Financial stress periods and their consequences on economic growth in Iran

In recent decades, due to the increase of stress in financial markets and its effect on economic growth, the need to find better models and indicators to deal with crisis events and reduce their effects is felt. This paper seeks to answer this question: What are the effects of the stress of the financial system and its main sub-sectors (banking system, stock market, and foreign exchange market) on economic growth in Iran? For this purpose, the quarterly data of the time-series 1370Q1 to 1395Q2 (1991Q2 to 2016Q3) from the banking sector and the stock and foreign exchange markets have been used. To construct a multi-lateral financial stress index "within" and "between" each sector/market, respectively, the method of Principal Component Analysis (PCA) and Credit Weighting (CW) has been used. Using the Auto-Regressive Moving Average (ARMA) and the Auto-Regressive Distributed Lags (ARDL) approach, the required optimal intervals were estimated and using the Exponential General Auto-Regressive Conditional Heteroskedastic (EGARCH) approach, the conditional variance of the desired indicators, which represents the volatility of the indicators, was calculated. Then, using the Markov-Switching approach, the impact of financial stress on Iran's economic growth has been evaluated. The results indicate that despite periods of financial stress in Iran, its effect on economic growth has been insignificant and meaningless in most cases.