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fixing bugs related to new functions

time-shift
Michel Juillard 2011-12-18 17:33:08 +01:00
parent c56a8e40e8
commit 336afa9f2b
5 changed files with 77 additions and 195 deletions
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60
matlab/AIM_first_order_solver.m
View File

@ -1,33 +1,31 @@
function [dr,info]=AIM_first_order_solver(jacobia,M_,dr)
try
[dr,aimcode]=dynAIMsolver1(jacobia_,M_,dr);
function [dr,info]=AIM_first_order_solver(jacobia,M,dr,qz_criterium,nd)
info = 0;
[dr,aimcode]=dynAIMsolver1(jacobia,M,dr);
% reuse some of the bypassed code and tests that may be needed
if aimcode ~=1
info(1) = aimcode;
info(2) = 1.0e+8;
return
end
[A,B] =transition_matrix(dr);
dr.eigval = eig(A);
nba = nd-sdim;
nyf = sum(kstate(:,2) > M_.maximum_endo_lag+1);
if nba ~= nyf
temp = sort(abs(dr.eigval));
if nba > nyf
temp = temp(nd-nba+1:nd-nyf)-1-options_.qz_criterium;
info(1) = 3;
elseif nba < nyf;
temp = temp(nd-nyf+1:nd-nba)-1-options_.qz_criterium;
info(1) = 4;
end
info(2) = temp'*temp;
return
end
catch
disp(lasterror.message)
error('Problem with AIM solver - Try to remove the "aim_solver" option')
if aimcode ~=1
info(1) = aimcode;
info(2) = 1.0e+8;
return
end
[A,B] =transition_matrix(dr);
dr.eigval = eig(A);
nd = size(dr.kstate,1);
nba = nd-sum( abs(dr.eigval) < qz_criterium );
nyf = dr.nfwrd+dr.nboth;
if nba ~= nyf
temp = sort(abs(dr.eigval));
if nba > nyf
temp = temp(nd-nba+1:nd-nyf)-1-qz_criterium;
info(1) = 3;
elseif nba < nyf;
temp = temp(nd-nyf+1:nd-nba)-1-qz_criterium;
info(1) = 4;
end
info(2) = temp'*temp;
return
end

1
matlab/dyn_first_order_solver.m
View File

@ -130,6 +130,7 @@ function [dr,info] = dyn_first_order_solver(jacobia,b,M_,dr,options,task)
k1 = find(kstate(n4:nd,2) == M_.maximum_endo_lag+1);
k2 = find(kstate(1:n3,2) == M_.maximum_endo_lag+2);
dr.gx = gx;
dr.ghx = [hx(k1,:); gx(k2(nboth+1:end),:)];
%lead variables actually present in the model

