Assessing the effect of macroeconomic shocks on systemic risk of the banking system using the SVAR model in Iran

In this study, we have used the total capital market index (TEDPIX) as an index of the real sector of the economy and the index of banks and credit financial institutions as an index that explains the developments of the banking system. Also, oil revenues, exchange rate uncertainty, tax revenues, liquidity, nominal interest rates, inflation uncertainty and GDP have been used as macroeconomic variables in the research period (1370-1396). To estimate the systemic risk of the banking system, the quarterly data of the banks' index is used and the value at risk of the return of the seasonal data of the index is estimated using an exponential GARCH model. In order to model the interaction of macroeconomic variables and systemic risk of the banking system, an unrestricted vector autoregression (VAR) model was estimated and then using instantaneous impact functions and based on Chulsky analysis, systemic risk response to other variables was investigated and analyzed. In order to identify the channels of impact of economic shocks on the systemic risk of the banking system, based on the structures of the Iranian economy, a structural vector autoregression (SVAR) model was specified and then the instantaneous impact functions were extracted and the effect of macro variable shocks on the systemic risk of the banking system was investigated. Also, the effect of systemic risk of the banking system on macroeconomic variables was investigated and analyzed using instantaneous impact functions. Finally, the interaction model of macroeconomic variables and systemic risk of the banking system was approved using the vector autoregressive model.