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Remove oo_.dr.{nstatic,npred,nboth,nfwrd,nspred,nsfwrd} 

Replace them by equivalents in M_ (and an extra one: M_.dynamic).

IMPORTANT POINT: oo_.dr.npred used to count both purely backward and mixed/both
variables. This was the cause of lots of confusion. The new M_.npred only
counts purely backward variables.

We now have the following indentities:

M_.npred + M_.nboth + M_.nfwrd + M_.nstatic = M_.endo_nbr
M_.nspred = M_.npred + M_.nboth
M_.nsfwrd = M_.nfwrd + M_.nboth
M_.ndynamic = M_.npred + M_.nboth + M_.nfwrd
time-shift
Sébastien Villemot 2012-11-16 20:05:13 +01:00
parent 92727ed75c
commit c121aa14b1
34 changed files with 217 additions and 248 deletions
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30
doc/dynare.texi
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@ -3387,32 +3387,31 @@ Dynare distinguishes four types of endogenous variables:
@table @emph
@item Purely backward (or purely predetermined) variables
@vindex oo_.dr.npred
@vindex oo_.dr.nboth
@vindex M_.npred
Those that appear only at current and past period in the model, but
not at future period (@i{i.e.} at @math{t} and @math{t-1} but not
@math{t+1}). The number of such variables is equal to
@code{oo_.dr.npred - oo_.dr.nboth}.
@code{M_.npred}.
@item Purely forward variables
@vindex oo_.dr.nfwrd
@vindex M_.nfwrd
Those that appear only at current and future period in the model, but
not at past period (@i{i.e.} at @math{t} and @math{t+1} but not
@math{t-1}). The number of such variables is stored in
@code{oo_.dr.nfwrd}.
@code{M_.nfwrd}.
@item Mixed variables
@vindex oo_.dr.nboth
@vindex M_.nboth
Those that appear at current, past and future period in the model
(@i{i.e.} at @math{t}, @math{t+1} and @math{t-1}). The number of such
variables is stored in @code{oo_.dr.nboth}.
variables is stored in @code{M_.nboth}.
@item Static variables
@vindex oo_.dr.nstatic
@vindex M_.nstatic
Those that appear only at current, not past and future period in the
model (@i{i.e.} only at @math{t}, not at @math{t+1} or
@math{t-1}). The number of such variables is stored in
@code{oo_.dr.nstatic}.
@code{M_.nstatic}.
@end table
Note that all endogenous variables fall into one of these four
@ -3421,7 +3420,7 @@ categories, since after the creation of auxiliary variables
and one lag. We therefore have the following identity:
@example
oo_.dr.npred + oo_.dr.nfwrd + oo_.dr.nstatic = M_.endo_nbr
M_.npred + M_.both + M_.nfwrd + M_.nstatic = M_.endo_nbr
@end example
Internally, Dynare uses two orderings of the endogenous variables: the
@ -3445,11 +3444,14 @@ to the endogenous variable numbered @code{oo_.dr_order_var(k)} in
declaration order. Conversely, k-th declared variable is numbered
@code{oo_.dr.inv_order_var(k)} in DR-order.
@vindex oo_.dr.npred
@vindex M_.nspred
@vindex M_.nsfwrd
@vindex M_.ndynamic
Finally, the state variables of the model are the purely backward variables
and the mixed variables. They are orderer in DR-order when they appear in
decision rules elements. There are @code{oo_.dr.npred} such
variables.
decision rules elements. There are @code{M_.nspred = M_.npred + M_.nboth} such
variables. Similarly, one has @code{M_.nfwrd = M_.nfwrd + M_.nboth},
and @code{M_.ndynamic = M_.nfwrd+M_.nboth+M_.npred}.
@node First order approximation
@subsection First order approximation
@ -3542,7 +3544,7 @@ where @math{y^s} is the steady state value of @math{y}, and @math{z_t} is a
vector consisting of the deviation from the steady state of the state
variables (in DR-order) at date @math{t-1} followed by the exogenous variables at
date @math{t} (in declaration order). The vector @math{z_t} is
therefore of size @math{n_z} = @code{oo_.dr.npred +
therefore of size @math{n_z} = @code{M_.nspred +
M_.exo_nbr}.
The coefficients of the decision rules are stored as follows:

12
matlab/AIM_first_order_solver.m
View File

@ -82,15 +82,15 @@ function [dr,info]=AIM_first_order_solver(jacobia,M,dr,qz_criterium)
nd = size(dr.kstate,1);
nba = nd-sum( abs(dr.eigval) < qz_criterium );
nyf = dr.nfwrd+dr.nboth;
nsfwrd = M.nsfwrd;
if nba ~= nyf
if nba ~= nsfwrd
temp = sort(abs(dr.eigval));
if nba > nyf
temp = temp(nd-nba+1:nd-nyf)-1-qz_criterium;
if nba > nsfwrd
temp = temp(nd-nba+1:nd-nsfwrd)-1-qz_criterium;
info(1) = 3;
elseif nba < nyf;
temp = temp(nd-nyf+1:nd-nba)-1-qz_criterium;
elseif nba < nsfwrd;
temp = temp(nd-nsfwrd+1:nd-nba)-1-qz_criterium;
info(1) = 4;
end
info(2) = temp'*temp;

8
matlab/UnivariateSpectralDensity.m
View File

@ -63,13 +63,13 @@ end
f = zeros(nvar,GridSize);
ghx = dr.ghx;
ghu = dr.ghu;
npred = dr.npred;
nstatic = dr.nstatic;
nspred = M_.nspred;
nstatic = M_.nstatic;
kstate = dr.kstate;
order = dr.order_var;
iv(order) = [1:length(order)];
nx = size(ghx,2);
ikx = [nstatic+1:nstatic+npred];
ikx = [nstatic+1:nstatic+nspred];
A = zeros(nx,nx);
k0 = kstate(find(kstate(:,2) <= M_.maximum_lag+1),:);
i0 = find(k0(:,2) == M_.maximum_lag+1);
@ -175,4 +175,4 @@ if pltinfo
box on
axis tight
end
end
end

13
matlab/check.m
View File

@ -38,7 +38,7 @@ function [result,info] = check(M, options, oo)
%! @end deftypefn
%@eod:
% Copyright (C) 2001-2011 Dynare Team
% Copyright (C) 2001-2012 Dynare Team
%
% This file is part of Dynare.
%
@ -77,16 +77,13 @@ if info(1) ~= 0 && info(1) ~= 3 && info(1) ~= 4
end
eigenvalues_ = dr.eigval;
if (options.block)
nyf = dr.nyf;
else
nyf = nnz(dr.kstate(:,2)>M.maximum_endo_lag+1);
end;
[m_lambda,i]=sort(abs(eigenvalues_));
n_explod = nnz(abs(eigenvalues_) > options.qz_criterium);
nsfwrd = M.nsfwrd
result = 0;
if (nyf== n_explod) && (dr.full_rank)
if (nsfwrd == n_explod) && (dr.full_rank)
result = 1;
end
@ -97,7 +94,7 @@ if options.noprint == 0
z=[m_lambda real(eigenvalues_(i)) imag(eigenvalues_(i))]';
disp(sprintf('%16.4g %16.4g %16.4g\n',z))
disp(sprintf('\nThere are %d eigenvalue(s) larger than 1 in modulus ', n_explod));
disp(sprintf('for %d forward-looking variable(s)',nyf));
disp(sprintf('for %d forward-looking variable(s)',nsfwrd));
disp(' ')
if result
disp('The rank condition is verified.')

