139 lines
5.8 KiB
Matlab
139 lines
5.8 KiB
Matlab
function y_=simult_(y0,dr,ex_,iorder)
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% Simulates the model using a perturbation approach, given the path for the exogenous variables and the
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% decision rules.
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%
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% INPUTS
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% y0 [double] n*1 vector, initial value (n is the number of declared endogenous variables plus the number
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% of auxilliary variables for lags and leads)
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% dr [struct] matlab's structure where the reduced form solution of the model is stored.
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% ex_ [double] T*q matrix of innovations.
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% iorder [integer] order of the taylor approximation.
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%
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% OUTPUTS
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% y_ [double] n*(T+1) time series for the endogenous variables.
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright (C) 2001-2011 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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global M_ options_
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iter = size(ex_,1);
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y_ = zeros(size(y0,1),iter+M_.maximum_lag);
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y_(:,1) = y0;
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% stoch_simul sets k_order_solver=1 if order=3, but does so only locally, so we
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% have to do it here also
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if options_.order == 3
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options_.k_order_solver = 1;
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end
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if ~options_.k_order_solver
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if iorder==1
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y_(:,1) = y_(:,1)-dr.ys;
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end
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end
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if options_.k_order_solver% Call dynare++ routines.
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ex_ = [zeros(1,M_.exo_nbr); ex_];
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switch options_.order
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case 1
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[err, y_] = dynare_simul_(1,dr.nstatic,dr.npred-dr.nboth,dr.nboth,dr.nfwrd,M_.exo_nbr, ...
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y_(dr.order_var,1),ex_',M_.Sigma_e,options_.DynareRandomStreams.seed,dr.ys(dr.order_var),...
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zeros(M_.endo_nbr,1),dr.g_1);
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case 2
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[err, y_] = dynare_simul_(2,dr.nstatic,dr.npred-dr.nboth,dr.nboth,dr.nfwrd,M_.exo_nbr, ...
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y_(dr.order_var,1),ex_',M_.Sigma_e,options_.DynareRandomStreams.seed,dr.ys(dr.order_var),dr.g_0, ...
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dr.g_1,dr.g_2);
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case 3
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[err, y_] = dynare_simul_(3,dr.nstatic,dr.npred-dr.nboth,dr.nboth,dr.nfwrd,M_.exo_nbr, ...
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y_(dr.order_var,1),ex_',M_.Sigma_e,options_.DynareRandomStreams.seed,dr.ys(dr.order_var),dr.g_0, ...
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dr.g_1,dr.g_2,dr.g_3);
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otherwise
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error(['order = ' int2str(order) ' isn''t supported'])
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end
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mexErrCheck('dynare_simul_', err);
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y_(dr.order_var,:) = y_;
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else
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if options_.block
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if M_.maximum_lag > 0
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k2 = dr.state_var;
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else
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k2 = [];
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end;
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order_var = 1:M_.endo_nbr;
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dr.order_var = order_var;
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else
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k2 = dr.kstate(find(dr.kstate(:,2) <= M_.maximum_lag+1),[1 2]);
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k2 = k2(:,1)+(M_.maximum_lag+1-k2(:,2))*M_.endo_nbr;
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order_var = dr.order_var;
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end;
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switch iorder
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case 1
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if isempty(dr.ghu)% For (linearized) deterministic models.
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for i = 2:iter+M_.maximum_lag
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yhat = y_(order_var(k2),i-1);
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y_(order_var,i) = dr.ghx*yhat;
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end
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elseif isempty(dr.ghx)% For (linearized) purely forward variables (no state variables).
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y_(dr.order_var,:) = dr.ghu*transpose(ex_);
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else
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epsilon = dr.ghu*transpose(ex_);
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for i = 2:iter+M_.maximum_lag
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yhat = y_(order_var(k2),i-1);
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y_(order_var,i) = dr.ghx*yhat + epsilon(:,i-1);
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end
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end
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y_ = bsxfun(@plus,y_,dr.ys);
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case 2
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constant = dr.ys(order_var)+.5*dr.ghs2;
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if options_.pruning
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y__ = y0;
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for i = 2:iter+M_.maximum_lag
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yhat1 = y__(order_var(k2))-dr.ys(order_var(k2));
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yhat2 = y_(order_var(k2),i-1)-dr.ys(order_var(k2));
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epsilon = ex_(i-1,:)';
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[abcOut1, err] = A_times_B_kronecker_C(.5*dr.ghxx,yhat1,options_.threads.kronecker.A_times_B_kronecker_C);
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mexErrCheck('A_times_B_kronecker_C', err);
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[abcOut2, err] = A_times_B_kronecker_C(.5*dr.ghuu,epsilon,options_.threads.kronecker.A_times_B_kronecker_C);
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mexErrCheck('A_times_B_kronecker_C', err);
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[abcOut3, err] = A_times_B_kronecker_C(dr.ghxu,yhat1,epsilon,options_.threads.kronecker.A_times_B_kronecker_C);
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mexErrCheck('A_times_B_kronecker_C', err);
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y_(order_var,i) = constant + dr.ghx*yhat2 + dr.ghu*epsilon ...
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+ abcOut1 + abcOut2 + abcOut3;
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y__(order_var) = dr.ys(order_var) + dr.ghx*yhat1 + dr.ghu*epsilon;
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end
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else
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for i = 2:iter+M_.maximum_lag
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yhat = y_(order_var(k2),i-1)-dr.ys(order_var(k2));
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epsilon = ex_(i-1,:)';
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[abcOut1, err] = A_times_B_kronecker_C(.5*dr.ghxx,yhat,options_.threads.kronecker.A_times_B_kronecker_C);
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mexErrCheck('A_times_B_kronecker_C', err);
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[abcOut2, err] = A_times_B_kronecker_C(.5*dr.ghuu,epsilon,options_.threads.kronecker.A_times_B_kronecker_C);
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mexErrCheck('A_times_B_kronecker_C', err);
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[abcOut3, err] = A_times_B_kronecker_C(dr.ghxu,yhat,epsilon,options_.threads.kronecker.A_times_B_kronecker_C);
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mexErrCheck('A_times_B_kronecker_C', err);
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y_(dr.order_var,i) = constant + dr.ghx*yhat + dr.ghu*epsilon ...
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+ abcOut1 + abcOut2 + abcOut3;
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end
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end
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end
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end |