Am 02.07.2014 11:14, schrieb Riccardo (Jack) Lucchetti:
On Wed, 2 Jul 2014, Deborah Sy wrote:
> Hi all,
>
> Yes, I'll be reading onto that. Another question I have is that I've been
> using a 9x9 matrix with a lot of constraints (here, it is 36) which is
> not
> random (i.e. they were backed up by theoretical assumptions). In such
> case,
> given any possible combinations of the 0's, the determinant will most
> likely be zero and therefore, no solution will exist (unless it is a
> Cholesky-decomposition or if there really exists a combination that
> provides a solution in this relatively large matrix). Does it follow
> that I
> will not be able to estimate the SVAR because no such solution exists?
> This
> has been bugging me for days already. Any ideas?
The problem is unlikely to be the rank of your contraint matrix. If you
fill a 9x9 matrix with 36 zeros at random, the probability if it being
singular is zero (it shouldn't be difficult to prove this formally)
although of course the event is not impossible (nice example of an event
with 0 Lebesgue measure).
Jack, I don't think this is true, for example the probability of getting
a column with all (9) zeros by chance may be small, but certainly not
zero if you allocate 36 zeros randomly. If I were good in combinatorics
I could give you the exact numbers, but I'm not.
Apart from that the constraints are not chosen at random. A line has
measure zero in a plane, but still I can pick exactly points on the line.
So I'm not saying the matrix is singular, but without further
investigation/thinking I cannot rule out that it is.
cheers,
sven