function [steady_state, params, check] = dyn_ramsey_static(ys_init, exo_ss, M_, options_) % [steady_state, params, check] = dyn_ramsey_static(ys_init, exo_ss, M_, options_) % Computes the steady state for optimal policy % % When there is no steady state file, relies on the fact that Lagrange % multipliers appear linearly in the system to be solved. Instead of directly % solving for the Lagrange multipliers along with the other variables, the % algorithms reduces the size of the problem by always computing the value of % the multipliers that minimizes the residuals, given the other variables % (using a minimum norm solution, easy to compute because of the linearity % property). % % INPUTS % ys_init: vector of endogenous variables or instruments % exo_ss vector of exogenous steady state (incl. deterministic exogenous) % M_: Dynare model structure % options: Dynare options structure % % OUTPUTS % steady_state: steady state value % params: parameters at steady state, potentially updated by % steady_state file % check: error indicator, 0 if everything is OK % % SPECIAL REQUIREMENTS % none % Copyright © 2003-2024 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 . params = M_.params; check = 0; options_.steadystate.nocheck = 1; %locally disable checking because Lagrange multipliers are not accounted for in evaluate_steady_state_file nl_func = @(x) dyn_ramsey_static_1(x,exo_ss,ys_init,M_,options_); if ~options_.steadystate_flag && check_static_model(ys_init,exo_ss,M_,options_) steady_state = ys_init; return elseif options_.steadystate_flag k_inst = []; inst_nbr = size(options_.instruments,1); for i = 1:inst_nbr k_inst = [k_inst; strmatch(options_.instruments{i}, M_.endo_names, 'exact')]; end if inst_nbr == 1 %solve for instrument, using univariate solver, starting at initial value for instrument [inst_val, info1]= csolve(nl_func,ys_init(k_inst),'',options_.solve_tolf,options_.ramsey.maxit); if info1==1 || info1==3 check=81; end if info1==4 check=87; end else %solve for instrument, using multivariate solver, starting at %initial value for instruments o_jacobian_flag = options_.jacobian_flag; options_.jacobian_flag = false; [inst_val, errorflag] = dynare_solve(nl_func, ys_init(k_inst), options_.ramsey.maxit, options_.solve_tolf, options_.solve_tolx, options_); options_.jacobian_flag = o_jacobian_flag; if errorflag check=81; end end ys_init(k_inst) = inst_val; [~,params] = evaluate_steady_state_file(ys_init,exo_ss,M_,options_,~options_.steadystate.nocheck); %run steady state file again to update parameters [~,~,steady_state] = nl_func(inst_val); %compute and return steady state else xx = ys_init(1:M_.orig_endo_nbr); o_jacobian_flag = options_.jacobian_flag; options_.jacobian_flag = false; [xx, errorflag] = dynare_solve(nl_func, xx, options_.ramsey.maxit, options_.solve_tolf, options_.solve_tolx, options_); options_.jacobian_flag = o_jacobian_flag; if errorflag check=81; end [~,~,steady_state] = nl_func(xx); end function [resids,rJ,steady_state] = dyn_ramsey_static_1(x,exo_ss,ys_init,M_,options_) resids = []; rJ = []; mult = []; inst_nbr = M_.ramsey_orig_endo_nbr - M_.ramsey_orig_eq_nbr; if options_.steadystate_flag k_inst = []; for i = 1:size(options_.instruments,1) k_inst = [k_inst; strmatch(options_.instruments{i}, M_.endo_names, 'exact')]; end ys_init(k_inst) = x; %set instrument, the only value required for steady state computation, to current value [x,M_.params,check] = evaluate_steady_state_file(ys_init,... %returned x now has size endo_nbr as opposed to input size of n_instruments exo_ss, ... M_,options_,~options_.steadystate.nocheck); if any(imag(x(1:M_.orig_endo_nbr))) %return with penalty resids=ones(inst_nbr,1)+sum(abs(imag(x(1:M_.orig_endo_nbr)))); %return with penalty steady_state=NaN(M_.endo_nbr,1); return end if check(1) %return resids=ones(inst_nbr,1)+sum(abs(x(1:M_.orig_endo_nbr))); %return with penalty steady_state=NaN(M_.endo_nbr,1); return end end xx = zeros(M_.endo_nbr,1); %initialize steady state vector xx(1:M_.orig_endo_nbr) = x(1:M_.orig_endo_nbr); %set values of original endogenous variables based on steady state file or initial value % Determine whether other auxiliary variables will need to be updated if any([M_.aux_vars.type] ~= 6) %auxiliary variables other than multipliers needs_set_auxiliary_variables = true; fh = str2func([M_.fname '.set_auxiliary_variables']); s_a_v_func = @(z) fh(z, exo_ss, M_.params); xx = s_a_v_func(xx); else needs_set_auxiliary_variables = false; end % Compute the value of the Lagrange multipliers that minimizes the norm of the % residuals, given the other endogenous if options_.bytecode res = bytecode('static', M_, options_, xx, exo_ss, M_.params, 'evaluate'); else res = feval([M_.fname '.sparse.static_resid'], xx, exo_ss, M_.params); end A = feval([M_.fname '.ramsey_multipliers_static_g1'], xx, exo_ss, M_.params, M_.ramsey_multipliers_static_g1_sparse_rowval, M_.ramsey_multipliers_static_g1_sparse_colval, M_.ramsey_multipliers_static_g1_sparse_colptr); y = res(1:M_.ramsey_orig_endo_nbr); mult = -A\y; resids1 = y+A*mult; if inst_nbr == 1 r1 = sqrt(resids1'*resids1); else [~,r] = qr([A y]'); k = size(A,1)+(1-inst_nbr:0); r1 = r(end,k)'; end if options_.steadystate_flag resids = r1; else resids = [res(M_.ramsey_orig_endo_nbr+(1:M_.orig_endo_nbr-inst_nbr)); r1]; end if needs_set_auxiliary_variables steady_state = s_a_v_func([xx(1:M_.ramsey_orig_endo_nbr); mult]); else steady_state = [xx(1:M_.ramsey_orig_endo_nbr); mult]; end function result = check_static_model(ys,exo_ss,M_,options_) result = false; if (options_.bytecode) res = bytecode('static', M_, options_, ys, exo_ss, M_.params, 'evaluate'); else res = feval([M_.fname '.sparse.static_resid'], ys, exo_ss, M_.params); end if norm(res) < options_.solve_tolf result = true; end