Generalized impulse responses (GIR) were proposed by Pesaran and Shin (1998) as an attempt to avoid the difficulties of identifying orthogonal shocks in VAR models. This is not a particularly complicated idea—in fact, all these do is compute the shocks with each variable in turn being first in a Cholesky order. These can be done quite easily using RATS: %GIRFMATRIX(%SIGMA) will compute the “factor” that will give you GIR when you use it to compute impulse responses.

 

While these can, quite easily, be done in RATS, we do not recommend them unless you understand exactly what you’re doing. While coming up with an orthogonalizing model can, in practice, be somewhat difficult, it is a necessary step. A set of responses to highly correlated shocks are almost impossible to interpret sensibly. For instance, you can’t run an ERRORS instruction to assess the economic significance of the responses, since that requires an orthogonal decomposition, and this isn’t one.

 

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