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function oo_=disp_th_moments(dr,var_list,M_,options_,oo_)
% Display theoretical moments of variables
% Copyright (C) 2001-2017 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 <http://www.gnu.org/licenses/>.
nodecomposition = options_.nodecomposition;
if options_.one_sided_hp_filter
error(['disp_th_moments:: theoretical moments incompatible with one-sided HP filter. Use simulated moments instead'])
end
if size(var_list,1) == 0
var_list = M_.endo_names(1:M_.orig_endo_nbr, :);
end
nvar = size(var_list,1);
ivar=zeros(nvar,1);
for i=1:nvar
i_tmp = strmatch(var_list(i,:),M_.endo_names,'exact');
if isempty(i_tmp)
error (['One of the variable specified does not exist']) ;
else
ivar(i) = i_tmp;
end
end
[oo_.gamma_y,stationary_vars] = th_autocovariances(dr,ivar,M_,options_, nodecomposition);
m = dr.ys(ivar);
non_stationary_vars = setdiff(1:length(ivar),stationary_vars);
m(non_stationary_vars) = NaN;
i1 = find(abs(diag(oo_.gamma_y{1})) > 1e-12);
s2 = diag(oo_.gamma_y{1});
sd = sqrt(s2);
if options_.order == 2 && ~M_.hessian_eq_zero
m = m+oo_.gamma_y{options_.ar+3};
end
z = [ m sd s2 ];
oo_.mean = m;
oo_.var = oo_.gamma_y{1};
if size(stationary_vars, 1) > 0
if ~nodecomposition
oo_.variance_decomposition=100*oo_.gamma_y{options_.ar+2};
end
if ~options_.noprint %options_.nomoments == 0
if options_.order == 2
title='APPROXIMATED THEORETICAL MOMENTS';
else
title='THEORETICAL MOMENTS';
end
title=add_filter_subtitle(title,options_);
headers=char('VARIABLE','MEAN','STD. DEV.','VARIANCE');
labels = deblank(M_.endo_names(ivar,:));
lh = size(labels,2)+2;
dyntable(options_,title,headers,labels,z,lh,11,4);
if options_.TeX
labels = deblank(M_.endo_names_tex(ivar,:));
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title,'th_moments',headers,labels,z,lh,11,4);
end
if M_.exo_nbr > 1 && ~nodecomposition
skipline()
if options_.order == 2
title='APPROXIMATED VARIANCE DECOMPOSITION (in percent)';
else
title='VARIANCE DECOMPOSITION (in percent)';
end
title=add_filter_subtitle(title,options_);
headers = M_.exo_names;
headers(M_.exo_names_orig_ord,:) = headers;
headers = char(' ',headers);
lh = size(deblank(M_.endo_names(ivar(stationary_vars),:)),2)+2;
dyntable(options_,title,headers,deblank(M_.endo_names(ivar(stationary_vars), ...
:)),100* ...
oo_.gamma_y{options_.ar+2}(stationary_vars,:),lh,8,2);
if options_.TeX
headers=M_.exo_names_tex;
headers = char(' ',headers);
labels = deblank(M_.endo_names_tex(ivar(stationary_vars),:));
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title,'th_var_decomp_uncond',headers,labels,100*oo_.gamma_y{options_.ar+2}(stationary_vars,:),lh,8,2);
end
end
end
conditional_variance_steps = options_.conditional_variance_decomposition;
if length(conditional_variance_steps)
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.transition_matrix,StateSpaceModel.impulse_matrix] = kalman_transition_matrix(dr,(1:M_.endo_nbr)',M_.nstatic+(1:M_.nspred)',M_.exo_nbr);
StateSpaceModel.state_innovations_covariance_matrix = M_.Sigma_e;
StateSpaceModel.order_var = dr.order_var;
oo_.conditional_variance_decomposition = conditional_variance_decomposition(StateSpaceModel,conditional_variance_steps,ivar);
if options_.noprint == 0
display_conditional_variance_decomposition(oo_.conditional_variance_decomposition,conditional_variance_steps,...
ivar,M_,options_);
end
end
end
if length(i1) == 0
skipline()
disp('All endogenous are constant or non stationary, not displaying correlations and auto-correlations')
skipline()
return
end
if options_.nocorr == 0 && size(stationary_vars, 1) > 0
corr=NaN(size(oo_.gamma_y{1}));
corr(i1,i1) = oo_.gamma_y{1}(i1,i1)./(sd(i1)*sd(i1)');
if options_.contemporaneous_correlation
oo_.contemporaneous_correlation = corr;
end
if ~options_.noprint
skipline()
if options_.order == 2
title='APPROXIMATED MATRIX OF CORRELATIONS';
else
title='MATRIX OF CORRELATIONS';
end
title=add_filter_subtitle(title,options_);
labels = deblank(M_.endo_names(ivar(i1),:));
headers = char('Variables',labels);
lh = size(labels,2)+2;
dyntable(options_,title,headers,labels,corr(i1,i1),lh,8,4);
if options_.TeX
labels = deblank(M_.endo_names_tex(ivar(i1),:));
headers=char('Variables',labels);
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title,'th_corr_matrix',headers,labels,corr(i1,i1),lh,8,4);
end
end
end
if options_.ar > 0 && size(stationary_vars, 1) > 0
z=[];
for i=1:options_.ar
oo_.autocorr{i} = oo_.gamma_y{i+1};
z(:,i) = diag(oo_.gamma_y{i+1}(i1,i1));
end
if ~options_.noprint
skipline()
if options_.order == 2
title='APPROXIMATED COEFFICIENTS OF AUTOCORRELATION';
else
title='COEFFICIENTS OF AUTOCORRELATION';
end
title=add_filter_subtitle(title,options_);
labels = deblank(M_.endo_names(ivar(i1),:));
headers = char('Order ',int2str([1:options_.ar]'));
lh = size(labels,2)+2;
dyntable(options_,title,headers,labels,z,lh,8,4);
if options_.TeX
labels = deblank(M_.endo_names_tex(ivar(i1),:));
headers=char('Order ',int2str([1:options_.ar]'));
lh = size(labels,2)+2;
dyn_latex_table(M_,options_,title,'th_autocorr_matrix',headers,labels,z,lh,8,4);
end
end
end
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