Can I add to Sven's answer that estimating the reduced form for the
endogenous variable allows one to test that the coefficient on the
instrument is non-zero? Otherwise, the system is not identified. (weak
instruments?)
John C Frain
3 Aranleigh Park
Rathfarnham
Dublin 14
Ireland
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On Sat, 22 Apr 2023 at 15:47, Sven Schreiber <sven.schreiber(a)fu-berlin.de>
wrote:
Am 21.04.2023 um 18:31 schrieb elfsog(a)yahoo.gr:
To be more specific:
I am trying to estimate a model with two predictors and an interaction feature using an
IV. Which would be the most appropriate approach, and how could I implement (the
following) model in Grelt?
The model is Y=b0+b1*X1+b2*X2+b3*X1*X2+e
Y is an ordinal six grade Likert variable,
X1 and X2 are binary variables. X1 is endogenous and X2 is exogenous.
Z1 is the Instrumental Variable for X1 and is an ordinal six grade Likert type variable.
If Y is ordinal then a natural additional question would be whether using
an ordered probit might be (more) needed.
In that sense I would tend to recommend an explicit two-stage approach,
regressing the endogenous RHS terms on the set of valid instruments and
continue with the fitted values from there, doing the ordinal probit in the
second stage. A standard ordered probit routine is "of course" available in
gretl. Just mark the LHS variable as discrete and then gretl will
automatically apply the ordered probit estimation.
But I'm no expert for setups such as these, so I certainly also recommend
reading up on the textbook econometrics on doing an IV ordered probit
estimation. To my knowledge doing ordered probit with IVs is not directly
available in gretl, but I may be missing something.
(The HIP addon for gretl does IV-probit, but not IV-ordered-probit, if I
understand correctly.)
cheers
sven
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