identification: separate error code and option
Solves issues with Monte Carlo sampling where error code affected option for later drawspac-components
Johannes Pfeifer
parent
459d6ded6e
commit
c60a1624d1
|
|
@ -24,7 +24,7 @@ function disp_identification(pdraws, ide_reducedform, ide_moments, ide_spectrum,
|
|||
% This function is called by
|
||||
% * dynare_identification.m
|
||||
% =========================================================================
|
||||
% Copyright (C) 2010-2019 Dynare Team
|
||||
% Copyright (C) 2010-2021 Dynare Team
|
||||
%
|
||||
% This file is part of Dynare.
|
||||
%
|
||||
|
|
@ -82,7 +82,7 @@ for jide = 1:4
|
|||
%% Set output strings depending on test
|
||||
if jide == 1
|
||||
strTest = 'REDUCED-FORM'; strJacobian = 'Tau'; strMeaning = 'Jacobian of steady state and reduced-form solution matrices';
|
||||
if ~no_identification_reducedform
|
||||
if ~no_identification_reducedform && ~ isempty(fieldnames(ide_reducedform))
|
||||
noidentification = 0; ide = ide_reducedform;
|
||||
if SampleSize == 1
|
||||
Jacob = ide.dREDUCEDFORM;
|
||||
|
|
@ -97,7 +97,7 @@ for jide = 1:4
|
|||
elseif options_ident.order == 3
|
||||
strMeaning = 'Jacobian of first-order minimal system and third-order accurate mean';
|
||||
end
|
||||
if ~no_identification_minimal
|
||||
if ~no_identification_minimal && ~(length(ide_minimal.minimal_state_space)==1 && ide_minimal.minimal_state_space==0)
|
||||
noidentification = 0; ide = ide_minimal;
|
||||
if SampleSize == 1
|
||||
Jacob = ide.dMINIMAL;
|
||||
|
|
@ -110,7 +110,7 @@ for jide = 1:4
|
|||
if options_ident.order > 1
|
||||
strTest = 'SPECTRUM (Mutschler, 2015)';
|
||||
end
|
||||
if ~no_identification_spectrum
|
||||
if ~no_identification_spectrum && ~isempty(fieldnames(ide_spectrum))
|
||||
noidentification = 0; ide = ide_spectrum;
|
||||
if SampleSize == 1
|
||||
Jacob = ide.dSPECTRUM;
|
||||
|
|
@ -123,7 +123,7 @@ for jide = 1:4
|
|||
if options_ident.order > 1
|
||||
strTest = 'MOMENTS (Mutschler, 2015)'; strJacobian = 'Mbar';
|
||||
end
|
||||
if ~no_identification_moments
|
||||
if ~no_identification_moments && ~isempty(fieldnames(ide_moments))
|
||||
noidentification = 0; ide = ide_moments;
|
||||
if SampleSize == 1
|
||||
Jacob = ide.si_dMOMENTS;
|
||||
|
|
@ -136,20 +136,39 @@ for jide = 1:4
|
|||
if ~noidentification
|
||||
%% display problematic parameters computed by identifcation_checks.m
|
||||
if ~checks_via_subsets
|
||||
if any(ide.ino) || any(any(ide.ind0==0)) || any(any(ide.jweak_pair))
|
||||
EffectiveSampleSize=SampleSize;
|
||||
non_minimal_state_space_error=0;
|
||||
if SampleSize>1 && jide==2 && any(~ide.minimal_state_space)
|
||||
EffectiveSampleSize=SampleSize-sum(~ide.minimal_state_space);
|
||||
non_minimal_state_space_error=1;
|
||||
ide.ino(~ide.minimal_state_space,:)=[];
|
||||
ide.ind0(~ide.minimal_state_space,:)=[];
|
||||
ide.jweak_pair(~ide.minimal_state_space,:)=[];
|
||||
ide.minimal_state_space(~ide.minimal_state_space,:)=[];
|
||||
end
|
||||
if any(ide.ino) || any(any(ide.ind0==0)) || any(any(ide.jweak_pair)) || non_minimal_state_space_error
|
||||
no_warning_message_display=0;
|
||||
skipline()
|
||||
disp([upper(strTest), ':'])
|
||||
disp(' !!!WARNING!!!');
|
||||
if SampleSize>1
|
||||
disp([' The rank of ', strJacobian, ' (', strMeaning, ') is deficient for ', num2str(length(find(ide.ino))),' out of ',int2str(SampleSize),' MC runs!' ]),
|
||||
if non_minimal_state_space_error
|
||||
fprintf(['\n The minimal state space could not be computed for %u out of %u cases.\n'],SampleSize-EffectiveSampleSize,SampleSize);
|
||||
end
|
||||
if jide==2
|
||||
if sum(ide.ino & ide.minimal_state_space)>0
|
||||
disp([' The rank of ', strJacobian, ' (', strMeaning, ') is deficient for ', num2str(sum(ide.ino & ide.minimal_state_space)),' out of ',int2str(EffectiveSampleSize),' effective MC runs!' ])
|
||||
end
|
||||
else
|
||||
disp([' The rank of ', strJacobian, ' (', strMeaning, ') is deficient for ', num2str(sum(ide.ino)),' out of ',int2str(EffectiveSampleSize),' effective MC runs!' ]),
|
||||
end
|
||||
else
|
||||
disp([' The rank of ', strJacobian, ' (', strMeaning, ') is deficient!']),
|
||||
end
|
||||
skipline()
|
||||
for j=1:totparam_nbr
|
||||
if any(ide.ind0(:,j)==0)
|
||||
pno = 100*length(find(ide.ind0(:,j)==0))/SampleSize;
|
||||
pno = 100*length(find(ide.ind0(:,j)==0))/EffectiveSampleSize;
|
||||
if SampleSize>1
|
||||
disp([' ',name{j},' is not identified for ',num2str(pno),'% of MC runs!' ])
|
||||
else
|
||||
|
|
@ -166,7 +185,7 @@ for jide = 1:4
|
|||
[jx,jy]=find(jmap_pair==j);
|
||||
jstore=[jstore jx(1) jy(1)];
|
||||
if SampleSize > 1
|
||||
disp([' [',name{jx(1)},',',name{jy(1)},'] are PAIRWISE collinear for ',num2str((iweak)/SampleSize*100),'% of MC runs!' ])
|
||||
disp([' [',name{jx(1)},',',name{jy(1)},'] are PAIRWISE collinear for ',num2str((iweak)/EffectiveSampleSize*100),'% of MC runs!' ])
|
||||
else
|
||||
disp([' [',name{jx(1)},',',name{jy(1)},'] are PAIRWISE collinear!' ])
|
||||
end
|
||||
|
|
@ -176,7 +195,7 @@ for jide = 1:4
|
|||
iweak = length(find(ide.jweak(:,j)));
|
||||
if iweak && ~ismember(j,jstore)
|
||||
if SampleSize>1
|
||||
disp([' ',name{j},' is collinear w.r.t. all other parameters for ',num2str(iweak/SampleSize*100),'% of MC runs!' ])
|
||||
disp([' ',name{j},' is collinear w.r.t. all other parameters for ',num2str(iweak/EffectiveSampleSize*100),'% of MC runs!' ])
|
||||
else
|
||||
disp([' ',name{j},' is collinear w.r.t. all other parameters!' ])
|
||||
end
|
||||
|
|
@ -241,7 +260,7 @@ end
|
|||
|
||||
|
||||
|
||||
%% Advanced identificaton patterns
|
||||
%% Advanced identification patterns
|
||||
if SampleSize==1 && options_ident.advanced
|
||||
skipline()
|
||||
for j=1:size(ide_moments.cosndMOMENTS,2)
|
||||
|
|
|
|||
|
|
@ -481,7 +481,7 @@ if iload <=0
|
|||
end
|
||||
options_ident.tittxt = parameters; %title text for graphs and figures
|
||||
% perform identification analysis for single point
|
||||
[ide_moments_point, ide_spectrum_point, ide_minimal_point, ide_hess_point, ide_reducedform_point, ide_dynamic_point, derivatives_info_point, info, options_ident] = ...
