/usr/share/dynare/matlab/simult_.m is in dynare-common 4.4.1-1build1.
This file is owned by root:root, with mode 0o644.
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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 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 | function y_=simult_(y0,dr,ex_,iorder)
% Simulates the model using a perturbation approach, given the path for the exogenous variables and the
% decision rules.
%
% INPUTS
% y0 [double] n*1 vector, initial value (n is the number of declared endogenous variables plus the number
% of auxilliary variables for lags and leads)
% dr [struct] matlab's structure where the reduced form solution of the model is stored.
% ex_ [double] T*q matrix of innovations.
% iorder [integer] order of the taylor approximation.
%
% OUTPUTS
% y_ [double] n*(T+1) time series for the endogenous variables.
%
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2001-2013 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_
iter = size(ex_,1);
endo_nbr = M_.endo_nbr;
exo_nbr = M_.exo_nbr;
y_ = zeros(size(y0,1),iter+M_.maximum_lag);
y_(:,1) = y0;
% stoch_simul sets k_order_solver=1 if order=3, but does so only locally, so we
% have to do it here also
if options_.order == 3
options_.k_order_solver = 1;
end
if ~options_.k_order_solver || (options_.k_order_solver && options_.pruning) %if k_order_pert is not used or if we do not use Dynare++ with k_order_pert
if iorder==1
y_(:,1) = y_(:,1)-dr.ys;
end
end
if options_.k_order_solver && ~options_.pruning % Call dynare++ routines.
ex_ = [zeros(M_.maximum_lag,M_.exo_nbr); ex_];
switch options_.order
case 1
[err, y_] = dynare_simul_(1,M_.nstatic,M_.npred,M_.nboth,M_.nfwrd,exo_nbr, ...
y_(dr.order_var,1),ex_',M_.Sigma_e,options_.DynareRandomStreams.seed,dr.ys(dr.order_var),...
zeros(endo_nbr,1),dr.g_1);
case 2
[err, y_] = dynare_simul_(2,M_.nstatic,M_.npred,M_.nboth,M_.nfwrd,exo_nbr, ...
y_(dr.order_var,1),ex_',M_.Sigma_e,options_.DynareRandomStreams.seed,dr.ys(dr.order_var),dr.g_0, ...
dr.g_1,dr.g_2);
case 3
[err, y_] = dynare_simul_(3,M_.nstatic,M_.npred,M_.nboth,M_.nfwrd,exo_nbr, ...
y_(dr.order_var,1),ex_',M_.Sigma_e,options_.DynareRandomStreams.seed,dr.ys(dr.order_var),dr.g_0, ...
dr.g_1,dr.g_2,dr.g_3);
otherwise
error(['order = ' int2str(order) ' isn''t supported'])
end
mexErrCheck('dynare_simul_', err);
y_(dr.order_var,:) = y_;
else
if options_.block
if M_.maximum_lag > 0
k2 = dr.state_var;
else
k2 = [];
end;
order_var = 1:endo_nbr;
dr.order_var = order_var;
else
k2 = dr.kstate(find(dr.kstate(:,2) <= M_.maximum_lag+1),[1 2]);
k2 = k2(:,1)+(M_.maximum_lag+1-k2(:,2))*endo_nbr;
order_var = dr.order_var;
end;
switch iorder
case 1
if isempty(dr.ghu)% For (linearized) deterministic models.
for i = 2:iter+M_.maximum_lag
yhat = y_(order_var(k2),i-1);
y_(order_var,i) = dr.ghx*yhat;
end
elseif isempty(dr.ghx)% For (linearized) purely forward variables (no state variables).
y_(dr.order_var,:) = dr.ghu*transpose(ex_);
else
epsilon = dr.ghu*transpose(ex_);
for i = 2:iter+M_.maximum_lag
yhat = y_(order_var(k2),i-1);
y_(order_var,i) = dr.ghx*yhat + epsilon(:,i-1);
end
end
y_ = bsxfun(@plus,y_,dr.ys);
case 2
constant = dr.ys(order_var)+.5*dr.ghs2;
if options_.pruning
y__ = y0;
for i = 2:iter+M_.maximum_lag
yhat1 = y__(order_var(k2))-dr.ys(order_var(k2));
yhat2 = y_(order_var(k2),i-1)-dr.ys(order_var(k2));
epsilon = ex_(i-1,:)';
[abcOut1, err] = A_times_B_kronecker_C(.5*dr.ghxx,yhat1,options_.threads.kronecker.A_times_B_kronecker_C);
mexErrCheck('A_times_B_kronecker_C', err);
[abcOut2, err] = A_times_B_kronecker_C(.5*dr.ghuu,epsilon,options_.threads.kronecker.A_times_B_kronecker_C);
mexErrCheck('A_times_B_kronecker_C', err);
[abcOut3, err] = A_times_B_kronecker_C(dr.ghxu,yhat1,epsilon,options_.threads.kronecker.A_times_B_kronecker_C);
mexErrCheck('A_times_B_kronecker_C', err);
y_(order_var,i) = constant + dr.ghx*yhat2 + dr.ghu*epsilon ...
