130 lines
3.6 KiB
Matlab
130 lines
3.6 KiB
Matlab
function [flag,endo_simul,err] = solve_perfect_foresight_model(endo_simul,exo_simul,pfm)
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% Copyright (C) 2012-2020 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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flag = 0;
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err = 0;
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stop = 0;
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nan_flag = 0;
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model_dynamic = pfm.dynamic_model;
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Y = endo_simul(:);
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if pfm.verbose
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disp (['-----------------------------------------------------']) ;
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disp (['MODEL SIMULATION :']) ;
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fprintf('\n') ;
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end
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if pfm.use_bytecode
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try
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endo_simul=bytecode(Y, exo_simul, pfm.params);
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flag = 0;
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catch ME
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disp(ME.message);
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flag = 1;
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end
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return
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end
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z = Y(find(pfm.lead_lag_incidence'));
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[d1,jacobian] = model_dynamic(z,exo_simul,pfm.params,pfm.steady_state,2);
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% Initialization of the jacobian of the stacked model.
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A = sparse([],[],[],pfm.periods*pfm.ny,pfm.periods*pfm.ny,pfm.periods*nnz(jacobian));
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% Initialization of the Newton residuals.
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res = zeros(pfm.periods*pfm.ny,1);
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h1 = clock;
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% Newton loop.
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for iter = 1:pfm.maxit_
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h2 = clock;
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i_rows = 1:pfm.ny;
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i_cols = find(pfm.lead_lag_incidence');
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i_cols_A = i_cols;
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% Fill the jacobian of the stacked model.
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for it = 2:(pfm.periods+1)
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[d1,jacobian] = model_dynamic(Y(i_cols),exo_simul,pfm.params,pfm.steady_state,it);
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if it == 2
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A(i_rows,pfm.i_cols_A1) = jacobian(:,pfm.i_cols_1);
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elseif it == pfm.periods+1
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A(i_rows,i_cols_A(pfm.i_cols_T)) = jacobian(:,pfm.i_cols_T);
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else
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A(i_rows,i_cols_A) = jacobian(:,pfm.i_cols_j);
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end
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res(i_rows) = d1;
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i_rows = i_rows + pfm.ny;
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i_cols = i_cols + pfm.ny;
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if it > 2
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i_cols_A = i_cols_A + pfm.ny;
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end
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end
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% Stop if Newton residuals are zero.
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err = max(abs(res));
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if err < pfm.tolerance
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stop = 1 ;
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if pfm.verbose
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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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end
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flag = 0;% Convergency obtained.
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endo_simul = reshape(Y,pfm.ny,pfm.periods+2);
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break
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end
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% Compute the Newton step.
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dy = -A\res;
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if any(isnan(dy))
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nan_flag = 1;
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break
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end
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% Update the endogenous variables paths.
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Y(pfm.i_upd) = Y(pfm.i_upd) + dy;
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end
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if ~stop
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if pfm.verbose
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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_.simul.maxit).']) ;
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fprintf('\n') ;
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end
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flag = 1;% more iterations are needed.
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endo_simul = 1;
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end
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if nan_flag
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if pfm.verbose
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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 : NaNs!']) ;
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fprintf('\n') ;
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end
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flag = 1;
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endo_simul = 1;
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end
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if pfm.verbose
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disp (['-----------------------------------------------------']) ;
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end
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