Quantification model of the consequences of monetary policy shocks

The monetary analysis based on the BVAR (Bayesian Vector Autoregression) model is extremely important in the monetary policy implementation strategy, the information provided is important not only for the Central Bank, but also for the economic agents and the population. Therefore, conducting this analysis at the level of Romania helps to understand better the mechanism by which monetary policy is transmitted in order to achieve the set target, namely inflation targeting, but it also provides us with important information regarding the accession to the euro area. The model we are trying to test helps us understand through the correlations between the interest rate, GDP and the inflation rate how monetary policy responds to shocks. The model follows the methodology presented by Sims and Zha (1998) in the paper "Bayesian Methods for Dynamic Multivariate Models and Using the Bayesian Autoregressive Vector". In the analysis of this model, quarterly data for a minimum of three years, three variables are used to make the results relevant. The data needed to model the model are used in logarithmic form, except for the interest rate, and the outcome is applied to a differentiated premium operator. Of the variables used, the interest rate is the only one that does not allow seasonal adjustment.