diff --git a/matlab/display_problematic_vars_Jacobian.m b/matlab/display_problematic_vars_Jacobian.m
new file mode 100644
index 0000000000000000000000000000000000000000..0cb42b581a4edb613dbe911a1a94b0fe800f352e
--- /dev/null
+++ b/matlab/display_problematic_vars_Jacobian.m
@@ -0,0 +1,73 @@
+function []=display_problematic_vars_Jacobian(problemrow,problemcol,M_,x,type,caller_string)
+% []=display_problematic_vars_Jacobian(problemrow,problemcol,M_,ys,caller_string)
+% print the equation numbers and variables associated with problematic entries
+% of the Jacobian
+%
+% INPUTS
+% problemrow [vector] rows associated with problematic entries
+% problemcol [vector] columns associated with problematic entries
+% M_ [matlab structure] Definition of the model.
+% x [vector] point at which the Jacobian was evaluated
+% type [string] 'static' or 'dynamic' depending on the type of
+% Jacobian
+% caller_string [string] contains name of calling function for printing
+%
+% OUTPUTS
+% none.
+%
+
+% Copyright (C) 2014 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 nargin<6
+ caller_string='';
+end
+if strcmp(type,'dynamic')
+ for ii=1:length(problemrow)
+ [var_row,var_index]=find(M_.lead_lag_incidence==problemcol(ii));
+ if var_row==2
+ type_string='';
+ elseif var_row==1
+ type_string='lag of';
+ elseif var_row==3;
+ type_string='lead of';
+ end
+ if var_index<=M_.orig_endo_nbr
+ fprintf('Derivative of Equation %d with respect to %s Variable %s (initial value of %s: %g) \n',problemrow(ii),type_string,deblank(M_.endo_names(var_index,:)),deblank(M_.endo_names(var_index,:)),x(var_index))
+ else %auxiliary vars
+ orig_var_index=M_.aux_vars(1,var_index-M_.orig_endo_nbr).orig_index;
+ fprintf('Derivative of Equation %d with respect to %s Variable %s (initial value of %s: %g) \n',problemrow(ii),type_string,deblank(M_.endo_names(orig_var_index,:)),deblank(M_.endo_names(orig_var_index,:)),x(orig_var_index))
+ end
+ end
+ fprintf('\n%s The problem most often occurs, because a variable with\n',caller_string)
+ fprintf('%s exponent smaller than 1 has been initialized to 0. Taking the derivative\n',caller_string)
+ fprintf('%s and evaluating it at the steady state then results in a division by 0.\n',caller_string)
+elseif strcmp(type,'static')
+ for ii=1:length(problemrow)
+ if problemcol(ii)<=M_.orig_endo_nbr
+ fprintf('Derivative of Equation %d with respect to Variable %s (initial value of %s: %g) \n',problemrow(ii),deblank(M_.endo_names(problemcol(ii),:)),deblank(M_.endo_names(problemcol(ii),:)),x(problemcol(ii)))
+ else %auxiliary vars
+ orig_var_index=M_.aux_vars(1,problemcol(ii)-M_.orig_endo_nbr).orig_index;
+ fprintf('Derivative of Equation %d with respect to Variable %s (initial value of %s: %g) \n',problemrow(ii),deblank(M_.endo_names(orig_var_index,:)),deblank(M_.endo_names(orig_var_index,:)),x(problemcol(ii)))
+ end
+ end
+ fprintf('\n%s The problem most often occurs, because a variable with\n',caller_string)
+ fprintf('%s exponent smaller than 1 has been initialized to 0. Taking the derivative\n',caller_string)
+ fprintf('%s and evaluating it at the steady state then results in a division by 0.\n',caller_string)
+else
+ error('Unknown Type')
+end
\ No newline at end of file
diff --git a/matlab/dynare_solve.m b/matlab/dynare_solve.m
index b1ab7aefd9cb1232a448131c9caf7e53b99b5e13..744d174e2cf019ed30bfc5b32a2e3d2fd022936e 100644
--- a/matlab/dynare_solve.m
+++ b/matlab/dynare_solve.m
@@ -46,20 +46,9 @@ if jacobian_flag
[infrow,infcol]=find(isinf(fjac) | isnan(fjac));
M=evalin('base','M_'); %get variable names from workspace
fprintf('\nSTEADY: The Jacobian contains Inf or NaN. The problem arises from: \n\n')
- for ii=1:length(infrow)
- if infcol(ii)<=M.orig_endo_nbr
- fprintf('STEADY: Derivative of Equation %d with respect to Variable %s (initial value of %s: %g) \n',infrow(ii),deblank(M.endo_names(infcol(ii),:)),deblank(M.endo_names(infcol(ii),:)),x(infcol(ii)))
- else %auxiliary vars
- orig_var_index=M.aux_vars(1,infcol(ii)-M.orig_endo_nbr).orig_index;
- fprintf('STEADY: Derivative of Equation %d with respect to Variable %s (initial value of %s: %g) \n',infrow(ii),deblank(M.endo_names(orig_var_index,:)),deblank(M.endo_names(orig_var_index,:)),x(infcol(ii)))
- end
- end
- fprintf('\nSTEADY: The problem most often occurs, because a variable with\n')
- fprintf('STEADY: exponent smaller than 1 has been initialized to 0. Taking the derivative\n')
- fprintf('STEADY: and evaluating it at the steady state then results in a division by 0.\n')
+ display_problematic_vars_Jacobian(infrow,infcol,M,x,'static','STEADY: ')
error('An element of the Jacobian is not finite or NaN')
end
-
else
fvec = feval(func,x,varargin{:});
fjac = zeros(nn,nn) ;
diff --git a/matlab/model_diagnostics.m b/matlab/model_diagnostics.m
index e49eb29ab979ac09c726e6e2f60f42a509b38d55..197953fe1eb267876d250397a42796df76dd0e5b 100644
--- a/matlab/model_diagnostics.m
+++ b/matlab/model_diagnostics.m
@@ -47,7 +47,7 @@ problem_dummy=0;
k = find(lead_lag_incidence(maximum_endo_lag+1,:)==0);
if ~isempty(k)
problem_dummy=1;
- disp(['The following endogenous variables aren''t present at ' ...
