299 lines
15 KiB
Matlab
299 lines
15 KiB
Matlab
function [expression, growthneutralitycorrection] = write_expectations(expectationmodelname, expectationmodelkind, iscrlf, aggregate)
|
|
|
|
% Prints the exansion of the VAR_EXPECTATION or PAC_EXPECTATION term in files.
|
|
%
|
|
% INPUTS
|
|
% - epxpectationmodelname [string] Name of the expectation model.
|
|
% - expectationmodelkind [string] Kind of the expectation model ('var' or 'pac').
|
|
% - iscrlf [string] Adds carriage return after each additive term if true.
|
|
%
|
|
% OUTPUTS
|
|
% - expression [string] Unrolled expectation expression.
|
|
% - growthneutralitycorrection [string]
|
|
|
|
% Copyright © 2019-2021 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/>.
|
|
|
|
global M_
|
|
|
|
if ismember(expectationmodelkind, {'var', 'pac'})
|
|
if isequal(expectationmodelkind, 'var')
|
|
expectationmodelfield = 'var_expectation';
|
|
else
|
|
expectationmodelfield = 'pac';
|
|
end
|
|
else
|
|
error('Value of third input argument must be ''var'' or ''pac''.')
|
|
end
|
|
|
|
expectationmodel = M_.(expectationmodelfield).(expectationmodelname);
|
|
|
|
if nargout>1 && isequal(expectationmodelkind, 'var')
|
|
error('Cannot return more than one argument if the expectation model is a VAR.')
|
|
end
|
|
|
|
if nargin<3
|
|
iscrlf = false;
|
|
aggregate = true;
|
|
end
|
|
|
|
if nargin<4
|
|
aggregate = true;
|
|
end
|
|
|
|
if isfield(expectationmodel, 'h_param_indices')
|
|
% Disaggregation requires components...
|
|
aggregate = true;
|
|
end
|
|
|
|
% Get the name of the associated VAR model and test its existence.
|
|
if ~isfield(M_.(expectationmodel.auxiliary_model_type), expectationmodel.auxiliary_model_name)
|
|
switch expectationmodelkind
|
|
case 'var-expectations'
|
|
error('Unknown VAR/TREND_COMPONENT model (%s) in VAR_EXPECTATION_MODEL (%s)!', expectationmodel.auxiliary_model_name, expectationmodelname)
|
|
case 'pac-expectations'
|
|
error('Unknown VAR/TREND_COMPONENT model (%s) in PAC_EXPECTATION_MODEL (%s)!', expectationmodel.auxiliary_model_name, expectationmodelname)
|
|
otherwise
|
|
end
|
|
end
|
|
|
|
auxmodel = M_.(expectationmodel.auxiliary_model_type).(expectationmodel.auxiliary_model_name);
|
|
|
|
maxlag = max(auxmodel.max_lag);
|
|
if isequal(expectationmodel.auxiliary_model_type, 'trend_component')
|
|
% Need to add a lag since the error correction equations are rewritten in levels.
|
|
maxlag = maxlag+1;
|
|
end
|
|
|
|
id = 0;
|
|
|
|
if isequal(expectationmodelkind, 'var')
|
|
timeindices = (0:(maxlag-1))+abs(expectationmodel.time_shift);
|
|
end
|
|
|
|
if isequal(expectationmodelkind, 'var') && isequal(expectationmodel.auxiliary_model_type, 'var')
|
|
id = id+1;
|
|
expression = sprintf('%s', M_.param_names{expectationmodel.param_indices(id)});
|
|
end
|
|
|
|
if isequal(expectationmodelkind, 'pac') && isequal(expectationmodel.auxiliary_model_type, 'var')
|
|
id = id+1;
|
|
if isfield(expectationmodel, 'h_param_indices')
|
|
expression = sprintf('%s', M_.param_names{expectationmodel.h_param_indices(id)});
|
|
else
|
|
if aggregate
|
|
if isequal(expectationmodel.components(1).coeff_str, '1')
|
|
expression = sprintf('%s', M_.param_names{expectationmodel.components(1).h_param_indices(id)});
|
|
else
|
|
expression = sprintf('%s*%s', expectationmodel.components(1).coeff_str, M_.param_names{expectationmodel.components(1).h_param_indices(id)});
|
|
end
|
|
for i=2:length(expectationmodel.components)
|
|
if isequal(expectationmodel.components(i).coeff_str, '1')
|
|
expression = sprintf('%s+%s', expression, M_.param_names{expectationmodel.components(i).h_param_indices(id)});
|
|
else
|
|
expression = sprintf('%s+%s*%s', expression, expectationmodel.components(i).coeff_str, M_.param_names{expectationmodel.components(i).h_param_indices(id)});
|
|
end
|
|
end
|
|
else
|
|
expression = cell(length(expectationmodel.components), 1);
|
|
for i=1:length(expectationmodel.components)
|
|
expression(i) = {M_.param_names{expectationmodel.components(i).h_param_indices(id)}};
|
|
end
|
|
end
|
|
end
|
|
end
|
|
|
|
for i=1:maxlag
|
|
for j=1:length(auxmodel.list_of_variables_in_companion_var)
|
|
id = id+1;
|
|
variable = auxmodel.list_of_variables_in_companion_var{j};
|
|
transformations = {};
|
|
ida = get_aux_variable_id(variable);
|
|
op = 0;
|
|
while ida
|
|
op = op+1;
|
|
if isequal(M_.aux_vars(ida).type, 8)
|
|
transformations(op) = {'diff'};
|
|
variable = M_.endo_names{M_.aux_vars(ida).orig_index};
|
|
ida = get_aux_variable_id(variable);
|
|
elseif isequal(M_.aux_vars(ida).type, 10)
|
|
transformations(op) = {M_.aux_vars(ida).unary_op};
|
|
variable = M_.endo_names{M_.aux_vars(ida).orig_index};
|
|
ida = get_aux_variable_id(variable);
|
|
else
|
|
error('This case is not implemented.')
