Harmonize FilteredVariables with Updated and Smoothed ones, by adding steady state to stored values, both point estimate and MCMC

(cherry picked from commit fd0d7d6d27a7937b135521c4dd76d7fa242d89ab)

matlab/convert_dyn_45_to_44.m

@@ -147,8 +147,13 @@ end
 if ~isempty(options_.nk) && options_.nk ~= 0 && ~isempty(bayestopt_)
     if ~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.pshape> 0) && options_.load_mh_file)) %no Bayesian estimation
         positions_in_decision_order=oo_.dr.inv_order_var(bayestopt_.smoother_var_list(bayestopt_.smoother_saved_var_list));
+            if  options_.loglinear == 1 %logged steady state must be used
+                constant_all_variables=log(oo_.dr.ys(bayestopt_.smoother_var_list(bayestopt_.smoother_saved_var_list)));
+            elseif options_.loglinear == 0 %unlogged steady state must be used
+                constant_all_variables=oo_.dr.ys(bayestopt_.smoother_var_list(bayestopt_.smoother_saved_var_list));
+            end
         if ~(options_.selected_variables_only && ~(options_.forecast > 0)) %happens only when selected_variables_only is not used
-            oo_.FilteredVariablesKStepAhead(:,positions_in_decision_order,:)=oo_.FilteredVariablesKStepAhead;
+            oo_.FilteredVariablesKStepAhead(:,positions_in_decision_order,:)=oo_.FilteredVariablesKStepAhead-constant_all_variables;
             if ~isempty(PK) %get K-step ahead variances
                 oo_.FilteredVariablesKStepAheadVariances(:,positions_in_decision_order,positions_in_decision_order,:)=oo_.FilteredVariablesKStepAheadVariances;
             end
@@ -184,4 +189,4 @@ if ~isempty(M_.osr.variable_indices)
 end
 if ~isempty(M_.osr.param_names)
    evalin('base','osr_params_=char(M_.osr.param_names)')
-end
+end

matlab/gsa/filt_mc_.m

@@ -169,7 +169,7 @@ if ~loadSA,
             rmse_mode = sqrt(mean((yobs(istart:end,:)-y0(istart:end,:)).^2));
             r2_mode = 1-sum((yobs(istart:end,:)-y0(istart:end,:)).^2)./sum(yobs(istart:end,:).^2);
         end
-        y0=yss*0;
+        y0=-yss;
         nbb=0;
         for j=1:length(filfilt),
             load([DirectoryName filesep M_.fname '_filter_step_ahead',num2str(j),'.mat']);

matlab/prior_posterior_statistics_core.m

@@ -237,14 +237,26 @@ for b=fpar:B
         end
         if naK
             %filtered variable E_t(y_t+k) requires to shift trend by k periods
-            %write percentage deviation of variables into declaration order
-            stock_filter_step_ahead(:,dr.order_var,:,irun(4)) = aK(options_.filter_step_ahead,1:endo_nbr,:);
+            %write variables into declaration order
+            if options_.loglinear %reads values from smoother results, which are in dr-order and put them into declaration order
+                constant_part=repmat(log(SteadyState(dr.order_var))',[length(options_.filter_step_ahead),1,gend+max(options_.filter_step_ahead)])
+            else
+                constant_part=repmat(SteadyState(dr.order_var)',[length(options_.filter_step_ahead),1,gend+max(options_.filter_step_ahead)]);
+            end       
+
+            stock_filter_step_ahead(:,dr.order_var,:,irun(4)) = aK(options_.filter_step_ahead,1:endo_nbr,:) + ...
+                constant_part;
             
-            %now add trend and constant to filtered variables
+            %now add trend to observables
             for ii=1:length(options_.filter_step_ahead)
-                stock_filter_step_ahead(ii,IdObs,:,irun(4)) = squeeze(stock_filter_step_ahead(ii,IdObs,:,irun(4)))...
-                +repmat(constant_part(:,1),1,gend+max(options_.filter_step_ahead))... %constant
-                +[trend_addition repmat(trend_addition(:,end),1,max(options_.filter_step_ahead))+trend_coeff*[1:max(options_.filter_step_ahead)]]; %trend
+                if options_.prefilter
+                    stock_filter_step_ahead(ii,IdObs,:,irun(4)) = squeeze(stock_filter_step_ahead(ii,IdObs,:,irun(4)))...
+                        +repmat(mean_correction(:,1),1,gend+max(options_.filter_step_ahead))... %constant correction
+                        +[trend_addition repmat(trend_addition(:,end),1,max(options_.filter_step_ahead))+trend_coeff*[1:max(options_.filter_step_ahead)]]; %trend
+                else
+                    stock_filter_step_ahead(ii,IdObs,:,irun(4)) = squeeze(stock_filter_step_ahead(ii,IdObs,:,irun(4)))...
+                        +[trend_addition repmat(trend_addition(:,end),1,max(options_.filter_step_ahead))+trend_coeff*[1:max(options_.filter_step_ahead)]]; %trend
+                end
             end
         end
 