4
matlab/disp_dr.m
View File

@ -8,7 +8,7 @@ function disp_dr(dr,order,var_list)
% var_list [char array]: list of endogenous variables for which the
% decision rules should be printed
% Copyright (C) 2001-2011 Dynare Team
% Copyright (C) 2001-2012 Dynare Team
%
% This file is part of Dynare.
%
@ -30,7 +30,7 @@ global M_ options_
nx =size(dr.ghx,2);
nu =size(dr.ghu,2);
if options_.block
k = dr.npred + dr.nboth;
k = M_.nspred;
k1 = 1:M_.endo_nbr;
else
k = find(dr.kstate(:,2) <= M_.maximum_lag+1);

4
matlab/disp_model_summary.m
View File

@ -7,7 +7,7 @@ function disp_model_summary(M,dr)
% M [matlab structure] Definition of the model.
% dr [matlab structure] Decision rules
%
% Copyright (C) 2001-2010 Dynare Team
% Copyright (C) 2001-2012 Dynare Team
%
% This file is part of Dynare.
%
@ -33,7 +33,7 @@ disp([' Number of state variables: ' ...
int2str(length(find(dr.kstate(:,2) <= M.maximum_lag+1)))])
disp([' Number of jumpers: ' ...
int2str(length(find(dr.kstate(:,2) == M.maximum_lag+2)))])
disp([' Number of static variables: ' int2str(dr.nstatic)])
disp([' Number of static variables: ' int2str(M.nstatic)])
my_title='MATRIX OF COVARIANCE OF EXOGENOUS SHOCKS';
labels = deblank(M.exo_names);
headers = char('Variables',labels);

6
matlab/display_conditional_variance_decomposition.m
View File

@ -16,7 +16,7 @@ function oo_ = display_conditional_variance_decomposition(Steps, SubsetOfVariabl
% [1] The covariance matrix of the state innovations needs to be diagonal.
% [2] In this version, absence of measurement errors is assumed...
% Copyright (C) 2010-2011 Dynare Team
% Copyright (C) 2010-2012 Dynare Team
%
% This file is part of Dynare.
%
@ -40,7 +40,7 @@ StateSpaceModel.number_of_state_innovations = exo_nbr;
StateSpaceModel.sigma_e_is_diagonal = M_.sigma_e_is_diagonal;
iv = (1:endo_nbr)';
ic = dr.nstatic+(1:dr.npred)';
ic = M_.nstatic+(1:M_.nspred)';
[StateSpaceModel.transition_matrix,StateSpaceModel.impulse_matrix] = kalman_transition_matrix(dr,iv,ic,exo_nbr);
StateSpaceModel.state_innovations_covariance_matrix = M_.Sigma_e;
@ -73,4 +73,4 @@ for i=1:length(Steps)
end
end
oo_.conditional_variance_decomposition = conditional_decomposition_array;
oo_.conditional_variance_decomposition = conditional_decomposition_array;

10
matlab/dr_block.m
View File

@ -74,10 +74,6 @@ end;
mexErrCheck('bytecode', chck);
dr.full_rank = 1;
dr.eigval = [];
dr.nstatic = 0;
dr.nfwrd = 0;
dr.npred = 0;
dr.nboth = 0;
dr.nd = 0;
dr.ghx = [];
@ -89,11 +85,6 @@ n_sv = size(dr.state_var, 2);
dr.ghx = zeros(M_.endo_nbr, length(dr.state_var));
dr.exo_var = 1:M_.exo_nbr;
dr.ghu = zeros(M_.endo_nbr, M_.exo_nbr);
dr.nstatic = M_.nstatic;
dr.nfwrd = M_.nfwrd;
dr.npred = M_.npred;
dr.nboth = M_.nboth;
dr.nyf = 0;
for i = 1:Size;
ghx = [];
indexi_0 = 0;
@ -107,7 +98,6 @@ for i = 1:Size;
n_fwrd = data(i).n_forward;
n_both = data(i).n_mixed;
n_static = data(i).n_static;
dr.nyf = dr.nyf + n_fwrd + n_both;
nd = n_pred + n_fwrd + 2*n_both;
dr.nd = dr.nd + nd;
n_dynamic = n_pred + n_fwrd + n_both;

10
matlab/dsge_simulated_theoretical_conditional_variance_decomposition.m
View File

@ -107,16 +107,16 @@ for file = 1:NumberOfDrawsFiles
end
if first_call
endo_nbr = M_.endo_nbr;
nstatic = dr.nstatic;
npred = dr.npred;
nstatic = M_.nstatic;
nspred = M_.nspred;
iv = (1:endo_nbr)';
ic = [ nstatic+(1:npred) endo_nbr+(1:size(dr.ghx,2)-npred) ]';
ic = [ nstatic+(1:nspred) endo_nbr+(1:size(dr.ghx,2)-nspred) ]';
StateSpaceModel.number_of_state_equations = M_.endo_nbr;
StateSpaceModel.number_of_state_innovations = M_.exo_nbr;
StateSpaceModel.sigma_e_is_diagonal = M_.sigma_e_is_diagonal;
StateSpaceModel.order_var = dr.order_var;
first_call = 0;
clear('endo_nbr','nstatic','npred','k');
clear('endo_nbr','nstatic','nspred','k');
end
[StateSpaceModel.transition_matrix,StateSpaceModel.impulse_matrix] = kalman_transition_matrix(dr,iv,ic,M_.exo_nbr);
StateSpaceModel.state_innovations_covariance_matrix = M_.Sigma_e;
@ -144,4 +144,4 @@ for file = 1:NumberOfDrawsFiles
end
end
options_.ar = nar;
options_.ar = nar;

32
matlab/dyn_first_order_solver.m
View File

@ -66,7 +66,7 @@ function [dr,info] = dyn_first_order_solver(jacobia,DynareModel,dr,DynareOptions
persistent reorder_jacobian_columns innovations_idx index_s index_m index_c
persistent index_p row_indx index_0m index_0p k1 k2 state_var
persistent ndynamic nstatic nfwrd npred nboth nd nyf n_current index_d
persistent ndynamic nstatic nfwrd npred nboth nd nsfwrd n_current index_d
persistent index_e index_d1 index_d2 index_e1 index_e2 row_indx_de_1
persistent row_indx_de_2 cols_b
@ -85,12 +85,12 @@ if isempty(reorder_jacobian_columns)
maximum_lag = DynareModel.maximum_endo_lag;
kstate = dr.kstate;
nfwrd = dr.nfwrd;
nboth = dr.nboth;
npred = dr.npred-nboth;
nstatic = dr.nstatic;
ndynamic = npred+nfwrd+nboth;
nyf = nfwrd + nboth;
nfwrd = DynareModel.nfwrd;
nboth = DynareModel.nboth;
npred = DynareModel.npred;
nstatic = DynareModel.nstatic;
ndynamic = DynareModel.ndynamic;
nsfwrd = DynareModel.nsfwrd;
n = DynareModel.endo_nbr;
k1 = 1:(npred+nboth);
@ -142,12 +142,12 @@ if isempty(reorder_jacobian_columns)
row_indx = nstatic+row_indx_de_1;
index_d = [index_0m index_p];
llx = lead_lag_incidence(:,order_var);
index_d1 = [find(llx(maximum_lag+1,nstatic+(1:npred))), npred+nboth+(1:nyf) ];
index_d1 = [find(llx(maximum_lag+1,nstatic+(1:npred))), npred+nboth+(1:nsfwrd) ];
index_d2 = npred+(1:nboth);
index_e = [index_m index_0p];
index_e1 = [1:npred+nboth, npred+nboth+find(llx(maximum_lag+1,nstatic+npred+(1: ...
nyf)))];
nsfwrd)))];
index_e2 = npred+nboth+(1:nboth);
[junk,cols_b] = find(lead_lag_incidence(maximum_lag+1, order_var));
@ -239,13 +239,13 @@ else
return
end
if nba ~= nyf
if nba ~= nsfwrd
temp = sort(abs(dr.eigval));
if nba > nyf
temp = temp(nd-nba+1:nd-nyf)-1-DynareOptions.qz_criterium;
if nba > nsfwrd
temp = temp(nd-nba+1:nd-nsfwrd)-1-DynareOptions.qz_criterium;
info(1) = 3;
elseif nba < nyf;
temp = temp(nd-nyf+1:nd-nba)-1-DynareOptions.qz_criterium;
elseif nba < nsfwrd;
temp = temp(nd-nsfwrd+1:nd-nba)-1-DynareOptions.qz_criterium;
info(1) = 4;
end
info(2) = temp'*temp;
@ -253,7 +253,7 @@ else
end
%First order approximation
indx_stable_root = 1: (nd - nyf); %=> index of stable roots
indx_stable_root = 1: (nd - nsfwrd); %=> index of stable roots
indx_explosive_root = npred + nboth + 1:nd; %=> index of explosive roots
% derivatives with respect to dynamic state variables
% forward variables
@ -326,4 +326,4 @@ end
% non-predetermined variables
dr.gx = gx;
%predetermined (endogenous state) variables, square transition matrix
dr.Gy = hx;
dr.Gy = hx;

