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A few fixes for k-order welfare assesment in `evaluate_planner_objective` 

As suggested in !1962
pac-components
Normann Rion 2021-12-03 11:07:16 +01:00 committed by Sébastien Villemot
parent 40b2565140
commit cf829fb28e
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3 changed files with 30 additions and 26 deletions
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20
matlab/evaluate_planner_objective.m
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@ -229,21 +229,23 @@ if options_.ramsey_policy
[W] = k_order_welfare(dr,M_,options_); [W] = k_order_welfare(dr,M_,options_);
% Appends the welfare decision rule to the endogenous variables decision % Appends the welfare decision rule to the endogenous variables decision
% rule % rule
g = dr;
for i=0:options_.order for i=0:options_.order
eval("g.g_"+num2str(i)+" = [dr.g_"+num2str(i)+"; W.W_"+num2str(i)+"];"); dr.(['g_' num2str(i)]) = [dr.(['g_' num2str(i)]); W.(['W_' num2str(i)])];
end end
% Amends the steady-state vector accordingly % Amends the steady-state vector accordingly
[U] = feval([M_.fname '.objective.static'],ys,zeros(1,exo_nbr), M_.params); [U] = feval([M_.fname '.objective.static'],ys,zeros(1,exo_nbr), M_.params);
ysteady = [ys(oo_.dr.order_var); U/(1-beta)]; ysteady = [ys(oo_.dr.order_var); U/(1-beta)];
% Generates the sequence of shocks to compute unconditional welfare % Generates the sequence of shocks to compute unconditional welfare
nper = 10000; i_exo_var = setdiff([1:M_.exo_nbr],find(diag(M_.Sigma_e) == 0));
nburn = 1000; nxs = length(i_exo_var);
chol_S = chol(M_.Sigma_e); chol_S = chol(M_.Sigma_e(i_exo_var,i_exo_var));
exo_simul = chol_S*randn(nper,M_.exo_nbr)'; exo_simul = zeros(M_.exo_nbr,options_.ramsey.nperiods);
if ~isempty(M_.Sigma_e)
exo_simul(i_exo_var,:) = chol_S*randn(nxs,options_.ramsey.nperiods);
end
yhat_start = zeros(M_.endo_nbr+1,1); yhat_start = zeros(M_.endo_nbr+1,1);
[moment] = k_order_mean(options_.order, M_.nstatic, M_.npred, M_.nboth, M_.nfwrd+1, M_.exo_nbr, 1, nburn, yhat_start, exo_simul, ysteady, g); [moment] = k_order_mean(options_.order, M_.nstatic, M_.npred, M_.nboth, M_.nfwrd+1, M_.exo_nbr, 1, options_.ramsey.drop, yhat_start, exo_simul, ysteady, dr);
% Stores the result for unconditional welfare % Stores the result for unconditional welfare
planner_objective_value.unconditional = moment(end); planner_objective_value.unconditional = moment(end);
@ -255,12 +257,12 @@ if options_.ramsey_policy
% Conditional welfare (i) with Lagrange multipliers set to their % Conditional welfare (i) with Lagrange multipliers set to their
% steady-state values % steady-state values
yhat_start(M_.nstatic+1:M_.nstatic+M_.npred+M_.nboth) = yhat_L_SS; yhat_start(M_.nstatic+1:M_.nstatic+M_.npred+M_.nboth) = yhat_L_SS;
[moment,sim] = k_order_mean(options_.order, M_.nstatic, M_.npred, M_.nboth, M_.nfwrd+1, M_.exo_nbr, 1, 0, yhat_start, u, ysteady, g); [~,sim] = k_order_mean(options_.order, M_.nstatic, M_.npred, M_.nboth, M_.nfwrd+1, M_.exo_nbr, 1, 0, yhat_start, u, ysteady, dr);
planner_objective_value.conditional.steady_initial_multiplier = sim(end,1); planner_objective_value.conditional.steady_initial_multiplier = sim(end,1);
% Conditional welfare (ii) with Lagrange multipliers set to 0 % Conditional welfare (ii) with Lagrange multipliers set to 0
yhat_start(M_.nstatic+1:M_.nstatic+M_.npred+M_.nboth) = yhat_L_0; yhat_start(M_.nstatic+1:M_.nstatic+M_.npred+M_.nboth) = yhat_L_0;
[moment,sim] = k_order_mean(options_.order, M_.nstatic, M_.npred, M_.nboth, M_.nfwrd+1, M_.exo_nbr, 1, nburn, yhat_start, u, ysteady, g); [~,sim] = k_order_mean(options_.order, M_.nstatic, M_.npred, M_.nboth, M_.nfwrd+1, M_.exo_nbr, 1, 0, yhat_start, u, ysteady, dr);
planner_objective_value.conditional.zero_initial_multiplier = sim(end,1); planner_objective_value.conditional.zero_initial_multiplier = sim(end,1);
end end
end end

2
tests/optimal_policy/neo_growth_ramsey_k_order.mod
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@ -31,6 +31,8 @@ end;
stoch_simul(order=6, irf=0); stoch_simul(order=6, irf=0);
options_.ramsey.nperiods = 10000;
options_.ramsey.drop = 1000;
evaluate_planner_objective; evaluate_planner_objective;
[W_dynpp] = k_order_welfare(oo_.dr, M_, options_); [W_dynpp] = k_order_welfare(oo_.dr, M_, options_);