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🐛 check_for_calibrated_covariances.m: correct logic of check 

Did not properly distinguish between unset correlation and starting value of 0
kalman-mex
Johannes Pfeifer 2023-10-07 16:34:22 +02:00 committed by Sébastien Villemot
parent a67cd58d1f
commit 94207ab851
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GPG Key ID: 2CECE9350ECEBE4A
3 changed files with 107 additions and 27 deletions
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2
matlab/+mom/run.m
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@ -316,7 +316,7 @@ if strcmp(options_mom_.mom.mom_method,'GMM') || strcmp(options_mom_.mom.mom_meth
end
% check for calibrated covariances before updating parameters
estim_params_ = check_for_calibrated_covariances(xparam0,estim_params_,M_);
estim_params_ = check_for_calibrated_covariances(estim_params_,M_);
% checks on parameter calibration and initialization
xparam_calib = get_all_parameters(estim_params_,M_); % get calibrated parameters

130
matlab/check_for_calibrated_covariances.m
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@ -1,10 +1,9 @@
function estim_params=check_for_calibrated_covariances(xparam1,estim_params,M)
% function check_for_calibrated_covariances(xparam1,estim_params,M)
function estim_params=check_for_calibrated_covariances(estim_params,M_)
% function check_for_calibrated_covariances(estim_params,M)
% find calibrated covariances to consider during estimation
% Inputs
% -xparam1 [vector] parameters to be estimated
% -estim_params [structure] describing parameters to be estimated
% -M [structure] describing the model
% -M_ [structure] describing the model
%
% Outputs
% -estim_params [structure] describing parameters to be estimated
@ -12,7 +11,7 @@ function estim_params=check_for_calibrated_covariances(xparam1,estim_params,M)
% Notes: M is local to this function and not updated when calling
% set_all_parameters
% Copyright © 2013-2017 Dynare Team
% Copyright © 2013-2023 Dynare Team
%
% This file is part of Dynare.
%
@ -28,27 +27,108 @@ function estim_params=check_for_calibrated_covariances(xparam1,estim_params,M)
%
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
Sigma_e_calibrated=M.Sigma_e;
H_calibrated=M.H;
%check covariance for structural errors
covariance_pos=find(tril(Sigma_e_calibrated,-1)); %off-diagonal elements set by covariances before updating correlation matrix to reflect estimated covariances
covariance_pos_ME=find(tril(H_calibrated,-1)); %off-diagonal elements set by covariances before updating correlation matrix to reflect estimated covariances
%locally updated M
M = set_all_parameters(xparam1,estim_params,M);
correlation_pos=find(tril(M.Correlation_matrix,-1)); %off-diagonal elements set by correlations after accounting for estimation
calibrated_covariance_pos=covariance_pos(~ismember(covariance_pos,correlation_pos));
if any(calibrated_covariance_pos)
[rows, columns]=ind2sub(size(M.Sigma_e),calibrated_covariance_pos); %find linear indices of lower triangular covariance entries
estim_params.calibrated_covariances.position=[calibrated_covariance_pos;sub2ind(size(M.Sigma_e),columns,rows)]; %get linear entries of upper triangular parts
estim_params.calibrated_covariances.cov_value=Sigma_e_calibrated(estim_params.calibrated_covariances.position);
if isfield(estim_params,'calibrated_covariances')
estim_params = rmfield(estim_params,'calibrated_covariances'); %remove if already present
end
if isfield(estim_params,'calibrated_covariances_ME')
estim_params = rmfield(estim_params,'calibrated_covariances_ME'); %remove if already present
end
correlation_pos_ME=find(tril(M.Correlation_matrix_ME,-1)); %off-diagonal elements set by correlations after accounting for estimation
calibrated_covariance_pos_ME=covariance_pos_ME(~ismember(covariance_pos_ME,correlation_pos_ME));
if any(calibrated_covariance_pos_ME)
[rows, columns]=ind2sub(size(M.H),calibrated_covariance_pos_ME); %find linear indices of lower triangular covariance entries
estim_params.calibrated_covariances_ME.position=[calibrated_covariance_pos_ME;sub2ind(size(M.H),columns,rows)]; %get linear entries of upper triangular parts
estim_params.calibrated_covariances_ME.cov_value=H_calibrated(estim_params.calibrated_covariances_ME.position);
