193 lines
9.6 KiB
Matlab
193 lines
9.6 KiB
Matlab
function [ysim, xsim, errorflag] = simul_backward_nonlinear_model_(initialconditions, samplesize, DynareOptions, DynareModel, DynareOutput, innovations, iy1, model_dynamic)
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% Simulates a stochastic non linear backward looking model with arbitrary precision (a deterministic solver is used).
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%
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% INPUTS
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% - initial_conditions [dseries] initial conditions for the endogenous variables.
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% - sample_size [integer] scalar, number of periods for the simulation.
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% - DynareOptions [struct] Dynare's options_ global structure.
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% - DynareModel [struct] Dynare's M_ global structure.
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% - DynareOutput [struct] Dynare's oo_ global structure.
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% - innovations [double] T*q matrix, innovations to be used for the simulation.
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%
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% OUTPUTS
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% - DynareOutput [struct] Dynare's oo_ global structure.
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% - errorflag [logical] scalar, equal to false iff the simulation did not fail.
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%
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% REMARKS
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% [1] The innovations used for the simulation are saved in DynareOutput.exo_simul, and the resulting paths for the endogenous
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% variables are saved in DynareOutput.endo_simul.
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% [2] The last input argument is not mandatory. If absent we use random draws and rescale them with the informations provided
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% through the shocks block.
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% [3] If the first input argument is empty, the endogenous variables are initialized with 0, or if available with the informations
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% provided thrtough the histval block.
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% Copyright © 2017-2023 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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debug = false;
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if ~isempty(innovations)
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DynareOutput.exo_simul(initialconditions.nobs+(1:samplesize),:) = innovations;
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end
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if ismember(DynareOptions.solve_algo, [12,14])
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[funcs, feedback_vars_idxs] = setup_time_recursive_block_simul(DynareModel);
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end
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function [r, J] = block_wrapper(z, feedback_vars_idx, func, y_dynamic, x, sparse_rowval, sparse_colval, sparse_colptr, T)
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% NB: do as few computations as possible inside this function, since it is
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% called a very large number of times
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y_dynamic(feedback_vars_idx) = z;
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[~, ~, r, J] = feval(func, y_dynamic, x, DynareModel.params, DynareOutput.steady_state, ...
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sparse_rowval, sparse_colval, sparse_colptr, T);
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end
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% Simulations (call a Newton-like algorithm for each period).
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for it = initialconditions.nobs+(1:samplesize)
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if debug
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dprintf('Period t = %s.', num2str(it-initialconditions.nobs));
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end
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y_ = DynareOutput.endo_simul(:,it-1);
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y = y_; % A good guess for the initial conditions is the previous values for the endogenous variables.
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try
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if ismember(DynareOptions.solve_algo, [12,14])
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x = DynareOutput.exo_simul(it,:);
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T = NaN(DynareModel.block_structure.dyn_tmp_nbr);
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y_dynamic = [y_; y; NaN(DynareModel.endo_nbr, 1)];
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for blk = 1:length(DynareModel.block_structure.block)
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sparse_rowval = DynareModel.block_structure.block(blk).g1_sparse_rowval;
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sparse_colval = DynareModel.block_structure.block(blk).g1_sparse_colval;
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sparse_colptr = DynareModel.block_structure.block(blk).g1_sparse_colptr;
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if DynareModel.block_structure.block(blk).Simulation_Type ~= 1 % Not an evaluate forward block
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[z, errorflag, ~, ~, errorcode] = dynare_solve(@block_wrapper, y_dynamic(feedback_vars_idxs{blk}), ...
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DynareOptions.simul.maxit, DynareOptions.dynatol.f, ...
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DynareOptions.dynatol.x, DynareOptions, ...
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feedback_vars_idxs{blk}, funcs{blk}, y_dynamic, x, sparse_rowval, sparse_colval, sparse_colptr, T);
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if errorflag
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error('Nonlinear solver routine failed with errorcode=%i in block %i and period %i.', errorcode, blk, it)
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end
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y_dynamic(feedback_vars_idxs{blk}) = z;
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end
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%% Compute endogenous if the block is of type evaluate or if there are recursive variables in a solve block.
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%% Also update the temporary terms vector.
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[y_dynamic, T] = feval(funcs{blk}, y_dynamic, x, DynareModel.params, ...
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DynareOutput.steady_state, sparse_rowval, sparse_colval, ...
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sparse_colptr, T);
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end
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DynareOutput.endo_simul(:,it) = y_dynamic(DynareModel.endo_nbr+(1:DynareModel.endo_nbr));
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else
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[DynareOutput.endo_simul(:,it), errorflag, ~, ~, errorcode] = ...