|
|
end
|
|
end
|
|
switch expectationmodelkind
|
|
case 'var'
|
|
parameter = M_.param_names{expectationmodel.param_indices(id)};
|
|
case 'pac'
|
|
if isfield(expectationmodel, 'h_param_indices')
|
|
parameter = M_.param_names{expectationmodel.h_param_indices(id)};
|
|
else
|
|
if aggregate
|
|
% TODO Check if we can have parameters entering with a minus sign in the linear combination defining the target.
|
|
if isequal(expectationmodel.components(1).coeff_str, '1')
|
|
parameter = M_.param_names{expectationmodel.components(1).h_param_indices(id)};
|
|
else
|
|
parameter = sprintf('%s*%s', expectationmodel.components(1).coeff_str, M_.param_names{expectationmodel.components(1).h_param_indices(id)});
|
|
end
|
|
for k=2:length(expectationmodel.components)
|
|
if isequal(expectationmodel.components(k).coeff_str, '1')
|
|
parameter = sprintf('%s+%s', parameter, M_.param_names{expectationmodel.components(k).h_param_indices(id)});
|
|
else
|
|
parameter = sprintf('%s+%s*%s', parameter, expectationmodel.components(k).coeff_str, M_.param_names{expectationmodel.components(k).h_param_indices(id)});
|
|
end
|
|
end
|
|
parameter = sprintf('(%s)', parameter);
|
|
else
|
|
parameter = cell(length(expectationmodel.components), 1);
|
|
for k=1:length(expectationmodel.components)
|
|
parameter(k) = {M_.param_names{expectationmodel.components(k).h_param_indices(id)}};
|
|
end
|
|
end
|
|
end
|
|
otherwise
|
|
end
|
|
switch expectationmodelkind
|
|
case 'var'
|
|
if timeindices(i)
|
|
variable = sprintf('%s(-%d)', variable, timeindices(i));
|
|
end
|
|
case 'pac'
|
|
variable = sprintf('%s(-%d)', variable, i);
|
|
otherwise
|
|
end
|
|
if ~isempty(transformations)
|
|
for k=length(transformations):-1:1
|
|
variable = sprintf('%s(%s)', transformations{k}, variable);
|
|
end
|
|
end
|
|
if isequal(id, 1)
|
|
if aggregate
|
|
if iscrlf
|
|
expression = sprintf('%s*%s\n', parameter, variable);
|
|
else
|
|
expression = sprintf('%s*%s', parameter, variable);
|
|
end
|
|
else
|
|
for k=1:length(expectationmodel.components)
|
|
if iscrlf
|
|
expression(k) = {sprintf('%s*%s\n', parameter{k}, variable)};
|
|
else
|
|
expression(k) = {sprintf('%s*%s', parameter{k}, variable)};
|
|
end
|
|
end
|
|
end
|
|
else
|
|
if aggregate
|
|
if iscrlf
|
|
expression = sprintf('%s + %s*%s\n', expression, parameter, variable);
|
|
else
|
|
expression = sprintf('%s + %s*%s', expression, parameter, variable);
|
|
end
|
|
else
|
|
for k=1:length(expectationmodel.components)
|
|
if iscrlf
|
|
expression(k) = {sprintf('%s + %s*%s\n', expression{k}, parameter{k}, variable)};
|
|
else
|
|
expression(k) = {sprintf('%s + %s*%s', expression{k}, parameter{k}, variable)};
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end
|
|
|
|
if aggregate
|
|
growthneutralitycorrection = '';
|
|
else
|
|
growthneutralitycorrection = {};
|
|
end
|
|
|
|
if isfield(expectationmodel, 'growth_neutrality_param_index')
|
|
if numel(expectationmodel.growth_linear_comb) == 1
|
|
growthneutralitycorrection = sprintf('%s*%s', M_.param_names{expectationmodel.growth_neutrality_param_index}, expectationmodel.growth_str);
|
|
else
|
|
growthneutralitycorrection = sprintf('%s*(%s)', M_.param_names{expectationmodel.growth_neutrality_param_index}, expectationmodel.growth_str);
|
|
end
|
|
else
|
|
if isfield(expectationmodel, 'components')
|
|
if aggregate
|
|
growthneutralitycorrection = '';
|
|
for i=1:length(expectationmodel.components)
|
|
if ~isequal(expectationmodel.components(i).kind, 'll')
|
|
if isfield(expectationmodel.components(i), 'growth_neutrality_param_index')
|
|
