Hi Allin and Jack,
since you mentioned that you're working on cointegration restrictions,
just a technical note on the switching algorithm for VECMs with alpha
and beta restrictions (Boswijk/Doornik section 4.4).
As could be expected, the starting values are very important. In
py4gretl_vecmrestrict <=0.9.4 (currently on the server) I simply used
the generically identified unrestricted estimates for alpha and beta
(and implicitly for the cov-matrix omega). However, that seemed to fail
quite often for the real-world cases I needed.
So today I tried out using generic starting values for alpha, beta, and
also omega, namely identity matrices (augmented by blocks of zeros to
get the right dimensions).
Although it's still very crude it seems to work much better! Of course,
one could add much more magic like comparing the results for different
starting values, scaling the data etc etc., but so far I don't need
that. The only difference with respect to results from PcGive is that my
standard errors are a bit higher, which I don't understand yet.
Apart from that I have also made a variant of the package which directly
uses the inputs G, h0, and H and is thus more flexible (but also less
user-friendly...). I'm not sure whether I should put that on the server,
So much for that.