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function [initialconditions, samplesize, innovations, DynareOptions, DynareModel, DynareOutput, endonames, exonames, nx, ny1, iy1, jdx, model_dynamic, y] = ...
simul_backward_model_init(initialconditions, samplesize, DynareOptions, DynareModel, DynareOutput, innovations)
% Initialization of the routines simulating backward models.
% Copyright (C) 2017-2019 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 <http://www.gnu.org/licenses/>.
% Test if the model is backward.
if DynareModel.maximum_lead
error('simul_backward_nonlinear_model:: The specified model is not backward looking!')
end
% Test if the first argument is a dseries object.
if ~(isdseries(initialconditions) || isempty(initialconditions))
error('First input argument must be a dseries object or an empty array!')
end
% If initialconditions is empty instantiates a dseries object with the informations available in DynareModel.endo_histval.
if isempty(initialconditions)
yinitdata = zeros(DynareModel.orig_endo_nbr, DynareModel.orig_maximum_lag);
yinitdata(:,1) = DynareModel.endo_histval(1:DynareModel.orig_endo_nbr);
xinitdata = zeros(DynareModel.exo_nbr, DynareModel.orig_maximum_lag);
if DynareModel.orig_maximum_endo_lag>1
for i = 1:length(DynareModel.aux_vars)
if DynareModel.aux_vars(i).type==1
yinitdata(DynareModel.aux_vars(i).orig_index, abs(DynareModel.aux_vars(i).orig_lead_lag)+1) = ...
DynareModel.endo_histval(DynareModel.orig_endo_nbr+i);
end
end
yinitdata = flip(yinitdata, 2);
end
if DynareModel.orig_maximum_exo_lag>0
for i = 1:length(DynareModel.aux_vars)
if DynareModel.aux_vars(i).type==3
xinitdata(DynareModel.aux_vars(i).orig_index, abs(DynareModel.aux_vars(i).orig_lead_lag)+1) = ...
DynareModel.endo_histval(DynareModel.orig_endo_nbr+i);
end
end
xinitdata = flip(xinitdata, 2);
end
initialconditions = dseries([transpose(yinitdata) transpose(xinitdata)], '1Y', ...
vertcat(DynareModel.endo_names(1:DynareModel.orig_endo_nbr), DynareModel.exo_names));
end
[initialconditions, info] = checkdatabase(initialconditions, DynareModel, false, true);
% Test if the first argument contains all the lagged endogenous variables
endonames = DynareModel.endo_names;
missingendogenousvariables = setdiff(endonames, initialconditions.name);
endolags = get_lags_on_endogenous_variables(DynareModel);
endolags_ = endolags(find(endolags));
endowithlagnames = endonames(find(endolags));
if ~isempty(missingendogenousvariables)
missingendogenousvariables = setdiff(endowithlagnames, initialconditions.name);
missingendogenouslaggedvariables = intersect(endowithlagnames, missingendogenousvariables);
if ~isempty(missingendogenouslaggedvariables)
disp('You have to initialize the following endogenous variables:')
msg = sprintf('%s\n', missingendogenouslaggedvariables{1:end-1});
msg = sprintf('%s%s', msg, missingendogenouslaggedvariables{end});
disp(msg)
skipline()
error('Please fix the dseries object used for setting the initial conditions!')
end
end
% Test if we have enough periods in the database.
maxlag = abs(min(endolags));
if maxlag>initialconditions.nobs
error('The dseries object provided as first input argument should at least have %s periods!', num2str(maxlag))
end
missinginitialcondition = false;
for i = 1:length(endowithlagnames)
lags = abs(endolags_(i));
variable = initialconditions{endowithlagnames{i}};
nanvalues = isnan(variable.data);
if any(nanvalues(end-(lags-1):end))
missinginitialcondition = true;
for j=variable.nobs:-1:variable.nobs-(lags-1)
if isnan(variable.data(j))
dprintf('Variable %s should not have a NaN value in period %s.', endowithlagnames{i}, date2string(variable.dates(j)))
end
end
end
end
if missinginitialcondition
skipline()
error('Please fix the dseries object used for setting the initial conditions!')
end
% If the model has lags on the exogenous variables, test if we have corresponding initial conditions.
