diff --git a/doc/manual/source/the-model-file.rst b/doc/manual/source/the-model-file.rst
index ac0f83733b08db684e9f062832f5c8eca98ee967..c8ea90fe3641dfabcc3dfa198870b11977642117 100644
--- a/doc/manual/source/the-model-file.rst
+++ b/doc/manual/source/the-model-file.rst
@@ -3428,20 +3428,18 @@ Getting information about the model
.. command:: model_info ;
model_info (OPTIONS...);
- |br| This command provides information about the model.
-
- When used outside the context of the ``block`` option of the ``model`` block,
+ |br| This command provides information about the model. By default,
it will provide a list of predetermined state variables, forward-looking variables,
and purely static variables.
- When used in conjunction with the ``block`` option of the ``model`` block,
- it displays:
+ The command also allows to display information on the dynamic and static
+ versions of the block decomposition of the model:
* The normalization of the model: an endogenous variable is
- attributed to each equation of the model;
+ attributed to each equation of the model (the dependent variable);
* The block structure of the model: for each block ``model_info``
- indicates its type, the equations number and endogenous
- variables belonging to this block.
+ indicates its type, size as well as the equation number(s) or name tags and
+ endogenous variables belonging to this block.
There are five different types of blocks depending on the
@@ -3450,37 +3448,37 @@ Getting information about the model
* ``EVALUATE FORWARD``
In this case the block contains only equations where the
- endogenous variable attributed to the equation appears
- at current period on the left hand side and where no forward looking
+ dependent variable :math:`j` attributed to the equation appears
+ contemporaneously on the left hand side and where no forward looking
endogenous variables appear. The block has the form:
:math:`y_{j,t} = f_j(y_t, y_{t-1}, \ldots, y_{t-k})`.
* ``EVALUATE BACKWARD``
- The block contains only equations where the endogenous variable
- attributed to the equation appears at current period on the left hand
- side and where no backward looking endogenous variables
+ The block contains only equations where the dependent variable :math:`j`
+ attributed to the equation appears contemporaneously on the left hand side
+ and where no backward looking endogenous variables
appear. The block has the form: :math:`y_{j,t} = f_j(y_t,
y_{t+1}, \ldots, y_{t+k})`.
* ``SOLVE BACKWARD x``
- The block contains only equations where the endogenous variable
- attributed to the equation does not appear at current period on the
+ The block contains only equations where the dependent variable :math:`j`
+ attributed to the equation does not appear contemporaneously on the
left hand side and where no forward looking endogenous
variables appear. The block has the form: :math:`g_j(y_{j,t},
- y_t, y_{t-1}, \ldots, y_{t-k})=0`. ``x`` is equal to ``SIMPLE``
- if the block has only one equation. If several equations
+ y_t, y_{t-1}, \ldots, y_{t-k})=0`. Here, ``x`` denotes the subtype of the block.
+ ``x`` is equal to ``SIMPLE`` if the block has only one equation. If several equations
appear in the block, ``x`` is equal to ``COMPLETE``.
* ``SOLVE FORWARD x``
- The block contains only equations where the endogenous variable
- attributed to the equation does not appear at current period on the
+ The block contains only equations where the dependent variable :math:`j`
+ attributed to the equation does not appear contemporaneously on the
left hand side and where no backward looking endogenous
variables appear. The block has the form: :math:`g_j(y_{j,t},
- y_t, y_{t+1}, \ldots, y_{t+k})=0`. ``x`` is equal to ``SIMPLE``
- if the block has only one equation. If several equations
+ y_t, y_{t+1}, \ldots, y_{t+k})=0`. Here, ``x`` denotes the subtype of the block.
+ ``x`` is equal to ``SIMPLE`` if the block has only one equation. If several equations
appear in the block, ``x`` is equal to ``COMPLETE``.
* ``SOLVE TWO BOUNDARIES x``
@@ -3488,22 +3486,24 @@ Getting information about the model
The block contains equations depending on both forward and
backward variables. The block looks like: :math:`g_j(y_{j,t},
y_t, y_{t-1}, \ldots, y_{t-k} ,y_t, y_{t+1}, \ldots,
- y_{t+k})=0`. ``x`` is equal to ``SIMPLE`` if the block has only
- one equation. If several equations appear in the block, ``x`` is
- equal to ``COMPLETE``.
