th_autocovariances.m creates Gamma_y{nar+2} (variance decomposition)

even if there is a single shock. In that case variance decomposition
is one. It is better if Gamma_y has always the expected
size. disp_th_moments.m only displays variance decomposition if there
is more than one shock.

matlab/th_autocovariances.m

@@ -177,7 +177,10 @@ if options_.hp_filter == 0
         end
     end
     % variance decomposition
-    if ~nodecomposition && M_.exo_nbr > 1 && size(stationary_vars, 1) > 0
+    if ~nodecomposition && M_.exo_nbr > 0 && size(stationary_vars, 1) > 0
+        if M_.exo_nbr == 1
+            Gamma_y{nar+2} = ones(nvar,1);
+        else
             Gamma_y{nar+2} = zeros(nvar,M_.exo_nbr);
             SS(exo_names_orig_ord,exo_names_orig_ord)=M_.Sigma_e+1e-14*eye(M_.exo_nbr);
             cs = chol(SS)';
@@ -203,6 +206,7 @@ if options_.hp_filter == 0
                                     2}(stationary_vars,i)./vv2;
             end
         end
+    end
 else% ==> Theoretical HP filter.
     % By construction, all variables are stationary when HP filtered
     iky = inv_order_var(ivar);  
@@ -244,7 +248,10 @@ else% ==> Theoretical HP filter.
         end
     end
     % Variance decomposition
-    if ~nodecomposition && M_.exo_nbr > 1
+    if ~nodecomposition && M_.exo_nbr > 0
+        if M_.exo_nbr == 1
+            Gamma_y{nar+2} = ones(nvar,1);
+        else
             Gamma_y{nar+2} = zeros(nvar,M_.exo_nbr);
             SS(exo_names_orig_ord,exo_names_orig_ord) = M_.Sigma_e+1e-14*eye(M_.exo_nbr);
             cs = chol(SS)';
@@ -290,6 +297,7 @@ else% ==> Theoretical HP filter.
             end
         end
     end
+end
 if isoctave
     warning('on', 'Octave:divide-by-zero')
 else