Search found 6 matches
- Wed Jan 23, 2013 3:59 am
- Forum: VARs (Vector Autoregression Models)
- Topic: Testing overidentifying SVAR models
- Replies: 2
- Views: 5228
Re: Testing overidentifying SVAR models
Thanks Tom!
- Tue Jan 22, 2013 4:55 pm
- Forum: VARs (Vector Autoregression Models)
- Topic: Testing overidentifying SVAR models
- Replies: 2
- Views: 5228
Testing overidentifying SVAR models
Hello, I used montesvar.rpf procedure to estimate an overidentified SVAR (nvar=7 and nfree=20). I was wondering if it is possible to obtain the likelihood ratio test for the overidentified restrictions from the procedure. In fact, when using DMATRIX=MARGINALIZED, as in montesvar.rpf, we do not obtai...
- Wed Aug 29, 2012 3:31 am
- Forum: VARs (Vector Autoregression Models)
- Topic: Problem with MONTEZHA.PRC
- Replies: 5
- Views: 8460
Re: Problem with MONTEZHA.PRC
The matrix changing is the "swish" which, according to my understanding, is the var-cov matrix of the SVAR. I will try with MONTESVAR procedure. Thanks !
- Tue Aug 28, 2012 4:13 am
- Forum: VARs (Vector Autoregression Models)
- Topic: Problem with MONTEZHA.PRC
- Replies: 5
- Views: 8460
Re: Problem with MONTEZHA.PRC
After all the suggested modifications, the procedure MONTEZHA.PRC works fine with 7 variables. Nevertheless, each time that I run the same code with the same data the covariance matrix change, and so do the responses function and forecast error. I am not sure if that is ok or there are a problem. I ...
- Thu Aug 02, 2012 4:34 am
- Forum: VARs (Vector Autoregression Models)
- Topic: Variance Decomposition for MONTEZHA.PRC
- Replies: 3
- Views: 5732
Re: Variance Decomposition for MONTEZHA.PRC
Thanks a lot Tom! I am working on that!
- Wed Aug 01, 2012 10:42 am
- Forum: VARs (Vector Autoregression Models)
- Topic: Variance Decomposition for MONTEZHA.PRC
- Replies: 3
- Views: 5732
Variance Decomposition for MONTEZHA.PRC
I am using the procedure MONTEZHA.PRC which shows how to implement Zha's procedure for overidentified BVAR. I work with a 7 variables model and, after some modifications, it works well, the problem is that I cannot compute variance decomposition in typical way (known by me). When I add the following...