133 lines
4.3 KiB
Matlab
133 lines
4.3 KiB
Matlab
function sim1
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% function sim1
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% performs deterministic simulations with lead or lag on one period
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%
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% INPUTS
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% ...
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% OUTPUTS
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% ...
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% ALGORITHM
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% Laffargue, Boucekkine, Juillard (LBJ)
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% see Juillard (1996) Dynare: A program for the resolution and
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% simulation of dynamic models with forward variables through the use
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% of a relaxation algorithm. CEPREMAP. Couverture Orange. 9602.
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%
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% SPECIAL REQUIREMENTS
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% None.
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% Copyright (C) 1996-2008 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_ oo_
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global iyp iyf ct_ M_ it_ c
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lead_lag_incidence = M_.lead_lag_incidence;
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ny = size(oo_.endo_simul,1) ;
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nyp = nnz(lead_lag_incidence(1,:)) ;
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nyf = nnz(lead_lag_incidence(3,:)) ;
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nrs = ny+nyp+nyf+1 ;
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nrc = nyf+1 ;
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iyf = find(lead_lag_incidence(3,:)>0) ;
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iyp = find(lead_lag_incidence(1,:)>0) ;
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isp = [1:nyp] ;
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is = [nyp+1:ny+nyp] ;
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isf = iyf+nyp ;
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isf1 = [nyp+ny+1:nyf+nyp+ny+1] ;
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stop = 0 ;
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iz = [1:ny+nyp+nyf];
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disp (['-----------------------------------------------------']) ;
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disp (['MODEL SIMULATION :']) ;
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fprintf('\n') ;
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it_init = M_.maximum_lag+1 ;
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h1 = clock ;
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for iter = 1:options_.maxit
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h2 = clock ;
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if ct_ == 0
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c = zeros(ny*options_.periods,nrc) ;
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else
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c = zeros(ny*(options_.periods+1),nrc) ;
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end
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it_ = it_init ;
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z = [oo_.endo_simul(iyp,it_-1) ; oo_.endo_simul(:,it_) ; oo_.endo_simul(iyf,it_+1)] ;
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[d1,M_.jacobia] = feval([M_.fname '_dynamic'],z,oo_.exo_simul, M_.params, it_);
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M_.jacobia = [M_.jacobia(:,iz) -d1] ;
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ic = [1:ny] ;
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icp = iyp ;
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c (ic,:) = M_.jacobia(:,is)\M_.jacobia(:,isf1) ;
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for it_ = it_init+(1:options_.periods-1)
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z = [oo_.endo_simul(iyp,it_-1) ; oo_.endo_simul(:,it_) ; oo_.endo_simul(iyf,it_+1)] ;
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[d1,M_.jacobia] = feval([M_.fname '_dynamic'],z,oo_.exo_simul, M_.params, it_);
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M_.jacobia = [M_.jacobia(:,iz) -d1] ;
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M_.jacobia(:,[isf nrs]) = M_.jacobia(:,[isf nrs])-M_.jacobia(:,isp)*c(icp,:) ;
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ic = ic + ny ;
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icp = icp + ny ;
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c (ic,:) = M_.jacobia(:,is)\M_.jacobia(:,isf1) ;
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end
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if ct_ == 1
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s = eye(ny) ;
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s(:,isf) = s(:,isf)+c(ic,1:nyf) ;
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ic = ic + ny ;
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c(ic,nrc) = s\c(:,nrc) ;
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c = bksup1(ny,nrc) ;
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c = reshape(c,ny,options_.periods+1) ;
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oo_.endo_simul(:,it_init+(0:options_.periods)) = oo_.endo_simul(:,it_init+(0:options_.periods))+options_.slowc*c ;
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else
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c = bksup1(ny,nrc) ;
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c = reshape(c,ny,options_.periods) ;
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oo_.endo_simul(:,it_init+(0:options_.periods-1)) = oo_.endo_simul(:,it_init+(0:options_.periods-1))+options_.slowc*c ;
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end
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err = max(max(abs(c./options_.scalv')));
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disp([num2str(iter) ' - err = ' num2str(err)]) ;
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disp([' Time of iteration :' num2str(etime(clock,h2))]) ;
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if err < options_.dynatol
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stop = 1 ;
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fprintf('\n') ;
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disp([' Total time of simulation :' num2str(etime(clock,h1))]) ;
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fprintf('\n') ;
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disp([' Convergency obtained.']) ;
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fprintf('\n') ;
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oo_.deterministic_simulation.status = 1;% Convergency obtained.
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oo_.deterministic_simulation.error = err;
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oo_.deterministic_simulation.iterations = iter;
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break
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end
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end
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if ~stop
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fprintf('\n') ;
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disp([' Total time of simulation :' num2str(etime(clock,h1))]) ;
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fprintf('\n') ;
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disp(['WARNING : maximum number of iterations is reached (modify options_.maxit).']) ;
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fprintf('\n') ;
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oo_.deterministic_simulation.status = 0;% more iterations are needed.
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oo_.deterministic_simulation.error = err;
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oo_.deterministic_simulation.errors = c/abs(err);
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oo_.deterministic_simulation.iterations = options_.maxit;
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end
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disp (['-----------------------------------------------------']) ;
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return ;
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% 08/24/01 MJ added start_simul |