+ disp(['MODEL_DIAGNOSTICS: The following endogenous variables aren''t present at ' ...
'the current period in the model:'])
for i=1:length(k)
disp(endo_names(k(i),:))
@@ -64,24 +64,25 @@ if M.exo_nbr == 0
end
% check if ys is steady state
+options.debug=1; %locally set debug option to 1
[dr.ys,params,check1]=evaluate_steady_state(oo.steady_state,M,options,oo,1);
% testing for problem
if check1(1)
problem_dummy=1;
- disp('model diagnostic can''t obtain the steady state')
+ disp('MODEL_DIAGNOSTICS: The steady state cannot be computed')
if any(isnan(dr.ys))
- disp(['model diagnostic obtains a steady state with NaNs'])
+ disp(['MODEL_DIAGNOSTICS: Steady state contains NaNs'])
end
if any(isinf(dr.ys))
- disp(['model diagnostic obtains a steady state with Inf'])
+ disp(['MODEL_DIAGNOSTICS: Steady state contains Inf'])
end
return;
end
if ~isreal(dr.ys)
problem_dummy=1;
- disp(['model diagnostic obtains a steady state with complex ' ...
+ disp(['MODEL_DIAGNOSTICS: Steady state contains complex ' ...
'numbers'])
return
end
@@ -110,13 +111,23 @@ for b=1:nb
else
[res,jacob]=feval([M.fname '_static'],dr.ys,exo,M.params);
end
- rank_jacob = rank(jacob);
+ if any(any(isinf(jacob) | isnan(jacob)))
+ problem_dummy=1;
+ [infrow,infcol]=find(isinf(jacob) | isnan(jacob));
+ fprintf('\nMODEL_DIAGNOSTICS: The Jacobian of the static model contains Inf or NaN. The problem arises from: \n\n')
+ display_problematic_vars_Jacobian(infrow,infcol,M,dr.ys,'static','MODEL_DIAGNOSTICS: ')
+ end
+ try
+ rank_jacob = rank(jacob); %can sometimes fail
+ catch
+ rank_jacob=size(jacob,1);
+ end
if rank_jacob < size(jacob,1)
problem_dummy=1;
singularity_problem = 1;
- disp(['model_diagnostic: the Jacobian of the static model is ' ...
+ disp(['MODEL_DIAGNOSTICS: The Jacobian of the static model is ' ...
'singular'])
- disp(['there is ' num2str(endo_nbr-rank_jacob) ...
+ disp(['MODEL_DIAGNOSTICS: there is ' num2str(endo_nbr-rank_jacob) ...
