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Hi Markus, Here the slow and fast variables matter for recovering common components, F other than R. In order to estimate common components F, we removes direct dependences of C(F,R) on R: 1. Estimate principal components, C(F, R) from entire dataset 2. Estimate C(F*) extracting principal components...

This thread is about the ARW add-in that implements Arias, Rubio-Ramirez and Waggoner algorithm for sign and zero restricted VARs.

The bug is fixed. I hope the moderator will upload the add-in soon.

Could you post the data?

When estimate the DY index just tick the save pairwise spillovers. After that do it manually get the net pairwise connectedness.

1. Is it possible to forecast individual series used to build factors? (not just factors themselves) Yes . this question was answered before Is it possible to draw factors from multiple datasets? Let's say I have sets X1 and X2 composed of different data series and I would like to use the first pri...

1. Is it possible to forecast individual series used to build factors? (not just factors themselves) Yes . this question is answered before Is it possible to draw factors from multiple datasets? Let's say I have sets X1 and X2 composed of different data series and I would like to use the first prin...

This thread is about the kilian add-in that that implements the Kilian bias-adjusted bootstrap for VAR impulse response.

The bug is fixed. Please update the add-in. I hope the moderator will post it soon. But carefully choose the rolling window parameter. It should not exceed the sample size.

Yes, you are right. It does not work for the version 11. I will fix it soon. But it can work for the version 10 if you have access to it.

What is your eviews version?

Would I need to set sn equal to 0.25/std(ffr) if I estimated the FAVAR with non-standardized data? I think you need to set sn equal to 0.25/std(ffr) if you estimated the FAVAR with standardized data. I would also like to know if the "favar" command allows for the inclusion of a constant a...

Yes, it is right. Use scale (1 or 0) and sn (scale number) command. For example,

Generally It will depend on the time horizons. That case the variance decomposition converged quickly the long run value.

Unfortunately, no.