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dynare_solve(@dynamic_backward_model_for_simulation, y, ...
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DynareOptions.simul.maxit, DynareOptions.dynatol.f, DynareOptions.dynatol.x, ...
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DynareOptions, ...
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model_dynamic, y_(iy1), DynareOutput.exo_simul, DynareModel.params, DynareOutput.steady_state, it);
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if errorflag
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error('Nonlinear solver routine failed with errorcode=%i in period %i.', errorcode, it)
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end
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end
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catch Error
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errorflag = true;
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DynareOutput.endo_simul = DynareOutput.endo_simul(:, 1:it-1);
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dprintf('Newton failed on iteration i = %s.', num2str(it-initialconditions.nobs));
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ytm = DynareOutput.endo_simul(:,end);
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xtt = DynareOutput.exo_simul(it,:);
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skipline()
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dprintf('Values of the endogenous variables before the nonlinear solver failure')
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dprintf('----------------------------------------------------------------------')
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skipline()
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dyntable(DynareOptions, '', {'VARIABLES','VALUES'}, DynareModel.endo_names(1:DynareModel.orig_endo_nbr), ytm(1:DynareModel.orig_endo_nbr), [], [], 6)
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skipline()
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dprintf('Values of the exogenous variables before the nonlinear solver failure')
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dprintf('---------------------------------------------------------------------')
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skipline()
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dyntable(DynareOptions, '', {'VARIABLES','VALUES'}, DynareModel.exo_names, transpose(DynareOutput.exo_simul(it,:)), [], [], 6)
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skipline(2)
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%
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% Get equation tags if any
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%
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if isfield(DynareModel, 'equations_tags')
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etags = cell(DynareModel.orig_endo_nbr, 1);
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for i = 1:DynareModel.orig_endo_nbr
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equations_tags = DynareModel.equations_tags(cellfun(@(x) isequal(x, i), DynareModel.equations_tags(:,1)), :);
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name = equations_tags(strcmpi(equations_tags(:,2), 'name'),:);
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if isempty(name)
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eqtags{i} = int2str(i);
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else
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if rows(name)>1
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error('Something is wrong in the equation tags.')
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else
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eqtags(i) = name(3);
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end
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end
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end
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else
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etags = split(int2str(1:DynareModel.orig_endo_nbr), ' ');
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end
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%
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% Evaluate and check the residuals
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%
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[r, J] = feval(@dynamic_backward_model_for_simulation, ytm, model_dynamic, ytm(iy1), DynareOutput.exo_simul, DynareModel.params, DynareOutput.steady_state, it);
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residuals_evaluating_to_nan = isnan(r);
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residuals_evaluating_to_inf = isinf(r);
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residuals_evaluating_to_complex = ~isreal(r);
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if any(residuals_evaluating_to_nan)
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dprintf('Following equations are evaluating to NaN:')
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skipline()
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display_names_of_problematic_equations(DynareModel, eqtags, residuals_evaluating_to_nan);
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skipline()
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end
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if any(residuals_evaluating_to_inf)
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dprintf('Following equations are evaluating to Inf:')
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skipline()
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display_names_of_problematic_equations(DynareModel, eqtags, residuals_evaluating_to_inf);
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skipline()
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end
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if any(residuals_evaluating_to_complex)
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dprintf('Following equations are evaluating to a complex number:')
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skipline()
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display_names_of_problematic_equations(DynareModel, eqtags, residuals_evaluating_to_complex);
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skipline()
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end
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dprintf('Newton failed in period %s with the following error message:', char(initialconditions.lastdate+(it-initialconditions.nobs)));
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skipline()
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dprintf('\t %s', Error.message);
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skipline()
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break
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% TODO Implement same checks with the jacobian matrix.
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% TODO Modify other solvers to return an exitflag.
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end
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end
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ysim = DynareOutput.endo_simul(1:DynareModel.orig_endo_nbr,:);
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xsim = DynareOutput.exo_simul;
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end
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function display_names_of_problematic_equations(DynareModel, eqtags, TruthTable)
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for i=1:DynareModel.orig_endo_nbr
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if TruthTable(i)
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dprintf(' - %s', eqtags{i})
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end
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end
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for i=DynareModel.orig_endo_nbr+1:DynareModel.endo_nbr
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if TruthTable(i)
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dprintf(' - Auxiliary equation for %s', DynareModel.endo_names{i})
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end
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end
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end
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