The Impact of Financial Uncertainty on Monetary Policy, Inflation and Output in Iran: A Markov Jump-Linear-Quadratic (MJLQ) Approach

Using a Markov Jumping Linear Quadratic (MJLQ) method, this paper examines the impact of financial uncertainty on monetary policy in Iran in the context of a new Keynesian model. This model allows us to study the impact of financial uncertainty on inflation and output gap. We allow the economy to switch between normal and abnormal states. Our model is estimated in two stages. We first estimate the parameters of our normal model by using maximum likelihood method. In the next stage, we use the parameters obtained in the first stage and Apply Metropolis-Hastings random walk method to estimate the parameters of our MJLQ model. This allows to investigate the reaction of key variables to shocks in inflation, output gap and interest spread. We find out that the reaction of monetary policy to these three shocks under certainty case in the abnormal time model is stronger than those under uncertainty case. This finding might have important policy implication for authorities when conducting monetary policy in the presence of financial frictions.