133 lines
4.5 KiB
Matlab
133 lines
4.5 KiB
Matlab
function sim1_lbj()
|
|
% function sim1_lbj
|
|
% performs deterministic simulations with lead or lag on one period
|
|
% using the historical LBJ algorithm
|
|
%
|
|
% INPUTS
|
|
% ...
|
|
% OUTPUTS
|
|
% ...
|
|
% ALGORITHM
|
|
% Laffargue, Boucekkine, Juillard (LBJ)
|
|
% see Juillard (1996) Dynare: A program for the resolution and
|
|
% simulation of dynamic models with forward variables through the use
|
|
% of a relaxation algorithm. CEPREMAP. Couverture Orange. 9602.
|
|
%
|
|
% SPECIAL REQUIREMENTS
|
|
% None.
|
|
|
|
% Copyright (C) 1996-2012 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_ oo_
|
|
|
|
lead_lag_incidence = M_.lead_lag_incidence;
|
|
|
|
ny = size(oo_.endo_simul,1) ;
|
|
nyp = nnz(lead_lag_incidence(1,:)) ;
|
|
nyf = nnz(lead_lag_incidence(3,:)) ;
|
|
nrs = ny+nyp+nyf+1 ;
|
|
nrc = nyf+1 ;
|
|
iyf = find(lead_lag_incidence(3,:)>0) ;
|
|
iyp = find(lead_lag_incidence(1,:)>0) ;
|
|
isp = [1:nyp] ;
|
|
is = [nyp+1:ny+nyp] ;
|
|
isf = iyf+nyp ;
|
|
isf1 = [nyp+ny+1:nyf+nyp+ny+1] ;
|
|
stop = 0 ;
|
|
iz = [1:ny+nyp+nyf];
|
|
|
|
disp (['-----------------------------------------------------']) ;
|
|
disp (['MODEL SIMULATION :']) ;
|
|
fprintf('\n') ;
|
|
|
|
it_init = M_.maximum_lag+1 ;
|
|
|
|
h1 = clock ;
|
|
for iter = 1:options_.simul.maxit
|
|
h2 = clock ;
|
|
|
|
if options_.terminal_condition == 0
|
|
c = zeros(ny*options_.periods,nrc) ;
|
|
else
|
|
c = zeros(ny*(options_.periods+1),nrc) ;
|
|
end
|
|
|
|
it_ = it_init ;
|
|
z = [oo_.endo_simul(iyp,it_-1) ; oo_.endo_simul(:,it_) ; oo_.endo_simul(iyf,it_+1)] ;
|
|
[d1,jacobian] = feval([M_.fname '_dynamic'],z,oo_.exo_simul, M_.params, oo_.steady_state,it_);
|
|
jacobian = [jacobian(:,iz) -d1] ;
|
|
ic = [1:ny] ;
|
|
icp = iyp ;
|
|
c (ic,:) = jacobian(:,is)\jacobian(:,isf1) ;
|
|
for it_ = it_init+(1:options_.periods-1)
|
|
z = [oo_.endo_simul(iyp,it_-1) ; oo_.endo_simul(:,it_) ; oo_.endo_simul(iyf,it_+1)] ;
|
|
[d1,jacobian] = feval([M_.fname '_dynamic'],z,oo_.exo_simul, ...
|
|
M_.params, oo_.steady_state, it_);
|
|
jacobian = [jacobian(:,iz) -d1] ;
|
|
jacobian(:,[isf nrs]) = jacobian(:,[isf nrs])-jacobian(:,isp)*c(icp,:) ;
|
|
ic = ic + ny ;
|
|
icp = icp + ny ;
|
|
c (ic,:) = jacobian(:,is)\jacobian(:,isf1) ;
|
|
end
|
|
|
|
if options_.terminal_condition == 1
|
|
s = eye(ny) ;
|
|
s(:,isf) = s(:,isf)+c(ic,1:nyf) ;
|
|
ic = ic + ny ;
|
|
c(ic,nrc) = s\c(ic,nrc) ;
|
|
c = bksup1(c,ny,nrc,iyf,options_.periods) ;
|
|
c = reshape(c,ny,options_.periods+1) ;
|
|
oo_.endo_simul(:,it_init+(0:options_.periods)) = oo_.endo_simul(:,it_init+(0:options_.periods))+options_.slowc*c ;
|
|
else
|
|
c = bksup1(c,ny,nrc,iyf,options_.periods) ;
|
|
c = reshape(c,ny,options_.periods) ;
|
|
oo_.endo_simul(:,it_init+(0:options_.periods-1)) = oo_.endo_simul(:,it_init+(0:options_.periods-1))+options_.slowc*c ;
|
|
end
|
|
|
|
err = max(max(abs(c./options_.scalv')));
|
|
disp([num2str(iter) ' - err = ' num2str(err)]) ;
|
|
disp([' Time of iteration :' num2str(etime(clock,h2))]) ;
|
|
|
|
if err < options_.dynatol.f
|
|
stop = 1 ;
|
|
fprintf('\n') ;
|
|
disp([' Total time of simulation :' num2str(etime(clock,h1))]) ;
|
|
fprintf('\n') ;
|
|
disp([' Convergency obtained.']) ;
|
|
fprintf('\n') ;
|
|
oo_.deterministic_simulation.status = 1;% Convergency obtained.
|
|
oo_.deterministic_simulation.error = err;
|
|
oo_.deterministic_simulation.iterations = iter;
|
|
break
|
|
end
|
|
end
|
|
|
|
if ~stop
|
|
fprintf('\n') ;
|
|
disp([' Total time of simulation :' num2str(etime(clock,h1))]) ;
|
|
fprintf('\n') ;
|
|
disp(['WARNING : maximum number of iterations is reached (modify options_.simul.maxit).']) ;
|
|
fprintf('\n') ;
|
|
oo_.deterministic_simulation.status = 0;% more iterations are needed.
|
|
oo_.deterministic_simulation.error = err;
|
|
oo_.deterministic_simulation.errors = c/abs(err);
|
|
oo_.deterministic_simulation.iterations = options_.simul.maxit;
|
|
end
|
|
disp (['-----------------------------------------------------']) ;
|
|
|