Many thanks, Jack!
I think I'll be abre to bootstrap the confidence intervals by myself. By
the way, it would be great to have it as a native function. I am having the
feeling that macros use it quite often.
Friendly,
Daniel
El lun., 5 de octubre de 2020 5:43, Riccardo (Jack) Lucchetti <
p002264(a)staff.univpm.it> escribió:
On Mon, 5 Oct 2020, Sven Schreiber wrote:
> What I don't get, however, how Jack wants to estimate the IRFs with that.
That would take a bit more work. Assuming one wants a recursive
identification scheme, here's a way; of course, computing confidence bands
would involve a little extra work, because you'd have to bootstrap the
system.
PS: actually, I'm beginning to think that, given that I find myself
writing functions like the one below over and over again, we may add a
similar function to our native repertoire.
<hansl>
function matrix IRF(matrix A, matrix C, scalar h)
n = rows(C)
matrix ret = {}
matrix M = C
loop i = 1 .. h --quiet
ret = ret | vec(M)'
M = A * M
endloop
return ret
end function
set verbose off
open AWM18.gdt --quiet
h = 40
set horizon h
y = log(YER)
c = log(PCR)
i = log(GCR)
list X = y c i
var 1 X --quiet
ii = 2
jj = 1
U_irf = irf(ii,jj)
# estimate VAR with constraints
system name=foo
equation y const y(-1)
equation c const X(-1)
equation i const X(-1)
end system
estimate foo method=sur
moo = IRF($sysA, cholesky($sigma), h)
R_irf = moo[, ii + (jj-1)*3]
PLT = U_irf ~ R_irf ~ seq(0,h-1)'
cnameset(PLT, "unrestricted restricted horizon")
gnuplot --matrix=PLT --output=display --single-yaxis --with-lines
</hansl>
-------------------------------------------------------
Riccardo (Jack) Lucchetti
Dipartimento di Scienze Economiche e Sociali (DiSES)
Università Politecnica delle Marche
(formerly known as Università di Ancona)
r.lucchetti(a)univpm.it
http://www2.econ.univpm.it/servizi/hpp/lucchetti
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