32
matlab/dyn_second_order_solver.m
View File

@ -56,16 +56,16 @@ function dr = dyn_second_order_solver(jacobia,hessian,dr,M_,threads_ABC,threads_
Gy = dr.Gy;
kstate = dr.kstate;
nstatic = dr.nstatic;
nfwrd = dr.nfwrd;
npred = dr.npred;
nboth = dr.nboth;
nyf = nfwrd+nboth;
nstatic = M_.nstatic;
nfwrd = M_.nfwrd;
nspred = M_.nspred;
nboth = M_.nboth;
nsfwrd = M_.nsfwrd;
order_var = dr.order_var;
nd = size(kstate,1);
lead_lag_incidence = M_.lead_lag_incidence;
np = nd - nyf;
np = nd - nsfwrd;
k1 = nonzeros(lead_lag_incidence(:,order_var)');
kk = [k1; length(k1)+(1:M_.exo_nbr+M_.exo_det_nbr)'];
@ -80,7 +80,7 @@ function dr = dyn_second_order_solver(jacobia,hessian,dr,M_,threads_ABC,threads_
zx(1:np,:)=eye(np);
k0 = [1:M_.endo_nbr];
gx1 = dr.ghx;
hu = dr.ghu(nstatic+[1:npred],:);
hu = dr.ghu(nstatic+[1:nspred],:);
k0 = find(lead_lag_incidence(M_.maximum_endo_lag+1,order_var)');
zx = [zx; gx1(k0,:)];
zu = [zu; dr.ghu(k0,:)];
@ -104,10 +104,10 @@ function dr = dyn_second_order_solver(jacobia,hessian,dr,M_,threads_ABC,threads_
k1 = find(kstate(:,2) == M_.maximum_endo_lag+2);
% Jacobian with respect to the variables with the highest lead
fyp = jacobia(:,kstate(k1,3)+nnz(M_.lead_lag_incidence(M_.maximum_endo_lag+1,:)));
B(:,nstatic+npred-dr.nboth+1:end) = fyp;
B(:,nstatic+M_.npred+1:end) = fyp;
[junk,k1,k2] = find(M_.lead_lag_incidence(M_.maximum_endo_lag+M_.maximum_endo_lead+1,order_var));
A(1:M_.endo_nbr,nstatic+1:nstatic+npred)=...
A(1:M_.endo_nbr,nstatic+[1:npred])+fyp*gx1(k1,1:npred);
A(1:M_.endo_nbr,nstatic+1:nstatic+nspred)=...
A(1:M_.endo_nbr,nstatic+[1:nspred])+fyp*gx1(k1,1:nspred);
C = Gy;
D = [rhs; zeros(n-M_.endo_nbr,size(rhs,2))];
@ -117,11 +117,11 @@ function dr = dyn_second_order_solver(jacobia,hessian,dr,M_,threads_ABC,threads_
%ghxu
%rhs
hu = dr.ghu(nstatic+1:nstatic+npred,:);
hu = dr.ghu(nstatic+1:nstatic+nspred,:);
[rhs, err] = sparse_hessian_times_B_kronecker_C(hessian,zx,zu,threads_BC);
mexErrCheck('sparse_hessian_times_B_kronecker_C', err);
hu1 = [hu;zeros(np-npred,M_.exo_nbr)];
hu1 = [hu;zeros(np-nspred,M_.exo_nbr)];
[nrhx,nchx] = size(Gy);
[nrhu1,nchu1] = size(hu1);
@ -150,7 +150,7 @@ function dr = dyn_second_order_solver(jacobia,hessian,dr,M_,threads_ABC,threads_
% derivatives of F with respect to forward variables
% reordering predetermined variables in diminishing lag order
O1 = zeros(M_.endo_nbr,nstatic);
O2 = zeros(M_.endo_nbr,M_.endo_nbr-nstatic-npred);
O2 = zeros(M_.endo_nbr,M_.endo_nbr-nstatic-nspred);
LHS = zeros(M_.endo_nbr,M_.endo_nbr);
LHS(:,k0) = jacobia(:,nonzeros(lead_lag_incidence(M_.maximum_endo_lag+1,order_var)));
RHS = zeros(M_.endo_nbr,M_.exo_nbr^2);
@ -159,11 +159,11 @@ function dr = dyn_second_order_solver(jacobia,hessian,dr,M_,threads_ABC,threads_
E = eye(M_.endo_nbr);
kh = reshape([1:nk^2],nk,nk);
kp = sum(kstate(:,2) <= M_.maximum_endo_lag+1);
E1 = [eye(npred); zeros(kp-npred,npred)];
E1 = [eye(nspred); zeros(kp-nspred,nspred)];
H = E1;
hxx = dr.ghxx(nstatic+[1:npred],:);
hxx = dr.ghxx(nstatic+[1:nspred],:);
[junk,k2a,k2] = find(M_.lead_lag_incidence(M_.maximum_endo_lag+2,order_var));
k3 = nnz(M_.lead_lag_incidence(1:M_.maximum_endo_lag+1,:))+(1:dr.nsfwrd)';
k3 = nnz(M_.lead_lag_incidence(1:M_.maximum_endo_lag+1,:))+(1:M_.nsfwrd)';
[B1, err] = sparse_hessian_times_B_kronecker_C(hessian(:,kh(k3,k3)),gu(k2a,:),threads_BC);
mexErrCheck('sparse_hessian_times_B_kronecker_C', err);
RHS = RHS + jacobia(:,k2)*guu(k2a,:)+B1;

14
matlab/dynare_estimation_init.m
View File

@ -201,9 +201,9 @@ objective_function_penalty_base = 1e8;
% Get informations about the variables of the model.
dr = set_state_space(oo_.dr,M_,options_);
oo_.dr = dr;
nstatic = dr.nstatic; % Number of static variables.
npred = dr.npred; % Number of predetermined variables.
nspred = dr.nspred; % Number of predetermined variables in the state equation.
nstatic = M_.nstatic; % Number of static variables.
npred = M_.nspred; % Number of predetermined variables.
nspred = M_.nspred; % Number of predetermined variables in the state equation.
% Test if observed variables are declared.
if isempty(options_.varobs)
@ -219,12 +219,12 @@ for i=1:n_varobs
end
% Define union of observed and state variables
k2 = union(var_obs_index,[dr.nstatic+1:dr.nstatic+dr.npred]', 'rows');
k2 = union(var_obs_index,[M_.nstatic+1:M_.nstatic+M_.nspred]', 'rows');
% Set restrict_state to postion of observed + state variables in expanded state vector.
oo_.dr.restrict_var_list = k2;
bayestopt_.restrict_var_list = k2;
% set mf0 to positions of state variables in restricted state vector for likelihood computation.
[junk,bayestopt_.mf0] = ismember([dr.nstatic+1:dr.nstatic+dr.npred]',k2);
[junk,bayestopt_.mf0] = ismember([M_.nstatic+1:M_.nstatic+M_.nspred]',k2);
% Set mf1 to positions of observed variables in restricted state vector for likelihood computation.
[junk,bayestopt_.mf1] = ismember(var_obs_index,k2);
% Set mf2 to positions of observed variables in expanded state vector for filtering and smoothing.
@ -271,11 +271,11 @@ if options_.block == 1
[junk,bayestopt_.smoother_mf] = ismember(k1, ...
bayestopt_.smoother_var_list);
else
k2 = union(var_obs_index,[dr.nstatic+1:dr.nstatic+dr.npred]', 'rows');
k2 = union(var_obs_index,[M_.nstatic+1:M_.nstatic+M_.nspred]', 'rows');
% Set restrict_state to postion of observed + state variables in expanded state vector.
oo_.dr.restrict_var_list = k2;
% set mf0 to positions of state variables in restricted state vector for likelihood computation.
[junk,bayestopt_.mf0] = ismember([dr.nstatic+1:dr.nstatic+dr.npred]',k2);
[junk,bayestopt_.mf0] = ismember([M_.nstatic+1:M_.nstatic+M_.nspred]',k2);
% Set mf1 to positions of observed variables in restricted state vector for likelihood computation.
[junk,bayestopt_.mf1] = ismember(var_obs_index,k2);
% Set mf2 to positions of observed variables in expanded state vector for filtering and smoothing.

