محسن بهزادی صوفیانی

The aim of this study is to examine the nonlinear effects of fiscal and monetary policies on inflation during 1990:3 to 2013:1 based on threshold model. First lag of the liquidity growth is recognized as threshold variable with threshold value estimated at 6.37 percent. In low liquidity growth, the results indicate that inflation expectations and the lagged liquidity growth are the most important determinants of inflation. In high liquidity growth, effects of the variables including liquidity, development and con-current expenditure, exchange rate, budget deficit and inflationary expectations are much stronger than low one. GDP and its lag in both regimes are anti-inflationary as expected. Oil revenues have no inflationary effects in both regimes, so it seems that the effect of oil shocks on inflation is captured by other variables such as exchange rate and money growth. Based on results, it seems that liquidity growth can be considered as the most important factor for regime change in the relationship between inflation and fiscal and monetary policies in the economy. So if economy benefits from the low liquidity regime, it can prevent the inflationary effects of variables like government expenditure or exchange rate and use the opportunity to control inflation expectations. It is recommendable, in low liquidity regime to use fiscal, monetary and exchange rate policies to stimulate production and real sector with low inflationary effects. Keywords: Inflation, Inflationary Regimes, Threshold Model, Nonlinear Model JEL Classification: E31, H5, C01

The present study investigates the impact of macroeconomic and bank-specific variables on non-performing loans (NPLs). To avoid the identification problem, two models are employed to address this impact. The first one tests the effect of macroeconomic variables including the growth of oil revenues, inflation, and the growth of GDP without the oil sector on the growth of NPLs. Data is quarterly over the period 2004:3 to 2019:3. The transition variable in this setup is the growth of oil revenues and its threshold is 9 percent, which divides the sample into oil booms and oil recessions. According to the results, inflation has a significant positive effect on NPLs. During the oil boom, oil revenues decrease the NPLs. Due to the immense size of the government and its current and capital expenditures, when oil revenues are lower, the government forces banks to allocate loans to finance projects with long maturity. Furthermore, the present study used PSTR to test the impact of bank-specific variables consisting of interest rate spread, loan loss provision, loan to deposit ratio, and NPLs. To do so, monthly data of 10 banks is used over 2016:04 to 2020:12. The transition variable is the interest rate spread at 1 percent, which categorizes the banks into two groups of good and bad. Good banks collect deposits with a low-interest rate and allocate high-rate loans with less chance of default. So, interest spread is the most important prominent determinant of decreasing NPLs, while the loan to deposit ratio is dependent on the banks belonging to which group. For good banks, the loan to deposit ratio decreases the NPLs, while for bad banks, it worsens the growth of NPLs.

Iranian stock market, as a reflection of the real sector of the country's economy, has experienced many uncertainties and challenges in recent years. One of the macroeconomic factors that vaguely affects stock market is exchange rate, which has a significant volatile pattern with several overshoots during recent years. As a result, analyzing the impact of the exchange rate on stock price has become important as always. Bearing the restrictions on Iran’s trade and spectacular role of exchange rate in Iranian economy along with monetary expansion and fiscal dominance in mind, stock market reacts to exchange rate fluctuations in an asymmetric way. In order to prevent the impact of outliers and parametrical failures, this study seeks to examine the impact of exchange rate fluctuations on the stock price using quantile regression. Based on daily data between 2020/10/12 till 2024/12/20 and using first difference of both stock price logarithm and exchange rate logarithm, it became vivid that the impact of the exchange rate on the stock price is different in estimated quantiles and it is U shaped. Meaning when Stock market is stable and there are no absolute pattern of growth or crash around the median, exchange rate could not explain the stock price significantly. However, if the stock market goes bearish or bullish, quantiles where market is on its lowest or in top two quantiles, exchange rate has a crucial positive impact on the market which complies with evidence in the sample period.