Am 05.01.2020 um 02:04 schrieb Alecos Papadopoulos:
I have the following two suspicions, can somebody please verify/dispel
them?
1) In a system of equations, currently I have no way to impose
non-linear restrictions on the coefficients (like ratios or products of
coefficients, nothing fancier). Right? Wrong?
Yes, I think so. (At least that's the documented state.) Of course if
you're happy estimating your system with TSLS, then you can pick out the
equation of interest and you should be able to formulate a restriction
in this single equation. If you aren't thinking of cross-equation
restrictions, that is.
And I guess I don't need to tell you that sometimes you can transfrom
and redefine your regressors to achieve ratios or stuff like that. If
that is feasible in your case, then a LR test might also be viable.
2) In using the Kalman filter together with maximum likelihood, consider
the following detail: say, in the "obsxmat" matrix there exists a
coefficient restriction, say a13 = a12/a11
...
scalar a13 = a12/a11
...
If my suspicion is right, then I think I have to define the matrix A by
matrix A = {a11, a12, a12/a11}
so that position a13 is also updated with the MLE estimate.
Right? Wrong?
This sounds right, but somehow I'm afraid I don't really get your
question, because you already seem to have answered it yourself.
Also, you can have helper variables like a scalar a13 inside your mle
block, which only serve to express the connections of your parameters,
without being params of interest themselves directly.
cheers
sven
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