stepan
/
dynare
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

disp_moments.m: filter out 0 variance variables 

Otherwise, division by 0 will result in incorrect moment displays

Closes #1736
time-shift
Johannes Pfeifer 2020-06-25 09:41:39 +02:00
parent a6907ba3e0
commit f0f02c3159
2 changed files with 22 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

1
matlab/default_option_values.m
View File

@ -151,6 +151,7 @@ end
% IRFs & other stoch_simul output
options_.irf = 40;
options_.impulse_responses.plot_threshold=1e-10;
options_.zero_moments_tolerance=1e-10;
options_.relative_irf = false;
options_.ar = 5;
options_.hp_filter = 0;

23
matlab/disp_moments.m
View File

@ -67,6 +67,8 @@ if ~all(M_.H==0)
y_ME=get_filtered_time_series(y_ME,m_ME,options_);
y_ME_only_filtered=get_filtered_time_series(y_ME_only,mean(y_ME_only),options_);
s2_ME = mean(y_ME.*y_ME);
s_ME = sqrt(s2_ME);
zero_variance_ME_var_index=index_subset(abs(s_ME')<options_.zero_moments_tolerance);
end
end
@ -83,11 +85,20 @@ oo_.var = y'*y/size(y,1);
oo_.skewness = (mean(y.^3)./s2.^1.5)';
oo_.kurtosis = (mean(y.^4)./(s2.*s2)-3)';
zero_variance_var_index=find(abs(s)<options_.zero_moments_tolerance);
oo_.skewness(zero_variance_var_index)=NaN;
oo_.kurtosis(zero_variance_var_index)=NaN;
s(zero_variance_var_index)=0;
s2(zero_variance_var_index)=0;
oo_.var(zero_variance_var_index,:)=0;
oo_.var(:,zero_variance_var_index)=0;
labels = M_.endo_names(ivar);
labels_TeX = M_.endo_names_tex(ivar);
if ~options_.nomoments
z = [ m' s' s2' (mean(y.^3)./s2.^1.5)' (mean(y.^4)./(s2.*s2)-3)' ];
z = [ m' s' s2' oo_.skewness oo_.kurtosis ];
title='MOMENTS OF SIMULATED VARIABLES';
title=add_filter_subtitle(title, options_);
headers = {'VARIABLE'; 'MEAN'; 'STD. DEV.'; 'VARIANCE'; 'SKEWNESS'; 'KURTOSIS'};
@ -99,6 +110,8 @@ end
if ~options_.nocorr
corr = (y'*y/size(y,1))./(s'*s);
corr(zero_variance_var_index,:)=NaN;
corr(:,zero_variance_var_index)=NaN;
if options_.contemporaneous_correlation
oo_.contemporaneous_correlation = corr;
end
@ -124,6 +137,8 @@ if ar > 0
autocorr = [];
for i=1:ar
oo_.autocorr{i} = y(ar+1:end,:)'*y(ar+1-i:end-i,:)./((size(y,1)-ar)*std(y(ar+1:end,:))'*std(y(ar+1-i:end-i,:)));
oo_.autocorr{i}(zero_variance_var_index,:)=NaN;
oo_.autocorr{i}(:,zero_variance_var_index)=NaN;
autocorr = [ autocorr diag(oo_.autocorr{i}) ];
end
if ~options_.noprint
@ -169,12 +184,16 @@ if ~options_.nodecomposition
y_sim_one_shock = simult_(M_,options_,y0,oo_.dr,temp_shock_mat,options_.order);
y_sim_one_shock=y_sim_one_shock(ivar,1+options_.drop+1:end)';
y_sim_one_shock=get_filtered_time_series(y_sim_one_shock,mean(y_sim_one_shock),options_);
oo_.variance_decomposition(:,i_exo_var(shock_iter))=var(y_sim_one_shock)./s2*100;
oo_.variance_decomposition(:,i_exo_var(shock_iter))=var(y_sim_one_shock)./s2*100;
end
oo_.variance_decomposition(zero_variance_var_index,:)=NaN;
if ME_present
oo_.variance_decomposition_ME=oo_.variance_decomposition(index_subset,:)...
.*repmat((s2(index_subset)./s2_ME)',1,length(i_exo_var));
oo_.variance_decomposition_ME(:,end+1)=var(y_ME_only_filtered)./s2_ME*100;
oo_.variance_decomposition_ME(ismember(observable_pos_requested_vars,intersect(zero_variance_ME_var_index,zero_variance_var_index)),:)=NaN;
oo_.variance_decomposition_ME(ismember(observable_pos_requested_vars,setdiff(zero_variance_var_index,zero_variance_ME_var_index)),1:end-1)=0;
oo_.variance_decomposition_ME(ismember(observable_pos_requested_vars,setdiff(zero_variance_var_index,zero_variance_ME_var_index)),end)=1;
end
if ~options_.noprint %options_.nomoments == 0
skipline()