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function [endogenousvariables, info] = solve_stacked_problem(endogenousvariables, exogenousvariables, steadystate, M, options)
% Solves the perfect foresight model using dynare_solve
%
% INPUTS
% - endogenousvariables [double] N*T array, paths for the endogenous variables (initial guess).
% - exogenousvariables [double] T*M array, paths for the exogenous variables.
% - steadystate [double] N*1 array, steady state for the endogenous variables.
% - M [struct] contains a description of the model.
% - options [struct] contains various options.
%
% OUTPUTS
% - endogenousvariables [double] N*T array, paths for the endogenous variables (solution of the perfect foresight model).
% - info [struct] contains informations about the results.
% Copyright (C) 2015-2019 Dynare Team
%
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% Dynare is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
[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] = ...
initialize_stacked_problem(endogenousvariables, options, M, steadystate);
if (options.solve_algo == 10 || options.solve_algo == 11)% mixed complementarity problem
[lb,ub,eq_index] = get_complementarity_conditions(M,options.ramsey_policy);
if options.linear_approximation
lb = lb - steadystate_y;
ub = ub - steadystate_y;
end
if options.solve_algo == 10
options.lmmcp.lb = repmat(lb,options.periods,1);
options.lmmcp.ub = repmat(ub,options.periods,1);
elseif options.solve_algo == 11
options.mcppath.lb = repmat(lb,options.periods,1);
options.mcppath.ub = repmat(ub,options.periods,1);
end
[y, check] = dynare_solve(@perfect_foresight_mcp_problem,z(:),options, ...
dynamicmodel, y0, yT, ...
exogenousvariables, M.params, steadystate, ...
M.maximum_lag, options.periods, M.endo_nbr, i_cols, ...
i_cols_J1, i_cols_1, i_cols_T, i_cols_j, i_cols_0, i_cols_J0, ...
eq_index);
else
[y, check] = dynare_solve(@perfect_foresight_problem,z(:), options, y0, yT, exogenousvariables, M.params, steadystate, options.periods, M, options);
end
if all(imag(y)<.1*options.dynatol.x)
if ~isreal(y)
y = real(y);
end
else
check = 1;
end
endogenousvariables(:, M.maximum_lag+(1:options.periods)) = reshape(y, M.endo_nbr, options.periods);
if check
info.status = false;
else
info.status = true;
end
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