|
||||
[ide_moments_point, ide_spectrum_point, ide_minimal_point, ide_hess_point, ide_reducedform_point, ide_dynamic_point, derivatives_info_point, info] = ...
|
||||
identification_analysis(params, indpmodel, indpstderr, indpcorr, options_ident, dataset_info, prior_exist, 1); %the 1 at the end implies initialization of persistent variables
|
||||
if info(1)~=0
|
||||
% there are errors in the solution algorithm
|
||||
|
|
@ -498,7 +498,7 @@ if iload <=0
|
|||
params = prior_draw();
|
||||
options_ident.tittxt = 'Random_prior_params'; %title text for graphs and figures
|
||||
% perform identification analysis
|
||||
[ide_moments_point, ide_spectrum_point, ide_minimal_point, ide_hess_point, ide_reducedform_point, ide_dynamic_point, derivatives_info_point, info, options_ident] = ...
|
||||
[ide_moments_point, ide_spectrum_point, ide_minimal_point, ide_hess_point, ide_reducedform_point, ide_dynamic_point, derivatives_info_point, info] = ...
|
||||
identification_analysis(params, indpmodel, indpstderr, indpcorr, options_ident, dataset_info, prior_exist, 1);
|
||||
end
|
||||
end
|
||||
|
|
@ -552,7 +552,7 @@ if iload <=0
|
|||
end
|
||||
options_ident.tittxt = []; % clear title text for graphs and figures
|
||||
% run identification analysis
|
||||
[ide_moments, ide_spectrum, ide_minimal, ide_hess, ide_reducedform, ide_dynamic, ide_derivatives_info, info, options_MC] = ...
|
||||
[ide_moments, ide_spectrum, ide_minimal, ide_hess, ide_reducedform, ide_dynamic, ide_derivatives_info, info, error_indicator] = ...
|
||||
identification_analysis(params, indpmodel, indpstderr, indpcorr, options_MC, dataset_info, prior_exist, 0); % the 0 implies that we do not initialize persistent variables anymore
|
||||
|
||||
if iteration==0 && info(1)==0 % preallocate storage in the first admissable run
|
||||
|
|
@ -564,7 +564,7 @@ if iload <=0
|
|||
STO_si_dDYNAMIC = zeros([size(ide_dynamic.si_dDYNAMIC, 1), modparam_nbr, MAX_RUNS_BEFORE_SAVE_TO_FILE]);
|
||||
STO_DYNAMIC = zeros(size(ide_dynamic.DYNAMIC, 1), SampleSize);
|
||||
IDE_DYNAMIC.ind_dDYNAMIC = ide_dynamic.ind_dDYNAMIC;
|
||||
IDE_DYNAMIC.in0 = zeros(SampleSize, modparam_nbr);
|
||||
IDE_DYNAMIC.ino = zeros(SampleSize, modparam_nbr);
|
||||
IDE_DYNAMIC.ind0 = zeros(SampleSize, modparam_nbr);
|
||||
IDE_DYNAMIC.jweak = zeros(SampleSize, modparam_nbr);
|
||||
IDE_DYNAMIC.jweak_pair = zeros(SampleSize, modparam_nbr*(modparam_nbr+1)/2);
|
||||
|
|
@ -576,7 +576,7 @@ if iload <=0
|
|||
STO_si_dREDUCEDFORM = zeros([size(ide_reducedform.si_dREDUCEDFORM, 1), totparam_nbr, MAX_RUNS_BEFORE_SAVE_TO_FILE]);
|
||||
STO_REDUCEDFORM = zeros(size(ide_reducedform.REDUCEDFORM, 1), SampleSize);
|
||||
IDE_REDUCEDFORM.ind_dREDUCEDFORM = ide_reducedform.ind_dREDUCEDFORM;
|
||||
IDE_REDUCEDFORM.in0 = zeros(SampleSize, 1);
|
||||
IDE_REDUCEDFORM.ino = zeros(SampleSize, 1);
|
||||
IDE_REDUCEDFORM.ind0 = zeros(SampleSize, totparam_nbr);
|
||||
IDE_REDUCEDFORM.jweak = zeros(SampleSize, totparam_nbr);
|
||||
IDE_REDUCEDFORM.jweak_pair = zeros(SampleSize, totparam_nbr*(totparam_nbr+1)/2);
|
||||
|
|
@ -593,7 +593,7 @@ if iload <=0
|
|||
STO_si_dMOMENTS = zeros([size(ide_moments.si_dMOMENTS, 1), totparam_nbr, MAX_RUNS_BEFORE_SAVE_TO_FILE]);
|
||||
STO_MOMENTS = zeros(size(ide_moments.MOMENTS, 1), SampleSize);
|
||||
IDE_MOMENTS.ind_dMOMENTS = ide_moments.ind_dMOMENTS;
|
||||
IDE_MOMENTS.in0 = zeros(SampleSize, 1);
|
||||
IDE_MOMENTS.ino = zeros(SampleSize, 1);
|
||||
IDE_MOMENTS.ind0 = zeros(SampleSize, totparam_nbr);
|
||||
IDE_MOMENTS.jweak = zeros(SampleSize, totparam_nbr);
|
||||
IDE_MOMENTS.jweak_pair = zeros(SampleSize, totparam_nbr*(totparam_nbr+1)/2);
|
||||
|
|
@ -611,7 +611,7 @@ if iload <=0
|
|||
if ~options_MC.no_identification_spectrum
|
||||
STO_dSPECTRUM = zeros([size(ide_spectrum.dSPECTRUM, 1), size(ide_spectrum.dSPECTRUM, 2), MAX_RUNS_BEFORE_SAVE_TO_FILE]);
|
||||
IDE_SPECTRUM.ind_dSPECTRUM = ide_spectrum.ind_dSPECTRUM;
|
||||
IDE_SPECTRUM.in0 = zeros(SampleSize, 1);
|
||||
IDE_SPECTRUM.ino = zeros(SampleSize, 1);
|
||||
IDE_SPECTRUM.ind0 = zeros(SampleSize, totparam_nbr);
|
||||
IDE_SPECTRUM.jweak = zeros(SampleSize, totparam_nbr);
|
||||
IDE_SPECTRUM.jweak_pair = zeros(SampleSize, totparam_nbr*(totparam_nbr+1)/2);
|
||||
|
|
@ -626,12 +626,13 @@ if iload <=0
|
|||
if ~options_MC.no_identification_minimal
|
||||
STO_dMINIMAL = zeros([size(ide_minimal.dMINIMAL, 1), size(ide_minimal.dMINIMAL, 2), MAX_RUNS_BEFORE_SAVE_TO_FILE]);
|
||||
IDE_MINIMAL.ind_dMINIMAL = ide_minimal.ind_dMINIMAL;
|
||||
IDE_MINIMAL.in0 = zeros(SampleSize, 1);
|
||||
IDE_MINIMAL.ino = zeros(SampleSize, 1);
|
||||
IDE_MINIMAL.ind0 = zeros(SampleSize, totparam_nbr);
|
||||
IDE_MINIMAL.jweak = zeros(SampleSize, totparam_nbr);
|
||||
IDE_MINIMAL.jweak_pair = zeros(SampleSize, totparam_nbr*(totparam_nbr+1)/2);
|
||||
IDE_MINIMAL.cond = zeros(SampleSize, 1);
|
||||
IDE_MINIMAL.Mco = zeros(SampleSize, totparam_nbr);
|
||||
IDE_MINIMAL.minimal_state_space = zeros(SampleSize, 1);
|
||||
else
|
||||
STO_dMINIMAL = {};
|
||||
IDE_MINIMAL = {};
|
||||
|
|
@ -654,7 +655,7 @@ if iload <=0
|
|||
IDE_DYNAMIC.Mco(iteration,:) = ide_dynamic.Mco;
|
||||
|
||||
% store results for reduced form
|
||||
if ~options_MC.no_identification_reducedform
|
||||
if ~options_MC.no_identification_reducedform && ~error_indicator.identification_reducedform
|
||||
STO_REDUCEDFORM(:,iteration) = ide_reducedform.REDUCEDFORM;
|
||||
STO_si_dREDUCEDFORM(:,:,run_index) = ide_reducedform.si_dREDUCEDFORM;
|
||||
IDE_REDUCEDFORM.cond(iteration,1) = ide_reducedform.cond;
|
||||
|
|
@ -666,7 +667,7 @@ if iload <=0
|
|||
end
|
||||
|
||||
% store results for moments
|
||||
if ~options_MC.no_identification_moments
|
||||
if ~options_MC.no_identification_moments && ~error_indicator.identification_moments
|
||||
STO_MOMENTS(:,iteration) = ide_moments.MOMENTS;
|
||||
STO_si_dMOMENTS(:,:,run_index) = ide_moments.si_dMOMENTS;
|
||||
IDE_MOMENTS.cond(iteration,1) = ide_moments.cond;
|
||||
|
|
@ -680,7 +681,7 @@ if iload <=0
|
|||
end
|
||||
|
||||
% store results for spectrum
|
||||
if ~options_MC.no_identification_spectrum
|
||||
if ~options_MC.no_identification_spectrum && ~error_indicator.identification_spectrum
|
||||
STO_dSPECTRUM(:,:,run_index) = ide_spectrum.dSPECTRUM;
|
||||
