Banks

The main objective of this paper is to evaluate the structure of the Iranian banking system and to measure the market power factor based on the Boone approach. In this paper, we investigated the Iranian organized money market, including 18 banks operating in the period of 2008-2015. To calculate the marginal cost (MC), we used a Translog Stochastic Frontier Cost Function . Findings based on the Boone approach confirm that the size of efficient-based competition is low in Iranian organized money market. Based on the Boone index, this value in the Iranian banking market equals -0.022, and Bank Melli and Bank Mellat due to having high marginal cost elasticity with respect to market share, have a higher power in market transformations and distortion of market structure towards monopoly. In contrast, Karafarin Bank, Post Bank, Sarmayeh, and Sina Bank have produced the least distortion in market structure.

Asset-liability mismatch in balance sheet of banks shows serious challenges in banks because of the traditional methods of recording assets and liabilities at book value in Iran. The Central Bank of the country motivated and advised banks to take concrete steps in minimizing the mismatch in the asset-liability composition. This paper attempts to suggest a micro funded framework that can evaluate the role of asset and liability management in banking sector in business cycles through a DSGE model. In this paper, we use Bayesian method to estimate parameters and use national account and balance sheet data from 1981 to 2013. Results show that tightening monetary policy decreases the cost of ALM .On the other hand, raising required reserve requirement increases the cost of asset and liability management; technology shock leads to decrease of asset and liability management cost, and the costs of ALM affects interest rate. Then, the increase of the cost of ALM leads to increase of interest rate. JEL Classification: E31, O42

In the Iranian economy, part of the government's fiscal policies and liabilities is always financed by banks. As government debt to banks increases, the private sector's access to loans and facilities is limited. It can cause undesirable macroeconomic outcomes. This study investigates the macroeconomic effects of government debt on banks in Iran over 1972–2016 by using an SVAR model. Results show that government debt to banks does not significantly affect the aggregate demand ratio to aggregate supply and GDP per labor. Still, it significantly increases the real exchange rate and decreases the non-tradable goods' ratio to tradable goods prices. In the long-run, the real exchange rate, the ratio of non-tradable goods to tradable goods price, and the general price level changed by 34.46, 20.95, and 46.4 percent, respectively, which can be explained by the government debt to banks. Results indicate that the government policy manages the Iranian economy.

The aim of this article is to investigate the dynamic correlation between the Global Economic Policy Uncertainty index (GEPU) and Non-Performing Loans (NPL) in Iran. The relationship between economic uncertainty and banking performance indices is significant because of the systemic importance of banks in every economy. We evaluated this relationship in this developing country, especially under economic sanctions. In this study, we used the Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) to assess the relationship between Global Economic Policy Uncertainty and Non-Performing Loans of Iranian banks using the statistics of these two indicators by R and Eviews programming and statistical software in the period from 2004 to 2021. Our results show that Iranian banks' Non-Performing Loans (NPL) are rather associated with Global Economic Policy Uncertainty (GEPU) during major global shocks such as the global financial crisis in 2008 or the Covid-19 pandemic. However, despite fluctuations in the correlation between Non-Performing Loans and Global Economic Policy Uncertainty over time, this study also illustrates that these correlations in some periods are generally somewhat low that some of the reasons could be the sanctions imposed on Iran's economy and banking system, imposed loans to banks by the government, forced interest rate, etc., which led to a limited connection among Iranian banks and global banking system. To prove this claim we estimate the model for some countries with an open economy, like Japan, Singapore, the US, Turkey, and Spain. The result shows that this correlation is much higher in comparison to Iran.