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Add posterior variance decomposition. 

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@1426 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
adjemian 2007-10-12 17:02:04 +00:00
parent 484f5d3034
commit 020035a81b
2 changed files with 150 additions and 1 deletions
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2
matlab/dsge_posterior_theoretical_covariance.m
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@ -22,7 +22,7 @@ global M_ options_ oo_
type = 'posterior';% To be defined as a input argument later...
NumberOfSimulations = 800;% To be defined in a global structure...
% Set varlist (vartan) if necessary
% Set varlist (vartan)
[ivar,vartan] = set_stationary_variables_list();
% Set various parameters & Check or create files and directories

149
matlab/dsge_posterior_theoretical_variance_decomposition.m Normal file
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@ -0,0 +1,149 @@
function dsge_posterior_theoretical_variance_decomposition()
% [stephane.adjemian@ens.fr][10-08-2007]
% This function estimates the posterior distribution of the variance
% decomposition of the observed endogenous variables.
%
% INPUTS
% None.
%
% OUTPUTS
% None.
%
% ALGORITHM
% None.
%
% SPECIAL REQUIREMENTS
% None.
%
%
% part of DYNARE, copyright Dynare Team (2007).
% Gnu Public License.
global M_ options_ oo_
type = 'posterior';% To be defined as a input argument later...
NumberOfSimulations = 800;% To be defined in a global structure...
% Set varlist (vartan)
[ivar,vartan] = set_stationary_variables_list();
ivar
vartan
% Set various parameters, Check or create files and directories &
% initialize arrays.
if strcmpi(type,'posterior')
MhDirectoryName = CheckPath('metropolis');
else
MhDirectoryName = CheckPath('prior');
end
fname = [ MhDirectoryName '/' M_.fname];
DrawsFiles = dir([fname '_' type '_draws*' ]);
if ~rows(DrawsFiles)
if strcmpi(type,'posterior')
SampleAddress = selec_posterior_draws(NumberOfSimulations,1);
else% (samples from the prior) To be done later...
end
DrawsFiles = dir([fname '_' type '_draws*']);
end
nar = options_.ar;% Saves size of the auto-correlation function.
options_.ar = 0;% Set the size of the auto-correlation function.
nexo = M_.exo_nbr;
nvar = length(ivar);
NumberOfDrawsFiles = rows(DrawsFiles);
NumberOfSavedElementsPerSimulation = nvar*(nexo+1);
MaXNumberOfDecompLines = ceil(options_.MaxNumberOfBytes/NumberOfSavedElementsPerSimulation/8);
if NumberOfSimulations<=MaXNumberOfDecompLines
Decomposition_array = zeros(NumberOfSimulations,nvar*(nexo+1));
NumberOfDecompFiles = 1;
else
Decomposition_array = zeros(MaXNumberOfDecompLines,nvar*(nexo+1));
NumberOfLinesInTheLastDecompFile = mod(NumberOfSimulations,MaXNumberOfDecompLines);
NumberOfDecompFiles = ceil(NumberOfSimulations/MaXNumberOfDecompLines);
end
NumberOfDecompLines = rows(Decomposition_array);
DecompFileNumber = 1;
% Compute total variances (covariances are not saved) and variances
% implied by each structural shock.
linea = 0;
for file = 1:NumberOfDrawsFiles
load([MhDirectoryName '/' DrawsFiles(file).name]);
NumberOfDraws = rows(pdraws);
for linee = 1:NumberOfDraws
linea = linea+1;
draw = pdraws(linee,:);
set_parameters(draw);
[dr,info] = resol(oo_.steady_state,0);
tmp = th_autocovariances(dr,ivar);
for i=1:nvar
Decomposition_array(linea,i) = tmp{1}(i,i);
end
for i=1:nvar
for j=1:nexo
Decomposition_array(linea,nvar+(i-1)*nexo+j) = tmp{2}(i,j);
end
end
if linea == NumberOfDecompLines
save([fname '_PosteriorVarianceDecomposition' int2str(DecompFileNumber)],'Decomposition_array');
DecompFileNumber = DecompFileNumber + 1;
linea = 0;
test = DecompFileNumber-NumberOfDecompFiles;
if ~(DecompFileNumber-NumberOfDecompFiles)% Prepare the last round...
Decomposition_array = zeros(NumberOfLinesInTheLastDecompFile,nvar*(nexo+1));
NumberOfDecompLines = NumberOfLinesInTheLastDecompFile;
elseif DecompFileNumber-NumberOfDecompFiles<0;
Decomposition_array = zeros(MaXNumberOfDecompLines,nvar*(nexo+1));
else
clear('Decomposition_array');
end
end
end
end
options_.ar = nar; clear('pdraws','tmp');
% Compute statistics and save in oo_
for i=1:nvar
for j=1:nexo
i1 = 1;
tmp = zeros(NumberOfSimulations,1);
for file = 1:NumberOfDrawsFiles
load([fname '_PosteriorVarianceDecomposition' int2str(file)]);
i2 = i1 + rows(Decomposition_array) - 1;
tmp(i1:i2) = Decomposition_array(:,nvar+(i-1)*nexo+j);
i1 = i2+1;
end
name = [ deblank(vartan(i,:)) '.' deblank(M_.exo_names(j,:)) ];
t1 = min(tmp); t2 = max(tmp);
t3 = t2-t1;% How to normalize ? t1 and t2 may be zero...
if t3<1.0e-12
if t1<1.0e-12
t1 = 0;
end
if abs(t1-1)<1.0e-12
t1 = 1;
end
post_mean = t1;
post_median = t1;
post_var = 0;
hpd_interval = NaN(2,1);
post_deciles = NaN(9,1);
density = NaN;
else
[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(tmp,1);
end
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.mean.' name ' = post_mean;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.median.' name ' = post_median;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.variance.' name ' = post_var;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.hpdinf.' name ' = hpd_interval(1);']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.hpdsup.' name ' = hpd_interval(2);']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.deciles.' name ' = post_deciles;']);
eval(['oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.density.' name ' = density;']);
end
end