124
matlab/dyn_ramsey_linearized_foc.m
View File

@ -1,124 +0,0 @@
function [jacobia_,dr,info,M_,oo_] = dyn_ramsey_linearized_foc(dr,M_,options_,oo_)
% function [jacobia_,dr,info,M_,oo_] = dyn_ramsey_linearized_foc(dr,M_,options_,oo_)
% computes the Jacobian of the linear approximation of the F.O.C of a
% Ramsey problem
%
% INPUTS
% dr [matlab structure] Decision rules for stochastic simulations.
% M_ [matlab structure] Definition of the model.
% options_ [matlab structure] Global options.
% oo_ [matlab structure] Results
%
% OUTPUTS
% dr [matlab structure] Decision rules for stochastic simulations.
% info [integer] info=1: the model doesn't define current variables uniquely
% info=2: problem in mjdgges.dll info(2) contains error code.
% info=3: BK order condition not satisfied info(2) contains "distance"
% absence of stable trajectory.
% info=4: BK order condition not satisfied info(2) contains "distance"
% indeterminacy.
% info=5: BK rank condition not satisfied.
% info=6: The jacobian matrix evaluated at the steady state is complex.
% M_ [matlab structure]
% options_ [matlab structure]
% oo_ [matlab structure]
%
% ALGORITHM
% ...
%
% SPECIAL REQUIREMENTS
% none.
%
% Copyright (C) 1996-2009 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/>.
info = 0;
if isfield(M_,'orig_model')
orig_model = M_.orig_model;
M_.endo_nbr = orig_model.endo_nbr;
M_.orig_endo_nbr = orig_model.orig_endo_nbr;
M_.aux_vars = orig_model.aux_vars;
M_.endo_names = orig_model.endo_names;
M_.lead_lag_incidence = orig_model.lead_lag_incidence;
M_.maximum_lead = orig_model.maximum_lead;
M_.maximum_endo_lead = orig_model.maximum_endo_lead;
M_.maximum_lag = orig_model.maximum_lag;
M_.maximum_endo_lag = orig_model.maximum_endo_lag;
end
if options_.steadystate_flag
k_inst = [];
instruments = options_.instruments;
for i = 1:size(instruments,1)
k_inst = [k_inst; strmatch(options_.instruments(i,:), ...
M_.endo_names,'exact')];
end
ys = oo_.steady_state;
[inst_val,info1] = dynare_solve('dyn_ramsey_static_', ...
oo_.steady_state(k_inst),0, ...
M_,options_,oo_,it_);
M_.params = evalin('base','M_.params;');
ys(k_inst) = inst_val;
[x,check] = feval([M_.fname '_steadystate'],...
ys,[oo_.exo_steady_state; ...
oo_.exo_det_steady_state]);
if size(x,1) < M_.endo_nbr
if length(M_.aux_vars) > 0
x = add_auxiliary_variables_to_steadystate(x,M_.aux_vars,...
M_.fname,...
oo_.exo_steady_state,...
oo_.exo_det_steady_state,...
M_.params);
else
error([M_.fname '_steadystate.m doesn''t match the model']);
end
end
oo_.steady_state = x;
[junk,junk,multbar] = dyn_ramsey_static_(oo_.steady_state(k_inst),M_,options_,oo_,it_);
else
[oo_.steady_state,info1] = dynare_solve('dyn_ramsey_static_', ...
oo_.steady_state,0,M_,options_,oo_,it_);
[junk,junk,multbar] = dyn_ramsey_static_(oo_.steady_state,M_,options_,oo_,it_);
end
check1 = max(abs(feval([M_.fname '_static'],...
oo_.steady_state,...
[oo_.exo_steady_state; ...
oo_.exo_det_steady_state], M_.params))) > options_.dynatol ;
if check1
info(1) = 20;
info(2) = check1'*check1;
return
end
[jacobia_,M_] = dyn_ramsey_dynamic_(oo_.steady_state,multbar,M_,options_,oo_,it_);
klen = M_.maximum_lag + M_.maximum_lead + 1;
dr.ys = [oo_.steady_state;zeros(M_.exo_nbr,1);multbar];
oo_.steady_state = dr.ys;
if options_.noprint == 0
disp_steady_state(M_,oo_)
for i=M_.orig_endo_nbr:M_.endo_nbr
if strmatch('mult_',M_.endo_names(i,:))
disp(sprintf('%s \t\t %g',M_.endo_names(i,:), ...
dr.ys(i)));
end
end
end

4
matlab/osr1.m
View File

@ -40,12 +40,12 @@ end
exe =zeros(M_.exo_nbr,1);
dr = set_state_space(oo_.dr,M_);
oo_.dr = set_state_space(oo_.dr,M_);
np = size(i_params,1);
t0 = M_.params(i_params);
inv_order_var = dr.inv_order_var;
inv_order_var = oo_.dr.inv_order_var;
H0 = 1e-4*eye(np);
crit = 1e-7;

