diff --git a/matlab/check_posterior_analysis_data.m b/matlab/check_posterior_analysis_data.m
index f54394442..551375f36 100644
--- a/matlab/check_posterior_analysis_data.m
+++ b/matlab/check_posterior_analysis_data.m
@@ -64,8 +64,8 @@ function [info,description] = check_posterior_analysis_data(type,M_)
generic_post_data_file_name = 'PosteriorVarianceDecomposition';
case 'correlation'
generic_post_data_file_name = 'PosteriorCorrelations';
- case 'dynamic_decomposition'
- generic_post_data_file_name = 'PosteriorDynamicVarianceDecomposition';
+ case 'conditional decomposition'
+ generic_post_data_file_name = 'PosteriorConditionalVarianceDecomposition';
otherwise
disp('This feature is not yest implemented!')
end
diff --git a/matlab/compute_moments_varendo.m b/matlab/compute_moments_varendo.m
index 9cce75da7..9dca0f865 100644
--- a/matlab/compute_moments_varendo.m
+++ b/matlab/compute_moments_varendo.m
@@ -35,6 +35,7 @@ function oo_ = compute_moments_varendo(options_,M_,oo_,var_list_)
NumberOfExogenousVariables = M_.exo_nbr;
list_of_exogenous_variables = M_.exo_names;
NumberOfLags = options_.ar;
+ Steps = options_.conditional_variance_decomposition_dates;
% COVARIANCE MATRIX.
for i=1:NumberOfEndogenousVariables
for j=i:NumberOfEndogenousVariables
@@ -54,4 +55,10 @@ function oo_ = compute_moments_varendo(options_,M_,oo_,var_list_)
for j=1:NumberOfExogenousVariables
oo_ = posterior_analysis('decomposition',var_list_(i,:),M_.exo_names(j,:),[],options_,M_,oo_);
end
+ end
+ % CONDITIONAL VARIANCE DECOMPOSITION.
+ for i=1:NumberOfEndogenousVariables
+ for j=1:NumberOfExogenousVariables
+ oo_ = posterior_analysis('conditional decomposition',var_list_(i,:),M_.exo_names(j,:),Steps,options_,M_,oo_);
+ end
end
\ No newline at end of file
diff --git a/matlab/conditional_variance_decomposition.m b/matlab/conditional_variance_decomposition.m
new file mode 100644
index 000000000..047200a38
--- /dev/null
+++ b/matlab/conditional_variance_decomposition.m
@@ -0,0 +1,54 @@
+function PackedConditionalVarianceDecomposition = conditional_variance_decomposition(StateSpaceModel, Steps, SubsetOfVariables)
+% This function computes the conditional variance decomposition of a given state space model
+% for a subset of endogenous variables.
+%
+% INPUTS
+% StateSpaceModel [structure] Specification of the state space model.
+% Steps [integer] 1*h vector of dates.
+% SubsetOfVariables [integer] 1*q vector of indices.
+%
+% OUTPUTS
+% PackedConditionalVarianceDecomposition [double] n(n+1)/2*p matrix, where p is the number of state innovations and
+% n is equal to length(SubsetOfVariables).
+%
+% SPECIAL REQUIREMENTS
+%
+% [1] The covariance matrix of the state innovations needs to be diagonal.
+% [2] In this version, absence of measurement errors is assumed...
+
+% Copyright (C) 2009 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 .
+ ConditionalVariance = zeros(StateSpaceModel.number_of_state_equations,StateSpaceModel.number_of_state_equations);
+ ConditionalVariance = repmat(ConditionalVariance,[1 1 length(Steps) StateSpaceModel.number_of_state_innovations]);
+ BB = StateSpaceModel.impulse_matrix*transpose(StateSpaceModel.impulse_matrix);
+ for h = 1:length(Steps)
+ for t = 0:Steps(h)
+ for i=1:StateSpaceModel.number_of_state_innovations
+ ConditionalVariance(:,:,h,i) = ...
+ StateSpaceModel.transition_matrix*ConditionalVariance(:,:,h,i)*transpose(StateSpaceModel.transition_matrix) ...
