Commit a42a9fff authored by Sébastien Villemot's avatar Sébastien Villemot
Browse files

Merge branch 'foresight_debug' into 'master'

perfect foresight: provide debugging information for singular Jacobian

Closes #1732

See merge request Dynare/dynare!1834
parents 59e087d4 b5a4c069
......@@ -6,14 +6,14 @@ function [endogenousvariables, info] = sim1(endogenousvariables, exogenousvariab
% INPUTS
% - endogenousvariables [double] N*(T+M.maximum_lag+M.maximum_lead) array, paths for the endogenous variables (initial condition + initial guess + terminal condition).
% - exogenousvariables [double] T*M array, paths for the exogenous variables.
% - steadystate [double] N*1 array, steady state for the endogenous variables.
% - steadystate [double] N*1 array, steady state for the endogenous variables.
% - M [struct] contains a description of the model.
% - options [struct] contains various options.
% OUTPUTS
% - endogenousvariables [double] N*(T+M.maximum_lag+M.maximum_lead) array, paths for the endogenous variables (solution of the perfect foresight model).
% - info [struct] contains informations about the results.
% Copyright (C) 1996-2019 Dynare Team
% Copyright (C) 1996-2021 Dynare Team
%
% This file is part of Dynare.
%
......@@ -65,7 +65,29 @@ for iter = 1:options.simul.maxit
h2 = clock;
[res, A] = perfect_foresight_problem(y, y0, yT, exogenousvariables, M.params, steadystate, periods, M, options);
% A is the stacked Jacobian with period x equations alongs the rows and
% periods times variables (in declaration order) along the columns
if options.debug && iter==1
row=find(all(A==0,2));
column=find(all(A==0,1));
if ~isempty(row) || ~isempty(column)
fprintf('The stacked Jacobian is singular. The problem derives from:\n')
if ~isempty(row)
time_period=ceil(row/ny);
equation=row-ny*(time_period-1);
for eq_iter=1:length(equation)
fprintf('The derivative of equation %d at time %d is zero for all variables\n',equation(eq_iter),time_period(eq_iter));
end
end
if ~isempty(column)
time_period=ceil(column/ny);
variable=column-ny*(time_period-1);
for eq_iter=1:length(variable)
fprintf('The derivative with respect to variable %d at time %d is zero for all equations\n',variable(eq_iter),time_period(eq_iter));
end
end
end
end
if options.endogenous_terminal_period && iter > 1
for it = 1:periods
if max(abs(res((it-1)*ny+(1:ny)))) < options.dynatol.f/1e7
......
......@@ -114,6 +114,22 @@ x = repmat(transpose(steadystate_x), 1+M.maximum_exo_lag+M.maximum_exo_lead, 1);
% Evaluate the Jacobian of the dynamic model at the deterministic steady state.
[d1, jacobian] = dynamicmodel(z, x, params, steadystate_y, M.maximum_exo_lag+1);
if options.debug
column=find(all(jacobian==0,1));
if ~isempty(column)
fprintf('The dynamic Jacobian is singular. The problem derives from:\n')
for iter=1:length(column)
[var_row,var_index]=find(M.lead_lag_incidence==column(iter));
if var_row==2
fprintf('The derivative with respect to %s being 0 for all equations.\n',M.endo_names{var_index})
elseif var_row==1
fprintf('The derivative with respect to the lag of %s being 0 for all equations.\n',M.endo_names{var_index})
elseif var_row==3
fprintf('The derivative with respect to the lead of %s being 0 for all equations.\n',M.endo_names{var_index})
end
end
end
end
% Check that the dynamic model was evaluated at the steady state.
if max(abs(d1))>options.solve_tolf
......
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