ارزیابی تأثیر مشخصه های بانک بر کانال وام دهی بانک ها با رویکرد FAVAR (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
هدف: در این پژوهش وجود کانال وام دهی بانک ها به عنوان یکی از سازوکار های انتقال سیاست پولی و اثرگذاری مشخصه های بانکی بر این کانال در اقتصاد ایران بررسی شده است. روش: مدل استفاده شده در این پژوهش، مدل FAVAR است که برنانکه، بووین و الیاس (۲۰۰۵) معرفی کرده اند. در این پژوهش، ۶۱ متغیر کلان اقتصادی، طی دوره ۱Q۱۳۸۳ تا ۴Q۱۳۹۸ و ۲۴ متغیر بانکی، طی دوره ۴Q۱۳۸۷ تا ۴Q۱۳۹۸ به کار گرفته شده است. یافته ها: نتایج نشان می دهد که سیاست پولی بر وام دهی بانک ها در اقتصاد ایران تأثیر با اهمیت و معناداری دارد. با بررسی اثر مشخصه های بانک بر کانال وام دهی، در دو حالت وام دهی تجمیع شده و تفکیک شده، نتایج نشان می دهد که واکنش وام دهی تجمیع شده بانک ها به سیاست پولی، بعد از لحاظ کردن مؤلفه های بانکی، به صورت بااهمیتی تغییر نمی کند؛ اما با درنظرگرفتن وام دهی تفکیک شده بانک ها، نتایج نشان می دهد که واکنش وام دهی برخی بانک ها به شوک سیاست پولی معنادار نیست و مشخصه های بانک تا حدی بر کانال وام دهی اثرگذارند. نتیجه گیری: کانال وام دهی را می توان در اقتصاد ایران کانالی فعال به شمار آورد که از طریق آن، بخش واقعی می تواند تحت تأثیر قرار گیرد. همچنین مشخصه های بانک بر کانال وام دهی اثر چشمگیری نمی گذارد.Evaluating the Effect of Bank Characteristics on Bank Lending Channel: A Factor-augmented Vector Autoregressive (FAVAR) Approach
Objective: In this study, we investigated the existence of the bank lending channel (BLC) as one of the monetary transmission mechanisms and the effect of banking characteristics on this channel in the Iranian economy.
Methods: The Factor-Augmented Vector Autoregressive (FAVAR) model, introduced by Bernanke, Boivin, and Eliasz (2005) was used. This research studied 61 macroeconomic variables from 2004Q2 to 2020Q1 and 24 banking variables from 2009Q1 to 2020Q1.
Results: The investigation delivered two main results. First, by considering the growth of M2 as a proxy of monetary policy, the monetary policy proved to have a significant effect on bank lending and the BLC in the Iranian economy. When identifying monetary policy shock, the response of real lending growth was found positive and significant in the quarter when the shock was identified and also in the following three quarters. Substituting nominal lending growth for real lending growth, lending growth had a more significant response to the monetary policy shock. Also, by considering the monetary base as a proxy of monetary policy, lending growth had a less significant response to the monetary policy shock. Second, we found that bank characteristics don’t have a significant effect on the BLC. We investigated the effect of bank characteristics on the BLC at both aggregated and disaggregated lending. The results of the analysis of aggregated lending response showed that by including the bank factors, compared with the case where there are only economic factors in the model, the aggregated lending response doesn’t change significantly after considering the bank factors. Therefore, the bank characteristics do not significantly impact the response of the aggregated lending growth to the monetary policy shock. The results of the analysis of disaggregated lending response showed that except for Parsian and Pasargad banks, whose lending response to monetary policy shock is positive and insignificant, other banks give positive and significant responses to monetary policy shock. Overall, the bank characteristics have a more significant effect on the BLC in the disaggregated lending case.
Conclusion: According to the achieved results, the BLC can be considered an active channel in the Iranian economy, by which the real economy can be affected. Also, the bank characteristics don’t have a significant effect on the BLC. Therefore, considering the strength of the BLC in the Iranian economy, the very close relationship between the BLC and monetary policy variable (M2), and regarding the insignificant effect of bank characteristics on the BLC, monetary policy-maker should take into account the BLC when setting monetary policy.
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