Error Bands for IRF with Short and Long-Run Restrictions
Error Bands for IRF with Short and Long-Run Restrictions
This is an example of calculation of error bands for a structural VAR identified by short- and long-run restrictions. This is an example from the 2nd edition of the VAR e-course which describes its workings in detail. This is considerably simpler that the Bjornland-Leitemo example, and so is a better choice as the base program for adapting to a different model. It's an example out of Martin, Hurn and Harris, based upon a paper by Peersman.
Note that this requires RATS v9.
Note that this requires RATS v9.
Re: Error Bands for IRF with Short and Long-Run Restrictions
Hi Tom,
I'm using your program in order to estimate a structural VAR with seven variables but I would like to modify the magnitude of the shocks (I mean: setting for example a 2 standard deviation shock). Can you help with this issue?
Thank you!
I'm using your program in order to estimate a structural VAR with seven variables but I would like to modify the magnitude of the shocks (I mean: setting for example a 2 standard deviation shock). Can you help with this issue?
Thank you!
Re: Error Bands for IRF with Short and Long-Run Restrictions
I'm not sure what the point of that is. The IRF's for double the shock are double the IRF's for a single shock. You can adjust the FLongShort procedure to multiply the factor by two, but I would suggest not doing that.
Re: Error Bands for IRF with Short and Long-Run Restrictions
Hi Tom,
In the above given code to peersman: What does this line mean: and why the 1979:5? What does this specific observation do?
In the above given code to peersman: What does this line mean:
Code: Select all
estimate(sigma) 1979:5 *Re: Error Bands for IRF with Short and Long-Run Restrictions
That means 1979:5 to the last possible entry (given the data).
This is an example out of Martin, Hurn and Harris. That's what they did and I think they copied that from Peersman's original article. If it's important, you would have to check that.
This is an example out of Martin, Hurn and Harris. That's what they did and I think they copied that from Peersman's original article. If it's important, you would have to check that.