137 lines
4.3 KiB
Matlab
137 lines
4.3 KiB
Matlab
function [endogenousvariables, info] = sim1_lbj(endogenousvariables, exogenousvariables, steadystate, M, options)
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% Performs deterministic simulations with lead or lag on one period using the historical LBJ algorithm
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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 © 1996-2022 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 <https://www.gnu.org/licenses/>.
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lead_lag_incidence = M.lead_lag_incidence;
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ny = size(endogenousvariables,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 = false;
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iz = [1:ny+nyp+nyf];
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dynamicmodel = sprintf('%s.dynamic', M.fname);
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verbose = options.verbosity;
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if verbose
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printline(56)
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disp(['MODEL SIMULATION :'])
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skipline()
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end
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it_init = M.maximum_lag+1;
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h1 = clock;
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for iter = 1:options.simul.maxit
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h2 = clock;
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if ~options.terminal_condition
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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 = [endogenousvariables(iyp,it_-1) ; endogenousvariables(:,it_) ; endogenousvariables(iyf,it_+1)];
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[d1, jacobian] = feval(dynamicmodel, z, exogenousvariables, M.params, steadystate, it_);
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jacobian = [jacobian(:,iz), -d1];
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ic = [1:ny];
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icp = iyp;
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c (ic,:) = jacobian(:,is)\jacobian(:,isf1);
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for it_ = it_init+(1:options.periods-1)
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z = [endogenousvariables(iyp,it_-1) ; endogenousvariables(:,it_) ; endogenousvariables(iyf,it_+1)];
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[d1, jacobian] = feval(dynamicmodel, z, exogenousvariables, M.params, steadystate, it_);
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jacobian = [jacobian(:,iz), -d1];
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jacobian(:,[isf nrs]) = jacobian(:,[isf nrs])-jacobian(:,isp)*c(icp,:);
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ic = ic + ny;
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icp = icp + ny;
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c (ic,:) = jacobian(:,is)\jacobian(:,isf1);
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end
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if options.terminal_condition == 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(ic,nrc);
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c = bksup1(c, ny, nrc, iyf, options.periods);
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c = reshape(c, ny, options.periods+1);
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endogenousvariables(:,it_init+(0:options.periods)) = endogenousvariables(:,it_init+(0:options.periods))+c;
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else
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c = bksup1(c, ny, nrc, iyf, options.periods);
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c = reshape(c, ny, options.periods);
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endogenousvariables(:,it_init+(0:options.periods-1)) = endogenousvariables(:,it_init+(0:options.periods-1))+c;
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end
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err = max(max(abs(c./options.scalv')));
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if verbose
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str = sprintf('Iter: %s,\t err. = %s, \t time = %s', num2str(iter), num2str(err), num2str(etime(clock, h2)));
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disp(str);
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end
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if err < options.dynatol.f
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stop = true;
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if verbose
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skipline()
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disp(sprintf('Total time of simulation: %s', num2str(etime(clock,h1))))
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end
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info.status = 1;% Convergency obtained.
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info.error = err;
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info.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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if verbose
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disp(sprintf('Total time of simulation: %s.', num2str(etime(clock,h1))))
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disp('Maximum number of iterations is reached (modify option maxit).')
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end
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info.status = 0;% more iterations are needed.
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info.error = err;
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info.errors = c/abs(err);
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info.iterations = options.simul.maxit;
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end
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if verbose
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if stop
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printline(56)
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else
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printline(62)
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end
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skipline()
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end
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