# Open source code for factor-augmented VAR (FAVAR) model

I am looking for an open source package (R, Python, Julia) that has an implemented FAVAR (factor-augmented VAR) class for time-series prediction problem.

I've already tried to use several solutions I could find on the Internet:

https://rdrr.io/github/joergrieger/bvar/src/R/favar.r - this class focused on computing impulse responses, rather than obtaining forecast $$\hat y_{T+1|T}$$

https://pythonhosted.org/pymaclab/#api-documentation - have problems while installing this package on Python, still unsure if FAVAR class in this package is the thing I need, since there is no package documentation

https://sites.google.com/site/hmumtaz77/code - also found this list of MATLAB codes, one of them for classical FAVAR, however not for prediction purpose

Also tried several Julia modules. All I managed find was implemented for computing impulse responses.

Popular Python packages like PyFlux, Statsmodels does not have FAVAR model, unfortunately.

Ideally it should work like  from magic_package.models import FAVAR model = FAVAR.fit({args}) y_hat = model.predict(h=12)

but I will be glad to consider all options you can suggest me.

In short, for time-series prediction problem algorithm is simple. One should retrieve the first K principal components from informational series $$X_t$$: $$\hat C(F_t,Y_t)$$. Then estimate standard VAR model in $$(\hat C(F_t,Y_t)',Y_t')$$.