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
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
|
function oo_ = ...
conditional_variance_decomposition_mc_analysis(NumberOfSimulations, type, dname, fname, Steps, exonames, exo, var_list, endogenous_variable_index, mh_conf_sig, oo_,options_)
% This function analyses the (posterior or prior) distribution of the
% endogenous variables' conditional variance decomposition.
%
% INPUTS
% NumberOfSimulations [integer] scalar, number of simulations.
% type [string] 'prior' or 'posterior'
% dname [string] directory name where to save
% fname [string] name of the mod-file
% Steps [integers] horizons at which to conduct decomposition
% exonames [string] (n_exo*char_length) character array with names of exogenous variables
% exo [string] name of current exogenous
% variable
% var_list [string] (n_endo*char_length) character array with name
% of endogenous variables
% endogenous_variable_index [integer] index of the current
% endogenous variable
% mh_conf_sig [double] 2 by 1 vector with upper
% and lower bound of HPD intervals
% oo_ [structure] Dynare structure where the results are saved.
%
% OUTPUTS
% oo_ [structure] Dynare structure where the results are saved.
% Copyright (C) 2009-2017 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/>.
if strcmpi(type,'posterior')
TYPE = 'Posterior';
PATH = [dname '/metropolis/'];
else
TYPE = 'Prior';
PATH = [dname '/prior/moments/'];
end
% $$$ indx = check_name(vartan,var);
% $$$ if isempty(indx)
% $$$ disp([ type '_analysis:: ' var ' is not a stationary endogenous variable!'])
% $$$ return
% $$$ end
% $$$ endogenous_variable_index = sum(1:indx);
exogenous_variable_index = check_name(exonames,exo);
if isempty(exogenous_variable_index)
disp([ type '_analysis:: ' exo ' is not a declared exogenous variable!'])
return
end
name_1 = deblank(var_list(endogenous_variable_index,:));
name_2 = deblank(exo);
name = [ name_1 '.' name_2 ];
if isfield(oo_, [ TYPE 'TheoreticalMoments' ])
temporary_structure = oo_.([TYPE 'TheoreticalMoments']);
if isfield(temporary_structure,'dsge')
temporary_structure = oo_.([TYPE 'TheoreticalMoments']).dsge;
if isfield(temporary_structure,'ConditionalVarianceDecomposition')
temporary_structure = oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.Mean;
if isfield(temporary_structure,name)
if sum(Steps-temporary_structure.(name)(1,:)) == 0
% Nothing (new) to do here...
return
end
end
end
end
end
ListOfFiles = dir([ PATH fname '_' TYPE 'ConditionalVarianceDecomposition*.mat']);
i1 = 1; tmp = zeros(NumberOfSimulations,length(Steps));
for file = 1:length(ListOfFiles)
load([ PATH ListOfFiles(file).name ]);
% 4D-array (endovar,time,exovar,simul)
i2 = i1 + size(Conditional_decomposition_array,4) - 1;
tmp(i1:i2,:) = transpose(dynare_squeeze(Conditional_decomposition_array(endogenous_variable_index,:,exogenous_variable_index,:)));
i1 = i2+1;
end
p_mean = NaN(1,length(Steps));
p_median = NaN(1,length(Steps));
p_variance = NaN(1,length(Steps));
p_deciles = NaN(9,length(Steps));
if options_.estimation.moments_posterior_density.indicator
p_density = NaN(2^9,2,length(Steps));
end
p_hpdinf = NaN(1,length(Steps));
p_hpdsup = NaN(1,length(Steps));
for i=1:length(Steps)
if options_.estimation.moments_posterior_density.indicator
[pp_mean, pp_median, pp_var, hpd_interval, pp_deciles, pp_density] = ...
posterior_moments(tmp(:,i),1,mh_conf_sig);
p_density(:,:,i) = pp_density;
else
[pp_mean, pp_median, pp_var, hpd_interval, pp_deciles] = ...
posterior_moments(tmp(:,i),0,mh_conf_sig);
end
p_mean(i) = pp_mean;
p_median(i) = pp_median;
p_variance(i) = pp_var;
p_deciles(:,i) = pp_deciles;
p_hpdinf(i) = hpd_interval(1);
p_hpdsup(i) = hpd_interval(2);
end
FirstField = sprintf('%sTheoreticalMoments', TYPE);
oo_.(FirstField).dsge.ConditionalVarianceDecomposition.Steps = Steps;
oo_.(FirstField).dsge.ConditionalVarianceDecomposition.Mean.(name_1).(name_2) = p_mean;
oo_.(FirstField).dsge.ConditionalVarianceDecomposition.Median.(name_1).(name_2) = p_median;
oo_.(FirstField).dsge.ConditionalVarianceDecomposition.Variance.(name_1).(name_2) = p_variance;
oo_.(FirstField).dsge.ConditionalVarianceDecomposition.HPDinf.(name_1).(name_2) = p_hpdinf;
oo_.(FirstField).dsge.ConditionalVarianceDecomposition.HPDsup.(name_1).(name_2) = p_hpdsup;
oo_.(FirstField).dsge.ConditionalVarianceDecomposition.deciles.(name_1).(name_2) = p_deciles;
if options_.estimation.moments_posterior_density.indicator
oo_.(FirstField).dsge.ConditionalVarianceDecomposition.density.(name_1).(name_2) = p_density;
end
|
