1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
|
function [endogenousvariables, success, maxerror] = solve_stacked_problem(endogenousvariables, exogenousvariables, steadystate, M_, options_)
% [endogenousvariables, success, maxerror] = 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).
% - success [logical] Whether a solution was found
% - maxerror [double] 1-norm of the residual
% Copyright © 2015-2023 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, res, ~, errorcode] = dynare_solve(@perfect_foresight_mcp_problem, z(:), ...
options_.simul.maxit, options_.dynatol.f, options_.dynatol.x, ...
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);
eq_to_ignore=find(isfinite(lb) | isfinite(ub));
else
[y, check, res, ~, errorcode] = dynare_solve(@perfect_foresight_problem, z(:), ...
options_.simul.maxit, options_.dynatol.f, options_.dynatol.x, ...
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);
residuals=zeros(size(endogenousvariables));
residuals(:, M_.maximum_lag+(1:options_.periods)) = reshape(res, M_.endo_nbr, options_.periods);
if (options_.solve_algo == 10 || options_.solve_algo == 11)% mixed complementarity problem
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;
end
maxerror = max(max(abs(residuals)));
success = ~check;
if ~success && options_.debug
dprintf('solve_stacked_problem: Nonlinear solver routine failed with errorcode=%i.', errorcode)
end
|