IDE_SPECTRUM.cond(iteration,1) = ide_spectrum.cond;
|
||||
IDE_SPECTRUM.ino(iteration,1) = ide_spectrum.ino;
|
||||
|
|
@ -691,14 +692,19 @@ if iload <=0
|
|||
end
|
||||
|
||||
% store results for minimal system
|
||||
if ~options_MC.no_identification_minimal
|
||||
STO_dMINIMAL(:,:,run_index) = ide_minimal.dMINIMAL;
|
||||
IDE_MINIMAL.cond(iteration,1) = ide_minimal.cond;
|
||||
IDE_MINIMAL.ino(iteration,1) = ide_minimal.ino;
|
||||
IDE_MINIMAL.ind0(iteration,:) = ide_minimal.ind0;
|
||||
IDE_MINIMAL.jweak(iteration,:) = ide_minimal.jweak;
|
||||
IDE_MINIMAL.jweak_pair(iteration,:) = ide_minimal.jweak_pair;
|
||||
IDE_MINIMAL.Mco(iteration,:) = ide_minimal.Mco;
|
||||
if ~options_MC.no_identification_minimal
|
||||
if ~error_indicator.identification_minimal
|
||||
STO_dMINIMAL(:,:,run_index) = ide_minimal.dMINIMAL;
|
||||
IDE_MINIMAL.cond(iteration,1) = ide_minimal.cond;
|
||||
IDE_MINIMAL.ino(iteration,1) = ide_minimal.ino;
|
||||
IDE_MINIMAL.ind0(iteration,:) = ide_minimal.ind0;
|
||||
IDE_MINIMAL.jweak(iteration,:) = ide_minimal.jweak;
|
||||
IDE_MINIMAL.jweak_pair(iteration,:) = ide_minimal.jweak_pair;
|
||||
IDE_MINIMAL.Mco(iteration,:) = ide_minimal.Mco;
|
||||
IDE_MINIMAL.minimal_state_space(iteration,:) = ide_minimal.minimal_state_space;
|
||||
else
|
||||
IDE_MINIMAL.minimal_state_space(iteration,:) = ide_minimal.minimal_state_space;
|
||||
end
|
||||
end
|
||||
|
||||
% save results to file: either to avoid running into memory issues, i.e. (run_index==MAX_RUNS_BEFORE_SAVE_TO_FILE) or if finished (iteration==SampleSize)
|
||||
|
|
@ -900,7 +906,7 @@ if SampleSize > 1
|
|||
fprintf('\nTesting %s.\n',tittxt);
|
||||
if ~iload
|
||||
options_ident.tittxt = tittxt; %title text for graphs and figures
|
||||
[ide_moments_max, ide_spectrum_max, ide_minimal_max, ide_hess_max, ide_reducedform_max, ide_dynamic_max, derivatives_info_max, info_max, options_ident] = ...
|
||||
[ide_moments_max, ide_spectrum_max, ide_minimal_max, ide_hess_max, ide_reducedform_max, ide_dynamic_max, derivatives_info_max, info_max] = ...
|
||||
identification_analysis(pdraws(jmax,:), indpmodel, indpstderr, indpcorr, options_ident, dataset_info, prior_exist, 1); %the 1 at the end initializes some persistent variables
|
||||
save([IdentifDirectoryName '/' fname '_identif.mat'], 'ide_hess_max', 'ide_moments_max', 'ide_spectrum_max', 'ide_minimal_max','ide_reducedform_max', 'ide_dynamic_max', 'jmax', '-append');
|
||||
end
|
||||
|
|
@ -918,7 +924,7 @@ if SampleSize > 1
|
|||
fprintf('Testing %s.\n',tittxt);
|
||||
if ~iload
|
||||
options_ident.tittxt = tittxt; %title text for graphs and figures
|
||||
[ide_moments_min, ide_spectrum_min, ide_minimal_min, ide_hess_min, ide_reducedform_min, ide_dynamic_min, derivatives_info_min, info_min, options_ident] = ...
|
||||
[ide_moments_min, ide_spectrum_min, ide_minimal_min, ide_hess_min, ide_reducedform_min, ide_dynamic_min, derivatives_info_min, info_min] = ...
|
||||
identification_analysis(pdraws(jmin,:), indpmodel, indpstderr, indpcorr, options_ident, dataset_info, prior_exist, 1); %the 1 at the end initializes persistent variables
|
||||
save([IdentifDirectoryName '/' fname '_identif.mat'], 'ide_hess_min', 'ide_moments_min','ide_spectrum_min','ide_minimal_min','ide_reducedform_min', 'ide_dynamic_min', 'jmin', '-append');
|
||||
end
|
||||
|
|
@ -940,7 +946,7 @@ if SampleSize > 1
|
|||
fprintf('\nTesting %s.\n',tittxt);
|
||||
if ~iload
|
||||
options_ident.tittxt = tittxt; %title text for graphs and figures
|
||||
[ide_moments_(j), ide_spectrum_(j), ide_minimal_(j), ide_hess_(j), ide_reducedform_(j), ide_dynamic_(j), derivatives_info_(j), info_resolve, options_ident] = ...
|
||||
[ide_moments_(j), ide_spectrum_(j), ide_minimal_(j), ide_hess_(j), ide_reducedform_(j), ide_dynamic_(j), derivatives_info_(j), info_resolve] = ...
|
||||
identification_analysis(pdraws(jcrit(j),:), indpmodel, indpstderr, indpcorr, options_ident, dataset_info, prior_exist, 1);
|
||||
end
|
||||
advanced0 = options_ident.advanced; options_ident.advanced = 1; %make sure advanced setting is on
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
function [ide_moments, ide_spectrum, ide_minimal, ide_hess, ide_reducedform, ide_dynamic, derivatives_info, info, options_ident] = identification_analysis(params, indpmodel, indpstderr, indpcorr, options_ident, dataset_info, prior_exist, init)
|
||||
% [ide_moments, ide_spectrum, ide_minimal, ide_hess, ide_reducedform, ide_dynamic, derivatives_info, info, options_ident] = identification_analysis(params, indpmodel, indpstderr, indpcorr, options_ident, dataset_info, prior_exist, init)
|
||||
function [ide_moments, ide_spectrum, ide_minimal, ide_hess, ide_reducedform, ide_dynamic, derivatives_info, info, error_indicator] = identification_analysis(params, indpmodel, indpstderr, indpcorr, options_ident, dataset_info, prior_exist, init)
|
||||
% [ide_moments, ide_spectrum, ide_minimal, ide_hess, ide_reducedform, ide_dynamic, derivatives_info, info, error_indicator] = identification_analysis(params, indpmodel, indpstderr, indpcorr, options_ident, dataset_info, prior_exist, init)
|
||||
% -------------------------------------------------------------------------
|
||||
% This function wraps all identification analysis, i.e. it
|
||||
% (1) wraps functions for the theoretical identification analysis based on moments (Iskrev, 2010),
|
||||
|
|
@ -47,8 +47,8 @@ function [ide_moments, ide_spectrum, ide_minimal, ide_hess, ide_reducedform, ide
|
|||
% info about first-order perturbation derivatives, used in dsge_likelihood.m
|
||||
% * info [integer]
|
||||
% output from dynare_resolve
|
||||
% * options_ident [structure]
|
||||
% updated identification options
|
||||
% * error_indicator [structure]
|
||||
% indicator on problems
|
||||
% -------------------------------------------------------------------------
|
||||
% This function is called by
|
||||
% * dynare_identification.m
|
||||
|
|
@ -71,7 +71,7 @@ function [ide_moments, ide_spectrum, ide_minimal, ide_hess, ide_reducedform, ide
|
|||
% * stoch_simul
|
||||
% * vec
|
||||
% =========================================================================
|
||||
% Copyright (C) 2008-2020 Dynare Team
|
||||
% Copyright (C) 2008-2021 Dynare Team
|
||||
%
|
||||
% This file is part of Dynare.
