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A COMPARISON OF BAYESIAN MODELS FOR MONETARY POLICY TRANSMISSION MECHANISM
Abstract
The monetary policy strategy of the National Bank of Romania is inflation rate targeting. This strategy was adopted in 2005 after making sure that all criteria requested in order to be able to adopt this strategy were fulfilled. Therefore, the main objective of the Central Bank is to ensure price stability, but without neglecting the aspect of sustainable economic growth. In order to achieve this goal, monetary policy transmission mechanism should be well known, as long as the available set of instruments and their impact on the national economy once they are implemented. The purpose of this study is to estimate the transmission for the Romanian economy by using models that imply Bayesian inference, more precisely Gibbs sampling algorithm, which is a particular variant of Markov Chain Monte Carlo method. And then to compare the results and to conclude about which one of the models performs better in measuring the way the transmission is being done. These models imply both constant and time varying parameters. Time varying parameters deliver more significant pieces of information, especially since the sample data starts before inflation targeting strategy was adopted. They also allow for a comparative analysis at different moments in time which is an advantage considering that the transmission evolved over time. This analysis provides a better image on whether the transmission has changed over time and which one of the models is more appropriate for doing the estimations.
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