+ +BB*StateSpaceModel.state_innovations_covariance_matrix(i,i);
+ end
+ end
+ end
+ ConditionalVariance = ConditionalVariance(SubsetOfVariables,SubsetOfVariables,:,:);
+ NumberOfVariables = length(SubsetOfVariables);
+ PackedConditionalVarianceDecomposition = zeros(NumberOfVariables*(NumberOfVariables+1)/2,length(Steps),StateSpaceModel.number_of_state_innovations);
+ for i=1:StateSpaceModel.number_of_state_innovations
+ for h = 1:length(Steps)
+ PackedConditionalVarianceDecomposition(:,h,i) = vech(ConditionalVariance(:,:,h,i));
+ end
+ end
\ No newline at end of file
diff --git a/matlab/conditional_variance_decomposition_posterior_analysis.m b/matlab/conditional_variance_decomposition_posterior_analysis.m
new file mode 100644
index 000000000..4b9a5fbea
--- /dev/null
+++ b/matlab/conditional_variance_decomposition_posterior_analysis.m
@@ -0,0 +1,83 @@
+function oo_ = conditional_variance_decomposition_posterior_analysis(NumberOfSimulations, dname, fname, ...
+ Steps, exonames, exo, vartan, var, mh_conf_sig, oo_)
+% Copyright (C) 2009 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 .
+
+ indx = check_name(vartan,var);
+ if isempty(indx)
+ disp(['posterior_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(['posterior_analysis:: ' exo ' is not a declared exogenous variable!'])
+ return
+ end
+
+ tmp = dir([ dname '/metropolis/' fname '_PosteriorConditionalVarianceDecomposition*.mat']);
+ NumberOfFiles = length(tmp);
+ i1 = 1; tmp = zeros(NumberOfSimulations,length(Steps));
+
+ for file = 1:NumberOfFiles
+ load([dname '/metropolis/' fname '_PosteriorConditionalVarianceDecomposition' int2str(file) '.mat']);
+ % (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
+ name = [ var '.' exo ];
+ if isfield(oo_,'PosteriorTheoreticalMoments')
+ if isfield(oo_.PosteriorTheoreticalMoments,'dsge')
+ if isfield(oo_.PosteriorTheoreticalMoments.dsge,'ConditionalVarianceDecomposition')
+ if isfield(oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.mean,name)
+ if sum(Steps-oo_.PosteriorTheoreticalMoments.dsge.VarianceDecomposition.mean.(name)(1,:)) == 0
+ % Nothing (new) to do here...
+ return
+ end
+ end
+ end
+ end
+ end
+ posterior_mean = NaN(2,length(Steps));
+ posterior_mean(1,:) = Steps;
+ posterior_median = NaN(1,length(Steps));
+ posterior_variance = NaN(1,length(Steps));
+ posterior_deciles = NaN(9,length(Steps));
+ posterior_density = NaN(2^9,2,length(Steps));
+ posterior_hpdinf = NaN(1,length(Steps));
+ posterior_hpdsup = NaN(1,length(Steps));
+ for i=1:length(Steps)
+ if ~isconst(tmp(:,i))
+ [post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
+ posterior_moments(tmp(:,i),1,mh_conf_sig);
+ posterior_mean(2,i) = post_mean;
+ posterior_median(i) = post_median;
+ posterior_variance(i) = post_var;
+ posterior_deciles(:,i) = post_deciles;
+ posterior_hpdinf(i) = hpd_interval(1);
+ posterior_hpdinf(i) = hpd_interval(2);
+ posterior_density(:,:,i) = density;
+ end
+ end
+ eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.mean.' name ' = posterior_mean;']);
+ eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.median.' name ' = posterior_median;']);
+ eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.variance.' name ' = posterior_variance;']);
+ eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.hpdinf.' name ' = posterior_hpdinf;']);
+ eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.hpdsup.' name ' = posterior_hpdsup;']);
+ eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.deciles.' name ' = posterior_deciles;']);
+ eval(['oo_.PosteriorTheoreticalMoments.dsge.ConditionalVarianceDecomposition.density.' name ' = posterior_density;']);
\ No newline at end of file
diff --git a/matlab/dsge_posterior_theoretical_conditional_variance_decomposition.m b/matlab/dsge_posterior_theoretical_conditional_variance_decomposition.m
new file mode 100644
index 000000000..30251a62b
--- /dev/null
+++ b/matlab/dsge_posterior_theoretical_conditional_variance_decomposition.m
@@ -0,0 +1,112 @@
+function [nvar,vartan,NumberOfConditionalDecompFiles] = ...
