function [nvar,vartan,NumberOfConditionalDecompFiles] = ... dsge_simulated_theoretical_conditional_variance_decomposition(SampleSize,Steps,M_,options_,oo_,type) % function [nvar,vartan,NumberOfConditionalDecompFiles] = ... % dsge_simulated_theoretical_conditional_variance_decomposition(SampleSize,Steps,M_,options_,oo_,type) % This function computes the posterior or prior distribution of the conditional variance % decomposition of the endogenous variables (or a subset of the endogenous variables). % % INPUTS % SampleSize [integer] scalar, number of simulations. % Steps [integers] horizons at which to conduct decomposition % 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). % NumberOfConditionalDecompFiles [integer] scalar, number of prior or posterior data files (for covariance). % Copyright © 2009-2021 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 . % 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_conditional_variance_decomposition:: Unknown type!') error() end %delete old stale files before creating new ones if posterior delete_stale_file([M_.dname '/metropolis/' M_.fname '_PosteriorConditionalVarianceDecomposition*']) delete_stale_file([M_.dname '/metropolis/' M_.fname '_PosteriorConditionalVarianceDecompositionME*']) else delete_stale_file([M_.dname '/prior/moments/' M_.fname '_PriorConditionalVarianceDecomposition*']) delete_stale_file([M_.dname '/prior/moments/' M_.fname '_PriorConditionalVarianceDecompositionME*']) end % Set varlist (vartan) if ~posterior if isfield(options_,'varlist') temp = options_.varlist; end options_.varlist = options_.prior_analysis_endo_var_list; end endo_names=options_.varlist; [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; NumberOfSavedElementsPerSimulation = nvar*M_.exo_nbr*length(Steps); MaXNumberOfConditionalDecompLines = ceil(options_.MaxNumberOfBytes/NumberOfSavedElementsPerSimulation/8); ME_present=0; if ~all(diag(M_.H)==0) [observable_pos_requested_vars,index_subset,index_observables]=intersect(ivar,options_.varobs_id,'stable'); if ~isempty(observable_pos_requested_vars) ME_present=1; nobs_ME=length(observable_pos_requested_vars); NumberOfSavedElementsPerSimulation_ME = nobs_ME*(M_.exo_nbr+1)*length(Steps); MaXNumberOfConditionalDecompLines_ME = ceil(options_.MaxNumberOfBytes/NumberOfSavedElementsPerSimulation_ME/8); end end if SampleSize<=MaXNumberOfConditionalDecompLines Conditional_decomposition_array = zeros(nvar,length(Steps),M_.exo_nbr,SampleSize); NumberOfConditionalDecompFiles = 1; else Conditional_decomposition_array = zeros(nvar,length(Steps),M_.exo_nbr,MaXNumberOfConditionalDecompLines); NumberOfLinesInTheLastConditionalDecompFile = mod(SampleSize,MaXNumberOfConditionalDecompLines); NumberOfConditionalDecompFiles = ceil(SampleSize/MaXNumberOfConditionalDecompLines); end if ME_present if SampleSize<=MaXNumberOfConditionalDecompLines_ME Conditional_decomposition_array_ME = zeros(nobs_ME,length(Steps),M_.exo_nbr+1,SampleSize); NumberOfConditionalDecompFiles_ME = 1; else Conditional_decomposition_array_ME = zeros(nobs_ME,length(Steps),M_.exo_nbr+1,SampleSize); NumberOfLinesInTheLastConditionalDecompFile_ME = mod(SampleSize,MaXNumberOfConditionalDecompLines_ME); NumberOfConditionalDecompFiles_ME = ceil(SampleSize/MaXNumberOfConditionalDecompLines_ME); end NumberOfConditionalDecompLines_ME = size(Conditional_decomposition_array_ME,4); ConditionalDecompFileNumber_ME = 0; end NumberOfConditionalDecompLines = size(Conditional_decomposition_array,4); ConditionalDecompFileNumber = 0; StateSpaceModel.number_of_state_equations = M_.endo_nbr; StateSpaceModel.number_of_state_innovations = M_.exo_nbr; first_call = 1; linea = 0; linea_ME = 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 isdrsaved = columns(temp.pdraws)-1; NumberOfDraws = rows(temp.pdraws); for linee = 1:NumberOfDraws linea = linea+1; linea_ME = linea_ME+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_,oo_] = compute_decision_rules(M_,options_,oo_) end if first_call endo_nbr = M_.endo_nbr; nstatic = M_.nstatic; nspred = M_.nspred; iv = (1:endo_nbr)'; ic = [ nstatic+(1:nspred) endo_nbr+(1:size(dr.ghx,2)-nspred) ]'; StateSpaceModel.number_of_state_equations = M_.endo_nbr; StateSpaceModel.number_of_state_innovations = M_.exo_nbr; StateSpaceModel.sigma_e_is_diagonal = M_.sigma_e_is_diagonal; StateSpaceModel.order_var = dr.order_var; StateSpaceModel.observable_pos=options_.varobs_id; first_call = 0; clear('endo_nbr','nstatic','nspred','k'); end [StateSpaceModel.transition_matrix,StateSpaceModel.impulse_matrix] = kalman_transition_matrix(dr,iv,ic,M_.exo_nbr); StateSpaceModel.state_innovations_covariance_matrix = M_.Sigma_e; M_ = set_measurement_errors(temp.pdraws{linee,1},temp.estim_params_,M_); StateSpaceModel.measurement_error=M_.H; clear('dr'); [ConditionalVarianceDecomposition, ConditionalVarianceDecomposition_ME]=conditional_variance_decomposition(StateSpaceModel, Steps, ivar); Conditional_decomposition_array(:,:,:,linea) =ConditionalVarianceDecomposition; if ME_present Conditional_decomposition_array_ME(:,:,:,linea) =ConditionalVarianceDecomposition_ME; end if linea == NumberOfConditionalDecompLines ConditionalDecompFileNumber = ConditionalDecompFileNumber + 1; linea = 0; if posterior save([M_.dname '/metropolis/' M_.fname '_PosteriorConditionalVarianceDecomposition' int2str(ConditionalDecompFileNumber) '.mat' ], ... 'Conditional_decomposition_array','endo_names'); else save([M_.dname '/prior/moments/' M_.fname '_PriorConditionalVarianceDecomposition' int2str(ConditionalDecompFileNumber) '.mat' ], ... 'Conditional_decomposition_array','endo_names'); end if (ConditionalDecompFileNumber==NumberOfConditionalDecompFiles-1)% Prepare last round. Conditional_decomposition_array = zeros(nvar, length(Steps),M_.exo_nbr,NumberOfLinesInTheLastConditionalDecompFile) ; NumberOfConditionalDecompLines = NumberOfLinesInTheLastConditionalDecompFile; elseif ConditionalDecompFileNumber