+ y_{t+k})=0`. Here, ``x`` denotes the subtype of the block.
+ ``x`` is equal to ``SIMPLE`` if the block has only one equation. If several equations
+ appear in the block, ``x`` is equal to ``COMPLETE``.
*Options*
- .. option:: static
+ .. option:: block_static
+
+ Prints out the block decomposition of the static model.
+
+ .. option:: block_dynamic
- Prints out the block decomposition of the static
- model. Without the ``static`` option, ``model_info`` displays the block
- decomposition of the dynamic model.
+ Prints out the block decomposition of the dynamic model.
.. option:: incidence
Displays the gross incidence matrix and the reordered incidence
- matrix of the block decomposed model.
+ matrix of the block decomposed model for the ``block_dynamic`` or ``block_static`` options.
.. command:: print_bytecode_dynamic_model ;
diff --git a/matlab/model_info.m b/matlab/model_info.m
index 5744a45f9fd2e41f1f1d14e1caefd303310ec491..054e53e9c1135eb283d1eca2c6a4516f266701fb 100644
--- a/matlab/model_info.m
+++ b/matlab/model_info.m
@@ -20,29 +20,42 @@ function model_info(options_model_info_)
global M_;
-static_ = isfield(options_model_info_, 'static') && options_model_info_.static;
+dynamic_ = isfield(options_model_info_, 'block_dynamic') && options_model_info_.block_dynamic;
+static_ = isfield(options_model_info_, 'block_static') && options_model_info_.block_static;
incidence = isfield(options_model_info_, 'incidence') && options_model_info_.incidence;
if static_
- fprintf(' Information about %s (static model)\n',M_.fname);
- block_structre_str = 'block_structure_stat';
- nb_leadlag = 1;
+ temp_string=sprintf('\nInformation about %s (static model)\n',M_.fname);
+ fprintf(temp_string);
+ block_structure_str = 'block_structure_stat';
+ if ~isfield(M_,'block_structure_stat')
+ fprintf('\nmodel_info: block information not present; skipping display.\n')
+ return;
+ else
+ nb_leadlag = 1;
+ end
else
- fprintf(' Information about %s (dynamic model)\n',M_.fname);
- block_structre_str = 'block_structure';
- nb_leadlag = 3;
+ temp_string=sprintf('\nInformation about %s (dynamic model)\n',M_.fname);
+ fprintf(temp_string);
+ block_structure_str = 'block_structure';
+ if dynamic_ && isfield(M_,'block_structure')
+ fprintf('\nmodel_info: block information not present; skipping display.\n')
+ return;
+ elseif dynamic_
+ nb_leadlag = length([M_.(block_structure_str).incidence.lead_lag]);
+ end
end
-if isfield(M_,block_structre_str)
+if dynamic_ || static_ || incidence %block information requested
if static_
block_structure = M_.block_structure_stat;
else
block_structure = M_.block_structure;
end
- fprintf(strcat(' ===================',char(ones(1,length(M_.fname))*'='),'\n\n'));
+ fprintf([char(ones(1,length(temp_string))*'='),'\n']);
nb_blocks=length(block_structure.block);
- fprintf('The model has %d equations and is decomposed in %d blocks as follow:\n',M_.endo_nbr,nb_blocks);
+ fprintf('The model has %d equations and is decomposed into %d blocks as follows:\n',M_.endo_nbr,nb_blocks);
fprintf('================================================================================================================================\n');
