تحلیل اثرات سیاست پولی در اقتصاد ایران با وجود بانکداری سایه، رویکرد تعادل عمومی پویای تصادفی (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
بانکداری سایه از زمان بحران مالی در سال 2007 به عنوان عامل بحران در جهان شناخته شد. این مقاله به طور تجربی رابطه بین بانکداری سایه و اجرای سیاست پولی در ایران را با استفاده از روش تعادل عمومی پویای تصادفی تحلیل می کند. مطالعه ما نشان می دهد که بانکداری سایه در ایران به سرعت در حال رشد است و به دلیل عدم فعالیت در چارچوب مقررات بانک مرکزی می تواند از کارآیی سیاست های پولی بکاهد. به منظور بررسی نقش بانکداری سایه، اثرات شوک سیاست پولی در دو سناریوی مختلف بررسی شده است. در هر دو حالت سیاست انبساطی پولی و یا سیاست انقباضی پولی، با سناریوی در نظر گرفتن بانکداری سایه در اقتصاد، اثرات اخلالی در متغیرهای رشد و تورم مشاهده گردید، به طوری که با اعمال سیاست پولی انبساطی تغییرات در تولید پس از یک دوره منفی شده و با اعمال سیاست انقباضی پولی نیز با در نظر گرفتن بانکداری سایه، میزان کاهش در تولید و سطح عمومی قیمت ها به مقدار کمتری رخ می دهد و در واقع از اثرات سیاست انقباضی کاسته شده است. در مدل پس از تشدید سیاست های پولی، بانک های عادی میزان وام های موجود در ترازنامه خود را کاهش می دهند در حالی که بانک های سایه وام دهی را افزایش می دهند. این امر اثرات واقعی شوک را کاهش می دهد، اما در عین حال بانک های سایه واکنش متغیرهای کلیدی به شوک های واقعی را تشدید می کنند و می توانند بخش مالی و کل اقتصاد را بی ثبات تر کنند و اقتصاد را از مسیر ثبات و توسعه خارج نمایند.Analysis the effects of monetary policy in Iran's economy with the existence of shadow banking, using dynamic stochastic general equilibrium method
Since the financial crisis in 2007, shadow banking has been recognized as the cause of the crisis in the world. This article empirically analysis the relationship between shadow banking and the implementation of monetary policy in Iran by using the dynamic stochastic general equilibrium method. This study shows that shadow banking is growing rapidly in Iran, and due to lack of activity within the framework of Central Bank regulations, it can reduce the effectiveness of monetary policies. In order to investigate the role of shadow banking, the effects of monetary policy shock have been investigated in two different scenarios. In both cases of expansionary monetary policy or contraction monetary policy, with the scenario of considering shadow banking in the economy, disruptive effects on growth and inflation variables were observed. So that with the application of expansionary monetary policy, the production changes after a period become negative, and with the application of contraction monetary policy, taking shadow banking into account, the amount of reduction in production and the general level of prices occurs to a lesser extent, and in fact The effects of the contraction policy have been reduced. In the model after tightening monetary policy, regular banks reduce the amount of loans on their balance sheet while shadow banks increase lending. This reduces the real effects of the shock, but at the same time shadow banks amplify the reaction of key variables to real shocks and can make the financial sector and the whole economy more unstable and take the economy out of the path of stability and development Extended Abstract Introduction At the forefront of macroeconomic research on the causes of the Great Financial Crisis (GFC) was and still is the usage of dynamic stochastic general equilibrium (DSGE) models. To capture the nonlinearities of the GFC, these models were enriched with a variety of financial frictions. This paper focuses on a special subset of these frictions, the shadow banking system. We provide a structured review of the strand of literature that considers shadow banking in DSGE setups and draw particular attention to the modeling approach as well as impact of shadow banking. Our analysis allows the following conclusions: firstly, models featuring shadow banking are better able to simulate realistic movements in the business cycle that are of comparable magnitude to the GFC. Secondly, the models consider amplification channels between the financial sector and the real economy that proved to be of importance during the crisis. Thirdly, the models display a good explanatory power of financial stability measures in the light of shadow banking There is a long-standing concern that financial innovation may undermine monetary control of the central bank. Such concern has intensified in recent years as the shadow banking sector has grown outside the traditional commercial banking sector. Has the rise of the shadow banking system affected the effectiveness of monetary policy? To answer this question, I simulate a counterfactual economy without shadow banks and compare it with the actual data In this paper I will answer the following questions: How does the monetary transmission channel via shadow banks work and how can it be modeled? How