' colinear relationships between the variables and the equations'])
ncol = null(jacob);
n_rel = size(ncol,2);
@@ -150,13 +161,60 @@ for b=1:nb
end
end
end
+
if singularity_problem
- fprintf('The presence of a singularity problem typically indicates that there is one\n')
- fprintf('redundant equation entered in the model block, while another non-redundant equation\n')
- fprintf('is missing. The problem often derives from Walras Law.\n')
+ fprintf('MODEL_DIAGNOSTICS: The presence of a singularity problem typically indicates that there is one\n')
+ fprintf('MODEL_DIAGNOSTICS: redundant equation entered in the model block, while another non-redundant equation\n')
+ fprintf('MODEL_DIAGNOSTICS: is missing. The problem often derives from Walras Law.\n')
+end
+
+%%check dynamic Jacobian
+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;
+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, it_);
+ 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
+
+if any(any(isinf(jacobia_) | isnan(jacobia_)))
+ problem_dummy=1;
+ [infrow,infcol]=find(isinf(jacobia_) | isnan(jacobia_));
+ fprintf('\nMODEL_DIAGNOSTICS: The Jacobian of the dynamic model contains Inf or NaN. The problem arises from: \n\n')
+ display_problematic_vars_Jacobian(infrow,infcol,M,dr.ys,'dynamic','MODEL_DIAGNOSTICS: ')
+end
+if any(any(isinf(hessian1) | isnan(hessian1)))
+ problem_dummy=1;
+ fprintf('\nMODEL_DIAGNOSTICS: The Hessian of the dynamic model contains Inf or NaN.\n')
end
if problem_dummy==0
- fprintf('model_diagnostics was not able to detect any obvious problems with this mod-file.\n')
+ fprintf('MODEL_DIAGNOSTICS: No obvious problems with this mod-file were detected.\n')
end
diff --git a/matlab/print_info.m b/matlab/print_info.m
index 7914043904defb569d193d3bfc1115af17275a40..34017e513f67f1fbb1e23a5824b40b420c03dde1 100644
--- a/matlab/print_info.m
+++ b/matlab/print_info.m
@@ -62,7 +62,7 @@ if ~noprint
error(['The Jacobian contains NaNs because the following parameters are NaN: '...
disp_string])
else
- error(['The Jacobian contains NaNs'])
+ error(['The Jacobian contains NaNs. For more information, use options_.debug.'])
end
case 9
error(['k_order_pert was unable to compute the solution'])
diff --git a/matlab/stochastic_solvers.m b/matlab/stochastic_solvers.m
index dd835e2ba611eb90ff732f71e1ccafd0e8406723..2738afc292185c2eee9e08cc99a806c0ead5ee2c 100644
--- a/matlab/stochastic_solvers.m
+++ b/matlab/stochastic_solvers.m
@@ -119,27 +119,10 @@ end
if options_.debug
if ~isempty(infrow)
- for ii=1:length(infrow)
- [var_row,var_index]=find(M_.lead_lag_incidence==infcol(ii));
- if var_row==2
- type_string='';
- elseif var_row==1
- type_string='lag of';
- elseif var_row==3;
- type_string='lead of';
- end
- if var_index<=M_.orig_endo_nbr
- fprintf('STOCHASTIC_SOLVER: Derivative of Equation %d with respect to %s Variable %s (initial value of %s: %g) \n',infrow(ii),type_string,deblank(M_.endo_names(var_index,:)),deblank(M_.endo_names(var_index,:)),dr.ys(var_index))
- else %auxiliary vars
- orig_var_index=M.aux_vars(1,var_index-M_.orig_endo_nbr).orig_index;
- fprintf('STOCHASTIC_SOLVER: Derivative of Equation %d with respect to %s Variable %s (initial value of %s: %g) \n',infrow(ii),type_string,deblank(M_.endo_names(orig_var_index,:)),deblank(M_.endo_names(orig_var_index,:)),dr.ys(orig_var_index))
- end
- end
- fprintf('\nSTOCHASTIC_SOLVER: The problem most often occurs, because a variable with\n')
- fprintf('STOCHASTIC_SOLVER: exponent smaller than 1 has been initialized to 0. Taking the derivative\n')
- fprintf('STOCHASTIC_SOLVER: and evaluating it at the steady state then results in a division by 0.\n')
- end
+ fprintf('\nSTOCHASTIC_SOLVER: The Jacobian of the dynamic model contains Inf. The problam is associated with:\n\n')
+ display_problematic_vars_Jacobian(infrow,infcol,M_,dr.ys,'dynamic','STOCHASTIC_SOLVER: ')
save([M_.fname '_debug.mat'],'jacobia_')
+ end
end
if ~isempty(infrow)
@@ -157,7 +140,16 @@ if ~isreal(jacobia_)
end
end
-if any(any(isnan(jacobia_)))
+[nanrow,nancol]=find(isnan(jacobia_));
+if options_.debug
+ if ~isempty(nanrow)
+ fprintf('\nSTOCHASTIC_SOLVER: The Jacobian of the dynamic model contains NaN. The problam is associated with:\n\n')
+ display_problematic_vars_Jacobian(nanrow,nancol,M_,dr.ys,'dynamic','STOCHASTIC_SOLVER: ')
+ save([M_.fname '_debug.mat'],'jacobia_')
+ end
+end
+
+if ~isempty(nanrow)
info(1) = 8;
NaN_params=find(isnan(M_.params));
info(2:length(NaN_params)+1) = NaN_params;
@@ -313,4 +305,5 @@ if options_.loglinear
error('Loglinear options currently only works at order 1')
end
end
+end