10
matlab/dynare_resolve.m
View File

@ -49,7 +49,7 @@ function [A,B,ys,info,Model,DynareOptions,DynareResults] = dynare_resolve(Model,
%! @end deftypefn
%@eod:
% Copyright (C) 2001-2011 Dynare Team
% Copyright (C) 2001-2012 Dynare Team
%
% This file is part of Dynare.
%
@ -83,11 +83,11 @@ end
switch nargin
case 3
endo_nbr = Model.endo_nbr;
nstatic = DynareResults.dr.nstatic;
npred = DynareResults.dr.npred;
nstatic = Model.nstatic;
nspred = Model.nspred;
iv = (1:endo_nbr)';
if DynareOptions.block == 0
ic = [ nstatic+(1:npred) endo_nbr+(1:size(DynareResults.dr.ghx,2)-npred) ]';
ic = [ nstatic+(1:nspred) endo_nbr+(1:size(DynareResults.dr.ghx,2)-nspred) ]';
else
ic = DynareResults.dr.restrict_columns;
end;
@ -104,4 +104,4 @@ if nargout==1
end
[A,B] = kalman_transition_matrix(DynareResults.dr,iv,ic,Model.exo_nbr);
ys = DynareResults.dr.ys;
ys = DynareResults.dr.ys;

28
matlab/evaluate_planner_objective.m
View File

@ -31,8 +31,8 @@ function planner_objective_value = evaluate_planner_objective(M,options,oo)
dr = oo.dr;
endo_nbr = M.endo_nbr;
exo_nbr = M.exo_nbr;
nstatic = dr.nstatic;
npred = dr.npred;
nstatic = M.nstatic;
nspred = M.nspred;
lead_lag_incidence = M.lead_lag_incidence;
beta = get_optimal_policy_discount_factor(M.params,M.param_names);
if options.ramsey_policy
@ -44,8 +44,8 @@ ipred = find(lead_lag_incidence(M.maximum_lag,:))';
order_var = dr.order_var;
LQ = true;
Gy = dr.ghx(nstatic+(1:npred),:);
Gu = dr.ghu(nstatic+(1:npred),:);
Gy = dr.ghx(nstatic+(1:nspred),:);
Gu = dr.ghu(nstatic+(1:nspred),:);
gy(dr.order_var,:) = dr.ghx;
gu(dr.order_var,:) = dr.ghu;
@ -53,10 +53,10 @@ if options.ramsey_policy && options.order == 1 && ~options.linear
options.order = 2;
options.qz_criterium = 1+1e-6;
[dr,info] = stochastic_solvers(oo.dr,0,M,options,oo);
Gyy = dr.ghxx(nstatic+(1:npred),:);
Guu = dr.ghuu(nstatic+(1:npred),:);
Gyu = dr.ghxu(nstatic+(1:npred),:);
Gss = dr.ghs2(nstatic+(1:npred),:);
Gyy = dr.ghxx(nstatic+(1:nspred),:);
Guu = dr.ghuu(nstatic+(1:nspred),:);
Gyu = dr.ghxu(nstatic+(1:nspred),:);
Gss = dr.ghs2(nstatic+(1:nspred),:);
gyy(dr.order_var,:) = dr.ghxx;
guu(dr.order_var,:) = dr.ghuu;
gyu(dr.order_var,:) = dr.ghxu;
@ -81,12 +81,12 @@ mexErrCheck('A_times_B_kronecker_C', err);
mexErrCheck('A_times_B_kronecker_C', err);
Wbar =U/(1-beta);
Wy = Uy*gy/(eye(npred)-beta*Gy);
Wy = Uy*gy/(eye(nspred)-beta*Gy);
Wu = Uy*gu+beta*Wy*Gu;
if LQ
Wyy = Uyygygy/(eye(npred*npred)-beta*kron(Gy,Gy));
Wyy = Uyygygy/(eye(nspred*nspred)-beta*kron(Gy,Gy));
else
Wyy = (Uy*gyy+Uyygygy+beta*Wy*Gyy)/(eye(npred*npred)-beta*kron(Gy,Gy));
Wyy = (Uy*gyy+Uyygygy+beta*Wy*Gyy)/(eye(nspred*nspred)-beta*kron(Gy,Gy));
end
[Wyygugu, err] = A_times_B_kronecker_C(Wyy,Gu,Gu,options.threads.kronecker.A_times_B_kronecker_C);
mexErrCheck('A_times_B_kronecker_C', err);
@ -115,8 +115,8 @@ if ~isempty(M.endo_histval)
yhat2(1:M.orig_endo_nbr) = M.endo_histval(1:M.orig_endo_nbr);
end
end
yhat1 = yhat1(dr.order_var(nstatic+(1:npred)),1)-dr.ys(dr.order_var(nstatic+(1:npred)));
yhat2 = yhat2(dr.order_var(nstatic+(1:npred)),1)-dr.ys(dr.order_var(nstatic+(1:npred)));
yhat1 = yhat1(dr.order_var(nstatic+(1:nspred)),1)-dr.ys(dr.order_var(nstatic+(1:nspred)));
yhat2 = yhat2(dr.order_var(nstatic+(1:nspred)),1)-dr.ys(dr.order_var(nstatic+(1:nspred)));
u = oo.exo_simul(1,:)';
[Wyyyhatyhat1, err] = A_times_B_kronecker_C(Wyy,yhat1,yhat1,options.threads.kronecker.A_times_B_kronecker_C);
@ -144,4 +144,4 @@ if ~options.noprint
disp([' - with initial Lagrange multipliers set to steady state: ' ...
num2str(planner_objective_value(1)) ])
disp(' ')
end
end

8
matlab/forcst.m
View File

@ -17,7 +17,7 @@ function [yf,int_width]=forcst(dr,y0,horizon,var_list)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2011 Dynare Team
% Copyright (C) 2003-2012 Dynare Team
%
% This file is part of Dynare.
%
@ -38,12 +38,12 @@ global M_ oo_ options_
make_ex_;
yf = simult_(y0,dr,zeros(horizon,M_.exo_nbr),1);
nstatic = dr.nstatic;
npred = dr.npred;
nstatic = M_.nstatic;
nspred = M_.nspred;
nc = size(dr.ghx,2);
endo_nbr = M_.endo_nbr;
inv_order_var = dr.inv_order_var;
[A,B] = kalman_transition_matrix(dr,nstatic+(1:npred),1:nc,M_.exo_nbr);
[A,B] = kalman_transition_matrix(dr,nstatic+(1:nspred),1:nc,M_.exo_nbr);
if size(var_list,1) == 0
var_list = M_.endo_names(1:M_.orig_endo_nbr,:);

8
matlab/get_variance_of_endogenous_variables.m
View File

@ -13,7 +13,7 @@ function vx1 = get_variance_of_endogenous_variables(dr,i_var)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2011 Dynare Team
% Copyright (C) 2003-2012 Dynare Team
%
% This file is part of Dynare.
%
@ -36,14 +36,14 @@ endo_nbr = M_.endo_nbr;
Sigma_e = M_.Sigma_e;
nstatic = dr.nstatic;
npred = dr.npred;
nstatic = M_.nstatic;
nspred = M_.nspred;
ghx = dr.ghx(i_var,:);
ghu = dr.ghu(i_var,:);
nc = size(ghx,2);
n = length(i_var);
[A,B] = kalman_transition_matrix(dr,nstatic+(1:npred),1:nc,M_.exo_nbr);
[A,B] = kalman_transition_matrix(dr,nstatic+(1:nspred),1:nc,M_.exo_nbr);
[vx,u] = lyapunov_symm(A,B*Sigma_e*B',options_.qz_criterium,options_.lyapunov_complex_threshold);