does the resulting credit intermediation of shadow banks affect the reaction of aggregate loan supply to monetary policy? In addition, if the inclusion of shadow banks changes the propagation of shocks, what has been its contribution to macroeconomic uctuations in recent years? To answer these questions. I develop a structural model that distinguishes between banks and shadow banks based on their ability to create credit. I use the monetary DSGE model with financial intermediaries by Gertler and Karadi (2011), (GK11 from here on) to describe bank behavior and credit creation, and I extend it with a shadow banking sector. In this model, banks create credit endogeneously in the sense of "inside money" as in Kiyotaki and Moore (2004). Shadow banks need to raise funds from households to satisfy _rm loan demand. I model fund raising by shadow banks as a search in the funding market for previously created deposits, which are held by the household sector. In GK11, an increase in the monetary policy rate leads to an increase in the external finance premium for borrowers, prompting a decrease in the value of their collateral, thereby decreasing the willingness of banks to lend. The resulting deleveraging results in a credit squeeze for the real sector, disinvestment and a fall in output. Simultaneously, increased deposit rates discourage households from current consumption and instead encourage savings. In this paper, savings in the form of deposit holdings constitute available funds for the shadow banking sector. After an increase in the monetary policy rate, this increase in available funds for shadow banks results in a higher share of savings owing into the shadow banking sector. Shadow banks lend out these additional funds and thereby alleviate the credit squeeze, mitigating the fall in investments and any consequent recession. Method The DSGE models that are currently the benchmark macroeconomic models resulted from the fusion of the real business-cycle models of the 1980s with the New Keynesian sticky-price models of the early 1990s. Some current versions still feature frictionless financial markets and a passive role for financial intermediaries, thus being utterly unsuitable for the analysis of financial booms and busts. This is the case of DSGE models currently used for monetary policy analysis at the main central banks—e.g., the SIGMA model at the Federal Reserve (Erceg, Guerrieri, and Gust 2006), the Smets and Wouters model at the European Central Bank (Smets and Wouters 2003), and the Bank of England’s Quarterly Model (Harrison et al. 2005). Dynamic stochastic general equilibrium (DSGE) is a macroeconomic model that facilitates macroeconomic analysis and policy making in central banks, as well as government and nongovernmental organizations (NGOs). DSGE models, such as the European Central Bank’s Smets-Wouters framework, perform time-based macroeconomic general equilibrium analysis of interactions between economic variables. DSGE models aim to describe the behavior of the economy in an equilibrium steady-state stemming from optimal microeconomic decisions associated with several representative agents (households, firms, governments, central banks, etc.). These decisions are based on the intertemporal optimizing the behavior of representative agents, with the first-order conditions of the optimization problem linearized around a constant steady-state using a first-order Taylor approximation; 2nd order terms raise problems beyond the scope of the present paper. This section lays out the basic model. It is the monetary DSGE model with financial intermediaries by Gertler and Karadi (2011) (GK11 from here on). I add a second financial intermediation sector, called the non-bank financial or shadow banking sector, that issues loans to firms. Shadow banks first need to raise funds from households in the form of deposits to engage in firm lending. Irrespective of whether shadow banks lend to the real sector directly, or whether they buy securitized credit claims of previously originated loans, shadow banks become the effective intermediary, and banks' balance sheets are freed up. In this model the economy is populated by six types of agents: households, banks, shadow banks, non-financial goods producers that demand loans, capital producers, and monopolistically competitive retailers. A central bank conducting monetary policy is the source of monetary disturbances and completes the model. The setup is equivalent to GK11 with the addition of shadow banks and an additional household savings technology. Results The relationship between the monetary and the real sector in both developed and developing countries is still one of the topics of interest among economists, according to some studies, credit shocks can even leave more severe effects than productivity shocks in the real