|
||||
%
|
||||
|
|
@ -115,7 +115,6 @@ if ~isempty(estim_params_)
|
|||
end
|
||||
|
||||
%get options (see dynare_identification.m for description of options)
|
||||
order = options_ident.order;
|
||||
nlags = options_ident.ar;
|
||||
advanced = options_ident.advanced;
|
||||
replic = options_ident.replic;
|
||||
|
|
@ -126,11 +125,11 @@ checks_via_subsets = options_ident.checks_via_subsets;
|
|||
tol_deriv = options_ident.tol_deriv;
|
||||
tol_rank = options_ident.tol_rank;
|
||||
tol_sv = options_ident.tol_sv;
|
||||
no_identification_strength = options_ident.no_identification_strength;
|
||||
no_identification_reducedform = options_ident.no_identification_reducedform;
|
||||
no_identification_moments = options_ident.no_identification_moments;
|
||||
no_identification_minimal = options_ident.no_identification_minimal;
|
||||
no_identification_spectrum = options_ident.no_identification_spectrum;
|
||||
error_indicator.identification_strength=0;
|
||||
error_indicator.identification_reducedform=0;
|
||||
error_indicator.identification_moments=0;
|
||||
error_indicator.identification_minimal=0;
|
||||
error_indicator.identification_spectrum=0;
|
||||
|
||||
%Compute linear approximation and fill dr structure
|
||||
[oo_.dr,info,M_,oo_] = compute_decision_rules(M_,options_,oo_);
|
||||
|
|
@ -140,71 +139,71 @@ if info(1) == 0 %no errors in solution
|
|||
[MEAN, dMEAN, REDUCEDFORM, dREDUCEDFORM, DYNAMIC, dDYNAMIC, MOMENTS, dMOMENTS, dSPECTRUM, dSPECTRUM_NO_MEAN, dMINIMAL, derivatives_info] = get_identification_jacobians(estim_params_, M_, oo_, options_, options_ident, indpmodel, indpstderr, indpcorr, indvobs);
|
||||
if isempty(dMINIMAL)
|
||||
% Komunjer and Ng is not computed if (1) minimality conditions are not fullfilled or (2) there are more shocks and measurement errors than observables, so we need to reset options
|
||||
no_identification_minimal = 1;
|
||||
options_ident.no_identification_minimal = 1;
|
||||
error_indicator.identification_minimal = 1;
|
||||
%options_ident.no_identification_minimal = 1;
|
||||
end
|
||||
|
||||
if init
|
||||
%check stationarity
|
||||
if ~no_identification_moments
|
||||
if ~options_ident.no_identification_moments
|
||||
if any(any(isnan(MOMENTS)))
|
||||
if options_.diffuse_filter == 1 % use options_ as it inherits diffuse_filter from options_ident if set by user
|
||||
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].')
|
||||
else
|
||||
error('There are NaN''s in the theoretical moments. Please check whether your model has units roots, and you forgot to set diffuse_filter=1.' )
|
||||
end
|
||||
error_indicator.identification_moments=1;
|
||||
end
|
||||
ind_dMOMENTS = (find(max(abs(dMOMENTS'),[],1) > tol_deriv)); %index for non-zero rows
|
||||
if isempty(ind_dMOMENTS) && any(any(isnan(dMOMENTS)))
|
||||
error('There are NaN in the dMOMENTS matrix.' )
|
||||
end
|
||||
|
||||
error('There are NaN in the dMOMENTS matrix.')
|
||||
error_indicator.identification_moments=1;
|
||||
end
|
||||
end
|
||||
if ~no_identification_spectrum
|
||||
if ~options_ident.no_identification_spectrum
|
||||
ind_dSPECTRUM = (find(max(abs(dSPECTRUM'),[],1) > tol_deriv)); %index for non-zero rows
|
||||
if any(any(isnan(dSPECTRUM)))
|
||||
warning_SPECTRUM = 'WARNING: There are NaN in the dSPECTRUM matrix. Note that identification based on spectrum does not support non-stationary models (yet).\n';
|
||||
warning_SPECTRUM = [warning_SPECTRUM ' Skip identification analysis based on spectrum.\n'];
|
||||
fprintf(warning_SPECTRUM);
|
||||
%reset options to neither display nor plot dSPECTRUM anymore
|
||||
no_identification_spectrum = 1;
|
||||
options_ident.no_identification_spectrum = 1;
|
||||
%set indicator to neither display nor plot dSPECTRUM anymore
|
||||
error_indicator.identification_spectrum = 1;
|
||||
end
|
||||
end
|
||||
if ~no_identification_minimal
|
||||
if ~options_ident.no_identification_minimal
|
||||
ind_dMINIMAL = (find(max(abs(dMINIMAL'),[],1) > tol_deriv)); %index for non-zero rows
|
||||
if any(any(isnan(dMINIMAL)))
|
||||
warning_MINIMAL = 'WARNING: There are NaN in the dMINIMAL matrix. Note that identification based on minimal system does not support non-stationary models (yet).\n';
|
||||
warning_MINIMAL = [warning_MINIMAL ' Skip identification analysis based on minimal system.\n'];
|
||||
fprintf(warning_MINIMAL);
|
||||
%reset options to neither display nor plot dMINIMAL anymore
|
||||
no_identification_minimal = 1;
|
||||
options_ident.no_identification_minimal = 1;
|
||||
%set indicator to neither display nor plot dMINIMAL anymore
|
||||
error_indicator.identification_minimal = 1;
|
||||
end
|
||||
end
|
||||
if no_identification_moments && no_identification_minimal && no_identification_spectrum
|
||||
%The following cannot be reached yet due to erroring out when
|
||||
%error_indicator.identification_moments is triggered
|
||||
if error_indicator.identification_moments && error_indicator.identification_minimal && error_indicator.identification_spectrum
|
||||
%display error if all three criteria fail
|
||||
error(sprintf('identification_analyis: Stationarity condition(s) failed and/or diffuse_filter option missing.\nMake sure that for non-stationary models stationary transformations of non-stationary observables are used for checking identification.\n[TIP: use first differences].'));
|
||||
end
|
||||
|
||||
% Check order conditions
|
||||
if ~no_identification_moments
|
||||
if ~options_ident.no_identification_moments && ~error_indicator.identification_moments
|
||||
%check order condition of Iskrev (2010)
|
||||
while length(ind_dMOMENTS) < totparam_nbr && nlags < 10
|
||||
%Try to add lags to autocovariogram if order condition fails
|
||||
disp('The number of moments with non-zero derivative is smaller than the number of parameters')
|
||||
disp(['Try increasing ar = ', int2str(nlags+1)])
|
||||
nlags = nlags + 1;
|
||||
options_ident.no_identification_minimal = 1; %do not recompute dMINIMAL
|
||||
options_ident.no_identification_spectrum = 1; %do not recompute dSPECTRUM
|
||||
options_ident.ar = nlags; %store new lag number
|
||||
options_.ar = nlags; %store new lag number
|
||||
[~, ~, ~, ~, ~, ~, MOMENTS, dMOMENTS, ~, ~, ~, ~] = get_identification_jacobians(estim_params_, M_, oo_, options_, options_ident, indpmodel, indpstderr, indpcorr, indvobs);
|
||||
options_ident_local=options_ident;
|
||||
options_ident_local.no_identification_minimal = 1; %do not recompute dMINIMAL
|
||||
options_ident_local.no_identification_spectrum = 1; %do not recompute dSPECTRUM
|
||||
options_ident_local.ar = nlags; %store new lag number
|
||||
options_.ar = nlags; %store new lag number
|
||||
[~, ~, ~, ~, ~, ~, MOMENTS, dMOMENTS, ~, ~, ~, ~] = get_identification_jacobians(estim_params_, M_, oo_, options_, options_ident_local, indpmodel, indpstderr, indpcorr, indvobs);
|
||||
|
||||
ind_dMOMENTS = (find(max(abs(dMOMENTS'),[],1) > tol_deriv)); %new index with non-zero rows
|
||||
end
|
||||
options_ident.no_identification_minimal = no_identification_minimal; % reset option to original setting
|
||||
options_ident.no_identification_spectrum = no_identification_spectrum; % reset option to original setting