[rows_calibrated, columns_calibrated]=ind2sub(size(M_.Sigma_e),find(tril(M_.Sigma_e,-1))); %find linear indices of preset lower triangular covariance entries
if estim_params.ncx %delete preset entries actually estimated
for i=1:estim_params.ncx
shock_1 = estim_params.corrx(i,1);
shock_2 = estim_params.corrx(i,2);
estimated_corr_pos=find(rows_calibrated==shock_1 & columns_calibrated==shock_2);
if ~isempty(estimated_corr_pos)
rows_calibrated(estimated_corr_pos)=[];
columns_calibrated(estimated_corr_pos)=[];
end
estimated_corr_pos=find(rows_calibrated==shock_2 & columns_calibrated==shock_1);
if ~isempty(estimated_corr_pos)
rows_calibrated(estimated_corr_pos)=[];
columns_calibrated(estimated_corr_pos)=[];
end
end
if any(rows_calibrated)
estim_params.calibrated_covariances.position=[sub2ind(size(M_.Sigma_e),rows_calibrated,columns_calibrated);sub2ind(size(M_.Sigma_e),columns_calibrated,rows_calibrated)]; %get linear entries of upper triangular parts
estim_params.calibrated_covariances.cov_value=M_.Sigma_e(estim_params.calibrated_covariances.position);
end
end
[rows_calibrated, columns_calibrated]=ind2sub(size(M_.H),find(tril(M_.H,-1))); %find linear indices of preset lower triangular covariance entries
if estim_params.ncn %delete preset entries actually estimated
for i=1:estim_params.ncn
shock_1 = estim_params.corrn(i,1);
shock_2 = estim_params.corrn(i,2);
estimated_corr_pos=find(rows_calibrated==shock_1 & columns_calibrated==shock_2);
if ~isempty(estimated_corr_pos)
rows_calibrated(estimated_corr_pos)=[];
columns_calibrated(estimated_corr_pos)=[];
end
estimated_corr_pos=find(rows_calibrated==shock_2 & columns_calibrated==shock_1);
if ~isempty(estimated_corr_pos)
rows_calibrated(estimated_corr_pos)=[];
columns_calibrated(estimated_corr_pos)=[];
end
end
end
if any(rows_calibrated)
estim_params.calibrated_covariances_ME.position=[sub2ind(size(M_.H),rows_calibrated,columns_calibrated);sub2ind(size(M_.H),columns_calibrated,rows_calibrated)]; %get linear entries of upper triangular parts
estim_params.calibrated_covariances_ME.cov_value=M_.H(estim_params.calibrated_covariances_ME.position);
end
return % --*-- Unit tests --*--
%@test:1
M_.Sigma_e=[1 0; 0 1];
M_.H=[1 0; 0 1];
M_.Correlation_matrix= [1 -0.5; -0.5 1];
M_.Correlation_matrix_ME=[1 -0.5; -0.5 1];
estim_params.ncx=1;
estim_params.ncn=1;
estim_params.corrx=[2 1 NaN -1 1 3 0 0.2000 NaN NaN NaN];
estim_params.corrn=[2 1 NaN -1 1 3 0 0.2000 NaN NaN NaN];
estim_params=check_for_calibrated_covariances(estim_params,M_);
if isfield(estim_params,'calibrated_covariances_ME') || isfield(estim_params,'calibrated_covariances')
t(1)=false;
else
t(1)=true;
end
M_.Sigma_e=[1 -0.1; -0.1 1];
M_.H=[1 -0.1; -0.1 1];
M_.Correlation_matrix= [1 -0.5; -0.5 1];
M_.Correlation_matrix_ME=[1 0; 0 1];
estim_params.ncx=1;
estim_params.ncn=0;
estim_params.corrx=[2 1 NaN -1 1 3 0 0.2000 NaN NaN NaN];
estim_params.corrn=[];
estim_params=check_for_calibrated_covariances(estim_params,M_);
t(2)=isequal(estim_params.calibrated_covariances_ME.position,[2;3]);
t(3)=isequal(estim_params.calibrated_covariances_ME.cov_value,[-0.1;-0.1]);
M_.Sigma_e=[1 -0.1; -0.1 1];
M_.H=[1 -0.1; -0.1 1];
M_.Correlation_matrix= [1 -0.5; -0.5 1];
M_.Correlation_matrix_ME=[1 0; 0 1];
estim_params.ncx=1;
estim_params.ncn=1;
estim_params.corrx=[2 1 NaN -1 1 3 0 0.2000 NaN NaN NaN];
estim_params.corrn=[2 1 NaN -1 1 3 0 0.2000 NaN NaN NaN];
estim_params=check_for_calibrated_covariances(estim_params,M_);
if isfield(estim_params,'calibrated_covariances_ME') || isfield(estim_params,'calibrated_covariances')
t(4)=false;
else
t(4)=true;
end
T = all(t);
%@eof:1

2
matlab/dynare_estimation_init.m
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@ -163,7 +163,7 @@ end
%check for calibrated covariances before updating parameters
if ~isempty(estim_params_) && ~(isfield(estim_params_,'nvx') && sum(estim_params_.nvx+estim_params_.nvn+estim_params_.ncx+estim_params_.ncn+estim_params_.np)==0)
estim_params_=check_for_calibrated_covariances(xparam1,estim_params_,M_);
estim_params_=check_for_calibrated_covariances(estim_params_,M_);
end
%%read out calibration that was set in mod-file and can be used for initialization