Added routine for simulating static models.

(cherry picked from commit b3af8c4a48)

matlab/backward/simul_backward_linear_model.m

@@ -38,7 +38,15 @@ function simulations = simul_backward_linear_model(varargin)
 % You should have received a copy of the GNU General Public License
 % along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
 
-[initialconditions, samplesize, innovations, DynareOptions, DynareModel, DynareOutput, endonames, exonames, nx, ny1, iy1, jdx, model_dynamic, y] = ...
+if M_.maximum_lead
+    error('Model defined in %s.mod is not backward.', M_.fname)
+end
+
+if M_.maximum_lag
+    error('Model defined in %s.mod is not backward.', M_.fname)
+end
+
+[initialconditions, samplesize, innovations, DynareOptions, DynareModel, DynareOutput, endonames, exonames, nx, ny1, iy1, jdx, model_dynamic] = ...
     simul_backward_model_init(varargin{:});
 
 [ysim, xsim] = simul_backward_linear_model_(initialconditions, samplesize, DynareOptions, DynareModel, DynareOutput, innovations, nx, ny1, iy1, jdx, model_dynamic);

matlab/backward/simul_backward_model.m

@@ -41,6 +41,12 @@ if M_.maximum_lead
     error('Model defined in %s.mod is not backward or static.', M_.fname)
 end
 
+if ~M_.maximum_lag
+    dprintf('Model defined in %s.mod is static. Use simul_static_model instead.', M_.fname)
+    simul_static_model(samplesize, innovations);
+    return
+end
+
 if nargin<3
     Innovations = [];
 else

matlab/backward/simul_backward_nonlinear_model.m

@@ -38,7 +38,15 @@ function simulations = simul_backward_nonlinear_model(varargin)
 % You should have received a copy of the GNU General Public License
 % along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
 
-[initialconditions, samplesize, innovations, DynareOptions, DynareModel, DynareOutput, endonames, exonames, nx, ny1, iy1, jdx, model_dynamic, y] = ...
+if M_.maximum_lead
+    error('Model defined in %s.mod is not backward.', M_.fname)
+end
+
+if M_.maximum_lag
+    error('Model defined in %s.mod is not backward.', M_.fname)
+end
+
+[initialconditions, samplesize, innovations, DynareOptions, DynareModel, DynareOutput, endonames, exonames, ~, ~, iy1, ~, model_dynamic] = ...
     simul_backward_model_init(varargin{:});
 
 [ysim, xsim] = simul_backward_nonlinear_model_(initialconditions, samplesize, DynareOptions, DynareModel, DynareOutput, innovations, iy1, model_dynamic);

matlab/simul_static_model.m

@@ -0,0 +1,105 @@
+function simulation = simul_static_model(samplesize, innovations)
+
+% Simulates a stochastic static model (with arbitrary precision).
+%
+% INPUTS
+% - samplesize          [integer]     scalar, number of periods for the simulation.
+% - innovations         [dseries]     innovations to be used for the simulation.
+%
+% OUTPUTS
+% - simulation          [dseries]     Simulated endogenous and exogenous variables.
+%
+% REMARKS
+% [1] The innovations used for the simulation are saved in DynareOutput.exo_simul, and the resulting paths for the endogenous
+%     variables are saved in DynareOutput.endo_simul.
+% [2] The last input argument is not mandatory. If absent we use random draws and rescale them with the informations provided
+%     through the shocks block.
+
+% Copyright (C) 2019 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/>.
+
+global M_ options_ oo_
+
+if M_.maximum_lag
+    error('%s.mod has lagged variables, but it should be a static model.', M_.fname)
+end
+
+if M_.maximum_lead
+    error('%s.mod has leaded variables, but it should be a static model.', M_.fname)
+end
+
+% Set innovations.
+if nargin<2 || isempty(innovations)
+    % Set the covariance matrix of the structural innovations.
+    variances = diag(M_.Sigma_e);
+    number_of_shocks = length(M_.Sigma_e);
+    positive_var_indx = find(variances>0);
+    effective_number_of_shocks = length(positive_var_indx);
+    covariance_matrix = M_.Sigma_e(positive_var_indx,positive_var_indx);
+    covariance_matrix_upper_cholesky = chol(covariance_matrix);
+    % Set seed to its default state.
+    if options_.bnlms.set_dynare_seed_to_default
+        set_dynare_seed('default');
+    end
+    % Simulate structural innovations.
+    switch options_.bnlms.innovation_distribution
+      case 'gaussian'
+        oo_.bnlms.shocks = randn(samplesize, effective_number_of_shocks)*covariance_matrix_upper_cholesky;
+      otherwise
+        error('%s distribution for the structural innovations is not (yet) implemented!', options_.bnlms.innovation_distribution)
+    end
+    % Put the simulated innovations in DynareOutput.exo_simul.
+    oo_.exo_simul = zeros(samplesize, number_of_shocks);
+    oo_.exo_simul(:,positive_var_indx) = oo_.bnlms.shocks;
+    innovations = [];
+else
+    if innovations.nobs<samplesize
+        error('Time span in third argument is too short (should not be less than %s, the value of the second argument)', num2str(samplesize))
+    end
+    % Set array holding innovations values.
+    Innovations = zeros(samplesize, M_.exo_nbr);
+    exonames = M_.exo_names;
+    for i=1:M_.exo_nbr
+        if ismember(exonames{i}, innovations.name)
+            Innovations(:,i) = innovations{exonames{i}}.data(1:samplesize);
+        else
+            dprintf('Exogenous variable %s is not available in third argument, default value is zero.', exonames{i});
+        end
+    end
+    oo_.exo_simul = Innovations;
+end
+
+staticmodel = sprintf('%s.static', M_.fname);
+
+% Simulations (call a Newton-like algorithm for each period).
+for t=1:samplesize
+    y = zeros(M_.endo_nbr, 1);
+    [oo_.endo_simul(:,t), info] = dynare_solve(staticmodel, y, options_, oo_.exo_simul(t,:), M_.params);
+    if info
+        error('Newton failed!')
+    end
+end
+
+ysim = oo_.endo_simul(1:M_.orig_endo_nbr,:);
+xsim = oo_.exo_simul;
+
+initperiod = dates('1Y');
+if isdseries(innovations)
+    initperiod = innovations.dates(1);
+end
+
+simulation = [dseries(ysim', initperiod, M_.endo_names(1:M_.orig_endo_nbr)), dseries(xsim, initperiod, M_.exo_names)];