10
matlab/gsa/ghx2transition.m
View File

@ -35,14 +35,14 @@ global oo_ M_
oo_.dr.ghx = ghx;
oo_.dr.ghu = ghu;
endo_nbr = M_.endo_nbr;
nstatic = oo_.dr.nstatic;
npred = oo_.dr.npred;
nstatic = M_.nstatic;
nspred = M_.nspred;
iv = (1:endo_nbr)';
ic = [ nstatic+(1:npred) endo_nbr+(1:size(oo_.dr.ghx,2)-npred) ]';
ic = [ nstatic+(1:nspred) endo_nbr+(1:size(oo_.dr.ghx,2)-nspred) ]';
aux = oo_.dr.transition_auxiliary_variables;
k = find(aux(:,2) > npred);
k = find(aux(:,2) > nspred);
aux(:,2) = aux(:,2) + nstatic;
aux(k,2) = aux(k,2) + oo_.dr.nfwrd;
aux(k,2) = aux(k,2) + M_.nfwrd;
end
n_iv = length(iv);
n_ir1 = size(aux,1);

6
matlab/gsa/map_ident_.m
View File

@ -111,10 +111,10 @@ if opt_gsa.load_ident_files==0,
[nr1, nc1, nnn] = size(T);
endo_nbr = M_.endo_nbr;
nstatic = oo_.dr.nstatic;
npred = oo_.dr.npred;
nstatic = M_.nstatic;
nspred = M_.nspred;
iv = (1:endo_nbr)';
ic = [ nstatic+(1:npred) endo_nbr+(1:size(oo_.dr.ghx,2)-npred) ]';
ic = [ nstatic+(1:nspred) endo_nbr+(1:size(oo_.dr.ghx,2)-nspred) ]';
dr.ghx = T(:, [1:(nc1-M_.exo_nbr)],1);
dr.ghu = T(:, [(nc1-M_.exo_nbr+1):end], 1);

2
matlab/gsa/redform_map.m
View File

@ -212,7 +212,7 @@ for j=1:size(anamendo,1)
iplo=0;
for je=1:size(anamlagendo,1)
namlagendo=deblank(anamlagendo(je,:));
ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(oo_.dr.nstatic+1:oo_.dr.nstatic+nsok),:),'exact');
ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(M_.nstatic+1:M_.nstatic+nsok),:),'exact');
disp(' ')
disp(['[', namendo,' vs. lagged ',namlagendo,']'])

4
matlab/gsa/redform_screen.m
View File

@ -48,7 +48,7 @@ end
load([dirname,'/',M_.fname,'_prior'],'lpmat','lpmat0','istable','T');
nspred=oo_.dr.nspred;
nspred=M_.nspred;
[kn, np]=size(lpmat);
nshock = length(bayestopt_.pshape)-np;
@ -110,7 +110,7 @@ for j=1:size(anamendo,1),
ifig=0;
for je=1:size(anamlagendo,1)
namlagendo=deblank(anamlagendo(je,:));
ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(oo_.dr.nstatic+1:oo_.dr.nstatic+nsok),:),'exact');
ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(M_.nstatic+1:M_.nstatic+nsok),:),'exact');
if ~isempty(ilagendo),
y0=teff(T(iendo,ilagendo,:),kn,istable);

6
matlab/gsa/stab_map_.m
View File

@ -76,9 +76,9 @@ ntra = opt_gsa.morris_ntra;
dr_ = oo_.dr;
%if isfield(dr_,'ghx'),
ys_ = oo_.dr.ys;
nspred = dr_.nspred; %size(dr_.ghx,2);
nboth = dr_.nboth;
nfwrd = dr_.nfwrd;
nspred = M_.nspred; %size(dr_.ghx,2);
nboth = M_.nboth;
nfwrd = M_.nfwrd;
%end
fname_ = M_.fname;

40
matlab/k_order_pert.m
View File

@ -25,7 +25,7 @@ M.var_order_endo_names = M.endo_names(dr.order_var,:);
order = options.order;
endo_nbr = M.endo_nbr;
exo_nbr = M.exo_nbr;
npred = dr.npred;
nspred = M.nspred;
switch(order)
case 1
@ -44,13 +44,13 @@ switch(order)
M,options);
dr.ghx = derivs.gy;
dr.ghu = derivs.gu;
dr.ghxx = unfold2(derivs.gyy,npred);
dr.ghxx = unfold2(derivs.gyy,nspred);
dr.ghxu = derivs.gyu;
dr.ghuu = unfold2(derivs.guu,exo_nbr);
dr.ghs2 = derivs.gss;
dr.ghxxx = unfold3(derivs.gyyy,npred);
dr.ghxxu = unfold21(derivs.gyyu,npred,exo_nbr);
dr.ghxuu = unfold12(derivs.gyuu,npred,exo_nbr);
dr.ghxxx = unfold3(derivs.gyyy,nspred);
dr.ghxxu = unfold21(derivs.gyyu,nspred,exo_nbr);
dr.ghxuu = unfold12(derivs.gyuu,nspred,exo_nbr);
dr.ghuuu = unfold3(derivs.guuu,exo_nbr);
dr.ghxss = derivs.gyss;
dr.ghuss = derivs.guss;
@ -71,10 +71,10 @@ if options.pruning
return
end
npred = dr.npred;
nspred = M.nspred;
dr.ghx = dr.g_1(:,1:npred);
dr.ghu = dr.g_1(:,npred+1:end);
dr.ghx = dr.g_1(:,1:nspred);
dr.ghu = dr.g_1(:,nspred+1:end);
if options.loglinear == 1
k = find(dr.kstate(:,2) <= M.maximum_endo_lag+1);
@ -90,27 +90,27 @@ if order > 1
dr.ghs2 = 2*g_0;
s0 = 0;
s1 = 0;
ghxx=zeros(endo_nbr, npred^2);
ghxu=zeros(endo_nbr, npred*exo_nbr);
ghxx=zeros(endo_nbr, nspred^2);
ghxu=zeros(endo_nbr, nspred*exo_nbr);
ghuu=zeros(endo_nbr, exo_nbr^2);
for i=1:size(g_2,2)
if s0 < npred && s1 < npred
ghxx(:,s0*npred+s1+1) = 2*g_2(:,i);
if s0 < nspred && s1 < nspred
ghxx(:,s0*nspred+s1+1) = 2*g_2(:,i);
if s1 > s0
ghxx(:,s1*npred+s0+1) = 2*g_2(:,i);
ghxx(:,s1*nspred+s0+1) = 2*g_2(:,i);
end
elseif s0 < npred && s1 < npred+exo_nbr
ghxu(:,(s0*exo_nbr+s1-npred+1)) = 2*g_2(:,i);
elseif s0 < npred+exo_nbr && s1 < npred+exo_nbr
ghuu(:,(s0-npred)*exo_nbr+s1-npred +1) = 2*g_2(:,i);
elseif s0 < nspred && s1 < nspred+exo_nbr
ghxu(:,(s0*exo_nbr+s1-nspred+1)) = 2*g_2(:,i);
elseif s0 < nspred+exo_nbr && s1 < nspred+exo_nbr
ghuu(:,(s0-nspred)*exo_nbr+s1-nspred +1) = 2*g_2(:,i);
if s1 > s0
ghuu(:,(s1-npred)*exo_nbr+s0-npred+1) = 2*g_2(:,i);
ghuu(:,(s1-nspred)*exo_nbr+s0-nspred+1) = 2*g_2(:,i);
end
else
error('dr1:k_order_perturbation:g_2','Unaccounted columns in g_2');
end
s1 = s1+1;
if s1 == npred+exo_nbr
if s1 == nspred+exo_nbr
s0 = s0+1;
s1 = s0;
end
@ -182,4 +182,4 @@ end