|
||||
if length(ind_dMOMENTS) < totparam_nbr
|
||||
warning_MOMENTS = 'WARNING: Order condition for dMOMENTS failed: There are not enough moments and too many parameters.\n';
|
||||
warning_MOMENTS = [warning_MOMENTS ' The number of moments with non-zero derivative is smaller than the number of parameters up to 10 lags.\n'];
|
||||
|
|
@ -212,31 +211,30 @@ if info(1) == 0 %no errors in solution
|
|||
warning_MOMENTS = [warning_MOMENTS ' Skip identification analysis based on moments.\n'];
|
||||
warning_MOMENTS = [warning_MOMENTS ' Skip identification strenght analysis.\n'];
|
||||
fprintf(warning_MOMENTS);
|
||||
%reset options to neither display nor plot dMOMENTS anymore
|
||||
no_identification_moments = 1;
|
||||
options_ident.no_identification_moments = 1;
|
||||
no_identification_strength = 1;
|
||||
options_ident.no_identification_strength = 1;
|
||||
%set indicator to neither display nor plot dMOMENTS anymore
|
||||
error_indicator.identification_moments = 1;
|
||||
%options_ident.no_identification_moments = 1;
|
||||
error_indicator.identification_strength = 1;
|
||||
%options_ident.no_identification_strength = 1;
|
||||
end
|
||||
end
|
||||
if ~no_identification_minimal
|
||||
if ~options_ident.no_identification_minimal && ~error_indicator.identification_minimal
|
||||
if length(ind_dMINIMAL) < size(dMINIMAL,2)
|
||||
warning_MINIMAL = 'WARNING: Order condition for dMINIMAL failed: There are too many parameters or too few observable variables.\n';
|
||||
warning_MINIMAL = [warning_MINIMAL ' The number of minimal system elements with non-zero derivative is smaller than the number of parameters.\n'];
|
||||
warning_MINIMAL = [warning_MINIMAL ' Either reduce the list of parameters, or increase number of observables.\n'];
|
||||
warning_MINIMAL = [warning_MINIMAL ' Skip identification analysis based on minimal state space system.\n'];
|
||||
fprintf(warning_MINIMAL);
|
||||
%resest options to neither display nor plot dMINIMAL anymore
|
||||
no_identification_minimal = 1;
|
||||
options_ident.no_identification_minimal = 1;
|
||||
%set indicator to neither display nor plot dMINIMAL anymore
|
||||
error_indicator.identification_minimal = 1;
|
||||
end
|
||||
end
|
||||
%Note that there is no order condition for dSPECTRUM, as the matrix is always of dimension totparam_nbr by totparam_nbr
|
||||
if no_identification_moments && no_identification_minimal && no_identification_spectrum
|
||||
if error_indicator.identification_moments && error_indicator.identification_minimal && error_indicator.identification_spectrum
|
||||
%error if all three criteria fail
|
||||
error('identification_analyis: Order condition(s) failed');
|
||||
end
|
||||
if ~no_identification_reducedform
|
||||
if ~options_ident.no_identification_reducedform && ~error_indicator.identification_reducedform
|
||||
ind_dREDUCEDFORM = (find(max(abs(dREDUCEDFORM'),[],1) > tol_deriv)); %index with non-zero rows
|
||||
end
|
||||
ind_dDYNAMIC = (find(max(abs(dDYNAMIC'),[],1) > tol_deriv)); %index with non-zero rows
|
||||
|
|
@ -244,16 +242,16 @@ if info(1) == 0 %no errors in solution
|
|||
|
||||
DYNAMIC = DYNAMIC(ind_dDYNAMIC); %focus only on non-zero entries
|
||||
si_dDYNAMIC = (dDYNAMIC(ind_dDYNAMIC,:)); %focus only on non-zero rows
|
||||
if ~no_identification_reducedform
|
||||
if ~options_ident.no_identification_reducedform && ~error_indicator.identification_reducedform
|
||||
REDUCEDFORM = REDUCEDFORM(ind_dREDUCEDFORM); %focus only on non-zero entries
|
||||
si_dREDUCEDFORM = (dREDUCEDFORM(ind_dREDUCEDFORM,:)); %focus only on non-zero rows
|
||||
end
|
||||
|
||||
if ~no_identification_moments
|
||||
if ~options_ident.no_identification_moments && ~error_indicator.identification_moments
|
||||
MOMENTS = MOMENTS(ind_dMOMENTS); %focus only on non-zero entries
|
||||
si_dMOMENTS = (dMOMENTS(ind_dMOMENTS,:)); %focus only on non-zero derivatives
|
||||
%% MOMENTS IDENTIFICATION STRENGTH ANALYSIS
|
||||
if ~no_identification_strength && init %only for initialization of persistent vars
|
||||
%% MOMENTS IDENTIFICATION STRENGTH ANALYSIS
|
||||
if ~options_ident.no_identification_strength && ~error_indicator.identification_strength && init %only for initialization of persistent vars
|
||||
ide_strength_dMOMENTS = NaN(1,totparam_nbr); %initialize
|
||||
ide_strength_dMOMENTS_prior = NaN(1,totparam_nbr); %initialize
|
||||
ide_uncert_unnormaliz = NaN(1,totparam_nbr); %initialize
|
||||
|
|
@ -438,7 +436,7 @@ if info(1) == 0 %no errors in solution
|
|||
ide_dynamic.dDYNAMIC = dDYNAMIC;
|
||||
ide_dynamic.DYNAMIC = DYNAMIC;
|
||||
|
||||
if ~no_identification_reducedform
|
||||
if ~options_ident.no_identification_reducedform && ~error_indicator.identification_reducedform
|
||||
if normalize_jacobians
|
||||
norm_dREDUCEDFORM = max(abs(si_dREDUCEDFORM),[],2);
|
||||
norm_dREDUCEDFORM = norm_dREDUCEDFORM(:,ones(totparam_nbr,1));
|
||||
|
|
@ -453,7 +451,7 @@ if info(1) == 0 %no errors in solution
|
|||
ide_reducedform.REDUCEDFORM = REDUCEDFORM;
|
||||
end
|
||||
|
||||
if ~no_identification_moments
|
||||
if ~options_ident.no_identification_moments && ~error_indicator.identification_moments
|
||||
if normalize_jacobians
|
||||
norm_dMOMENTS = max(abs(si_dMOMENTS),[],2);
|
||||
norm_dMOMENTS = norm_dMOMENTS(:,ones(totparam_nbr,1));
|
||||
|
|
@ -469,7 +467,7 @@ if info(1) == 0 %no errors in solution
|
|||
|
||||
if advanced
|
||||
% here we do not normalize (i.e. we set norm_dMOMENTS=1) as the OLS in ident_bruteforce is very sensitive to norm_dMOMENTS
|
||||
[ide_moments.pars, ide_moments.cosndMOMENTS] = ident_bruteforce(dMOMENTS(ind_dMOMENTS,:), max_dim_cova_group, options_.TeX, options_ident.name_tex, options_ident.tittxt, options_ident.tol_deriv);
|
||||
[ide_moments.pars, ide_moments.cosndMOMENTS] = ident_bruteforce(dMOMENTS(ind_dMOMENTS,:), max_dim_cova_group, options_.TeX, options_ident.name_tex, options_ident.tittxt, tol_deriv);
|
||||
end
|
||||
|
||||
%here we focus on the unnormalized S and V, which is then used in plot_identification.m and for prior_mc > 1
|
||||
|
|
@ -485,7 +483,7 @@ if info(1) == 0 %no errors in solution
|
|||
end
|
||||
end
|
||||
|
||||
if ~no_identification_minimal
|
||||
if ~options_ident.no_identification_minimal && ~error_indicator.identification_minimal
|
||||
if normalize_jacobians
|
||||
ind_dMINIMAL = (find(max(abs(dMINIMAL'),[],1) > tol_deriv)); %index for non-zero rows
|
||||
norm_dMINIMAL = max(abs(dMINIMAL(ind_dMINIMAL,:)),[],2);
|
||||
|
|
@ -499,7 +497,7 @@ if info(1) == 0 %no errors in solution
|
|||
ide_minimal.dMINIMAL = dMINIMAL;
|
||||
end
|
||||
|
||||
if ~no_identification_spectrum
|
||||
if ~options_ident.no_identification_spectrum && ~error_indicator.identification_spectrum
|
||||
if normalize_jacobians
|
||||
ind_dSPECTRUM = (find(max(abs(dSPECTRUM'),[],1) > tol_deriv)); %index for non-zero rows
|
||||
tilda_dSPECTRUM = zeros(size(dSPECTRUM));
|
||||
|
|
@ -523,23 +521,33 @@ if info(1) == 0 %no errors in solution
|
|||
if checks_via_subsets
|
||||
% identification_checks_via_subsets is only for debugging
|
||||
[ide_dynamic, ide_reducedform, ide_moments, ide_spectrum, ide_minimal] = ...
