عنوان مقاله [English]
The purpose of this paper is to provide an empirical framework for assessing monetary policy shocks in two Iranian stock and housing markets in high and low volatility regimes. For this purpose, firstly, using Markov Switching models, both stock and housing markets are divided into two regimes and probabilities associated with each regime. It should be noted that the Markov Switching Modeling Approach is used to identify two distinct environments for each market where the environment is referred to as high fluctuations and low fluctuation environments. Then, using Probit models, the effects of monetary policy on the probability of housing and stock markets in a regime with high fluctuations are investigated in the next step. For this purpose, the monthly data on money base, the stock market and housing stock returns, inflation rates and dollar return during the period of 2010-2016 were used. The results show that money base and higher inflation rates will keep stock and housing stock in a highly volatile regime. The rise in dollar yields also reduces the probability of the two above-mentioned markets fluctuating in the regime. The findings are very useful for policy makers, because the studies conducted in this paper provide a degree of predictive power that can be used in monetary policy decisions.