19
matlab/mult_elimination.m
View File

@ -12,7 +12,7 @@ function dr=mult_elimination(varlist,M_, options_, oo_)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2011 Dynare Team
% Copyright (C) 2003-2012 Dynare Team
%
% This file is part of Dynare.
%
@ -31,21 +31,21 @@ function dr=mult_elimination(varlist,M_, options_, oo_)
dr = oo_.dr;
nstatic = dr.nstatic;
npred = dr.npred;
nstatic = M_.nstatic;
nspred = M_.nspred;
order_var = dr.order_var;
nstates = M_.endo_names(order_var(nstatic+(1:npred)),:);
nstates = M_.endo_names(order_var(nstatic+(1:nspred)),:);
il = strmatch('MULT_',nstates);
nil = setdiff(1:dr.npred,il);
nil = setdiff(1:nspred,il);
m_nbr = length(il);
nm_nbr = length(nil);
AA1 = dr.ghx(:,nil);
AA2 = dr.ghx(:,il);
A1 = dr.ghx(nstatic+(1:npred),nil);
A2 = dr.ghx(nstatic+(1:npred),il);
B = dr.ghu(nstatic+(1:npred),:);
A1 = dr.ghx(nstatic+(1:nspred),nil);
A2 = dr.ghx(nstatic+(1:nspred),il);
B = dr.ghu(nstatic+(1:nspred),:);
A11 = A1(nil,:);
A21 = A1(il,:);
A12 = A2(nil,:);
@ -68,7 +68,7 @@ M2 = AA2*E2*[R2_1*Q2(:,1:n2)'*[Q1_12' Q1_22']*[A11;A21]; zeros(m_nbr-n2,length(n
M3 = dr.ghu;
M4 = AA2*E2*[R2_1*Q2(:,1:n2)'*[Q1_12' Q1_22']*[B1;B2]; zeros(m_nbr-n2,size(B,2))];
k1 = nstatic+(1:npred);
k1 = nstatic+(1:nspred);
k1 = k1(nil);
endo_nbr = M_.orig_endo_nbr;
@ -100,7 +100,6 @@ dr.M3 = M3;
dr.M4 = M4;
nvar = length(varlist);
nspred = dr.nspred;
if nvar > 0 && options_.noprint == 0
res_table = zeros(2*(nm_nbr+M_.exo_nbr),nvar);

18
matlab/partial_information/dr1_PI.m
View File

@ -157,10 +157,10 @@ end
dr=set_state_space(dr,M_,options_);
kstate = dr.kstate;
nstatic = dr.nstatic;
nfwrd = dr.nfwrd;
npred = dr.npred;
nboth = dr.nboth;
nstatic = M_.nstatic;
nfwrd = M_.nfwrd;
nspred = M_.nspred;
nboth = M_.nboth;
order_var = dr.order_var;
nd = size(kstate,1);
nz = nnz(M_.lead_lag_incidence);
@ -240,7 +240,7 @@ end % end if useAIM and...
% E_t z(t+3)
% partition jacobian:
jlen=dr.nspred+dr.nsfwrd+M_.endo_nbr+M_.exo_nbr; % length of jacobian
jlen=M_.nspred+M_.nsfwrd+M_.endo_nbr+M_.exo_nbr; % length of jacobian
PSI=-jacobia_(:, jlen-M_.exo_nbr+1:end); % exog
% first transpose M_.lead_lag_incidence';
lead_lag=M_.lead_lag_incidence';
@ -251,12 +251,12 @@ end % end if useAIM and...
AA2=AA0; % empty A2 and A3
AA3=AA0;
if xlen==nendo % && M_.maximum_lag <=1 && M_.maximum_lead <=1 % apply a shortcut
AA1=jacobia_(:,npred+1:npred+nendo);
AA1=jacobia_(:,nspred+1:nspred+nendo);
if M_.maximum_lead ==1
fnd = find(lead_lag(:,M_.maximum_lag+2));
AA0(:, fnd)= jacobia_(:,nonzeros(lead_lag(:,M_.maximum_lag+2))); %forwd jacobian
end
if npred>0 && M_.maximum_lag ==1
if nspred>0 && M_.maximum_lag ==1
fnd = find(lead_lag(:,1));
AA2(:, fnd)= jacobia_(:,nonzeros(lead_lag(:,1))); %backward
end
@ -264,7 +264,7 @@ end % end if useAIM and...
if nendo-xlen==num_inst
PSI=[PSI;zeros(num_inst, M_.exo_nbr)];
% AA1 contemporary
AA_all=jacobia_(:,npred+1:npred+nendo);
AA_all=jacobia_(:,nspred+1:nspred+nendo);
AA1=AA_all(:,lq_instruments.m_var); % endo without instruments
lq_instruments.ij1=AA_all(:,lq_instruments.inst_var_indices); % instruments only
lq_instruments.B1=-[lq_instruments.ij1; eye(num_inst)];
@ -279,7 +279,7 @@ end % end if useAIM and...
lq_instruments.B0=[lq_instruments.ij0; eye(num_inst)];
AA0=[AA0, zeros(xlen,num_inst); zeros(num_inst,xlen+num_inst)];
end
if npred>0 && M_.maximum_lag ==1
if nspred>0 && M_.maximum_lag ==1
AA_all(:,:)=0.0;
fnd = find(lead_lag(:,1));
AA_all(:, fnd)= jacobia_(:,nonzeros(lead_lag(:,1))); %backward

14
matlab/set_state_space.m
View File

@ -34,7 +34,7 @@ function dr=set_state_space(dr,DynareModel,DynareOptions)
%! @end deftypefn
%@eod:
% Copyright (C) 1996-2011 Dynare Team
% Copyright (C) 1996-2012 Dynare Team
%
% This file is part of Dynare.
%
@ -69,10 +69,6 @@ else
both_var = [];
stat_var = setdiff([1:endo_nbr]',fwrd_var);
end
nboth = length(both_var);
npred = length(pred_var);
nfwrd = length(fwrd_var);
nstatic = length(stat_var);
if DynareOptions.block == 1
order_var = DynareModel.block_structure.variable_reordered;
else
@ -116,14 +112,6 @@ kstate = kstate(i_kmask,:);
dr.order_var = order_var;
dr.inv_order_var = inv_order_var';
dr.nstatic = nstatic;
dr.npred = npred+nboth;
dr.kstate = kstate;
dr.nboth = nboth;
dr.nfwrd = nfwrd;
% number of forward variables in the state vector
dr.nsfwrd = nfwrd+nboth;
% number of predetermined variables in the state vector
dr.nspred = npred+nboth;
dr.transition_auxiliary_variables = [];

18
matlab/simult_.m
View File

@ -15,7 +15,7 @@ function y_=simult_(y0,dr,ex_,iorder)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2001-2011 Dynare Team
% Copyright (C) 2001-2012 Dynare Team
%
% This file is part of Dynare.
%
@ -57,15 +57,15 @@ if options_.k_order_solver && ~options_.pruning % Call dynare++ routines.
ex_ = [zeros(1,exo_nbr); ex_];
switch options_.order
case 1
[err, y_] = dynare_simul_(1,dr.nstatic,dr.npred-dr.nboth,dr.nboth,dr.nfwrd,exo_nbr, ...
[err, y_] = dynare_simul_(1,M_.nstatic,M_.npred,M_.nboth,M_.nfwrd,exo_nbr, ...
y_(dr.order_var,1),ex_',M_.Sigma_e,options_.DynareRandomStreams.seed,dr.ys(dr.order_var),...
zeros(endo_nbr,1),dr.g_1);
case 2
[err, y_] = dynare_simul_(2,dr.nstatic,dr.npred-dr.nboth,dr.nboth,dr.nfwrd,exo_nbr, ...
[err, y_] = dynare_simul_(2,M_.nstatic,M_.npred,M_.nboth,M_.nfwrd,exo_nbr, ...
y_(dr.order_var,1),ex_',M_.Sigma_e,options_.DynareRandomStreams.seed,dr.ys(dr.order_var),dr.g_0, ...
dr.g_1,dr.g_2);
case 3
[err, y_] = dynare_simul_(3,dr.nstatic,dr.npred-dr.nboth,dr.nboth,dr.nfwrd,exo_nbr, ...
[err, y_] = dynare_simul_(3,M_.nstatic,M_.npred,M_.nboth,M_.nfwrd,exo_nbr, ...
y_(dr.order_var,1),ex_',M_.Sigma_e,options_.DynareRandomStreams.seed,dr.ys(dr.order_var),dr.g_0, ...
dr.g_1,dr.g_2,dr.g_3);
otherwise
@ -152,11 +152,11 @@ else
ghxss = dr.ghxss;
ghuss = dr.ghuss;
threads = options_.threads.kronecker.A_times_B_kronecker_C;
npred = dr.npred;
ipred = dr.nstatic+(1:npred);
nspred = M_.nspred;
ipred = M_.nstatic+(1:nspred);
yhat1 = y0(order_var(k2))-dr.ys(order_var(k2));
yhat2 = zeros(npred,1);
yhat3 = zeros(npred,1);
yhat2 = zeros(nspred,1);
yhat3 = zeros(nspred,1);
for i=2:iter+M_.maximum_lag
u = ex_(i-1,:)';
[gyy, err] = A_times_B_kronecker_C(ghxx,yhat1,threads);
@ -188,4 +188,4 @@ else
yhat3 = yhat3(ipred);
end
end
end
end

