2015-03-01 15:12:34 +01:00
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function [trend_addition, trend_coeff]=compute_trend_coefficients(M_,DynareOptions,nvarobs,ntobs)
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% [trend_addition, trend_coeff]=compute_trend_coefficients(DynareOptions,nvarobs,ntobs)
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% Computes the trend coefficiencts and the trend, accounting for
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% prefiltering
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%
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% INPUTS
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% M_ [structure] describing the model; called in the eval
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% statement
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% DynareOptions [structure] describing the options
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% nvarobs [scalar] number of observed variables
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% ntobs [scalar] length of data sample for estimation
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%
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% OUTPUTS
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% trend_addition [nvarobs by ntobs double] matrix storing deterministic
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% trend component
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% trend_coeff [nvarobs by 1] vector storing trend slope
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%
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% SPECIAL REQUIREMENTS
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% none
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2022-04-13 13:15:19 +02:00
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% Copyright © 2014-2016 Dynare Team
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2015-03-01 15:12:34 +01:00
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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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2021-06-09 17:33:48 +02:00
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% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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2015-03-01 15:12:34 +01:00
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trend_coeff = zeros(nvarobs,1);
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t = DynareOptions.trend_coeffs;
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for i=1:length(t)
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if ~isempty(t{i})
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trend_coeff(i) = eval(t{i});
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end
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end
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trend_addition=trend_coeff*[DynareOptions.first_obs:DynareOptions.first_obs+ntobs-1];
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if DynareOptions.prefilter
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trend_addition = bsxfun(@minus,trend_addition,mean(trend_addition,2));
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end
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