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Bug fix (wrong condition). 

Also add comments about the choice for the definition of the linear
combination of the VAR companion variables.

We should test the numbe of output arguments, not the number of input
arguments. This was bug was probably not affecting the outcomes since
the number of input arguments is always greater than 1.
dprior
Stéphane Adjemian (Argos) 2024-01-19 17:40:50 +01:00
parent 942d8846e4
commit a48a03bc67
Signed by: stepan
GPG Key ID: 295C1FE89E17EB3C
1 changed files with 6 additions and 6 deletions
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12
matlab/pac-tools/hVectors.m
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@ -18,7 +18,7 @@ function [h, lrcp] = hVectors(params, H, auxmodel, kind, id)
% params(2:end-1) ⟶ Autoregressive parameters.
% params(end) ⟶ Discount factor.
% Copyright © 2018-2021 Dynare Team
% Copyright © 2018-2024 Dynare Team
%
% This file is part of Dynare.
%
@ -52,21 +52,21 @@ n = length(H);
tmp = eye(n*m)-kron(G, transpose(H)); % inv(W2)
switch kind
case 'll'
case 'll' % (A.84), page 28 in Brayton, Davis and Tulip (2000) ⟹ The target is stationary (level-level).
h = A_1*A_b*((kron(iota(m, m), H))'*(tmp\kron(iota(m, m), iota(n, id))));
case 'dd'
case 'dd' % (A.79), page 26 in Brayton, Davis and Tulip (2000) ⟹ The target appears in first difference as a dependent variable in the auxiliary model.
h = A_1*A_b*(kron(iota(m, m)'*inv(eye(m)-G), H')*(tmp\kron(iota(m, m), iota(n, id))));
case 'dl'
case 'dl' % (A.74), page 24 in Brayton, Davis and Tulip (2000) ⟹ The target appears in level as a dependent variable in the auxiliary model.
h = A_1*A_b*(kron(iota(m, m)'*inv(eye(m)-G), (H'-eye(length(H))))*(tmp\kron(iota(m, m), iota(n, id))));
otherwise
error('Unknown kind value in PAC model.')
end
if nargin>1
if nargout>1
if isequal(kind, 'll')
lrcp = NaN;
else
d = A_1*A_b*(iota(m, m)'*inv((eye(m)-G)*(eye(m)-G))*iota(m, m));
lrcp = (1-sum(params(2:end-1))-d);
end
end
end