+ abcOut1 + abcOut2 + abcOut3;
y__(order_var) = dr.ys(order_var) + dr.ghx*yhat1 + dr.ghu*epsilon;
end
else
for i = 2:iter+M_.maximum_lag
yhat = y_(order_var(k2),i-1)-dr.ys(order_var(k2));
epsilon = ex_(i-1,:)';
[abcOut1, err] = A_times_B_kronecker_C(.5*dr.ghxx,yhat,options_.threads.kronecker.A_times_B_kronecker_C);
mexErrCheck('A_times_B_kronecker_C', err);
[abcOut2, err] = A_times_B_kronecker_C(.5*dr.ghuu,epsilon,options_.threads.kronecker.A_times_B_kronecker_C);
mexErrCheck('A_times_B_kronecker_C', err);
[abcOut3, err] = A_times_B_kronecker_C(dr.ghxu,yhat,epsilon,options_.threads.kronecker.A_times_B_kronecker_C);
mexErrCheck('A_times_B_kronecker_C', err);
y_(dr.order_var,i) = constant + dr.ghx*yhat + dr.ghu*epsilon ...
+ abcOut1 + abcOut2 + abcOut3;
end
end
case 3
% only with pruning
% the third moments of the shocks are assumed null. We don't have
% an interface for specifying them
ghx = dr.ghx;
ghu = dr.ghu;
ghxx = dr.ghxx;
ghxu = dr.ghxu;
ghuu = dr.ghuu;
ghs2 = dr.ghs2;
ghxxx = dr.ghxxx;
ghxxu = dr.ghxxu;
ghxuu = dr.ghxuu;
ghuuu = dr.ghuuu;
ghxss = dr.ghxss;
ghuss = dr.ghuss;
threads = options_.threads.kronecker.A_times_B_kronecker_C;
nspred = M_.nspred;
ipred = M_.nstatic+(1:nspred);
%construction follows Andreasen et al (2013), Technical
%Appendix, Formulas (65) and (66)
%split into first, second, and third order terms
yhat1 = y0(order_var(k2))-dr.ys(order_var(k2));
yhat2 = zeros(nspred,1);
yhat3 = zeros(nspred,1);
for i=2:iter+M_.maximum_lag
u = ex_(i-1,:)';
%construct terms of order 2 from second order part, based
%on linear component yhat1
[gyy, err] = A_times_B_kronecker_C(ghxx,yhat1,threads);
mexErrCheck('A_times_B_kronecker_C', err);
[guu, err] = A_times_B_kronecker_C(ghuu,u,threads);
mexErrCheck('A_times_B_kronecker_C', err);
[gyu, err] = A_times_B_kronecker_C(ghxu,yhat1,u,threads);
mexErrCheck('A_times_B_kronecker_C', err);
%construct terms of order 3 from second order part, based
%on order 2 component yhat2
[gyy12, err] = A_times_B_kronecker_C(ghxx,yhat1,yhat2,threads);
mexErrCheck('A_times_B_kronecker_C', err);
[gy2u, err] = A_times_B_kronecker_C(ghxu,yhat2,u,threads);
mexErrCheck('A_times_B_kronecker_C', err);
%construct terms of order 3, all based on first order component yhat1
y2a = kron(yhat1,yhat1);
[gyyy, err] = A_times_B_kronecker_C(ghxxx,y2a,yhat1,threads);
mexErrCheck('A_times_B_kronecker_C', err);
u2a = kron(u,u);
[guuu, err] = A_times_B_kronecker_C(ghuuu,u2a,u,threads);
mexErrCheck('A_times_B_kronecker_C', err);
yu = kron(yhat1,u);
[gyyu, err] = A_times_B_kronecker_C(ghxxu,yhat1,yu,threads);
mexErrCheck('A_times_B_kronecker_C', err);
[gyuu, err] = A_times_B_kronecker_C(ghxuu,yu,u,threads);
mexErrCheck('A_times_B_kronecker_C', err);
%add all terms of order 3, linear component based on third
%order yhat3
yhat3 = ghx*yhat3 +gyy12 ... % prefactor is 1/2*2=1, see (65) Appendix Andreasen et al.
+ gy2u ... % prefactor is 1/2*2=1, see (65) Appendix Andreasen et al.
+ 1/6*(gyyy + guuu + 3*(gyyu + gyuu + ghxss*yhat1 + ghuss*u)); %note: s is treated as variable, thus xss and uss are third order
yhat2 = ghx*yhat2 + 1/2*(gyy + guu + 2*gyu + ghs2);
yhat1 = ghx*yhat1 + ghu*u;
y_(order_var,i) = dr.ys(order_var)+yhat1 + yhat2 + yhat3; %combine terms again
yhat1 = yhat1(ipred);
yhat2 = yhat2(ipred);
yhat3 = yhat3(ipred);
end
end
end
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