dynare/matlab/evaluate_planner_objective.m

115 lines
4.0 KiB
Matlab

function planner_objective_value = evaluate_planner_objective(M,options,oo)
%function oo1 = evaluate_planner_objective(dr,M,oo,options)
% computes value of planner objective function
%
% INPUTS
% M: (structure) model description
% options: (structure) options
% oo: (structure) output results
%
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2007-2020 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/>.
if options.order>1
fprintf('\nevaluate_planner_objective: order>1 not yet supported\n')
planner_objective_value = NaN;
return
end
dr = oo.dr;
exo_nbr = M.exo_nbr;
nstatic = M.nstatic;
nspred = M.nspred;
if nspred > 180
fprintf('\nevaluate_planner_objective: model too large, can''t evaluate planner objective\n')
planner_objective_value = NaN;
return
end
beta = get_optimal_policy_discount_factor(M.params, M.param_names);
Gy = dr.ghx(nstatic+(1:nspred),:);
Gu = dr.ghu(nstatic+(1:nspred),:);
gy(dr.order_var,:) = dr.ghx;
gu(dr.order_var,:) = dr.ghu;
ys = oo.dr.ys;
[U,Uy,Uyy] = feval([M.fname '.objective.static'],ys,zeros(1,exo_nbr), ...
M.params);
%second order terms
Uyy = full(Uyy);
Uyygygy = A_times_B_kronecker_C(Uyy,gy,gy);
Uyygugu = A_times_B_kronecker_C(Uyy,gu,gu);
Uyygygu = A_times_B_kronecker_C(Uyy,gy,gu);
Wbar =U/(1-beta); %steady state welfare
Wy = Uy*gy/(eye(nspred)-beta*Gy);
Wu = Uy*gu+beta*Wy*Gu;
Wyy = Uyygygy/(eye(nspred*nspred)-beta*kron(Gy,Gy));
Wyygugu = A_times_B_kronecker_C(Wyy,Gu,Gu);
Wyygygu = A_times_B_kronecker_C(Wyy,Gy,Gu);
Wuu = Uyygugu+beta*Wyygugu;
Wyu = Uyygygu+beta*Wyygygu;
Wss = beta*Wuu*M.Sigma_e(:)/(1-beta); % at period 0, we are in steady state, so the deviation term only starts in period 1, thus the beta in front
% initialize yhat1 at the steady state
yhat1 = oo.steady_state;
if options.ramsey_policy
% initialize le Lagrange multipliers to 0 in yhat2
yhat2 = zeros(M.endo_nbr,1);
yhat2(1:M.orig_endo_nbr) = oo.steady_state(1:M.orig_endo_nbr);
end
if ~isempty(M.endo_histval)
% initialize endogenous state variable to histval if necessary
yhat1(1:M.orig_endo_nbr) = M.endo_histval(1:M.orig_endo_nbr);
if options.ramsey_policy
yhat2(1:M.orig_endo_nbr) = M.endo_histval(1:M.orig_endo_nbr);
end
end
yhat1 = yhat1(dr.order_var(nstatic+(1:nspred)),1)-dr.ys(dr.order_var(nstatic+(1:nspred)));
u = oo.exo_simul(1,:)';
Wyyyhatyhat1 = A_times_B_kronecker_C(Wyy,yhat1,yhat1);
Wuuuu = A_times_B_kronecker_C(Wuu,u,u);
Wyuyhatu1 = A_times_B_kronecker_C(Wyu,yhat1,u);
planner_objective_value(1) = Wbar+Wy*yhat1+Wu*u+Wyuyhatu1 ...
+ 0.5*(Wyyyhatyhat1 + Wuuuu+Wss);
if options.ramsey_policy
yhat2 = yhat2(dr.order_var(nstatic+(1:nspred)),1)-dr.ys(dr.order_var(nstatic+(1:nspred)));
Wyyyhatyhat2 = A_times_B_kronecker_C(Wyy,yhat2,yhat2);
Wyuyhatu2 = A_times_B_kronecker_C(Wyu,yhat2,u);
planner_objective_value(2) = Wbar+Wy*yhat2+Wu*u+Wyuyhatu2 ...
+ 0.5*(Wyyyhatyhat2 + Wuuuu+Wss);
end
if ~options.noprint
fprintf('\nApproximated value of planner objective function\n')
if options.ramsey_policy
fprintf(' - with initial Lagrange multipliers set to 0: %10.8f\n', ...
planner_objective_value(2))
fprintf(' - with initial Lagrange multipliers set to steady state: %10.8f\n\n', ...
planner_objective_value(1))
elseif options.discretionary_policy
fprintf('with discretionary policy: %10.8f\n\n',planner_objective_value(1))
end
end