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
131
132
133
134
135
136
137
138
|
function [nvar,vartan,CovarFileNumber] = dsge_simulated_theoretical_covariance(SampleSize,M_,options_,oo_,type)
% function [nvar,vartan,CovarFileNumber] = dsge_simulated_theoretical_covariance(SampleSize,M_,options_,oo_,type)
% This function computes the posterior or prior distribution of the endogenous
% variables second order moments.
%
% INPUTS
% SampleSize [integer] scalar, number of simulations.
% M_ [structure] Dynare structure describing the model.
% options_ [structure] Dynare structure defining global options.
% oo_ [structure] Dynare structure where the results are saved.
% type [string] 'prior' or 'posterior'
%
%
% OUTPUTS
% nvar [integer] nvar is the number of stationary variables.
% vartan [char] array of characters (with nvar rows).
% CovarFileNumber [integer] scalar, number of prior or posterior data files (for covariance).
% Copyright (C) 2007-2020 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/>.
nodecomposition = 1;
% Get informations about the _posterior_draws files.
if strcmpi(type,'posterior')
NumberOfDrawsFiles = length(dir([M_.dname '/metropolis/' M_.fname '_' type '_draws*' ]));
posterior = 1;
elseif strcmpi(type,'prior')
NumberOfDrawsFiles = length(dir([M_.dname '/prior/draws/' type '_draws*' ]));
CheckPath('prior/moments',M_.dname);
posterior = 0;
else
disp('dsge_simulated_theoretical_covariance:: Unknown type!')
error();
end
%delete old stale files before creating new ones
if posterior
delete_stale_file([M_.dname '/metropolis/' M_.fname '_Posterior2ndOrderMoments*'])
else
delete_stale_file([M_.dname '/prior/moments/' M_.fname '_Prior2ndOrderMoments*'])
end
% Set varlist (vartan)
if ~posterior
if isfield(options_,'varlist')
temp = options_.varlist;
end
options_.varlist = options_.prior_analysis_endo_var_list;
end
[ivar,vartan] = get_variables_list(options_,M_);
if ~posterior
if exist('temp','var')
options_.varlist = temp;
end
end
nvar = length(ivar);
% Set the size of the auto-correlation function to zero.
nar = options_.ar;
options_.ar = 0;
% Number of lines in posterior data files.
MaXNumberOfCovarLines = ceil(options_.MaxNumberOfBytes/(nvar*(nvar+1)/2)/8);
if SampleSize<=MaXNumberOfCovarLines
Covariance_matrix = zeros(SampleSize,nvar*(nvar+1)/2);
NumberOfCovarFiles = 1;
else
Covariance_matrix = zeros(MaXNumberOfCovarLines,nvar*(nvar+1)/2);
NumberOfLinesInTheLastCovarFile = mod(SampleSize,MaXNumberOfCovarLines);
NumberOfCovarFiles = ceil(SampleSize/MaXNumberOfCovarLines);
end
NumberOfCovarLines = rows(Covariance_matrix);
CovarFileNumber = 1;
% Compute 2nd order moments and save them in *_[Posterior, Prior]2ndOrderMoments* files
linea = 0;
for file = 1:NumberOfDrawsFiles
if posterior
temp=load([M_.dname '/metropolis/' M_.fname '_' type '_draws' num2str(file) ]);
else
temp=load([M_.dname '/prior/draws/' type '_draws' num2str(file) ]);
end
NumberOfDraws = rows(temp.pdraws);
isdrsaved = columns(temp.pdraws)-1;
for linee = 1:NumberOfDraws
linea = linea+1;
if isdrsaved
M_=set_parameters_locally(M_,temp.pdraws{linee,1});% Needed to update the covariance matrix of the state innovations.
dr = temp.pdraws{linee,2};
else
M_=set_parameters_locally(M_,temp.pdraws{linee,1});
[dr,info,M_,options_,oo_] = resol(0,M_,options_,oo_);
end
tmp = th_autocovariances(dr,ivar,M_,options_,nodecomposition);
for i=1:nvar
for j=i:nvar
Covariance_matrix(linea,symmetric_matrix_index(i,j,nvar)) = tmp{1}(i,j);
end
end
if linea == NumberOfCovarLines
if posterior
save([ M_.dname '/metropolis/' M_.fname '_Posterior2ndOrderMoments' int2str(CovarFileNumber) '.mat' ],'Covariance_matrix');
else
save([ M_.dname '/prior/moments/' M_.fname '_Prior2ndOrderMoments' int2str(CovarFileNumber) '.mat' ],'Covariance_matrix');
end
CovarFileNumber = CovarFileNumber + 1;
linea = 0;
test = CovarFileNumber-NumberOfCovarFiles;
if ~test% Prepare the last round...
Covariance_matrix = zeros(NumberOfLinesInTheLastCovarFile,nvar*(nvar+1)/2);
NumberOfCovarLines = NumberOfLinesInTheLastCovarFile;
elseif test<0
Covariance_matrix = zeros(MaXNumberOfCovarLines,nvar*(nvar+1)/2);
else
clear('Covariance_matrix');
end
end
end
end
options_.ar = nar;
|