@@ -434,10 +446,10 @@ if RemoteFlag==1,
                         OutputFileName_filter_step_ahead;
                         OutputFileName_param;
                         OutputFileName_forc_mean;
-                        OutputFileName_forc_point
-                        OutputFileName_filter_covar
-                        OutputFileName_trend_coeff
-                        OutputFileName_smoothed_trend
+                        OutputFileName_forc_point;
+                        OutputFileName_filter_covar;
+                        OutputFileName_trend_coeff;
+                        OutputFileName_smoothed_trend;
                         OutputFileName_smoothed_constant];
 end
 

matlab/store_smoother_results.m

@@ -120,9 +120,16 @@ end
 %get indices of smoothed variables
 i_endo_in_bayestopt_smoother_varlist = bayestopt_.smoother_saved_var_list;
 i_endo_in_dr_matrices=bayestopt_.smoother_var_list(i_endo_in_bayestopt_smoother_varlist);
-if ~isempty(options_.nk) && options_.nk ~= 0 
-    %write deviations from steady state, add constant for observables later
-    oo_.FilteredVariablesKStepAhead = aK(options_.filter_step_ahead,i_endo_in_dr_matrices,:);    
+if ~isempty(options_.nk) && options_.nk ~= 0
+    %% Compute constant
+    i_endo_declaration_order = oo_.dr.order_var(i_endo_in_dr_matrices); %get indices of smoothed variables in name vector
+    if  options_.loglinear == 1 %logged steady state must be used
+        constant_all_variables=repmat(log(ys(i_endo_declaration_order))',[length(options_.filter_step_ahead),1,gend+max(options_.filter_step_ahead)]);
+    elseif options_.loglinear == 0 %unlogged steady state must be used
+        constant_all_variables=repmat((ys(i_endo_declaration_order))',[length(options_.filter_step_ahead),1,gend+max(options_.filter_step_ahead)]);
+    end
+    % add constant
+    oo_.FilteredVariablesKStepAhead = aK(options_.filter_step_ahead,i_endo_in_dr_matrices,:)+constant_all_variables;
     if ~isempty(PK) %get K-step ahead variances
         oo_.FilteredVariablesKStepAheadVariances = ...
             PK(options_.filter_step_ahead,i_endo_in_dr_matrices,i_endo_in_dr_matrices,:);
@@ -145,7 +152,7 @@ for i_endo_in_bayestopt_smoother_varlist=bayestopt_.smoother_saved_var_list'
     oo_.Smoother.Constant.(deblank(M_.endo_names(i_endo_declaration_order,:)))=constant_current_variable;
     oo_.SmoothedVariables.(deblank(M_.endo_names(i_endo_declaration_order,:)))=atT(i_endo_in_dr,:)'+constant_current_variable;
     if ~isempty(options_.nk) && options_.nk > 0 && ~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.pshape> 0) && options_.load_mh_file))
-        oo_.FilteredVariables.(deblank(M_.endo_names(i_endo_declaration_order,:)))=squeeze(aK(1,i_endo_in_dr,2:end-(options_.nk-1)));
+        oo_.FilteredVariables.(deblank(M_.endo_names(i_endo_declaration_order,:)))=squeeze(aK(1,i_endo_in_dr,2:end-(options_.nk-1)))+constant_current_variable;
     end
     oo_.UpdatedVariables.(deblank(M_.endo_names(i_endo_declaration_order,:)))=updated_variables(i_endo_in_dr,:)'+constant_current_variable;
 end
@@ -212,4 +219,4 @@ if ~isequal(M_.H,0)
     for meas_error_iter=1:length(options_.varobs)
        oo_.SmoothedMeasurementErrors.(options_.varobs{meas_error_iter})= measurement_error(meas_error_iter,:)';
     end
-end
+end