This thesis demonstrates how a Taylor rule could capture the monetary policy decision pro- cess with imperfect information. The changes in the weights present in the rule reflect policy regime shifts. This framework is suitable in studying a small open transitional economy such as Hungary in recent years. This thesis employs the State-Space model which may capture the time-varying weights in the Taylor rule and an Autoregressive Hidden Markov Model which may identify unobservable or hidden underlying regimes using structural breaks. This thesis employs a sample period from 2000Q1-2020Q2, which finds that an active monetary policy regime transitions to a passive regime which becomes dominant in the second half of the sample, namely from 2014Q1 onward. Additionally, evidence of ineffective monetary policy is found. As general evidence, this thesis finds support for the Taylor rule constructed through the partial use of intermediate policy targets such as the real effective exchange rate. Which becomes ineffective towards the end of the sample, as the nominal interest rate degrades from two percent towards the zero lower bound.