8
matlab/simultxdet.m
View File

@ -14,7 +14,7 @@ function [y_,int_width]=simultxdet(y0,ex,ex_det, iorder,var_list,M_,oo_,options_
% The condition size(ex,1)+M_.maximum_lag=size(ex_det,1) must be verified
% for consistency.
% Copyright (C) 2008-2011 Dynare Team
% Copyright (C) 2008-2012 Dynare Team
%
% This file is part of Dynare.
%
@ -35,8 +35,8 @@ dr = oo_.dr;
ykmin = M_.maximum_lag;
endo_nbr = M_.endo_nbr;
exo_det_steady_state = oo_.exo_det_steady_state;
nstatic = dr.nstatic;
npred =dr.npred;
nstatic = M_.nstatic;
nspred = M_.nspred;
nc = size(dr.ghx,2);
iter = size(ex,1);
if size(ex_det, 1) ~= iter+ykmin
@ -114,7 +114,7 @@ elseif iorder == 2
end
end
[A,B] = kalman_transition_matrix(dr,nstatic+(1:npred),1:nc,M_.exo_nbr);
[A,B] = kalman_transition_matrix(dr,nstatic+(1:nspred),1:nc,M_.exo_nbr);
inv_order_var = dr.inv_order_var;
ghx1 = dr.ghx(inv_order_var(ivar),:);

13
matlab/stoch_simul.m
View File

@ -88,16 +88,9 @@ if ~options_.noprint
disp(' ')
disp([' Number of variables: ' int2str(M_.endo_nbr)])
disp([' Number of stochastic shocks: ' int2str(M_.exo_nbr)])
if (options_.block)
disp([' Number of state variables: ' int2str(oo_.dr.npred+oo_.dr.nboth)])
disp([' Number of jumpers: ' int2str(oo_.dr.nfwrd+oo_.dr.nboth)])
else
disp([' Number of state variables: ' ...
int2str(length(find(oo_.dr.kstate(:,2) <= M_.maximum_lag+1)))])
disp([' Number of jumpers: ' ...
int2str(length(find(oo_.dr.kstate(:,2) == M_.maximum_lag+2)))])
end;
disp([' Number of static variables: ' int2str(oo_.dr.nstatic)])
disp([' Number of state variables: ' int2str(M_.nspred)])
disp([' Number of jumpers: ' int2str(M_.nsfwrd)])
disp([' Number of static variables: ' int2str(M_.nstatic)])
my_title='MATRIX OF COVARIANCE OF EXOGENOUS SHOCKS';
labels = deblank(M_.exo_names);
headers = char('Variables',labels);

38
matlab/stochastic_solvers.m
View File

@ -128,11 +128,11 @@ if any(any(isnan(jacobia_)))
end
kstate = dr.kstate;
nstatic = dr.nstatic;
nfwrd = dr.nfwrd;
npred = dr.npred;
nboth = dr.nboth;
nfwrds = nfwrd+nboth;
nstatic = M_.nstatic;
nfwrd = M_.nfwrd;
nspred = M_.nspred;
nboth = M_.nboth;
nsfwrd = M_.nsfwrd;
order_var = dr.order_var;
nd = size(kstate,1);
nz = nnz(M_.lead_lag_incidence);
@ -194,34 +194,34 @@ if M_.exo_det_nbr > 0
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,nfwrds-nboth)]);
M1 = inv(f0+[zeros(M_.endo_nbr,nstatic) f1*gx zeros(M_.endo_nbr,nsfwrd-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-nfwrds+1:end,:);
dr.ghud{i} = -M2*dr.ghud{i-1}(end-nsfwrd+1:end,:);
end
if options_.order > 1
lead_lag_incidence = M_.lead_lag_incidence;
k0 = find(lead_lag_incidence(M_.maximum_endo_lag+1,order_var)');
k1 = find(lead_lag_incidence(M_.maximum_endo_lag+2,order_var)');
hu = dr.ghu(nstatic+[1:npred],:);
hud = dr.ghud{1}(nstatic+1:nstatic+npred,:);
zx = [eye(npred);dr.ghx(k0,:);gx*dr.Gy;zeros(M_.exo_nbr+M_.exo_det_nbr, ...
npred)];
zu = [zeros(npred,M_.exo_nbr); dr.ghu(k0,:); gx*hu; zeros(M_.exo_nbr+M_.exo_det_nbr, ...
hu = dr.ghu(nstatic+[1:nspred],:);
hud = dr.ghud{1}(nstatic+1:nstatic+nspred,:);
zx = [eye(nspred);dr.ghx(k0,:);gx*dr.Gy;zeros(M_.exo_nbr+M_.exo_det_nbr, ...
nspred)];
zu = [zeros(nspred,M_.exo_nbr); dr.ghu(k0,:); gx*hu; zeros(M_.exo_nbr+M_.exo_det_nbr, ...
M_.exo_nbr)];
zud=[zeros(npred,M_.exo_det_nbr);dr.ghud{1};gx(:,1:npred)*hud;zeros(M_.exo_nbr,M_.exo_det_nbr);eye(M_.exo_det_nbr)];
zud=[zeros(nspred,M_.exo_det_nbr);dr.ghud{1};gx(:,1:nspred)*hud;zeros(M_.exo_nbr,M_.exo_det_nbr);eye(M_.exo_det_nbr)];
R1 = hessian1*kron(zx,zud);
dr.ghxud = cell(M_.exo_det_length,1);
kf = [M_.endo_nbr-nfwrd-nboth+1:M_.endo_nbr];
kp = nstatic+[1:npred];
kp = nstatic+[1:nspred];
dr.ghxud{1} = -M1*(R1+f1*dr.ghxx(kf,:)*kron(dr.ghx(kp,:),dr.ghud{1}(kp,:)));
Eud = eye(M_.exo_det_nbr);
for i = 2:M_.exo_det_length
hudi = dr.ghud{i}(kp,:);
zudi=[zeros(npred,M_.exo_det_nbr);dr.ghud{i};gx(:,1:npred)*hudi;zeros(M_.exo_nbr+M_.exo_det_nbr,M_.exo_det_nbr)];
zudi=[zeros(nspred,M_.exo_det_nbr);dr.ghud{i};gx(:,1:nspred)*hudi;zeros(M_.exo_nbr+M_.exo_det_nbr,M_.exo_det_nbr)];
R2 = hessian1*kron(zx,zudi);
dr.ghxud{i} = -M2*(dr.ghxud{i-1}(kf,:)*kron(dr.Gy,Eud)+dr.ghxx(kf,:)*kron(dr.ghx(kp,:),dr.ghud{i}(kp,:)))-M1*R2;
end
@ -231,7 +231,7 @@ if M_.exo_det_nbr > 0
Eud = eye(M_.exo_det_nbr);
for i = 2:M_.exo_det_length
hudi = dr.ghud{i}(kp,:);
zudi=[zeros(npred,M_.exo_det_nbr);dr.ghud{i};gx(:,1:npred)*hudi;zeros(M_.exo_nbr+M_.exo_det_nbr,M_.exo_det_nbr)];
zudi=[zeros(nspred,M_.exo_det_nbr);dr.ghud{i};gx(:,1:nspred)*hudi;zeros(M_.exo_nbr+M_.exo_det_nbr,M_.exo_det_nbr)];
R2 = hessian1*kron(zu,zudi);
dr.ghuud{i} = -M2*dr.ghxud{i-1}(kf,:)*kron(hu,Eud)-M1*R2;
end
@ -239,8 +239,8 @@ if M_.exo_det_nbr > 0
dr.ghudud = cell(M_.exo_det_length,M_.exo_det_length);
dr.ghudud{1,1} = -M1*R1-M2*dr.ghxx(kf,:)*kron(hud,hud);
for i = 2:M_.exo_det_length
hudi = dr.ghud{i}(nstatic+1:nstatic+npred,:);
zudi=[zeros(npred,M_.exo_det_nbr);dr.ghud{i};gx(:,1:npred)*hudi+dr.ghud{i-1}(kf,:);zeros(M_.exo_nbr+M_.exo_det_nbr,M_.exo_det_nbr)];
hudi = dr.ghud{i}(nstatic+1:nstatic+nspred,:);
zudi=[zeros(nspred,M_.exo_det_nbr);dr.ghud{i};gx(:,1:nspred)*hudi+dr.ghud{i-1}(kf,:);zeros(M_.exo_nbr+M_.exo_det_nbr,M_.exo_det_nbr)];
R2 = hessian1*kron(zudi,zudi);
dr.ghudud{i,i} = -M2*(dr.ghudud{i-1,i-1}(kf,:)+...
2*dr.ghxud{i-1}(kf,:)*kron(hudi,Eud) ...
@ -251,7 +251,7 @@ if M_.exo_det_nbr > 0
-M1*R2;
for j=2:i-1
hudj = dr.ghud{j}(kp,:);
zudj=[zeros(npred,M_.exo_det_nbr);dr.ghud{j};gx(:,1:npred)*hudj;zeros(M_.exo_nbr+M_.exo_det_nbr,M_.exo_det_nbr)];
zudj=[zeros(nspred,M_.exo_det_nbr);dr.ghud{j};gx(:,1:nspred)*hudj;zeros(M_.exo_nbr+M_.exo_det_nbr,M_.exo_det_nbr)];
R2 = hessian1*kron(zudj,zudi);
dr.ghudud{j,i} = -M2*(dr.ghudud{j-1,i-1}(kf,:)+dr.ghxud{j-1}(kf,:)* ...
kron(hudi,Eud)+dr.ghxud{i-1}(kf,:)* ...

