function [simulations, errorflag] = simul_backward_linear_model(initialconditions, samplesize, DynareOptions, DynareModel, DynareOutput, innovations) % Simulates a stochastic linear backward looking model. % % INPUTS % - initialconditions [dseries] initial conditions for the endogenous variables. % - samplesize [integer] scalar, number of periods for the simulation. % - DynareOptions [struct] Dynare's options_ global structure. % - DynareModel [struct] Dynare's M_ global structure. % - DynareOutput [struct] Dynare's oo_ global structure. % - innovations [double] T*q matrix, innovations to be used for the simulation. % % OUTPUTS % - DynareOutput [struct] Dynare's oo_ global structure. % - errorflag [logical] scalar, equal to false iff the simulation did not fail. % % 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. % [3] If the first input argument is empty, the endogenous variables are initialized with 0, or if available with the informations % provided thrtough the histval block. % Copyright © 2012-2023 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 . if DynareModel.maximum_lead error('Model defined in %s.mod is not backward.', DynareModel.fname) end if ~DynareModel.maximum_lag error('Model defined in %s.mod is not backward.', DynareModel.fname) end if nargin<6 innovations = []; end [initialconditions, samplesize, innovations, DynareOptions, DynareModel, DynareOutput, endonames, exonames, nx, ny1, iy1, jdx, model_dynamic] = ... simul_backward_model_init(initialconditions, samplesize, DynareOptions, DynareModel, DynareOutput, innovations); [ysim, xsim, errorflag] = simul_backward_linear_model_(initialconditions, samplesize, DynareOptions, DynareModel, DynareOutput, innovations, nx, ny1, iy1, jdx, model_dynamic); simulations = [dseries(ysim', initialconditions.init, endonames(1:DynareModel.orig_endo_nbr)), dseries(xsim, initialconditions.init, exonames)];