fprintf('| %10s | %10s | %30s | %31s | %31s |\n','Block no','Size','Block Type','Equation','Dependent variable');
fprintf('|============|============|================================|=================================|=================================|\n');
@@ -62,7 +75,7 @@ if isfield(M_,block_structre_str)
fprintf('================================================================================================================================\n');
fprintf('\n');
if static_
- fprintf('%-30s %s','the variable','is used in the following equations contemporaneously');
+ fprintf('%-30s %s','The variable','is used contemporaneously in the following equations:');
if(size(block_structure.incidence.sparse_IM,1)>0)
IM=sortrows(block_structure.incidence.sparse_IM,2);
else
@@ -78,14 +91,14 @@ if isfield(M_,block_structre_str)
last=IM(i,2);
end
fprintf('\n\n');
- else
+ else %dynamic model
for k=1:M_.maximum_endo_lag+M_.maximum_endo_lead+1
if(k==M_.maximum_endo_lag+1)
- fprintf('%-30s %s','the variable','is used in the following equations Contemporaneously');
+ fprintf('%-30s %s','The variable','is used in the following equations contemporaneously');
elseif(k<M_.maximum_endo_lag+1)
- fprintf('%-30s %s %d','the variable','is used in the following equations with lag ',M_.maximum_endo_lag+1-k);
+ fprintf('%-30s %s %d','The variable','is used in the following equations with lag ',M_.maximum_endo_lag+1-k);
else
- fprintf('%-30s %s %d','the variable','is used in equations with lead ',k-(M_.maximum_endo_lag+1));
+ fprintf('%-30s %s %d','The variable','is used in equations with lead ',k-(M_.maximum_endo_lag+1));
end
if(size(block_structure.incidence(k).sparse_IM,1)>0)
IM=sortrows(block_structure.incidence(k).sparse_IM,2);
@@ -104,34 +117,36 @@ if isfield(M_,block_structre_str)
fprintf('\n\n');
end
end
-
- %printing the gross incidence matrix
- IM_star = char([kron(ones(M_.endo_nbr, M_.endo_nbr-1), double(blanks(3))) double(blanks(M_.endo_nbr)')]);
- for i = 1:nb_leadlag
- n = size(block_structure.incidence(i).sparse_IM,1);
- for j = 1:n
- if ismember(block_structure.incidence(i).sparse_IM(j,2), M_.state_var)
- IM_star(block_structure.incidence(i).sparse_IM(j,1), 3 * (block_structure.incidence(i).sparse_IM(j,2) - 1) + 1) = 'X';
- else
- IM_star(block_structure.incidence(i).sparse_IM(j,1), 3 * (block_structure.incidence(i).sparse_IM(j,2) - 1) + 1) = '1';
+ if incidence
+
+ %printing the gross incidence matrix
+ IM_star = char([kron(ones(M_.endo_nbr, M_.endo_nbr-1), double(blanks(3))) double(blanks(M_.endo_nbr)')]);
+ for i = 1:nb_leadlag
+ n = size(block_structure.incidence(i).sparse_IM,1);
+ for j = 1:n
+ if ismember(block_structure.incidence(i).sparse_IM(j,2), M_.state_var)
+ IM_star(block_structure.incidence(i).sparse_IM(j,1), 3 * (block_structure.incidence(i).sparse_IM(j,2) - 1) + 1) = 'X';
+ else
+ IM_star(block_structure.incidence(i).sparse_IM(j,1), 3 * (block_structure.incidence(i).sparse_IM(j,2) - 1) + 1) = '1';
+ end
end
end
- end
- seq = 1: M_.endo_nbr;
- blank = [ blanks(cellofchararraymaxlength(M_.endo_names)); blanks(cellofchararraymaxlength(M_.endo_names))];
- for i = 1:M_.endo_nbr
- if i == 1
- var_names = char(blank, M_.endo_names{i});
- else
- var_names = char(var_names, blank, M_.endo_names{i});
+ seq = 1: M_.endo_nbr;
