Added routines for VAR_EXPECTATION_MODEL.
Stéphane Adjemian(Charybdis)
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988015e6a3
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function DynareModel = parameters(varexpectationmodelname, DynareModel, DynareOutput)
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% Updates the VAR expectation reduced form parameters.
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%
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% INPUTS
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% - varexpectationmodelname [string] Name of the pac equation.
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% - DynareModel [struct] M_ global structure (model properties)
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% - DynareOutput [struct] oo_ global structure (model results)
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%
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% OUTPUTS
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% - DynareModel [struct] M_ global structure (with updated params field)
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright (C) 2018 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 <http://www.gnu.org/licenses/>.
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% Check that the first input is a row character array.
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if ~isrow(varexpectationmodelname)==1 || ~ischar(varexpectationmodelname)
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error('First input argument must be a row character array!')
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end
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% Check that the model exists.
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if ~isfield(DynareModel.var_expectation, varexpectationmodelname)
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error('VAR_EXPECTATION_MODEL %s is not defined!', varexpectationmodelname)
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end
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% Get the VAR model description
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varexpectationmodel = DynareModel.var_expectation.(varexpectationmodelname);
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% Get the name of the associated VAR model and test its existence.
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if ~isfield(DynareModel.var, varexpectationmodel.var_model_name)
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error('Unknown VAR (%s) in VAR_EXPECTATION_MODEL (%s)!', varexpectationmodel.var_model_name, varexpectationmodelname)
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end
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varmodel = DynareModel.var.(varexpectationmodel.var_model_name);
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% Check that we have the values of the VAR matrices.
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if ~isfield(DynareOutput.var, varexpectationmodel.var_model_name)
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error('VAR model %s has to be estimated or calibrated first!', varexpectationmodel.var_model_name)
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end
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varcalib = DynareOutput.var.(varexpectationmodel.var_model_name);
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if ~isfield(varcalib, 'CompanionMatrix') || any(isnan(varcalib.CompanionMatrix(:)))
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message = sprintf('VAR model %s has to be estimated first.', varexpectationmodel.var_model_name);
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message = sprintf('s\nPlease use get_companion_matrix command first.', message);
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error(message)
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end
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% Set discount factor
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if isfield(varexpectationmodel, 'discount_value')
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discountfactor = varexpectationmodel.discount_value;
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else
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if isfield(varexpectationmodel, 'discount_index')
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discountfactor = DynareModel.params(varexpectationmodel.discount_index);
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else
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error('This is most likely a bug. Pleasse conntact the Dynare Team.')
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end
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end
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% A discount factor has to be positive.
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if discountfactor<=0
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error('The discount factor must be positive.')
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end
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% A discount factor cannot be greater than one.
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if discountfactor>1
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error('The discount cannot be greater than one.')
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end
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% Set variable_id in VAR model
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variable_id_in_var = find(varexpectationmodel.variable_id==varmodel.lhs);
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% Get the horizon parameter.
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horizon = varexpectationmodel.horizon;
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% Check the horizon parameter
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wrong_horizon_parameter = true;
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if length(horizon)==1
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if isnumeric(horizon)
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if isfinite(horizon)
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if isint(horizon)
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if horizon>0
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wrong_horizon_parameter = false;
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end
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end
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end
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end
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elseif length(horizon)==2
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if isnumeric(horizon)
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if isfinite(horizon(1))
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if isint(horizon(1))
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if horizon(1)>=0
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if isinf(horizon(2)) || (isint(horizon(2)) && horizon(2)>horizon(1))
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wrong_horizon_parameter = false;
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end
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end
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end
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end
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end
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end
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if wrong_horizon_parameter
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error('horizon must be an integer scalar or an integer vector with two elements.')
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end
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% Get the companion matrix
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CompanionMatrix = varcalib.CompanionMatrix;
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% Get the dimension of the problem.
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n = length(CompanionMatrix);
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% Set the selection vector
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alpha = zeros(1, length(CompanionMatrix));
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alpha(variable_id_in_var) = 1;
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if length(horizon)==1
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% Compute the reduced form parameters of the (discounted) forecast in period t+horizon(1)
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if varexpectationmodel.horizon==1
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parameters = discountfactor*(alpha*CompanionMatrix);
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elseif horizon>1
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parameters = alpha*mpower(discountfactor*CompanionMatrix, varexpectationmodel.horizon);
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end
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else
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% Compute the reduced form parameters of the discounted sum of forecasts between t+horizon(1) and
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% t+horizon(2). Not that horzizon(2) need not be finite.
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if horizon(1)==0 && isinf(horizon(2))
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parameters = alpha/(eye(n)-discountfactor*CompanionMatrix);
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elseif horizon(1)>0 && isinf(horizon(2))
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% Define the discounted companion matrix
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DiscountedCompanionMatrix = discountfactor*CompanionMatrix;
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% First compute the parameters implied by the discounted sum from h=0 to h=horizon(1)-1
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tmp1 = eye(n);
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for h=1:horizon(1)
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tmp1 = tmp1 + mpower(DiscountedCompanionMatrix, h);
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end
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tmp1 = alpha*tmp1;
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% Second compute the parameters implied by the discounted sum from h=0 to h=Inf
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tmp2 = alpha/(eye(n)-DiscountedCompanionMatrix);
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% Finally
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parameters = tmp2-tmp1;
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elseif isfinite(horizon(2))
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% Define the discounted companion matrix
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DiscountedCompanionMatrix = discountfactor*CompanionMatrix;
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tmp = zeros(n);
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for h=horizon(1):horizon(2)
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tmp = tmp + mpower(DiscountedCompanionMatrix, h);
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end
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parameters = alpha*tmp;
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end
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end
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% Update reduced form parameters in M_.params.
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DynareModel.params(varexpectationmodel.param_indices) = parameters;
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@ -0,0 +1,33 @@
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function update(varexpectationmodelname)OA
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% Updates the parameters of a VAR_EXPECTATION_MODEL.
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%
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% INPUTS
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% - varepxpectationmodelname [string] Name of the VAR expectation model.
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%
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% OUTPUTS
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% - none
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright (C) 2018 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 <http://www.gnu.org/licenses/>.
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global M_ oo_
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M_ = var_expectation.update.parameters(varexpectationmodelname, M_, oo_);
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