Orthogonality of _P_ implies that the RHS of (6) reduces to _A_<sup> ̃</sup><sup>_−_1 ̃</sup> _B_ Σ _vB_<sup> ̃</sup><sup>_′_</sup> _A_<sup> ̃</sup><sup>_′−_1</sup> = Σ<sup> ̃</sup> _u_ , and so Σ _u_ = Σ<sup> ̃</sup> _u_ .

A SVAR is said to be globally identified if the only such orthogonal matrix _P_ is the identity matrix. If this is the case, then there is only one set of structural parameters that can be deduced from the estimation of the reduced-form VAR. For a model to be identified, it is necessary to impose restrictions on its parameters. Thus, the task of the structural VAR literature consists in finding an appealing story that establishes how the underlying shocks build up to the observed news. One can think of two general principles to follow when building such a story. First, it must be so parsimonious as to provide enough restrictions for the model to be identified. The necessary and sufficient conditions for identification upon this paper relies are the ones given in Rubio-Ram ́ırez et al. [31]. Second, and not less important, the identification strategy should not rest on any particular theoretical model. Otherwise, it would not be possible to provide a neutral “arena within which macroeconomic theories confront reality and thereby each other” (Sims [36]).

By far the most popular identification strategy consists in ordering the endogenous variables by their degree of “exogeneity.” This allows the researcher to rest on the uniqueness of the Cholesky factorization, so that only one possible structural model can be behind a certain reduced-form covariance matrix. With the years, more sophisticated strategies where developed, allowing to deal with models where the claim of a Wold causal ordering could not be sustained.

The first building block of the identification strategy to be developed in the present study consists in representing the economy with two sub-vectors of variables that together conform the vector _Zt_ of endogenous variables: _Yt_ denotes the _l ×_ 1 vector of variables of the production sector, whereas the ( _k −l_ ) _×_ 1 vector _Pt_ includes the variables of the transactions sector of the economy.<sup>2</sup> Bernanke and Blinder [3] argue that there are two alternative assumptions that facilitate identification. Namely, one could assume either that there is no contemporaneous feedback from the production sector to the transactions sector or that shocks within the transaction sector do not affect the production sector contemporaneously. In both cases, _A_ becomes a block triangular matrix and _B_ a block diagonal matrix. The approach here follows Bernanke and Mihov [6], who assume that shocks in the transaction sector do not affect the production sector within the current period. In other words, we assume a sluggish production sector that responds to innovations in the transactions sector only with a lag (see, e.g., Kim [20]). If then we have that 2Even when the taxonomy adopted here might be misleading, it seems more appropriate in the present case than the nomenclature usually adopted in the literature. Bernanke and Blinder [3] label the former the “nonpolicy variables,” and the latter the “policy variables.” In the model to be constructed below, however, _Pt_ includes variables that are far from being controlled by the monetary authority.

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