously determined balance sheet constraints. Considering the importance of the banking sector in transferring the effects of economic policy, it has been attempted to add the financial model to the standard model. To do so, a seasonal data set from 1998 to 2016 is used. The results shows, a positive technology shock, the productivity, capital stock and labor demanded by manufacturing firms will increase as a result of household income resulting from the rental of capital and wages, as well as the consumption of goods and services and savings deposits will increase. On the other hand, due to the increase in aggregate supply, the inflation rate is decreasing. Reducing inflation and increasing the attraction of banking resources will increase financial stability banks. The positive interest rate shock as in creating financial repression diminishes the banks' financial stability by decreasing the attraction of bank resources with increasing the cost of bank credits, reducing credit and net worth of financial intermediaries. Also, government expenditures shock by creating instability demand leads to unsustainable production and short-term economic growth.

کلیدواژه‌ها [English]

  • Financial intermediaries
  • DSGE Model
  • Intrest Rate Shock
  • Productivity Shock
  • Fiscal Shock

Ahmadyan, A. (2016). Modeling a Dynamic Stochastic General Equilibrium Model for the Iranian Bank Withdrawal. The Journal of Economic Policy, 7(14), 77-103. [In Persian]

 
Bernanke, B. (1983). Non Monetary Effects of the Financial Crisis in the Propagation of the Great Depression. American Economic Review. 73 (1), 257-276.
Bernanke, B. & Mark, G. (1989). Agency Costs, Net Worth and Business Fluctuations. American Economic Review, 79(1), 14-31.
Bernanke, B.; Gertler, M. & Gilchrist, S. (1999). The Financial Accelerator in a Quantitative Business Cycle Framework. In: Taylor, J. B., Woodford, M. (Eds.), Handbook of Macroeconomics, North-Holland, Amsterdam: 1341-1393.
Carlstrom, Ch. T.; Timothy, S. F. & Paustian, M. (2016). Optimal Contracts, Aggregate Risk, and the Financial Accelerator. American Economic Journal: Macroeconomics, 8(1), 119-147. 
Christiano, L. J.; Trabandt, M. & K. Walenti. (2011). Introducing Financial Frictions and Unemployment into a Small Open Economy Model. Journal of Economic Dynamics and Control, 35(12), 1999-2041.
Damjanovic, T.; Damjanovic, V., & Nolan, Ch. (2017). Default, Bailouts and theVertical Structure of Financial Intermediaries. Working Paper, Retrieved from http://oxfordre.com/economics/abstract/10.1093/acrefore/9780190625979.
Dargahi, H. & Hadian, M. (2016). Evaluation of Interactions Between the Real and Financial Sectors of Iran’s Economy: A DSGE Approach, The Applied Theories of Economics, 3(1),1-28.
.DeJong, D. N. & Dave., C. (2007). Structural Macro Econometrics. Princeton University Press. Retrieved from, https://press.princeton.edu/titles/9622.html.
Duncan, A., & Nolan, Ch. (2017b). Financial Macroeconomics with Complete Business Cycle Risk Markets. Working Paper, Retrieved from https://www.kent.ac.uk/economics/documents/research/papers/2017/1719.pdf.
Gertler, M. & Kiyotaki, N. (2009). Financial Intermediation and Credit policy in Business Cycle Analysis. In preparation for the Handbook of Monetary Economics. 3(53), 547-599.
Gertler, M. & Kiyotaki, N. (2015). Banking, Liquidity, and Bank Runs in an Infinite Horizon Economy. American Economic Review, 105(7), 2011–2043.
Gertler, M., Karadi, P. (2011). A model of unconventional monetary policy, J Monet Econ, 58(1): pp. 17-34.
Gertler, M.; Kiyotaki, N., & Prestipino, A. (2016).Wholesale Banking and Bank Runs in Macroeconomic Modeling of Financial Crises,” in John B. Taylor and Harald Uhlig (Eds.). Handbook of Macroeconomics, 2, Elsevier, North Holland, 1345-1425.
Hafstead, Marc. & Smith, J. (2012). Financial Shocks, Bank Intermediation, and Monetary Policy in a DSGE Model. Stanford University: Working Paper,Retrieved from https://pdfs.semanticscholar.org/7e70/af7c9abce56cf0a4f7cac2ea81bd62af00f7pdf.
Heidari, H. & Molabahrami, A. (2017). Financial Accelerator in a DSGE Model with Financial and Banking Sectors for Iran. Journal of Money Banking Research Institute, 10(36), 97-117.
Iacoviello, M. (2005). House Prices, Borrowing Constraints, and monetary Policy in the Business Cycle. American Economic Review, 95(1), 739-764.
Iacoviello, M., & Neri, S. (2010).Housing Market Spillovers: Evidence from an Estimated DSGE Model. American Economic Journal: Macroeconomics, 2(2), 125-64.
Kiyotaki, N. & Moor, J. (1997). Credit Cycles. Journal of Plotical Economy, 105(2), 211-248.
Khalilzadeh, J.; Heidari, H.; Feizi, S. & Bashiri, S. (2016).  Investigation of Producers Financial Challenging’s with Emphasis on the Role of Monetary Policy and the Banking Sector Credits: Application of DSGE Model, The Applied Theories of Economics, 4(4), 61-90. [In Persian]
Mehrara, M.; Tavakolian, H. and Rhmani, A. (2016). The Role of Economic Fluctuations on the Banks' Concessional Facilities from the Bank's Additional Capital Channel. The Journal of financial Economics, 10(37), 1-15. [In Persian]
.Merola, R. (2014). The role of Financial Frictions During the Crisis: an Estimated DSGE Model. Dynare Working Paper Series, Retrieved from www.dynare.org/wp-repo/dynarewp033.pdf.
Mozafari, Z.; Kazerooni, A & Rahimi, F. (2018). Effect of Financial Structure on Instability of Iran's Economic Growth.  The Journal of financial Economics, 18(1), 1-31. [In Persian]
Palic, I. (2018). The Empirical Evaluation of Monetary Policy Shock in Dynamic Stochastic General Equilibrium Model with Financial Frictions: Case of Croatia. International of Engineering Business Management, 10(1), 1-11.
Stephen P. M.; Varadi, A. & Yashiv, E. (2017). The Interaction of Financial Frictions and Labor Market Frictions in a DSGE Model. WorkingPaper,Retrievedfromwww.patrickminford.net/emf/emf_2017/Frictions%20Working%20Paper.pdf
Smets, F. and Wouters, R. (2007). Shocks and Frictions in U.S. Business Cycles:   a Bayesian DSGE approach. American Economic Review, 97(3), 586-606.