+ dsge_posterior_theoretical_conditional_variance_decomposition(SampleSize,Steps,M_,options_,oo_)
+% This function estimates the posterior distribution of the conditional variance
+% decomposition of the endogenous variables (or a subset of the endogenous variables).
+%
+% INPUTS
+% SampleSize [integer] scalar, number of draws in the posterior distribution.
+% Steps [integer] 1*h vector of dates.
+%
+% OUTPUTS
+% nvar [integer] scalar, number of endogenous variables.
+% vartan [string] array, list of endogenous variables.
+% NumberOfConditionalDecompFiles [integer] scalar.
+
+% Copyright (C) 2009 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 .
+
+type = 'posterior';% To be defined as a input argument later...
+
+% Set varlist (vartan)
+[ivar,vartan] = set_stationary_variables_list;
+nvar = length(ivar);
+
+% Set the size of the auto-correlation function to zero.
+nar = options_.ar;
+options_.ar = 0;
+
+% Get informations about the _posterior_draws files.
+DrawsFiles = dir([M_.dname '/metropolis/' M_.fname '_' type '_draws*' ]);
+NumberOfDrawsFiles = length(DrawsFiles);
+
+NumberOfDrawsFiles = rows(DrawsFiles);
+NumberOfSavedElementsPerSimulation = nvar*(nvar+1)/2*M_.exo_nbr*length(Steps);
+MaXNumberOfConditionalDecompLines = ceil(options_.MaxNumberOfBytes/NumberOfSavedElementsPerSimulation/8);
+
+if SampleSize<=MaXNumberOfConditionalDecompLines
+ Conditional_decomposition_array = zeros(nvar*(nvar+1)/2,length(Steps),M_.exo_nbr,SampleSize);
+ NumberOfConditionalDecompFiles = 1;
+else
+ Conditional_decomposition_array = zeros(nvar*(nvar+1)/2,length(Steps),M_.exo_nbr,MaXNumberOfConditionalDecompLines);
+ NumberOfLinesInTheLastConditionalDecompFile = mod(SampleSize,MaXNumberOfConditionalDecompLines);
+ NumberOfConditionalDecompFiles = ceil(SampleSize/MaXNumberOfCOnditionalDecompLines);
+end
+
+NumberOfConditionalDecompLines = rows(Conditional_decomposition_array);
+ConditionalDecompFileNumber = 1;
+
+StateSpaceModel.number_of_state_equations = M_.endo_nbr;
+StateSpaceModel.number_of_state_innovations = M_.exo_nbr;
+
+endo_nbr = M_.endo_nbr;
+nstatic = oo_.dr.nstatic;
+npred = oo_.dr.npred;
+iv = (1:endo_nbr)';
+ic = [ nstatic+(1:npred) endo_nbr+(1:size(oo_.dr.ghx,2)-npred) ]';
+aux = oo_.dr.transition_auxiliary_variables;
+k = find(aux(:,2) > npred);
+aux(:,2) = aux(:,2) + nstatic;
+aux(k,2) = aux(k,2) + oo_.dr.nfwrd;
+
+linea = 0;
+for file = 1:NumberOfDrawsFiles
+ load([M_.dname '/metropolis/' DrawsFiles(file).name ]);
+ isdrsaved = columns(pdraws)-1;
+ NumberOfDraws = rows(pdraws);
+ for linee = 1:NumberOfDraws
+ linea = linea+1;
+ if isdrsaved
+ set_parameters(pdraws{linee,1});% Needed to update the covariance matrix of the state innovations.
+ dr = pdraws{linee,2};
+ else
+ set_parameters(pdraws{linee,1});
+ [dr,info] = resol(oo_.steady_state,0);
+ end
+ [StateSpaceModel.transition_matrix,StateSpaceModel.impulse_matrix] = kalman_transition_matrix(dr,iv,ic,aux,M_.exo_nbr);
+ StateSpaceModel.state_innovations_covariance_matrix = M_.Sigma_e;
+ clear('dr');
+ Conditional_decomposition_array(:,:,:,linea) = conditional_variance_decomposition(StateSpaceModel, Steps, ivar);
+ if linea == NumberOfConditionalDecompLines
+ save([M_.dname '/metropolis/' M_.fname '_PosteriorConditionalVarianceDecomposition' int2str(ConditionalDecompFileNumber) '.mat' ], ...
