Am 05.03.2019 um 08:56 schrieb ΑΝΔΡΕΑΣ ΖΕΡΒΑΣ:
> Hi all,
>
> I have a question regarding DFM package, version 0.2 on Gretl 2018c (or
> b) . It is about using unbalanced time series. I understand that dynamic
> factor models are estimated on the common sample of the time series.
> However, my understanding of the literature is that if some of these
> time series from which the factors are extracted have longer sample,
> then it is possible to use the Kalman filter to fill the missing values
> of the dynamic factors. In the help such a feature is not mentioned. Is
> it possible to do it in a quick way, or we would have to wait for a new
> version?

Good morning, I'm not an author of the DFM package (which BTW for those
who don't know it stands for "dynamic factor models"), but could you
give a concrete reference for the "literature" you are talking about.

People always say "the Kalman filter can do it", and I guess you mean a
latent variable approach, but IMO it all depends on the specific
assumptions. Because to me the Kalman filter is just a framework, not a
specific model.

cheers
sven
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