commit
5f8d204c02
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@ -38,6 +38,8 @@ function [pdraws, TAU, GAM, LRE, gp, H, JJ] = dynare_identification(options_iden
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global M_ options_ oo_ bayestopt_ estim_params_
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options0_ = options_;
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if isoctave
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warning('off'),
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else
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@ -280,7 +282,7 @@ if iload <=0,
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parameters_TeX = 'Current parameter values';
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disp('Testing current parameter values')
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end
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[idehess_point, idemoments_point, idemodel_point, idelre_point, derivatives_info_point, info] = ...
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[idehess_point, idemoments_point, idemodel_point, idelre_point, derivatives_info_point, info, options_ident] = ...
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identification_analysis(params,indx,indexo,options_ident,dataset_, dataset_info, prior_exist, name_tex,1);
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if info(1)~=0,
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skipline()
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@ -323,7 +325,7 @@ if iload <=0,
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while kk<50 && info(1),
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kk=kk+1;
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params = prior_draw();
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[idehess_point, idemoments_point, idemodel_point, idelre_point, derivatives_info_point, info] = ...
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[idehess_point, idemoments_point, idemodel_point, idelre_point, derivatives_info_point, info, options_ident] = ...
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identification_analysis(params,indx,indexo,options_ident,dataset_,dataset_info, prior_exist, name_tex,1);
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end
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end
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@ -376,7 +378,7 @@ if iload <=0,
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else
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params = prior_draw();
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end
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[dum1, ideJ, ideH, ideGP, dum2 , info] = ...
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[dum1, ideJ, ideH, ideGP, dum2 , info, options_MC] = ...
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identification_analysis(params,indx,indexo,options_MC,dataset_, dataset_info, prior_exist, name_tex,0);
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if iteration==0 && info(1)==0,
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MAX_tau = min(SampleSize,ceil(MaxNumberOfBytes/(size(ideH.siH,1)*nparam)/8));
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@ -547,7 +549,7 @@ if SampleSize > 1,
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fprintf('\n')
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disp(['Testing ',tittxt, '. Press ENTER']), pause(5),
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if ~iload,
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[idehess_max, idemoments_max, idemodel_max, idelre_max, derivatives_info_max] = ...
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[idehess_max, idemoments_max, idemodel_max, idelre_max, derivatives_info_max, info_max, options_ident] = ...
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identification_analysis(pdraws(jmax,:),indx,indexo,options_ident,dataset_,dataset_info, prior_exist, name_tex,1);
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save([IdentifDirectoryName '/' M_.fname '_identif.mat'], 'idehess_max', 'idemoments_max','idemodel_max', 'idelre_max', 'jmax', '-append');
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end
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@ -562,7 +564,7 @@ if SampleSize > 1,
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fprintf('\n')
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disp(['Testing ',tittxt, '. Press ENTER']), pause(5),
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if ~iload,
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[idehess_min, idemoments_min, idemodel_min, idelre_min, derivatives_info_min] = ...
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[idehess_min, idemoments_min, idemodel_min, idelre_min, derivatives_info_min, info_min, options_ident] = ...
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identification_analysis(pdraws(jmin,:),indx,indexo,options_ident,dataset_, dataset_info, prior_exist, name_tex,1);
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save([IdentifDirectoryName '/' M_.fname '_identif.mat'], 'idehess_min', 'idemoments_min','idemodel_min', 'idelre_min', 'jmin', '-append');
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end
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@ -577,7 +579,7 @@ if SampleSize > 1,
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fprintf('\n')
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disp(['Testing ',tittxt, '. Press ENTER']), pause(5),
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if ~iload,
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[idehess_(j), idemoments_(j), idemodel_(j), idelre_(j), derivatives_info_(j)] = ...
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[idehess_(j), idemoments_(j), idemodel_(j), idelre_(j), derivatives_info_(j), info_resolve, options_ident] = ...
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identification_analysis(pdraws(jcrit(j),:),indx,indexo,options_ident,dataset_, dataset_info, prior_exist, name_tex,1);
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end
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disp_identification(pdraws(jcrit(j),:), idemodel_(j), idemoments_(j), name,1);
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@ -603,3 +605,5 @@ end
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skipline()
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disp(['==== Identification analysis completed ====' ]),
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skipline(2)
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options_ = options0_;
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@ -1,4 +1,4 @@
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function [ide_hess, ide_moments, ide_model, ide_lre, derivatives_info, info] = identification_analysis(params,indx,indexo,options_ident,dataset_,dataset_info, prior_exist, name_tex, init)
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function [ide_hess, ide_moments, ide_model, ide_lre, derivatives_info, info, options_ident] = identification_analysis(params,indx,indexo,options_ident,dataset_,dataset_info, prior_exist, name_tex, init)
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% function [ide_hess, ide_moments, ide_model, ide_lre, derivatives_info, info] = identification_analysis(params,indx,indexo,options_ident,data_info, prior_exist, name_tex, init)
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% given the parameter vector params, wraps all identification analyses
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%
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@ -88,6 +88,8 @@ if info(1)==0,
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indJJ = (find(max(abs(JJ'),[],1)>1.e-8));
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if isempty(indJJ) && any(any(isnan(JJ)))
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error('There are NaN in the JJ matrix. Please check whether your model has units roots and you forgot to set diffuse_filter=1.' )
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elseif any(any(isnan(gam)))
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error('There are NaN''s in the theoretical moments: make sure that for non-stationary models stationary transformations of non-stationary observables are used for checking identification. [TIP: use first differences].')
