146 lines
6.0 KiB
Matlab
146 lines
6.0 KiB
Matlab
function [oo_, maxerror] = perfect_foresight_solver_core(M_, options_, oo_)
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%function [oo_, maxerror] = perfect_foresight_solver_core(M_, options_, oo_)
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% Core function calling solvers for perfect foresight model
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%
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% INPUTS
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% - M_ [struct] contains a description of the model.
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% - options_ [struct] contains various options.
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% - oo_ [struct] contains results
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%
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% OUTPUTS
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% - oo_ [struct] contains results
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% - maxerror [double] contains the maximum absolute error
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% Copyright (C) 2015-2017 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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if options_.lmmcp.status
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options_.stack_solve_algo=7;
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options_.solve_algo = 10;
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end
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if options_.linear_approximation && ~(isequal(options_.stack_solve_algo,0) || isequal(options_.stack_solve_algo,7))
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error('perfect_foresight_solver: Option linear_approximation is only available with option stack_solve_algo equal to 0.')
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end
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if options_.linear && isequal(options_.stack_solve_algo,0)
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options_.linear_approximation = 1;
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end
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if options_.block
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if options_.bytecode
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try
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[info, tmp] = bytecode('dynamic', oo_.endo_simul, oo_.exo_simul, M_.params, repmat(oo_.steady_state,1,options_.periods+2), options_.periods);
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catch
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info = 1;
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end
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if info
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oo_.deterministic_simulation.status = false;
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else
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oo_.endo_simul = tmp;
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oo_.deterministic_simulation.status = true;
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end
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if options_.no_homotopy
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mexErrCheck('bytecode', info);
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end
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else
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oo_ = feval([M_.fname '_dynamic'], options_, M_, oo_);
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end
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else
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if options_.bytecode
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try
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[info, tmp] = bytecode('dynamic', oo_.endo_simul, oo_.exo_simul, M_.params, repmat(oo_.steady_state,1,options_.periods+2), options_.periods);
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catch
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info = 1;
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end
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if info
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oo_.deterministic_simulation.status = false;
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else
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oo_.endo_simul = tmp;
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oo_.deterministic_simulation.status = true;
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end
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if options_.no_homotopy
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mexErrCheck('bytecode', info);
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end
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else
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if M_.maximum_endo_lead == 0 % Purely backward model
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[oo_.endo_simul, oo_.deterministic_simulation] = ...
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sim1_purely_backward(oo_.endo_simul, oo_.exo_simul, oo_.steady_state, M_, options_);
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elseif M_.maximum_endo_lag == 0 % Purely forward model
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[oo_.endo_simul, oo_.deterministic_simulation] = ...
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sim1_purely_forward(oo_.endo_simul, oo_.exo_simul, oo_.steady_state, M_, options_);
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else % General case
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switch options_.stack_solve_algo
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case 0
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if options_.linear_approximation
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[oo_.endo_simul, oo_.deterministic_simulation] = ...
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sim1_linear(oo_.endo_simul, oo_.exo_simul, oo_.steady_state, oo_.exo_steady_state, M_, options_);
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else
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[oo_.endo_simul, oo_.deterministic_simulation] = ...
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sim1(oo_.endo_simul, oo_.exo_simul, oo_.steady_state, M_, options_);
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end
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case 6
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if options_.linear_approximation
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error('Invalid value of stack_solve_algo option!')
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end
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[oo_.endo_simul, oo_.deterministic_simulation] = ...
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sim1_lbj(oo_.endo_simul, oo_.exo_simul, oo_.steady_state, M_, options_);
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case 7
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if options_.linear_approximation
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if isequal(options_.solve_algo, 10)
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warning('It would be more efficient to set option solve_algo equal to 0!')
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end
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[oo_.endo_simul, oo_.deterministic_simulation] = ...
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solve_stacked_linear_problem(oo_.endo_simul, oo_.exo_simul, oo_.steady_state, oo_.exo_steady_state, M_, options_);
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else
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[oo_.endo_simul, oo_.deterministic_simulation] = ...
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solve_stacked_problem(oo_.endo_simul, oo_.exo_simul, oo_.steady_state, M_, options_);
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end
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otherwise
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error('Invalid value of stack_solve_algo option!')
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end
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end
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end
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end
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if nargout>1
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y0 = oo_.endo_simul(:,1);
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yT = oo_.endo_simul(:,options_.periods+2);
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yy = oo_.endo_simul(:,2:options_.periods+1);
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if ~exist('illi')
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illi = M_.lead_lag_incidence';
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[i_cols,junk,i_cols_j] = find(illi(:));
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illi = illi(:,2:3);
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[i_cols_J1,junk,i_cols_1] = find(illi(:));
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i_cols_T = nonzeros(M_.lead_lag_incidence(1:2,:)');
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end
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if options_.block && ~options_.bytecode
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maxerror = oo_.deterministic_simulation.error;
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else
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if options_.bytecode
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[chck, residuals, junk]= bytecode('dynamic','evaluate', oo_.endo_simul, oo_.exo_simul, M_.params, oo_.steady_state, 1);
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else
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residuals = perfect_foresight_problem(yy(:),str2func([M_.fname '_dynamic']), y0, yT, ...
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oo_.exo_simul,M_.params,oo_.steady_state, ...
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M_.maximum_lag,options_.periods,M_.endo_nbr,i_cols, ...
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i_cols_J1, i_cols_1, i_cols_T, i_cols_j, ...
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M_.NNZDerivatives(1));
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end
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maxerror = max(max(abs(residuals)));
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end
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end
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