Evaluating the Effect of Bank Characteristics on Bank Lending Channel: A Factor-augmented Vector Autoregressive (FAVAR) Approach

Document Type : Research Paper


1 Ph.D. Candidate, Department of Finance and Insurance, Faculty of Management, University of Tehran, Tehran, Iran.

2 Prof., Department of Finance and Insurance, Faculty of Management, University of Tehran, Tehran, Iran.

3 Assistant Prof., Department of Finance and Insurance, Faculty of Management, University of Tehran, Tehran, Iran.

4 Associate Prof., Department of Leadership and Human Capital, Faculty of Management, University of Tehran, Tehran, Iran.



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.


Main Subjects

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