1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
|
function [ysim, xsim] = simul_backward_nonlinear_model_(initialconditions, samplesize, DynareOptions, DynareModel, DynareOutput, innovations, iy1, model_dynamic)
% Simulates a stochastic non linear backward looking model with arbitrary precision (a deterministic solver is used).
%
% INPUTS
% - initial_conditions [double] n*1 vector, initial conditions for the endogenous variables.
% - sample_size [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.
%
% 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 © 2017-2020 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 <https://www.gnu.org/licenses/>.
debug = false;
model_dynamic_s = str2func('dynamic_backward_model_for_simulation');
if ~isempty(innovations)
DynareOutput.exo_simul(initialconditions.nobs+(1:samplesize),:) = innovations;
end
% Simulations (call a Newton-like algorithm for each period).
for it = initialconditions.nobs+(1:samplesize)
if debug
dprintf('Période t = %s.', num2str(it-initialconditions.nobs));
end
y_ = DynareOutput.endo_simul(:,it-1);
ylag = y_(iy1); % Set lagged variables.
y = y_; % A good guess for the initial conditions is the previous values for the endogenous variables.
try
if ismember(DynareOptions.solve_algo, [12,14])
[DynareOutput.endo_simul(:,it), info] = ...
dynare_solve(model_dynamic_s, y, DynareOptions, ...
DynareModel.isloggedlhs, DynareModel.isauxdiffloggedrhs, DynareModel.endo_names, DynareModel.lhs, ...
model_dynamic, ylag, DynareOutput.exo_simul, DynareModel.params, DynareOutput.steady_state, it);
else
[DynareOutput.endo_simul(:,it), info] = ...
dynare_solve(model_dynamic_s, y, DynareOptions, ...
model_dynamic, ylag, DynareOutput.exo_simul, DynareModel.params, DynareOutput.steady_state, it);
end
if info
error('Newton failed!')
end
catch
DynareOutput.endo_simul(:, 1:it-1);
dprintf('Newton failed on iteration i = %s.', num2str(it-initialconditions.nobs));
break
end
end
ysim = DynareOutput.endo_simul(1:DynareModel.orig_endo_nbr,:);
xsim = DynareOutput.exo_simul;
|