|
||||
identification_checks_via_subsets(ide_dynamic, ide_reducedform, ide_moments, ide_spectrum, ide_minimal, totparam_nbr, modparam_nbr, options_ident);
|
||||
identification_checks_via_subsets(ide_dynamic, ide_reducedform, ide_moments, ide_spectrum, ide_minimal, totparam_nbr, modparam_nbr, options_ident, error_indicator);
|
||||
if ~error_indicator.identification_minimal
|
||||
ide_minimal.minimal_state_space=1;
|
||||
else
|
||||
ide_minimal.minimal_state_space=0;
|
||||
end
|
||||
else
|
||||
[ide_dynamic.cond, ide_dynamic.rank, ide_dynamic.ind0, ide_dynamic.indno, ide_dynamic.ino, ide_dynamic.Mco, ide_dynamic.Pco, ide_dynamic.jweak, ide_dynamic.jweak_pair] = ...
|
||||
identification_checks(dDYNAMIC(ind_dDYNAMIC,:)./norm_dDYNAMIC, 1, tol_rank, tol_sv, modparam_nbr);
|
||||
if ~no_identification_reducedform
|
||||
if ~options_ident.no_identification_reducedform && ~error_indicator.identification_reducedform
|
||||
[ide_reducedform.cond, ide_reducedform.rank, ide_reducedform.ind0, ide_reducedform.indno, ide_reducedform.ino, ide_reducedform.Mco, ide_reducedform.Pco, ide_reducedform.jweak, ide_reducedform.jweak_pair] = ...
|
||||
identification_checks(dREDUCEDFORM(ind_dREDUCEDFORM,:)./norm_dREDUCEDFORM, 1, tol_rank, tol_sv, totparam_nbr);
|
||||
end
|
||||
if ~no_identification_moments
|
||||
if ~options_ident.no_identification_moments && ~error_indicator.identification_moments
|
||||
[ide_moments.cond, ide_moments.rank, ide_moments.ind0, ide_moments.indno, ide_moments.ino, ide_moments.Mco, ide_moments.Pco, ide_moments.jweak, ide_moments.jweak_pair] = ...
|
||||
identification_checks(dMOMENTS(ind_dMOMENTS,:)./norm_dMOMENTS, 1, tol_rank, tol_sv, totparam_nbr);
|
||||
end
|
||||
if ~no_identification_minimal
|
||||
[ide_minimal.cond, ide_minimal.rank, ide_minimal.ind0, ide_minimal.indno, ide_minimal.ino, ide_minimal.Mco, ide_minimal.Pco, ide_minimal.jweak, ide_minimal.jweak_pair] = ...
|
||||
identification_checks(dMINIMAL(ind_dMINIMAL,:)./norm_dMINIMAL, 2, tol_rank, tol_sv, totparam_nbr);
|
||||
if ~options_ident.no_identification_minimal
|
||||
if ~error_indicator.identification_minimal
|
||||
[ide_minimal.cond, ide_minimal.rank, ide_minimal.ind0, ide_minimal.indno, ide_minimal.ino, ide_minimal.Mco, ide_minimal.Pco, ide_minimal.jweak, ide_minimal.jweak_pair] = ...
|
||||
identification_checks(dMINIMAL(ind_dMINIMAL,:)./norm_dMINIMAL, 2, tol_rank, tol_sv, totparam_nbr);
|
||||
ide_minimal.minimal_state_space=1;
|
||||
else
|
||||
ide_minimal.minimal_state_space=0;
|
||||
end
|
||||
end
|
||||
if ~no_identification_spectrum
|
||||
if ~options_ident.no_identification_spectrum && ~error_indicator.identification_spectrum
|
||||
[ide_spectrum.cond, ide_spectrum.rank, ide_spectrum.ind0, ide_spectrum.indno, ide_spectrum.ino, ide_spectrum.Mco, ide_spectrum.Pco, ide_spectrum.jweak, ide_spectrum.jweak_pair] = ...
|
||||
identification_checks(tilda_dSPECTRUM, 3, tol_rank, tol_sv, totparam_nbr);
|
||||
end
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
function [ide_dynamic, ide_reducedform, ide_moments, ide_spectrum, ide_minimal] = identification_checks_via_subsets(ide_dynamic, ide_reducedform, ide_moments, ide_spectrum, ide_minimal, totparam_nbr, modparam_nbr, options_ident)
|
||||
%[ide_dynamic, ide_reducedform, ide_moments, ide_spectrum, ide_minimal] = identification_checks_via_subsets(ide_dynamic, ide_reducedform, ide_moments, ide_spectrum, ide_minimal, totparam_nbr, modparam_nbr, options_ident)
|
||||
function [ide_dynamic, ide_reducedform, ide_moments, ide_spectrum, ide_minimal] = identification_checks_via_subsets(ide_dynamic, ide_reducedform, ide_moments, ide_spectrum, ide_minimal, totparam_nbr, modparam_nbr, options_ident,error_indicator)
|
||||
%[ide_dynamic, ide_reducedform, ide_moments, ide_spectrum, ide_minimal] = identification_checks_via_subsets(ide_dynamic, ide_reducedform, ide_moments, ide_spectrum, ide_minimal, totparam_nbr, modparam_nbr, options_ident,error_indicator)
|
||||
% -------------------------------------------------------------------------
|
||||
% Finds problematic sets of paramters via checking the necessary rank condition
|
||||
% of the Jacobians for all possible combinations of parameters. The rank is
|
||||
|
|
@ -23,22 +23,23 @@ function [ide_dynamic, ide_reducedform, ide_moments, ide_spectrum, ide_minimal]
|
|||
% INPUTS
|
||||
% ide_reducedform: [structure] Containing results from identification
|
||||
% analysis based on the reduced-form solution (Ratto
|
||||
% and Iskrev, 2011). If ide_reducedform.no_identification_reducedform
|
||||
% is 1 then the search for problematic parameter sets will be skipped
|
||||
% and Iskrev, 2011). If either options_ident.no_identification_reducedform
|
||||
% or error_indicator.identification_reducedform are 1 then the search for problematic parameter sets will be skipped
|
||||
% ide_moments: [structure] Containing results from identification
|
||||
% analysis based on moments (Iskrev, 2010). If
|
||||
% ide_moments.no_identification_moments is 1 then the search for
|
||||
% analysis based on moments (Iskrev, 2010). If either
|
||||
% options_ident.no_identification_moments or error_indicator.identification_moments are 1 then the search for
|
||||
% problematic parameter sets will be skipped
|
||||
% ide_spectrum: [structure] Containing results from identification
|
||||
% analysis based on the spectrum (Qu and Tkachenko, 2012).
