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How can I influence the order of variables in a VAR Model for solving the identification problem in the irf?

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Moritz Arold
Moritz Arold on 14 May 2021
Commented: Moritz Arold on 18 May 2021
I am analyzing some financial time series with a VAR Model, and I would like to produce an orthogonalized IRF ordering the variable accountable for the IRF shock of relevance last in the vector of endogenous variables.
Is the only thing I have to do to account for this to put the respective variable last in the code when providing the model with my data? Taking as an example the case study from
EstMdl = estimate(Mdl,[rcpi unrate])
In this case, would unrate be the varibale ordered last in the Vector of endogenous variables in the model, lets call it Y_t? I assume this is the case, but I am not certain about this and would like to make sure I am correct. In the subsection Algorithms and in the case study of, there is some reference to variable orders on VARs, but I cannot find explicit info on this.
Thanks a lot for your help; please apologize for any potential lapse in my post.

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