+ blank = [ blanks(cellofchararraymaxlength(M_.endo_names)); blanks(cellofchararraymaxlength(M_.endo_names))];
+ for i = 1:M_.endo_nbr
+ if i == 1
+ var_names = char(blank, M_.endo_names{i});
+ else
+ var_names = char(var_names, blank, M_.endo_names{i});
+ end
end
- end
- if incidence
topp = [char(kron(double(blanks(ceil(log10(M_.endo_nbr)))),ones(cellofchararraymaxlength(M_.endo_names),1))) var_names' ];
bott = [int2str(seq') blanks(M_.endo_nbr)' blanks(M_.endo_nbr)' IM_star];
- fprintf('\n Gross incidence matrix\n');
- fprintf(' =======================\n');
- disp([topp; bott]);
+ fprintf('\nGross incidence matrix\n');
+ fprintf('=======================\n');
+ disp(topp);
+ skipline;
+ disp(bott);
%printing the reordered incidence matrix
IM_star_reordered = char([kron(ones(M_.endo_nbr, M_.endo_nbr-1), double(blanks(3))) double(blanks(M_.endo_nbr)')]);
@@ -145,12 +160,12 @@ if isfield(M_,block_structre_str)
cur_block = cur_block + 1;
end
if i == 1
- var_names = [blank; M_.endo_names{block_structure.variable_reordered(i)}];
+ var_names = char(blank, M_.endo_names{block_structure.variable_reordered(i)});
else
if past_block ~= cur_block
- var_names = [var_names; barre_blank; M_.endo_names{block_structure.variable_reordered(i)}];
+ var_names = char(var_names, barre_blank, M_.endo_names{block_structure.variable_reordered(i)});
else
- var_names = [var_names; blank; M_.endo_names{block_structure.variable_reordered(i)}];
+ var_names = char(var_names, blank, M_.endo_names{block_structure.variable_reordered(i)});
end
end
end
@@ -174,7 +189,7 @@ if isfield(M_,block_structre_str)
end
end
end
- fprintf('1: non nul element, X: non nul element related to a state variable\n');
+ fprintf('\n1: non-null element, X: non-null element related to a state variable\n');
cur_block = 1;
i_last = 0;
@@ -203,12 +218,14 @@ if isfield(M_,block_structre_str)
end
bott = [int2str(block_structure.equation_reordered') blanks(M_.endo_nbr)' blanks(M_.endo_nbr)' IM_star_reordered];
- fprintf('\n Reordered incidence matrix\n');
- fprintf(' ==========================\n');
- disp([topp; bott]);
- fprintf('1: non nul element, X: non nul element related to a state variable\n');
+ fprintf('\nReordered incidence matrix\n');
+ fprintf('==========================\n');
+ disp(topp);
+ skipline;
+ disp(bott);
+ fprintf('\n1: non-null element, X: non-null element related to a state variable\n');
end
-else
+else %non-block information
% print states
if M_.maximum_endo_lag~=0
lag_index=find(M_.lead_lag_incidence(1,:));
@@ -263,7 +280,7 @@ function print_line(names,var_index,lead_lag,M_)
else
aux_index=find([M_.aux_vars(:).endo_index]==var_index);
aux_type=M_.aux_vars(aux_index).type;
- if isempty(M_.aux_vars(aux_index).orig_lead_lag)
+ if ~isfield(M_.aux_vars(aux_index),'orig_lead_lag') || isempty(M_.aux_vars(aux_index).orig_lead_lag)
if ismember(aux_type,[1,3])
str = subst_auxvar(var_index, -1, M_);
elseif ismember(aux_type,[0,2])
diff --git a/matlab/subst_auxvar.m b/matlab/subst_auxvar.m
index 5a65f5ef592249de666b0e481090480445530c6a..ec266e2f48fb5bcd707cb9e4a417716b1c51b1fd 100644
--- a/matlab/subst_auxvar.m
+++ b/matlab/subst_auxvar.m
@@ -44,10 +44,17 @@ if ~isempty(aux_index)
orig_name = M_.endo_names{M_.aux_vars(aux_index).orig_index};
