97 lines
3.8 KiB
C++
97 lines
3.8 KiB
C++
/*
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* Copyright © 2005 Ondra Kamenik
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* Copyright © 2019-2021 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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*/
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#include <utility>
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#include "kord_exception.hh"
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#include "approximation_welfare.hh"
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ApproximationWelfare::ApproximationWelfare(KordwDynare &w, double discount_factor_arg, const FGSContainer &rule_ders_arg, const FGSContainer &rule_ders_s_arg, Journal &j)
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: welfare{w}, discount_factor(discount_factor_arg), cond(1),
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nvs{welfare.getModel().nys(), welfare.getModel().nexog(), welfare.getModel().nexog(), 1}, journal{j}
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{
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rule_ders = std::make_unique<FGSContainer>(rule_ders_arg);
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rule_ders_s = std::make_unique<FGSContainer>(rule_ders_s_arg);
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}
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/* This methods assumes that the deterministic steady state is
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model.getSteady(). It makes an approximation about it and stores the
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derivatives to ‘rule_ders’ and ‘rule_ders_ss’. Also it runs a check() for
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σ=0. */
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void
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ApproximationWelfare::approxAtSteady()
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{
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welfare.calcDerivativesAtSteady();
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KOrderWelfare korderwel(welfare.getModel().nstat(), welfare.getModel().npred(), welfare.getModel().nboth(), welfare.getModel().nforw(), welfare.getModel().nexog(), welfare.getModel().order(), discount_factor, welfare.getPlannerObjDerivatives(), get_rule_ders(), get_rule_ders_s(), welfare.getModel().getVcov(), journal);
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for (int k = 1; k <= welfare.getModel().order(); k++)
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korderwel.performStep<Storage::fold>(k);
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saveRuleDerivs(korderwel.getFoldU(), korderwel.getFoldW());
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// construct the welfare approximations
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calcStochShift(); //conditional welfare
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// construct the resulting decision rules
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unc_fdr = std::make_unique<FoldDecisionRule>(*unc_ders, welfare.getModel().nys(), welfare.getModel().nexog(), welfare.getModel().getSteady());
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cond_fdr = std::make_unique<FoldDecisionRule>(*cond_ders, welfare.getModel().nys(), welfare.getModel().nexog(), welfare.getModel().getSteady());
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}
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/* This just returns ‘fdr’ with a check that it is created. */
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const FoldDecisionRule &
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ApproximationWelfare::getFoldUncWel() const
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{
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KORD_RAISE_IF(!unc_fdr,
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"Folded decision rule has not been created in ApproximationWelfare::getFoldUncWel");
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return *unc_fdr;
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}
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const FoldDecisionRule &
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ApproximationWelfare::getFoldCondWel() const
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{
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KORD_RAISE_IF(!cond_fdr,
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"Folded decision rule has not been created in ApproximationWelfare::getFoldCondWel");
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return *cond_fdr;
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}
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void
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ApproximationWelfare::saveRuleDerivs(const FGSContainer &U, const FGSContainer &W)
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{
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unc_ders = std::make_unique<FGSContainer>(U);
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cond_ders = std::make_unique<FGSContainer>(W);
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}
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/* This method calculates the shift of the conditional welfare function w.r.t its steady-state value because of the presence of stochastic shocks, i.e.
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1
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W ≈ Wbar + ∑ ── W_σᵈ
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d=1 d!
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*/
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void
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ApproximationWelfare::calcStochShift()
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{
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cond.zeros();
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cond.add(1.0/(1.0-discount_factor), welfare.getResid());
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KORD_RAISE_IF(cond.length() != 1,
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"Wrong length of output vector for ApproximationWelfare::calcStochShift");
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int dfac = 1;
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for (int d = 1; d <= cond_ders->getMaxDim(); d++, dfac *= d)
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if (KOrderWelfare::is_even(d))
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{
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Symmetry sym{0, 0, 0, d};
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cond.add(1.0/dfac, cond_ders->get(sym).getData());
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}
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}
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