+ 'Conditional_decomposition_array');
+ ConditionalDecompFileNumber = ConditionalDecompFileNumber + 1;
+ linea = 0;
+ test = ConditionalDecompFileNumber-NumberOfConditionalDecompFiles;
+ if ~test% Prepare the last round...
+ Conditional_decomposition_array = zeros(nvar*(nvar+1)/2,length(Steps),M_.exo_nbr,NumberOfLinesInTheLastConditionalDecompFile);
+ NumberOfConditionalDecompLines = NumberOfLinesInTheLastConditionalDecompFile;
+ ConditionalDecompFileNumber = ConditionalDecompFileNumber - 1;
+ elseif test<0;
+ Conditional_decomposition_array = zeros(nvar*(nvar+1)/2,length(Steps),M_.exo_nbr,MaXNumberOfConditionalDecompLines);
+ else
+ clear('Conditional_decomposition_array');
+ end
+ end
+ end
+end
+
+options_.ar = nar;
\ No newline at end of file
diff --git a/matlab/global_initialization.m b/matlab/global_initialization.m
index 3b8307333..6583077cc 100644
--- a/matlab/global_initialization.m
+++ b/matlab/global_initialization.m
@@ -183,10 +183,17 @@ function global_initialization()
options_.student_degrees_of_freedom = 3;
options_.trace_plot_ma = 200;
options_.mh_autocorrelation_function_size = 30;
- options_.plot_priors = 0;
+ options_.plot_priors = 1;
options_.cova_compute = 1;
options_.parallel = 0;
-
+ options_.number_of_grid_points_for_kde = 2^9;
+ quarter = 1;
+ years = [1 2 3 4 5 10 20 30 40 50];
+ options_.conditional_variance_decomposition_dates = zeros(1,length(years));
+ for i=1:length(years)
+ options_.conditional_variance_decomposition_dates(i) = ...
+ (years(i)-1)*4+quarter;
+ end
% Misc
options_.conf_sig = 0.6;
oo_.exo_simul = [];
diff --git a/matlab/posterior_analysis.m b/matlab/posterior_analysis.m
index 15b656514..8639571dd 100644
--- a/matlab/posterior_analysis.m
+++ b/matlab/posterior_analysis.m
@@ -1,5 +1,4 @@
function oo_ = posterior_analysis(type,arg1,arg2,arg3,options_,M_,oo_)
-
% Copyright (C) 2008 Dynare Team
%
% This file is part of Dynare.
@@ -46,7 +45,7 @@ function oo_ = posterior_analysis(type,arg1,arg2,arg3,options_,M_,oo_)
function oo_ = job(type,SampleSize,arg1,arg2,arg3,options_,M_,oo_,nvar,vartan)
narg1 = 8;
narg2 = 10;
- if ~(nargin==narg1 | nargin==narg2)
+ if ~(nargin==narg1 || nargin==narg2)
error('posterior_analysis:: Call to function job is buggy!')
end
switch type
@@ -70,7 +69,14 @@ function oo_ = job(type,SampleSize,arg1,arg2,arg3,options_,M_,oo_,nvar,vartan)
dsge_posterior_theoretical_correlation(SampleSize,arg3,M_,options_,oo_);
end
oo_ = correlation_posterior_analysis(SampleSize,M_.dname,M_.fname,...
- vartan,nvar,arg1,arg2,arg3,options_.mh_conf_sig,oo_,M_,options_);
+ vartan,nvar,arg1,arg2,arg3,options_.mh_conf_sig,oo_,M_,options_);
+ case 'conditional decomposition'
+ if nargin==narg1
+ [nvar,vartan,NumberOfFiles] = ...
+ dsge_posterior_theoretical_conditional_variance_decomposition(SampleSize,arg3,M_,options_,oo_);
+ end
+ oo_ = conditional_variance_decomposition_posterior_analysis(SampleSize,M_.dname,M_.fname,...
+ arg3,M_.exo_names,arg2,vartan,arg1,options_.mh_conf_sig,oo_);
otherwise
disp('Not yet implemented')
end
\ No newline at end of file