Measuring the Effects of a Shock to Monetary Policy - Humboldt ...

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Bayesian FAVARs with Agnostic Identification 33 6 Structural FAVARs 6.1 Identification of Shocks The issue of identifying structural shocks from the reduced form VAR innovations, and in particular identifying a shock to monetary policy has been dealt with in a huge body of literature. There have been introduced a lot of variations on how to achieve identification. The most prominent ones are explained below. As there are various approaches to deal with the same question it seems clear that there is also a controversial debate about which scheme to choose in order to reveal the true propagation mechanism attributable to a monetary policy shock. After considering the different approaches available, it seems to for me to be advisable to head the challenge of identification through applying the agnostic identification using sign restrictions 32 . Especially from the perspective of an economist it seems to me plausible to have an identification scheme that incorporates economic theory and through imposing the impulse responses to satisfy the conventional wisdom. Although this is a weaker identification scheme 33 . In this section the well known identification schemes are presented, afterwards I show briefly how they were extended to be applicable to large scale DFMs and to the FAVAR framework. And finally in the last part of this section I elaborate on the extension of the sign restriction of Uhlig (2005) to the FAVAR framework that incorporates the Gibbs sampling. In the common VAR framework one is required to deduce the structural shocks for the VAR innovations. In the DFM and FAVAR framework the task is actually the same with the main distinction that the structural shocks are not required to be deduced from the reduced form VAR innovation, but from the FAVAR innovation, including the factors that drive the dynamics of the informational variables or the observed data. 32 Agnostic because no restriction on output. 33 weaker in a sense that only restriction is on the mentioned variables according to the conventional wisdom. The aim is to restrict as little as necessary a priori.
34 Bayesian FAVARs with Agnostic Identification 6.2 Identification Schemes in SVARs In the well know SVAR framework, which is the mostly known and applied framework for the identification of the monetary policy shock. The widely applied ones are the recursive Cholesky identification that was advanced CEE [1999], the long-run identification that goes back to Blanchard and Quah [1989], and the combination of the previous two that sets zero restrictions on the coefficient matrix introduced by Leeper, Sims and Zha [1996]. Very good surveys about the Identification in SVARs can be found in CEE [1999] and Leeper, Sims and Zha [1996]. They document the progress that has been done over the time what versions there are around and what the state-of-the-art is. 6.3 Identification in DFMs and FAVARs Equivalently to the SVAR case, the structural shocks in DFMs and FAVARs have to be derived from the reduced form innovation, with the distinction that here one refers not to the VAR but to the innovation in the FAVAR strictly speaking on the Yt or in case that Yt consists of more than one variable, the one that the researcher is interested in. There are already some identification schemes applied to the framework of DFMs and FAVARs around which shall be discussed here very briefly. There is a very good survey by Stock and Watson (2005), which introduces broadly the different approaches and how to set restrictions to identify factors and factor loadings. Furthermore they elaborate on the different identification schemes to figure out the structural shocks in DFMs and FAVARs. As they mostly deal with the nonparametric and the frequentists approach, the reader is kindly referred to this reference for further details. My thesis concentrates on the Bayesian approach combined also with a Bayesian identification, namely the agnostic identification. Therefore in the following the other approaches are mentioned briefly with the relevant references, and for the rest I focus on the model and methodology that I chose to analyze described above. The identification schemes that are around are surveyed by Stock and Watson (2005).
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