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end
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while length(indJJ)<nparam && nlags<10,
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disp('The number of moments with non-zero derivative is smaller than the number of parameters')
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@ -97,14 +99,14 @@ if info(1)==0,
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derivatives_info.DT=dA;
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derivatives_info.DOm=dOm;
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derivatives_info.DYss=dYss;
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evalin('caller',['options_ident.ar=',int2str(nlags),';']);
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options_.ar=nlags;
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indJJ = (find(max(abs(JJ'),[],1)>1.e-8));
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end
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if length(indJJ)<nparam,
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disp('The number of moments with non-zero derivative is smaller than the number of parameters')
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disp('up to 10 lags: check your model')
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disp('Either further increase ar or reduce the list of estimated parameters')
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error('IDETooManyParams',''),
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error('identification_analysis: there are not enough moments and too many parameters'),
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end
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indH = (find(max(abs(H'),[],1)>1.e-8));
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indLRE = (find(max(abs(gp'),[],1)>1.e-8));
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@ -154,7 +156,7 @@ if info(1)==0,
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options_.analytic_derivation = analytic_derivation;
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AHess=-AHess;
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if min(eig(AHess))<0,
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error('Analytic Hessian is not positive semi-definite!')
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error('identification_analysis: Analytic Hessian is not positive semi-definite!')
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end
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% chol(AHess);
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ide_hess.AHess= AHess;
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@ -183,7 +185,7 @@ if info(1)==0,
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catch,
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% replic = max([replic, nparam*(nparam+1)/2*10]);
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replic = max([replic, length(indJJ)*3]);
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cmm = simulated_moment_uncertainty(indJJ, periods, replic);
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cmm = simulated_moment_uncertainty(indJJ, periods, replic,options_,M_,oo_);
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% [V,D,W]=eig(cmm);
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sd=sqrt(diag(cmm));
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cc=cmm./(sd*sd');
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@ -1,7 +1,17 @@
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function [cmm, mm] = simulated_moment_uncertainty(indx, periods, replic)
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% function [cmm, mm] = simulated_moment_uncertainty(indx, periods, replic)
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%
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function [cmm, mm] = simulated_moment_uncertainty(indx, periods, replic,options_,M_,oo_)
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% function [cmm, mm] = simulated_moment_uncertainty(indx, periods, replic,options_,M_,oo_)
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% Compute the uncertainty around simulated moments
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% Inputs
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% - indx [n_moments by 1] index vector of moments
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% - periods [scalar] number of simulation periods
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% - replic [scalar] number of simulation replications
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% - options_ Dynare options structure
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% - M_ Dynare Model structure
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% - oo_ Dynare results structure
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% Outputs:
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% - cmm: [n_moments by n_moments] covariance matrix of simulated moments
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% - mm: [n_moments by replic] matrix of moments
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%
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% Copyright (C) 2009-2016 Dynare Team
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%
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% This file is part of Dynare.
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@ -19,20 +29,64 @@ function [cmm, mm] = simulated_moment_uncertainty(indx, periods, replic)
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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global options_ oo_
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mm=zeros(length(indx),replic);
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disp('Evaluating simulated moment uncertainty ... please wait')
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disp(['Doing ',int2str(replic),' replicas of length ',int2str(periods),' periods.'])
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noprint0 = options_.noprint;
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h = dyn_waitbar(0,'Simulated moment uncertainty ...');
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%Do check whether simulation is possible
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if options_.periods == 0
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error('simulated_moment_uncertainty: Periods must be bigger than 0')
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end
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if options_.periods <= options_.drop
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error('simulated_moment_uncertainty: The horizon of simulation is shorter than the number of observations to be dropped. Either increase options_.periods or decrease options_.drop.')
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end
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%locally set options
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options_.TeX=0;
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options_.noprint = 1;
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options_.order = 1;
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options_.periods = periods;
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if isempty(options_.qz_criterium)
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options_.qz_criterium = 1+1e-6;
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end
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if M_.exo_nbr > 0
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oo_.exo_simul= ones(max(options_.periods,1) + M_.maximum_lag + M_.maximum_lead,1) * oo_.exo_steady_state';
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end
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oo_.dr=set_state_space(oo_.dr,M_,options_);
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if options_.logged_steady_state %if steady state was previously logged, undo this
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oo_.dr.ys=exp(oo_.dr.ys);
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oo_.steady_state=exp(oo_.steady_state);
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options_.logged_steady_state=0;
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logged_steady_state_indicator=1;
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evalin('base','options_.logged_steady_state=0;')
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end
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[dr,info,M_,options_,oo_] = resol(0,M_,options_,oo_);
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oo_.dr=dr;
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if info(1)
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fprintf('\nsimulated_moment_uncertainty: model could not be solved')
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print_info(info,0,options_);
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end
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%set starting point of simulations
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if isempty(M_.endo_histval)
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y0 = oo_.dr.ys;
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else
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y0 = M_.endo_histval;
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end
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for j=1:replic;
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options_.irf = 0;
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options_.noprint = 1;
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options_.order = 1;
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options_.periods = periods;
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info = stoch_simul(char(options_.varobs));
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[ys, oo_] = simult(y0,oo_.dr,M_,options_,oo_);%do simulation
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oo_=disp_moments(ys,char(options_.varobs),M_,options_,oo_); %get moments
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dum=[oo_.mean; dyn_vech(oo_.var)];
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sd = sqrt(diag(oo_.var));
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for i=1:options_.ar;
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@ -42,6 +96,9 @@ for j=1:replic;
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dyn_waitbar(j/replic,h,['Simulated moment uncertainty. Replic ',int2str(j),'/',int2str(replic)])
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end;
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dyn_waitbar_close(h);
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options_.noprint = noprint0;
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if logged_steady_state_indicator
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evalin('base','options_.logged_steady_state=1;') %reset base workspace option to conform to base oo_
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end
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cmm = cov(mm');
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disp('Simulated moment uncertainty ... done!')
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