[Gretl-devel] The "omit" command once again

[Allin Cottrell]

Thanks to Jack for shaking things up on this point.

In current CVS, the English help file contains a more accurate 
description than hitherto of what the "omit" command actually 
does.  It's a bit convoluted.  I'll try to summarize more 
critically here.

(1) "Traditionally", the default behaviour of "omit" was to 
estimate the restricted model (that is, the source model minus 
the independent variables selected for omission), and to push 
this restricted model onto the stack as the "last model 
estimated".  In the process, if the source model was estimated 
using OLS, we calculated the F-test for the joint significance 
of the omitted variables, using the restricted and unrestricted 
SSRs and their respective degrees of freedom,

(2) Some time ago, it occurred to me that this was a bit weak 
with regard to models estimated via methods other than OLS (no 
test statistic was provided); furthermore, it was problematic 
with regard to models estimated via OLS but calling for "robust 
standard errors" (an innovation relative to old-style gretl).

(3) I therefore modified the behavior of "omit" so that

(i) if the original model used OLS with "robust standard 
errors", we formulated a Wald-type statistic using the robust 
covariance matrix from the original model, in F-form, and

(ii) if the original estimator was something other than OLS, we 
used a Wald test (chi-square form) based on the covariance 
matrix for the original model.

Modifications (i) and (ii) enabled us to present a test 
statistic for the joint significance of the omitted variables in 
cases where we'd previously skipped the reporting of such a 
statistic.  However, I maintained the old behaviour of 
estimating (and "returning") the restricted model, even if that 
model was not used in computing the test statistic for the 
omitted variables.

Jack is now pointing out that in some cases we really don't want 
to base our test statistic on explicit estimation of the 
restricted model -- even if that method is valid "in principle",
we'd rather just use the Wald method on the original covariance 
matrix.  I agree.

Here's the question I'm working towards: Do you think we'd be 
better off if we changed the behaviour of the "omit" command so 
that it calculates and reports a test statistic -- possibly by 
means of estimating the restricted model, depending on the 
original estimator and relevant option switches -- but never 
replaces the "current model" with a restricted model?

In practical scripting terms:

ols 1 0 2 3 4 5
omit 4 5
omit 4 5

Currently, the third line above is an error: you can't omit vars 
4 and 5 because they're already omitted: by this time the 
"current model" has spec "ols 1 0 2 3".

In the possible new-style behaviour, line 3 would not be an 
error, it would simply repeat the test done on line 2.

In current CVS, line 3 would _not_ be an error if we used the 
"--wald" option flag, which suppresses estimation of the 
restricted model.  That is,

ols 1 0 2 3 4 5
omit 4 5 --wald
omit 4 5 --wald

would be valid, if repititious.

Allin.