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Posted: Sat Jun 04, 2016 3:55 am
This thread is about localirfs
add-in for VAR-type models. It is a complementary tool for VAR object just as hdecomp
The add-in allows you to produce impulse responses by local projection method introduced by Jordà (2005) and generate associated confidence bands as detailed in Jordà (2009). For further instruction, please see the documentation that comes with the add-in.
There is also an example file
available, which outlines use of add-in through Jordà (2009) study.
Posted: Sat Jun 04, 2016 11:26 pm
Good job. Thank you very much, Erin for the very useful, interesting add-in.
Posted: Tue Sep 13, 2016 2:00 pm
Thanks for this add-in. I installed it on my eviews 9. I estimated a VAR model and then used this add-in. In so doing, I followed http://blog.eviews.com/2016/06/impulse- ... ns_43.html
However, the local projections IRFGRPHs are those without any responses reported. Only VAR IRFs are reported. Those individual graphs for LP IRFs are simply graphs with a zero line plus frames, with response-matrix of zeros.
I tried different datasets and different VARs, but ended with the same LP IRFs.
Did I do something wrong? Can somebody help? I really need it for my ongoing project.
Thanks a lot.
Posted: Wed Sep 14, 2016 8:48 am
Have you tried out this add-in? Any hint on how it works would be of my great appreciation.
I tried the example file as well and got the localirf of all zeros.
Posted: Fri Apr 02, 2021 7:10 am
it is a great tool indeed, but I'm having troubles with the "order" option.
In theory this should allow you to change the (Cholesky) ordering used to calculate the responses. In practice, it doesnt seem to work: i tried to assign "order" using a row vector, a column vector or a matrix but I always get an error saying that "the number of variables does not match" (so the default ordering is used instead).
The number of variables does match though: for a 4-variable VAR, for instance, I'd set order=[1 4 2 3].
I even tried to drop intercept and constant from the VAR (to avoid confusion between variables and deterministic parts), but that doesn't help.
Any ideas on how to fix this?