## FAVAR add-in

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### Re: FAVAR add-in

Dakila - Thank you for the useful add-in. Is there a way to apply the scaled IRF add-in to the FAVAR add-in?

### Re: FAVAR add-in

Good idea. I will try to code it.

### Re: FAVAR add-in

Thank you, Dakila. Is there a possibility of running cumulative IRFs in your add-in?

### Re: FAVAR add-in

Yes, It actually do the cumulative IRFs when you transform the variable. For example, if you put the transformation code 4 or 5 it will accumulate the IRFs.

### Re: FAVAR add-in

Hi,

I tried to get the factors by the usual way of principal components, but I didn´t have the same series. Also I can see that the final factors used in VAR have "rot" in its labels. Does it have any other treatment, or could you please tell me the way to get it? Thanks!

I tried to get the factors by the usual way of principal components, but I didn´t have the same series. Also I can see that the final factors used in VAR have "rot" in its labels. Does it have any other treatment, or could you please tell me the way to get it? Thanks!

### Re: FAVAR add-in

"ROT" means the rotated factors. In order to estimate the factors do the following steps:

1) estimate factors (C) using all variables except FFR (you did this step)

2) estimate slow moving factors (Fs) from the slow moving variables.

3) estimate the regression by OLS : C=b1*Fs + b2*FFR + e

4) estimate the rotated factors : C-b2*FFR

1) estimate factors (C) using all variables except FFR (you did this step)

2) estimate slow moving factors (Fs) from the slow moving variables.

3) estimate the regression by OLS : C=b1*Fs + b2*FFR + e

4) estimate the rotated factors : C-b2*FFR

### Re: FAVAR add-in

Thank you! I got them but with a very small difference. Maybe that's because I didn't standardize my variables (since all of them were stationaries), do you think thats made the difference?

### Re: FAVAR add-in

Yes, I think that made the difference.

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