A Statistical Comparison of Alternative Identification Schemes for Monetary Policy Shocks
Different identification schemes for monetary policy shocks have been proposed in the literature. They typically specify just-identifying restrictions in a standard structural vector autoregressive (SVAR) framework. Thus, in this framework the different schemes cannot be checked against the data with statistical tests. We consider different approaches how to use the data properties to augment the standard SVAR setup for identifying the shocks. Thereby it becomes possible to test models which are just identified in a standard setting. For monthly US data it is found that a model where monetary shocks are induced via the federal funds rate is the only one which cannot be rejected when the data properties are used for identification.
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