Browsing by Author "Jokiluoma, Antti"

During the past decade, central banks have become even more central to modern economies than before. Their main goal is price stability, and they try to achieve it with various methods. The effectivity of the traditional methods, especially controlling the short-term interest rates, has become smaller due to the zero lower bound constraint, and new unconventional methods have been introduced. This thesis investigates the effects of the unconventional monetary policy actions of the European Central Bank. Structural vector autoregressive models are one of the main tools in studying the effects of the monetary policy. To identify a monetary policy shock, one traditionally needs to impose restrictions to the model. However, that requires restrictive assumptions about the dynamics of the model which is being studied. To overcome this issue, one can identify the shocks statistically by some properties of the data, without any additional restrictions. A key benefit of statistical identification is the possibility to test the plausibility of previously used sign or zero restrictions. In the empirical application of this thesis, a Bayesian vector autoregressive model identified statistically based on non-normality of the error terms is utilised to study the effects of the European Central Bank's unconventional monetary policy. The Bayesian estimation was performed with a Differential Evolution Markov Chain algorithm, allowing fast calculation. The empirical analysis resulted in two key findings. First, the impulse response functions implied by the model are in line with previous studies and the statistically identified model gives support to the previously used sign restrictions. Second, the model is sensitive to the sample period which suggests that the effects of the European Central Banks policy actions might have changed over time.