exonames = DynareModel.exo_names;
missingexogenousvariables = setdiff(exonames, initialconditions.name);
exolags = get_lags_on_exogenous_variables(DynareModel);
exolags_ = exolags(find(exolags));
exowithlagnames = exonames(find(exolags));
if ~isempty(missingexogenousvariables)
missingexogenousvariables = setdiff(exowithlagnames, initialconditions.name);
missingexogenouslaggedvariables = intersect(exowithlagnames, missingexogenousvariables);
if ~isempty(missingexogenouslaggedvariables)
disp('You have to initialize the following exogenous variables:')
msg = sprintf('%s\n', missingexogenouslaggedvariables{1:end-1});
msg = sprintf('%s%s', msg, missingexogenouslaggedvariables{end});
disp(msg)
skipline()
error('Please fix the dseries object used for setting the initial conditions!')
end
end
% Test if we have enough periods in the database.
maxlag = abs(min(exolags));
if maxlag>initialconditions.nobs
error('The dseries object provided as first input argument should at least have %s periods!', num2str(maxlag))
end
missinginitialcondition = false;
for i = 1:length(exowithlagnames)
lags = abs(exolags_(i));
variable = initialconditions{exowithlagnames{i}};
nanvalues = isnan(variable.data);
if any(nanvalues(end-(lags-1):end))
missinginitialcondition = true;
for j=variable.nobs:-1:variable.nobs-(lags-1)
if isnan(variable.data(j))
dprintf('Variable %s should not have a NaN value in period %s.', exowithlagnames{i}, date2string(variable.dates(j)))
end
end
end
end
if missinginitialcondition
skipline()
error('Please fix the dseries object used for setting the initial conditions!')
end
if nargin<6 || isempty(innovations)
% Set the covariance matrix of the structural innovations.
variances = diag(DynareModel.Sigma_e);
number_of_shocks = length(DynareModel.Sigma_e);
positive_var_indx = find(variances>0);
effective_number_of_shocks = length(positive_var_indx);
covariance_matrix = DynareModel.Sigma_e(positive_var_indx,positive_var_indx);
covariance_matrix_upper_cholesky = chol(covariance_matrix);
% Set seed to its default state.
if DynareOptions.bnlms.set_dynare_seed_to_default
set_dynare_seed('default');
end
% Simulate structural innovations.
switch DynareOptions.bnlms.innovation_distribution
case 'gaussian'
DynareOutput.bnlms.shocks = randn(samplesize,effective_number_of_shocks)*covariance_matrix_upper_cholesky;
otherwise
error(['simul_backward_nonlinear_model:: ' DynareOption.bnlms.innovation_distribution ' distribution for the structural innovations is not (yet) implemented!'])
end
% Put the simulated innovations in DynareOutput.exo_simul.
DynareOutput.exo_simul = zeros(samplesize,number_of_shocks);
DynareOutput.exo_simul(:,positive_var_indx) = DynareOutput.bnlms.shocks;
innovations = DynareOutput.exo_simul;
else
DynareOutput.exo_simul = innovations; % innovations
end
% Initialization of the returned simulations.
DynareOutput.endo_simul = NaN(DynareModel.endo_nbr, samplesize+initialconditions.nobs);
for i=1:length(endonames)
if ismember(endonames{i}, initialconditions.name)
DynareOutput.endo_simul(i,1:initialconditions.nobs) = transpose(initialconditions{endonames{i}}.data);
end
end
% Initialization of the array for the exogenous variables.
DynareOutput.exo_simul = [NaN(initialconditions.nobs, DynareModel.exo_nbr); DynareOutput.exo_simul ];
for i=1:length(exonames)
if ismember(exonames{i}, initialconditions.name)
DynareOutput.exo_simul(1:initialconditions.nobs, i) = initialconditions{exonames{i}}.data;
end
end
if nargout>8
nx = size(DynareOutput.exo_simul,2);
ny0 = nnz(DynareModel.lead_lag_incidence(2,:));
ny1 = nnz(DynareModel.lead_lag_incidence(1,:));
iy1 = find(DynareModel.lead_lag_incidence(1,:)>0);
idx = 1:DynareModel.endo_nbr;
jdx = idx+ny1;
% Get the name of the dynamic model routine.
model_dynamic = str2func([DynareModel.fname,'.dynamic']);
% initialization of vector y.
y = NaN(length(idx)+ny1,1);
end
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