100 lines
4.5 KiB
Matlab
100 lines
4.5 KiB
Matlab
function [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_y)
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% Sets up the stacked perfect foresight problem for use with dynare_solve.m
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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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% - options [struct] contains various options.
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% - M [struct] contains a description of the model.
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% - steadystate_y [double] N*1 array, steady state for the endogenous variables.
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%
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% OUTPUTS
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% - options [struct] contains various options.
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% - y0 [double] N*1 array, initial conditions for the endogenous variables
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% - yT [double] N*1 array, terminal conditions for the endogenous variables
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% - z [double] T*M array, paths for the exogenous variables.
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% - i_cols [double] indices of variables appearing in M.lead_lag_incidence
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% and that need to be passed to _dynamic-file
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% - i_cols_J1 [double] indices of contemporaneous and forward looking variables
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% appearing in M.lead_lag_incidence
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% - i_cols_T [double] columns of dynamic Jacobian related to
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% contemporaneous and backward-looking
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% variables (relevant in last period)
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% - i_cols_j [double] indices of variables in M.lead_lag_incidence
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% in dynamic Jacobian (relevant in intermediate periods)
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% - i_cols_1 [double] indices of contemporaneous and forward looking variables in
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% M.lead_lag_incidence in dynamic Jacobian (relevant in first period)
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% - i_cols_0 [double] indices of contemporaneous variables in M.lead_lag_incidence in dynamic
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% Jacobian (relevant in problems with periods=1)
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% - i_cols_J0 [double] indices of contemporaneous variables appearing in M.lead_lag_incidence (relevant in problems with periods=1)
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% - dynamicmodel [handle] function handle to _dynamic-file
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% Copyright © 2015-2020 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 <https://www.gnu.org/licenses/>.
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periods = options.periods;
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if (options.solve_algo == 10)
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if ~isfield(options.lmmcp,'lb')
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[lb,ub,pfm.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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options.lmmcp.lb = repmat(lb,periods,1);
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options.lmmcp.ub = repmat(ub,periods,1);
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end
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elseif (options.solve_algo == 11)
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if ~isfield(options.mcppath,'lb')
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[lb,ub,pfm.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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options.mcppath.lb = repmat(lb,periods,1);
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options.mcppath.ub = repmat(ub,periods,1);
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end
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end
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if M.maximum_lag > 0
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y0 = endogenousvariables(:, M.maximum_lag);
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else
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y0 = NaN(M.endo_nbr, 1);
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end
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if M.maximum_lead > 0
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yT = endogenousvariables(:, M.maximum_lag+periods+1);
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else
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yT = NaN(M.endo_nbr, 1);
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end
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z = endogenousvariables(:,M.maximum_lag+(1:periods));
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illi = M.lead_lag_incidence';
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[i_cols,~,i_cols_j] = find(illi(:));
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if M.maximum_endo_lag == 0
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i_cols = i_cols + M.endo_nbr;
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end
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illi = illi(:,(1+M.maximum_endo_lag):(1+M.maximum_endo_lag+M.maximum_endo_lead));
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[i_cols_J1,~,i_cols_1] = find(illi(:));
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i_cols_T = nonzeros(M.lead_lag_incidence(1:(1+M.maximum_endo_lag),:)');
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if periods==1
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i_cols_0 = nonzeros(M.lead_lag_incidence(1+M.maximum_endo_lag,:)');
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i_cols_J0 = find(M.lead_lag_incidence(1+M.maximum_endo_lag,:)');
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else
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i_cols_0 = [];
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i_cols_J0 = [];
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end
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dynamicmodel = str2func([M.fname,'.dynamic']);
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