Liquidity Creation Index Calculation in the Framework of Berger and Baumann's Pattern and its Impact on Banking Crises: An Application of the Logit and Probit Panel Model

Banks play an important role in the economy and financial markets by allocating funds. In fact, banks act as financial intermediaries. Banks are also a pool of liquidity, creating this liquidity through the maturity of balance sheet items. Due to the importance of bank liquidity, this research has attempted to calculate the liquidity creation index in the banking system of Iran using the Berger and Bauman method (2009). Since banks are the most important economic centers, it should be noted that liquidity will have a serious impact on their performance as well as on the economic situation of the community, and banks will be subject to crisis and instability. The Markov-Switching model is used to characterize years based on the banking crisis. Probit-Logit model has been used to investigate the impact of liquidity on the banking crisis. Data from 2005 to 2017 of 17 private and public banks are included. The results of this study will show that by using Berger and Bowman's (2009) model, liquidity creation has been calculated for 13 years and with the help of Logit model, the best model has been selected and shows that liquidity will have a positive impact on the banking crisis. Assets, credit risk, inflation and deferred claims will have a positive impact, but free trade and capital adequacy will have a negative impact on the banking crisis. In fact, banks create liquidity to prevent bankruptcy. However, liquidity creation will first cause loss for the banks themselves and then for the economic society.