Search found 259 matches

by dakila
Tue Oct 17, 2017 6:30 am
Forum: Add-in Support
Topic: Large Bayesian VAR
Replies: 14
Views: 861

Re: Large Bayesian VAR

If you have the missing observations because of the first order difference, then you should adjust the sample size.
by dakila
Fri Oct 13, 2017 3:13 pm
Forum: Add-in Support
Topic: Large Bayesian VAR
Replies: 14
Views: 861

Re: Large Bayesian VAR

You should put the irw vector into the Random walk prior box.
by dakila
Thu Oct 12, 2017 3:48 pm
Forum: Add-in Support
Topic: Large Bayesian VAR
Replies: 14
Views: 861

Re: Large Bayesian VAR

You need to create the vector for Random walk prior box. For example: vector irw=@zeros(10) If fifth variable is non-stationary then irw(5)=1 You manually entered lambda and tau. So you don't need to fit evaluation variables. If you choose grid search then you need the fit evaluation variables. Fit ...
by dakila
Mon Oct 02, 2017 11:58 pm
Forum: Add-in Support
Topic: Sign Restricted VAR
Replies: 25
Views: 6255

Re: Sign Restricted VAR

No. You cannot interpret like that. First define the shock by the sign restriction, then interpret impulse response function of Y and X as the effect of that shock.
by dakila
Mon Sep 25, 2017 3:41 pm
Forum: Add-in Support
Topic: Dynamic Model Averaging
Replies: 3
Views: 1496

Re: Dynamic Model Averaging

I am confused about what the 4 5 digits mean. 4 is forecast horizon. 5 is transformation code (log difference) for dependent variable. I tried estimating the model using the combo box but I keep getting an error msge: "3 is not a valid index for vector-series-coefficient tcode". I am esti...
by dakila
Thu Sep 21, 2017 5:22 pm
Forum: Add-in Support
Topic: Large Bayesian VAR
Replies: 14
Views: 861

Re: Large Bayesian VAR

can you check your private message?
by dakila
Tue Sep 12, 2017 5:14 pm
Forum: Estimation
Topic: implement Generalized IRF from system object (VAR estimated with GMM)
Replies: 5
Views: 253

Re: implement Generalized IRF from system object (VAR estimated with GMM)

First, estimate GIRF using eviews built-in command or dialog box. Then use the sirf add-in.
by dakila
Tue Sep 12, 2017 6:05 am
Forum: Estimation
Topic: implement Generalized IRF from system object (VAR estimated with GMM)
Replies: 5
Views: 253

Re: implement Generalized IRF from system object (VAR estimated with GMM)

2. Is there a way in EViews to implement a ONE UNIT shock of generalized impulse response function? EViews is giving one-standard deviation shock for generalized impulse response function, according to my knowledge.


Try the sirf add-in.
by dakila
Mon Sep 11, 2017 3:40 pm
Forum: Add-in Support
Topic: Threshold Structural VAR
Replies: 95
Views: 14181

Re: Threshold Structural VAR

thanks for the comment
by dakila
Fri Sep 08, 2017 7:42 am
Forum: Estimation
Topic: SVAR restrictions
Replies: 7
Views: 679

Re: SVAR restrictions

For the pure sign restriction method you can. You can do it recursively. After identifying the first shock, then the second so on. The order of sign restriction is does not matter for the pure sign restriction method. However for penalty function approach you cannot. The next version will include th...
by dakila
Thu Sep 07, 2017 2:44 am
Forum: Estimation
Topic: SVAR restrictions
Replies: 7
Views: 679

Re: SVAR restrictions

your question is unclear.
by dakila
Tue Sep 05, 2017 6:13 pm
Forum: Econometric Discussions
Topic: I(1),I(0) and cointegration
Replies: 3
Views: 256

Re: I(1),I(0) and cointegration

Try the ardl cointegration method (Pesaran 2001).
http://davegiles.blogspot.com/2013/06/a ... tests.html
by dakila
Mon Sep 04, 2017 7:44 pm
Forum: Add-in Support
Topic: Large Bayesian VAR
Replies: 14
Views: 861

Re: Large Bayesian VAR

This thread is about the LBVAR add-in not BVAR.
by dakila
Fri Sep 01, 2017 3:58 pm
Forum: Estimation
Topic: VAR Cholesky IRF - One unit shock
Replies: 5
Views: 308

Re: VAR Cholesky IRF - One unit shock

Try the sirf add-in
by dakila
Wed Aug 30, 2017 6:42 pm
Forum: Add-in Support
Topic: Large Bayesian VAR
Replies: 14
Views: 861

Re: Large Bayesian VAR

if your data have missing values then adjust the sample size.

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