sector of the economy (Jerman and Vincenzo, 2012). This article, paying special attention to the shadow banking sector in Iran and considering the credit channel as the most important monetary policy transmission channel in Iran, has investigated and analyzed the effects of the presence of shadow banking in Iran's economy using the DSGE method. The counterfactual analysis offers insights on how shadow banks affect the transmission of monetary policy. In an economy without shadow banks, when yield-sensitive depositors. Become unsatisfied with the low rates offered by commercial banks, they flow out of the banking system in periods of monetary tightening, leading to a reduction in money supply and credit supply. In contrast, in an economy with shadow banks, yield-sensitive depositors can switch within the banking system from commercial banks to shadow banks. With more deposit inflow, shadow banks are able to increase their lending, which buffers the decline in commercial bank lending and dampens the impact of monetary tightening. The results of the model processing show that the proposed model with the presence of shadow banking has better processing capabilities than the model without the presence of shadow banking, and with the occurrence of a positive monetary shock, the mean and standard deviation of the variables in the second scenario and with the presence of shadow banking in explaining the key variables of the economy, including the inflation rate, production and money volume, has a higher explanatory power and is closer to the reality of Iran's economy. Table 1. Comparing the actual values of the mean and standard deviation with the estimated values based on the model Standard deviation of simulated data Average of simulated data The standard deviation of the actual data Actual average variable (gap) scenario 0/0613 0/066 0/069 0/63 Production Scenario (1) No shadow banking 0/074 0/10 0/096 0/13 inflation 0/0655 0/64 0/069 0/63 Production Scenario (2) With shadow banking 0/083 0/16 0/096 0/13 inflation With special attention to the shadow banking sector in Iran and considering the credit channel as the most important channel of monetary policy transmission in Iran, this article has investigated and analyzed the effects of the presence of shadow banking in Iran's economy using the DSGE method. In order to investigate shadow banking in Iran's economy, while planning two different scenarios including the presence and absence of shadow banking, the existential effects of shadow banking in the economy were discussed separately. The current research examines the effect of expansionary and contractionary monetary policy under the two scenarios on inflation and production variables through the credit channel. The results of solving the model, while confirming the assumptions of the article about the disruptive effects of the presence of shadow banks in the economy, show that shadow banking can reduce the effectiveness of monetary policies due to the lack of supervision by the central bank. The following table briefly shows the results of expansionary and contractionary monetary policies under the two scenarios introduced for better comparison. Table 2. Comparison of monetary policy in the form of two scenarios mentioned in the article policy Scenario (1) No shadow banking Scenario (2) With shadow banking Production inflation Production inflation Expansionary monetary policy Increasing production and reaching the long-term level after seven periods Positive inflationary effect The increasing effect on production is neutralized after a period and then production decreases Inflationary effect more than scenario 1 Contractionary monetary policy Decrease in production level A decrease in the level of prices and a negative inflationary effect Decrease at a lower rate of scenario 1 and then increase production Decreasing inflation at a higher rate than scenario 1 Ethical Considerations Compliance with ethical guidelines : All ethical principles have been observed in this article. All sources used in this article are mentioned. Regarding the method of collecting statistics and data used in the article, sources are also mentioned. In this article, due to being the leader in the issues related to shadow banking in Iran, we encountered many problems, including the lack of Persian articles and the lack of necessary statistics and information. Funding: This research received no external funding. Authors’ contribution: Conceptualization, methodology, validation, formal analysis, resources, Writing original draft preparation, writing review and editing; all authors. Conflict of interest: The authors declare no conflict of interest. Acknowledgments: We are grateful, without implication, to an anonymous referee for helpful comments
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