|
||||
% If ide_spectrum.no_identification_spectrum is 1 then the search for
|
||||
% If either options_ident.no_identification_spectrum or error_indicator.identification_spectrum are 1 then the search for
|
||||
% problematic parameter sets will be skipped
|
||||
% ide_minimal: [structure] Containing results from identification
|
||||
% analysis based on the minimal state space system
|
||||
% (Komunjer and Ng, 2011). If ide_minimal.no_identification_minimal
|
||||
% is 1 then the search for problematic parameter sets will be skipped
|
||||
% (Komunjer and Ng, 2011). If either options_ident.no_identification_minimal or
|
||||
% error_indicator.identification_minimal are 1 then the search for problematic parameter sets will be skipped
|
||||
% totparam_nbr: [integer] number of estimated stderr, corr and model parameters
|
||||
% numzerotolrank: [double] tolerance level for rank compuations
|
||||
% error_indicator [structure] indicators whether objects could be computed
|
||||
% -------------------------------------------------------------------------
|
||||
% OUTPUTS
|
||||
% ide_reducedform, ide_moments, ide_spectrum, ide_minimal are augmented by the
|
||||
|
|
@ -51,7 +52,7 @@ function [ide_dynamic, ide_reducedform, ide_moments, ide_spectrum, ide_minimal]
|
|||
% This function is called by
|
||||
% * identification_analysis.m
|
||||
% =========================================================================
|
||||
% Copyright (C) 2019 Dynare Team
|
||||
% Copyright (C) 2019-2021 Dynare Team
|
||||
%
|
||||
% This file is part of Dynare.
|
||||
%
|
||||
|
|
@ -113,7 +114,7 @@ else
|
|||
end
|
||||
|
||||
% initialize for reduced form solution criteria
|
||||
if ~no_identification_reducedform
|
||||
if ~no_identification_reducedform && ~error_indicator.identification_reducedform
|
||||
dREDUCEDFORM = ide_reducedform.dREDUCEDFORM;
|
||||
dREDUCEDFORM(ide_reducedform.ind_dREDUCEDFORM,:) = dREDUCEDFORM(ide_reducedform.ind_dREDUCEDFORM,:)./ide_reducedform.norm_dREDUCEDFORM; %normalize
|
||||
if strcmp(tol_rank,'robust')
|
||||
|
|
@ -136,7 +137,7 @@ else
|
|||
end
|
||||
|
||||
% initialize for moments criteria
|
||||
if ~no_identification_moments
|
||||
if ~no_identification_moments && ~error_indicator.identification_moments
|
||||
dMOMENTS = ide_moments.dMOMENTS;
|
||||
dMOMENTS(ide_moments.ind_dMOMENTS,:) = dMOMENTS(ide_moments.ind_dMOMENTS,:)./ide_moments.norm_dMOMENTS; %normalize
|
||||
if strcmp(tol_rank,'robust')
|
||||
|
|
@ -159,7 +160,7 @@ else
|
|||
end
|
||||
|
||||
% initialize for spectrum criteria
|
||||
if ~no_identification_spectrum
|
||||
if ~no_identification_spectrum && ~error_indicator.identification_spectrum
|
||||
dSPECTRUM = ide_spectrum.tilda_dSPECTRUM; %tilda dSPECTRUM is normalized dSPECTRUM matrix in identification_analysis.m
|
||||
%alternative normalization
|
||||
%dSPECTRUM = ide_spectrum.dSPECTRUM;
|
||||
|
|
@ -184,7 +185,7 @@ else
|
|||
end
|
||||
|
||||
% initialize for minimal system criteria
|
||||
if ~no_identification_minimal
|
||||
if ~no_identification_minimal && ~error_indicator.identification_minimal
|
||||
dMINIMAL = ide_minimal.dMINIMAL;
|
||||
dMINIMAL(ide_minimal.ind_dMINIMAL,:) = dMINIMAL(ide_minimal.ind_dMINIMAL,:)./ide_minimal.norm_dMINIMAL; %normalize
|
||||
dMINIMAL_par = dMINIMAL(:,1:totparam_nbr); %part of dMINIMAL that is dependent on parameters
|
||||
|
|
@ -223,7 +224,7 @@ for j=1:totparam_nbr
|
|||
end
|
||||
end
|
||||
end
|
||||
if ~no_identification_reducedform
|
||||
if ~no_identification_reducedform && ~error_indicator.identification_reducedform
|
||||
% Columns correspond to single parameters, i.e. full rank would be equal to 1
|
||||
if strcmp(tol_rank,'robust')
|
||||
if rank(full(dREDUCEDFORM(:,j))) == 0
|
||||
|
|
@ -235,7 +236,7 @@ for j=1:totparam_nbr
|
|||
end
|
||||
end
|
||||
end
|
||||
if ~no_identification_moments
|
||||
if ~no_identification_moments && ~error_indicator.identification_moments
|
||||
% Columns correspond to single parameters, i.e. full rank would be equal to 1
|
||||
if strcmp(tol_rank,'robust')
|
||||
if rank(full(dMOMENTS(:,j))) == 0
|
||||
|
|
@ -247,13 +248,13 @@ for j=1:totparam_nbr
|
|||
end
|
||||
end
|
||||
end
|
||||
if ~no_identification_spectrum
|
||||
if ~no_identification_spectrum && ~error_indicator.identification_spectrum
|
||||
% Diagonal values correspond to single parameters, absolute value needs to be greater than tolerance level
|
||||
if abs(dSPECTRUM(j,j)) < tol_rank
|
||||
spectrum_problpars{1} = [spectrum_problpars{1};j];
|
||||
end
|
||||
end
|
||||
if ~no_identification_minimal
|
||||
if ~no_identification_minimal && ~error_indicator.identification_minimal
|
||||
% Columns of dMINIMAL_par correspond to single parameters, needs to be augmented with dMINIMAL_rest (part that is independent of parameters),
|
||||
% full rank would be equal to 1+dMINIMAL_fixed_rank_nbr
|
||||
if strcmp(tol_rank,'robust')
|
||||
|
|
@ -278,7 +279,7 @@ if ~no_identification_dynamic
|
|||
indparam_dDYNAMIC(dynamic_problpars{1}) = []; %remove single unidentified parameters from higher-order sets of indparam
|
||||
end
|
||||
end
|
||||
if ~no_identification_reducedform
|
||||
if ~no_identification_reducedform && ~error_indicator.identification_reducedform
|
||||
if size(reducedform_problpars{1},1) == (totparam_nbr - rank_dREDUCEDFORM)
|
||||
%found all nonidentified parameter sets
|
||||
no_identification_reducedform = 1; %skip in the following
|
||||
|
|
@ -287,7 +288,7 @@ if ~no_identification_reducedform
|
|||
indparam_dREDUCEDFORM(reducedform_problpars{1}) = []; %remove single unidentified parameters from higher-order sets of indparam
|
||||
end
|
||||
end
|
||||
if ~no_identification_moments
|
||||
if ~no_identification_moments && ~error_indicator.identification_moments
|
||||
if size(moments_problpars{1},1) == (totparam_nbr - rank_dMOMENTS)
|
||||
%found all nonidentified parameter sets
|
||||
no_identification_moments = 1; %skip in the following
|
||||
|
|
@ -296,7 +297,7 @@ if ~no_identification_moments
|
|||
indparam_dMOMENTS(moments_problpars{1}) = []; %remove single unidentified parameters from higher-order sets of indparam
|
||||
end
|
||||
end
|
||||
if ~no_identification_spectrum
|
||||
if ~no_identification_spectrum && ~error_indicator.identification_spectrum
|
||||
if size(spectrum_problpars{1},1) == (totparam_nbr - rank_dSPECTRUM)
|
||||
%found all nonidentified parameter sets
|
||||
no_identification_spectrum = 1; %skip in the following
|
||||
|
|
@ -305,7 +306,7 @@ if ~no_identification_spectrum
|
|||
indparam_dSPECTRUM(spectrum_problpars{1}) = []; %remove single unidentified parameters from higher-order sets of indparam
|
||||
end
|
||||
end
|
||||
if ~no_identification_minimal
|
||||
if ~no_identification_minimal && ~error_indicator.identification_minimal
|
||||
if size(minimal_problpars{1},1) == (totparam_nbr + dMINIMAL_fixed_rank_nbr - rank_dMINIMAL)
|
||||
%found all nonidentified parameter sets
|
||||
no_identification_minimal = 1; %skip in the following
|
||||
|
|
@ -323,7 +324,11 @@ indtotparam = unique([indparam_dDYNAMIC indparam_dREDUCEDFORM indparam_dMOMENTS
|
|||
for j=2:min(length(indtotparam),max_dim_subsets_groups) % Check j-element subsets
|
||||
h = dyn_waitbar(0,['Brute force collinearity for ' int2str(j) ' parameters.']);
|
||||
%Step1: get all possible unique subsets of j elements
|
||||
if ~no_identification_dynamic || ~no_identification_reducedform || ~no_identification_moments || ~no_identification_spectrum || ~no_identification_minimal
|
||||
if ~no_identification_dynamic ...