11
matlab/th_autocovariances.m
View File

@ -24,7 +24,7 @@ function [Gamma_y,stationary_vars] = th_autocovariances(dr,ivar,M_,options_,node
% SPECIAL REQUIREMENTS
%
% Copyright (C) 2001-2011 Dynare Team
% Copyright (C) 2001-2012 Dynare Team
%
% This file is part of Dynare.
%
@ -65,15 +65,15 @@ nvar = size(ivar,1);
ghx = dr.ghx;
ghu = dr.ghu;
npred = dr.npred;
nstatic = dr.nstatic;
nspred = M_.nspred;
nstatic = M_.nstatic;
nx = size(ghx,2);
if options_.block == 0
%order_var = dr.order_var;
inv_order_var = dr.inv_order_var;
kstate = dr.kstate;
ikx = [nstatic+1:nstatic+npred];
ikx = [nstatic+1:nstatic+nspred];
k0 = kstate(find(kstate(:,2) <= M_.maximum_lag+1),:);
i0 = find(k0(:,2) == M_.maximum_lag+1);
i00 = i0;
@ -96,13 +96,12 @@ else
trend = 1:M_.endo_nbr;
inv_order_var = trend(M_.block_structure.variable_reordered);
ghu1(1:length(dr.state_var),:) = ghu(dr.state_var,:);
npred = npred + dr.nboth;
end;
b = ghu1*M_.Sigma_e*ghu1';
if options_.block == 0
ipred = nstatic+(1:npred)';
ipred = nstatic+(1:nspred)';
else
ipred = dr.state_var;
end;

4
matlab/transition_matrix.m
View File

@ -13,7 +13,7 @@ function [A,B] = transition_matrix(dr, varargin)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2003-2009 Dynare Team
% Copyright (C) 2003-2012 Dynare Team
%
% This file is part of Dynare.
%
@ -41,7 +41,7 @@ ykmin_ = M_.maximum_endo_lag;
nx = size(dr.ghx,2);
kstate = dr.kstate;
ikx = [dr.nstatic+1:dr.nstatic+dr.npred];
ikx = [M_.nstatic+1:M_.nstatic+M_.nspred];
A = zeros(nx,nx);
k0 = kstate(find(kstate(:,2) <= ykmin_+1),:);

16
mex/sources/k_order_perturbation/k_order_perturbation.cc
View File

@ -130,17 +130,17 @@ extern "C" {
if (!ySteady.isFinite())
DYN_MEX_FUNC_ERR_MSG_TXT("The steady state vector contains NaN or Inf");
mxFldp = mxGetField(dr, 0, "nstatic");
mxFldp = mxGetField(M_, 0, "nstatic");
const int nStat = (int) mxGetScalar(mxFldp);
mxFldp = mxGetField(dr, 0, "npred");
int nPred = (int) mxGetScalar(mxFldp);
mxFldp = mxGetField(dr, 0, "nspred");
mxFldp = mxGetField(M_, 0, "npred");
const int nPred = (int) mxGetScalar(mxFldp);
mxFldp = mxGetField(M_, 0, "nspred");
const int nsPred = (int) mxGetScalar(mxFldp);
mxFldp = mxGetField(dr, 0, "nboth");
mxFldp = mxGetField(M_, 0, "nboth");
const int nBoth = (int) mxGetScalar(mxFldp);
mxFldp = mxGetField(dr, 0, "nfwrd");
mxFldp = mxGetField(M_, 0, "nfwrd");
const int nForw = (int) mxGetScalar(mxFldp);
mxFldp = mxGetField(dr, 0, "nsfwrd");
mxFldp = mxGetField(M_, 0, "nsfwrd");
const int nsForw = (int) mxGetScalar(mxFldp);
mxFldp = mxGetField(M_, 0, "exo_nbr");
@ -150,8 +150,6 @@ extern "C" {
mxFldp = mxGetField(M_, 0, "param_nbr");
const int nPar = (int) mxGetScalar(mxFldp);
nPred -= nBoth; // correct nPred for nBoth.
mxFldp = mxGetField(dr, 0, "order_var");
dparams = mxGetPr(mxFldp);
npar = (int) mxGetM(mxFldp);

5
preprocessor/DynamicModel.cc
View File

@ -2341,7 +2341,10 @@ DynamicModel::writeOutput(ostream &output, const string &basename, bool block_de
output << "M_.nstatic = " << nstatic << ";" << endl
<< "M_.nfwrd = " << nfwrd << ";" << endl
<< "M_.npred = " << npred << ";" << endl
<< "M_.nboth = " << nboth << ";" << endl;
<< "M_.nboth = " << nboth << ";" << endl
<< "M_.nsfwrd = " << nfwrd+nboth << ";" << endl
<< "M_.nspred = " << npred+nboth << ";" << endl
<< "M_.ndynamic = " << npred+nboth+nfwrd << ";" << endl;
// Write equation tags
output << "M_.equations_tags = {" << endl;

4
tests/optimal_policy/mult_elimination_test.mod
View File

@ -49,9 +49,9 @@ ramsey_policy(order=1,irf=0,planner_discount=0.95);
dr2 = mult_elimination({'R'},M_,options_,oo_);
k1 = oo_.dr.nstatic+(1:oo_.dr.npred);
k1 = M_.nstatic+(1:M_.nspred);
k2 = strmatch('MULT_',M_.endo_names(oo_.dr.order_var(k1),:));
k3 = k1(setdiff(1:oo_.dr.npred,k2));
k3 = k1(setdiff(1:M_.nspred,k2));
k4 = oo_.dr.order_var(k3);
V0 = oo_.var(k4,k4);