File: get_variance_of_endogenous_variables.m

package info (click to toggle)
dynare 4.6.3-4
  • links: PTS, VCS
  • area: main
  • in suites: bullseye
  • size: 74,896 kB
  • sloc: cpp: 98,057; ansic: 28,929; pascal: 13,844; sh: 5,947; objc: 4,236; yacc: 4,215; makefile: 2,583; lex: 1,534; fortran: 877; python: 647; ruby: 291; lisp: 152; xml: 22
file content (59 lines) | stat: -rw-r--r-- 1,808 bytes parent folder | download | duplicates (2)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
function vx1 = get_variance_of_endogenous_variables(dr,i_var)

% function vx1 = get_variance_of_endogenous_variables(dr,i_var)
% Gets the variance of a variables subset
%
% INPUTS
%    dr:        structure of decisions rules for stochastic simulations
%    i_var:     indices of a variables list
%
% OUTPUTS
%    vx1:       variance-covariance matrix
%
% SPECIAL REQUIREMENTS
%    none

% Copyright (C) 2003-2017 Dynare Team
%
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% Dynare is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with Dynare.  If not, see <http://www.gnu.org/licenses/>.

global M_ options_

endo_nbr = M_.endo_nbr;

Sigma_e = M_.Sigma_e;

nstatic = M_.nstatic;
nspred = M_.nspred;
ghx = dr.ghx(i_var,:);
ghu = dr.ghu(i_var,:);
nc = size(ghx,2);
n = length(i_var);

[A,B] = kalman_transition_matrix(dr,nstatic+(1:nspred),1:nc,M_.exo_nbr);

[vx,u] = lyapunov_symm(A,B*Sigma_e*B',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold, [], options_.debug);

if size(u,2) > 0
    i_stat = find(any(abs(ghx*u) < options_.Schur_vec_tol,2)); %only set those variances of objective function for which variance is finite
    ghx = ghx(i_stat,:);
    ghu = ghu(i_stat,:);
else
    i_stat = (1:n)';
end

vx1 = Inf*ones(n,n);
vx1(i_stat,i_stat) = ghx*vx*ghx'+ghu*Sigma_e*ghu';