if isempty(growthneutralitycorrection)
|
|
if ~isempty(expectationmodel.components(i).growth_str)
|
|
if isequal(expectationmodel.components(i).coeff_str, '1')
|
|
if numel(expectationmodel.components(i).growth_linear_comb) == 1
|
|
growthneutralitycorrection = sprintf('%s*%s', M_.param_names{expectationmodel.components(i).growth_neutrality_param_index}, expectationmodel.components(i).growth_str);
|
|
else
|
|
growthneutralitycorrection = sprintf('%s*(%s)', M_.param_names{expectationmodel.components(i).growth_neutrality_param_index}, expectationmodel.components(i).growth_str);
|
|
end
|
|
else
|
|
if numel(expectationmodel.components(i).growth_linear_comb) == 1
|
|
growthneutralitycorrection = sprintf('%s*%s*%s', expectationmodel.components(i).coeff_str, M_.param_names{expectationmodel.components(i).growth_neutrality_param_index}, expectationmodel.components(i).growth_str);
|
|
else
|
|
growthneutralitycorrection = sprintf('%s*%s*(%s)', expectationmodel.components(i).coeff_str, M_.param_names{expectationmodel.components(i).growth_neutrality_param_index}, expectationmodel.components(i).growth_str);
|
|
end
|
|
end
|
|
end
|
|
else
|
|
if ~isempty(expectationmodel.components(i).growth_str)
|
|
if isequal(expectationmodel.components(i).coeff_str, '1')
|
|
if numel(expectationmodel.components(i).growth_linear_comb) == 1
|
|
growthneutralitycorrection = sprintf('%s+%s*%s', growthneutralitycorrection, M_.param_names{expectationmodel.components(i).growth_neutrality_param_index}, expectationmodel.components(i).growth_str);
|
|
else
|
|
growthneutralitycorrection = sprintf('%s+%s*(%s)', growthneutralitycorrection, M_.param_names{expectationmodel.components(i).growth_neutrality_param_index}, expectationmodel.components(i).growth_str);
|
|
end
|
|
else
|
|
if numel(expectationmodel.components(i).growth_linear_comb) == 1
|
|
growthneutralitycorrection = sprintf('%s+%s*%s*%s', growthneutralitycorrection, expectationmodel.components(i).coeff_str, M_.param_names{expectationmodel.components(i).growth_neutrality_param_index}, expectationmodel.components(i).growth_str);
|
|
else
|
|
growthneutralitycorrection = sprintf('%s+%s*%s*(%s)', growthneutralitycorrection, expectationmodel.components(i).coeff_str, M_.param_names{expectationmodel.components(i).growth_neutrality_param_index}, expectationmodel.components(i).growth_str);
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end % if growth neutrality correction for this component
|
|
end % if non stationary component
|
|
end
|
|
else
|
|
growthneutralitycorrection = repmat({''}, length(expectationmodel.components), 1);
|
|
for i=1:length(growthneutralitycorrection)
|
|
if ~isequal(expectationmodel.components(i).kind, 'll')
|
|
if isfield(expectationmodel.components(i), 'growth_neutrality_param_index')
|
|
if ~isempty(expectationmodel.components(i).growth_str)
|
|
if numel(expectationmodel.components(i).growth_linear_comb) == 1
|
|
growthneutralitycorrection(i) = {sprintf('%s*%s', M_.param_names{expectationmodel.components(i).growth_neutrality_param_index}, expectationmodel.components(i).growth_str)};
|
|
else
|
|
growthneutralitycorrection(i) = {sprintf('%s*(%s)', M_.param_names{expectationmodel.components(i).growth_neutrality_param_index}, expectationmodel.components(i).growth_str)};
|
|
end
|
|
end
|
|
end % if growth neutrality correction for this component
|
|
end % if non stationary component
|
|
end
|
|
end % if aggregate
|
|
end
|
|
end
|
|
|
|
if nargout==1 && ~isempty(growthneutralitycorrection)
|
|
expression = sprintf('%s + %s', expression, growthneutralitycorrection);
|
|
end
|