83
matlab/stochastic_solvers.m
View File

@ -66,35 +66,42 @@ if options_.k_order_solver;
return;
end
if options_.ramsey_policy
% expanding system for Optimal Linear Regulator
[jacobia_,dr,info,M_,oo_] = dyn_ramsey_linearized_foc(dr,M_,options_,oo_);
else
klen = M_.maximum_lag + M_.maximum_lead + 1;
iyv = M_.lead_lag_incidence';
iyv = iyv(:);
iyr0 = find(iyv) ;
it_ = M_.maximum_lag + 1 ;
if M_.exo_nbr == 0
oo_.exo_steady_state = [] ;
end
it_ = M_.maximum_lag + 1;
z = repmat(dr.ys,1,klen);
z = z(iyr0) ;
if options_.order == 1
[junk,jacobia_] = feval([M_.fname '_dynamic'],z,[oo_.exo_simul ...
oo_.exo_det_simul], M_.params, dr.ys, it_);
elseif options_.order == 2
[junk,jacobia_,hessian1] = feval([M_.fname '_dynamic'],z,...
[oo_.exo_simul ...
oo_.exo_det_simul], M_.params, dr.ys, it_);
if options_.use_dll
% In USE_DLL mode, the hessian is in the 3-column sparse representation
hessian1 = sparse(hessian1(:,1), hessian1(:,2), hessian1(:,3), ...
size(jacobia_, 1), size(jacobia_, 2)*size(jacobia_, 2));
end
klen = M_.maximum_lag + M_.maximum_lead + 1;
exo_simul = [repmat(oo_.exo_steady_state',klen,1) repmat(oo_.exo_det_steady_state',klen,1)];
iyv = M_.lead_lag_incidence';
iyv = iyv(:);
iyr0 = find(iyv) ;
it_ = M_.maximum_lag + 1 ;
if M_.exo_nbr == 0
oo_.exo_steady_state = [] ;
end
it_ = M_.maximum_lag + 1;
z = repmat(dr.ys,1,klen);
if options_.order == 1
if (options_.bytecode)
[chck, junk, loc_dr] = bytecode('dynamic','evaluate', z,exo_simul, ...
M_.params, dr.ys, 1);
jacobia_ = [loc_dr.g1 loc_dr.g1_x loc_dr.g1_xd];
else
[junk,jacobia_] = feval([M_.fname '_dynamic'],z(iyr0),exo_simul, ...
M_.params, dr.ys, it_);
end;
elseif options_.order == 2
if (options_.bytecode)
[chck, junk, loc_dr] = bytecode('dynamic','evaluate', z,exo_simul, ...
M_.params, dr.ys, 1);
jacobia_ = [loc_dr.g1 loc_dr.g1_x];
else
[junk,jacobia_,hessian1] = feval([M_.fname '_dynamic'],z(iyr0),...
exo_simul, ...
M_.params, dr.ys, 3);
end;
if options_.use_dll
% In USE_DLL mode, the hessian is in the 3-column sparse representation
hessian1 = sparse(hessian1(:,1), hessian1(:,2), hessian1(:,3), ...
size(jacobia_, 1), size(jacobia_, 2)*size(jacobia_, 2));
end
end
@ -119,6 +126,7 @@ nstatic = dr.nstatic;
nfwrd = dr.nfwrd;
npred = dr.npred;
nboth = dr.nboth;
nfwrds = nfwrd+nboth;
order_var = dr.order_var;
nd = size(kstate,1);
nz = nnz(M_.lead_lag_incidence);
@ -135,10 +143,9 @@ if M_.maximum_endo_lead == 0
% If required, use AIM solver if not check only
if options_.order == 1
[k1,junk,k2] = find(kstate(:,4));
temp = -b\jacobia_(:,[k2 nz+1:end]);
dr.ghx = temp(:,1:npred);
dr.ghx(:,k1) = -b\jacobia_(:,k2);
if M_.exo_nbr
dr.ghu = temp(:,npred+1:end);
dr.ghu = -b\jacobia_(:,nz+1:end);
end
dr.eigval = eig(transition_matrix(dr));
dr.rank = 0;
@ -154,16 +161,16 @@ if M_.maximum_endo_lead == 0
'backward models'])
end
elseif M_.maximum_endo_lag == 0
% purely forward model
dr.ghx = [];
dr.ghu = -b\jacobia_(:,nz+1:end);
% purely forward model
dr.ghx = [];
dr.ghu = -b\jacobia_(:,nz+1:end);
elseif options_.risky_steadystate
[dr,info] = dyn_risky_steadystate_solver(oo_.steady_state,M_,dr, ...
options_,oo_);
else
% If required, use AIM solver if not check only
if (options_.aim_solver == 1) && (task == 0)
[dr,info] = AIM_first_order_solver(jacobia_,M_,dr,sdim);
[dr,info] = AIM_first_order_solver(jacobia_,M_,dr,options_.qz_criterium);
else % use original Dynare solver
[dr,info] = dyn_first_order_solver(jacobia_,b,M_,dr,options_,task);
@ -187,12 +194,12 @@ else
f1 = sparse(jacobia_(:,nonzeros(M_.lead_lag_incidence(M_.maximum_endo_lag+2:end,order_var))));
f0 = sparse(jacobia_(:,nonzeros(M_.lead_lag_incidence(M_.maximum_endo_lag+1,order_var))));
fudet = sparse(jacobia_(:,nz+M_.exo_nbr+1:end));
M1 = inv(f0+[zeros(M_.endo_nbr,nstatic) f1*gx zeros(M_.endo_nbr,nyf-nboth)]);
M1 = inv(f0+[zeros(M_.endo_nbr,nstatic) f1*dr.gx zeros(M_.endo_nbr,nfwrds-nboth)]);
M2 = M1*f1;
dr.ghud = cell(M_.exo_det_length,1);
dr.ghud{1} = -M1*fudet;
for i = 2:M_.exo_det_length
dr.ghud{i} = -M2*dr.ghud{i-1}(end-nyf+1:end,:);
dr.ghud{i} = -M2*dr.ghud{i-1}(end-nfwrds+1:end,:);
end
end