case 2
% exo leads >= 1
- orig_name = M_.exo_names{M_.aux_vars(aux_index).orig_index};
+ str = sprintf('%s(+1)', M_.aux_vars(aux_index).orig_expr);
+ return
case 3
% exo lags >= 1
orig_name = M_.exo_names{M_.aux_vars(aux_index).orig_index};
+ if M_.aux_vars(aux_index).orig_lead_lag==0
+ str = sprintf('%s(%d)', orig_name, M_.aux_vars(aux_index).orig_lead_lag+aux_lead_lag-1);%orig_lead_lag is actually -1 due to being a lagged exogenous
+ else
+ str = sprintf('%s(%d)', orig_name, M_.aux_vars(aux_index).orig_lead_lag+aux_lead_lag);
+ end
+ return;
case 4
% Expectation operator
str = sprintf('%s', M_.aux_vars(aux_index).orig_expr);
diff --git a/tests/Makefile.am b/tests/Makefile.am
index d35890de8fbd4e458c479b6ada5e26af30d27c03..83b5338063b4dcbf19835c6ced12100199776cd7 100644
--- a/tests/Makefile.am
+++ b/tests/Makefile.am
@@ -86,6 +86,8 @@ MODFILES = \
estimation/univariate/nls/staticmodel.mod \
estimation/univariate/nls/dynamicmodel1.mod \
estimation/univariate/nls/dynamicmodel2.mod \
+ model_info/NKM_3_back.mod \
+ model_info/NKM_3_forward.mod \
moments/example1_var_decomp.mod \
moments/example1_bp_test.mod \
moments/test_AR1_spectral_density.mod \
diff --git a/tests/model_info/NKM_3_back.mod b/tests/model_info/NKM_3_back.mod
new file mode 100644
index 0000000000000000000000000000000000000000..35f7792b44b0836efb988acdf27af59dbb48b659
--- /dev/null
+++ b/tests/model_info/NKM_3_back.mod
@@ -0,0 +1,41 @@
+parameters betta sigma phipi phiy omega kappa r_ss;
+
+var c r ui;
+
+varexo pai;
+
+betta = 0.99; % discount rate patient
+sigma = 1.5; % risk aversion param
+omega = 0.75; % calvo param
+phipi = 1.5;
+phiy = 0.5;
+r_ss = 0;
+kappa = (1-omega)*(1-omega*betta)/omega;
+
+model(linear);
+[name='Euler']
+c = c(+1) - (1/sigma)*(r - r_ss - pai(-2));
+[name='NKPC']
+pai = betta*pai(+2) + kappa*c;
+[name='Taylor rule']
+r = phipi*pai + phiy*c + ui;
+
+end;
+
+initval;
+ui = 0;
+c = 0;
+r = 0;
+end;
+
+steady;
+
+shocks;
+var pai;
+periods 1,2,3,4,5,6,7,8,9,10;
+values 0.006, 0.005854795, 0.00550196, 0.0052, 0.0048, 0.0043, 0.0037, 0.0028, 0.0022, 0.0015;
+end;
+model_info;
+model_info(block_static,incidence);
+
+model_info(block_dynamic,incidence);
diff --git a/tests/model_info/NKM_3_forward.mod b/tests/model_info/NKM_3_forward.mod
new file mode 100644
index 0000000000000000000000000000000000000000..3df40ccb3f9feeea8728e49729b25ff104ec4ba7
--- /dev/null
+++ b/tests/model_info/NKM_3_forward.mod
@@ -0,0 +1,41 @@
+parameters betta sigma phipi phiy omega kappa r_ss;
+
+var c r ui;
+
+varexo pai;
+
+betta = 0.99; % discount rate patient
+sigma = 1.5; % risk aversion param
+omega = 0.75; % calvo param
+phipi = 1.5;
+phiy = 0.5;
+r_ss = 0;
+kappa = (1-omega)*(1-omega*betta)/omega;
+
+model(linear);
+[name='Euler']
+c = c(+1) - (1/sigma)*(r - r_ss - pai(+1));
+[name='NKPC']
+pai = betta*pai(+1) + kappa*c;
+[name='Taylor rule']
+r = phipi*pai + phiy*c + ui;
+
+end;
+
+initval;
+ui = 0;
+c = 0;
+r = 0;
+end;
+
+steady;
+
+shocks;
+var pai;
+periods 1,2,3,4,5,6,7,8,9,10;
+values 0.006, 0.005854795, 0.00550196, 0.0052, 0.0048, 0.0043, 0.0037, 0.0028, 0.0022, 0.0015;
+end;
+model_info;
+model_info(block_static,incidence);
+
+model_info(block_dynamic,incidence);