86 lines
4.3 KiB
Matlab
86 lines
4.3 KiB
Matlab
function [endogenousvariables, success, maxerror] = solve_stacked_problem(endogenousvariables, exogenousvariables, steadystate, M_, options_)
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% [endogenousvariables, success, maxerror] = solve_stacked_problem(endogenousvariables, exogenousvariables, steadystate, M_, options_)
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% Solves the perfect foresight model using dynare_solve
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%
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% INPUTS
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% - endogenousvariables [double] N*T array, paths for the endogenous variables (initial guess).
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% - exogenousvariables [double] T*M array, paths for the exogenous variables.
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% - steadystate [double] N*1 array, steady state for the endogenous variables.
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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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%
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% OUTPUTS
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% - endogenousvariables [double] N*T array, paths for the endogenous variables (solution of the perfect foresight model).
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% - success [logical] Whether a solution was found
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% - maxerror [double] 1-norm of the residual
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% Copyright © 2015-2023 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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[options_, y0, yT, z, i_cols, i_cols_J1, i_cols_T, i_cols_j, i_cols_1, i_cols_0, i_cols_J0, dynamicmodel] = ...
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initialize_stacked_problem(endogenousvariables, options_, M_, steadystate);
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if (options_.solve_algo == 10 || options_.solve_algo == 11)% mixed complementarity problem
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[lb,ub,eq_index] = get_complementarity_conditions(M_,options_.ramsey_policy);
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if options_.linear_approximation
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lb = lb - steadystate_y;
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ub = ub - steadystate_y;
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end
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if options_.solve_algo == 10
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options_.lmmcp.lb = repmat(lb,options_.periods,1);
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options_.lmmcp.ub = repmat(ub,options_.periods,1);
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elseif options_.solve_algo == 11
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options_.mcppath.lb = repmat(lb,options_.periods,1);
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options_.mcppath.ub = repmat(ub,options_.periods,1);
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end
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[y, check, res, ~, errorcode] = dynare_solve(@perfect_foresight_mcp_problem, z(:), ...
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options_.simul.maxit, options_.dynatol.f, options_.dynatol.x, ...
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options_, ...
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dynamicmodel, y0, yT, ...
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exogenousvariables, M_.params, steadystate, ...
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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, i_cols_0, i_cols_J0, ...
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eq_index);
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eq_to_ignore=find(isfinite(lb) | isfinite(ub));
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else
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[y, check, res, ~, errorcode] = dynare_solve(@perfect_foresight_problem, z(:), ...
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options_.simul.maxit, options_.dynatol.f, options_.dynatol.x, ...
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options_, y0, yT, exogenousvariables, M_.params, steadystate, options_.periods, M_, options_);
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end
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if all(imag(y)<.1*options_.dynatol.x)
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if ~isreal(y)
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y = real(y);
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end
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else
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check = 1;
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end
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endogenousvariables(:, M_.maximum_lag+(1:options_.periods)) = reshape(y, M_.endo_nbr, options_.periods);
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residuals=zeros(size(endogenousvariables));
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residuals(:, M_.maximum_lag+(1:options_.periods)) = reshape(res, M_.endo_nbr, options_.periods);
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if (options_.solve_algo == 10 || options_.solve_algo == 11)% mixed complementarity problem
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residuals(eq_to_ignore,bsxfun(@le, endogenousvariables(eq_to_ignore,:), lb(eq_to_ignore)+eps) | bsxfun(@ge,endogenousvariables(eq_to_ignore,:),ub(eq_to_ignore)-eps))=0;
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end
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maxerror = max(max(abs(residuals)));
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success = ~check;
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if ~success && options_.debug
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dprintf('solve_stacked_problem: Nonlinear solver routine failed with errorcode=%i.', errorcode)
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end
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