|
||||
|| (~no_identification_reducedform && ~error_indicator.identification_reducedform)...
|
||||
|| (~no_identification_moments && ~error_indicator.identification_moments)...
|
||||
|| (~no_identification_spectrum && ~error_indicator.identification_spectrum)...
|
||||
|| (~no_identification_minimal && ~error_indicator.identification_minimal)
|
||||
indexj=nchoosek(int16(indtotparam),j); % int16 speeds up nchoosek
|
||||
% One could also use a mex version of nchoosek to speed this up, e.g.VChooseK from https://de.mathworks.com/matlabcentral/fileexchange/26190-vchoosek
|
||||
end
|
||||
|
|
@ -335,25 +340,25 @@ for j=2:min(length(indtotparam),max_dim_subsets_groups) % Check j-element subset
|
|||
else
|
||||
indexj_dDYNAMIC = [];
|
||||
end
|
||||
if ~no_identification_reducedform
|
||||
if ~no_identification_reducedform && ~error_indicator.identification_reducedform
|
||||
indexj_dREDUCEDFORM = RemoveProblematicParameterSets(indexj,reducedform_problpars);
|
||||
rankj_dREDUCEDFORM = zeros(size(indexj_dREDUCEDFORM,1),1);
|
||||
else
|
||||
indexj_dREDUCEDFORM = [];
|
||||
end
|
||||
if ~no_identification_moments
|
||||
if ~no_identification_moments && ~error_indicator.identification_moments
|
||||
indexj_dMOMENTS = RemoveProblematicParameterSets(indexj,moments_problpars);
|
||||
rankj_dMOMENTS = zeros(size(indexj_dMOMENTS,1),1);
|
||||
else
|
||||
indexj_dMOMENTS = [];
|
||||
end
|
||||
if ~no_identification_spectrum
|
||||
if ~no_identification_spectrum && ~error_indicator.identification_spectrum
|
||||
indexj_dSPECTRUM = RemoveProblematicParameterSets(indexj,spectrum_problpars);
|
||||
rankj_dSPECTRUM = zeros(size(indexj_dSPECTRUM,1),1);
|
||||
else
|
||||
indexj_dSPECTRUM = [];
|
||||
end
|
||||
if ~no_identification_minimal
|
||||
if ~no_identification_minimal && ~error_indicator.identification_minimal
|
||||
indexj_dMINIMAL = RemoveProblematicParameterSets(indexj,minimal_problpars);
|
||||
rankj_dMINIMAL = zeros(size(indexj_dMINIMAL,1),1);
|
||||
else
|
||||
|
|
@ -375,7 +380,7 @@ for j=2:min(length(indtotparam),max_dim_subsets_groups) % Check j-element subset
|
|||
end
|
||||
end
|
||||
end
|
||||
if ~no_identification_reducedform
|
||||
if ~no_identification_reducedform && ~error_indicator.identification_reducedform
|
||||
k_dREDUCEDFORM = k_dREDUCEDFORM+1;
|
||||
if k_dREDUCEDFORM <= size(indexj_dREDUCEDFORM,1)
|
||||
dREDUCEDFORM_j = dREDUCEDFORM(:,indexj_dREDUCEDFORM(k_dREDUCEDFORM,:)); % pick columns that correspond to parameter subset
|
||||
|
|
@ -386,7 +391,7 @@ for j=2:min(length(indtotparam),max_dim_subsets_groups) % Check j-element subset
|
|||
end
|
||||
end
|
||||
end
|
||||
if ~no_identification_moments
|
||||
if ~no_identification_moments && ~error_indicator.identification_moments
|
||||
k_dMOMENTS = k_dMOMENTS+1;
|
||||
if k_dMOMENTS <= size(indexj_dMOMENTS,1)
|
||||
dMOMENTS_j = dMOMENTS(:,indexj_dMOMENTS(k_dMOMENTS,:)); % pick columns that correspond to parameter subset
|
||||
|
|
@ -397,7 +402,7 @@ for j=2:min(length(indtotparam),max_dim_subsets_groups) % Check j-element subset
|
|||
end
|
||||
end
|
||||
end
|
||||
if ~no_identification_minimal
|
||||
if ~no_identification_minimal && ~error_indicator.identification_minimal
|
||||
k_dMINIMAL = k_dMINIMAL+1;
|
||||
if k_dMINIMAL <= size(indexj_dMINIMAL,1)
|
||||
dMINIMAL_j = [dMINIMAL_par(:,indexj_dMINIMAL(k_dMINIMAL,:)) dMINIMAL_rest]; % pick columns in dMINIMAL_par that correspond to parameter subset and augment with parameter-indepdendet part dMINIMAL_rest
|
||||
|
|
@ -408,7 +413,7 @@ for j=2:min(length(indtotparam),max_dim_subsets_groups) % Check j-element subset
|
|||
end
|
||||
end
|
||||
end
|
||||
if ~no_identification_spectrum
|
||||
if ~no_identification_spectrum && ~error_indicator.identification_spectrum
|
||||
k_dSPECTRUM = k_dSPECTRUM+1;
|
||||
if k_dSPECTRUM <= size(indexj_dSPECTRUM,1)
|
||||
dSPECTRUM_j = dSPECTRUM(indexj_dSPECTRUM(k_dSPECTRUM,:),indexj_dSPECTRUM(k_dSPECTRUM,:)); % pick rows and columns that correspond to parameter subset
|
||||
|
|
@ -426,16 +431,16 @@ for j=2:min(length(indtotparam),max_dim_subsets_groups) % Check j-element subset
|
|||
if ~no_identification_dynamic
|
||||
dynamic_problpars{j} = indexj_dDYNAMIC(rankj_dDYNAMIC < j,:);
|
||||
end
|
||||
if ~no_identification_reducedform
|
||||
if ~no_identification_reducedform && ~error_indicator.identification_reducedform
|
||||
reducedform_problpars{j} = indexj_dREDUCEDFORM(rankj_dREDUCEDFORM < j,:);
|
||||
end
|
||||
if ~no_identification_moments
|
||||
if ~no_identification_moments && ~error_indicator.identification_moments
|
||||
moments_problpars{j} = indexj_dMOMENTS(rankj_dMOMENTS < j,:);
|
||||
end
|
||||
if ~no_identification_minimal
|
||||
if ~no_identification_minimal && ~error_indicator.identification_minimal
|
||||
minimal_problpars{j} = indexj_dMINIMAL(rankj_dMINIMAL < (j+dMINIMAL_fixed_rank_nbr),:);
|
||||
end
|
||||
if ~no_identification_spectrum
|
||||
if ~no_identification_spectrum && ~error_indicator.identification_spectrum
|
||||
spectrum_problpars{j} = indexj_dSPECTRUM(rankj_dSPECTRUM < j,:);
|
||||
end
|
||||
% % Optional Step 5: % remove redundant 2-sets, eg. if the problematic sets are [(p1,p2);(p1,p3);(p2,p3)], then the unique problematic parameter sets are actually only [(p1,p2),(p1,p3)]
|
||||
|
|
|
|||
Loading…
Reference in New Issue