diff --git a/matlab/perfect-foresight-models/linear_perfect_foresight_problem.m b/matlab/perfect-foresight-models/linear_perfect_foresight_problem.m
new file mode 100644
index 000000000..306960b4c
--- /dev/null
+++ b/matlab/perfect-foresight-models/linear_perfect_foresight_problem.m
@@ -0,0 +1,69 @@
+function [residuals,JJacobian] = perfect_foresight_problem(y, dynamicjacobian, Y0, YT, ...
+ exo_simul, params, steady_state, ...
+ maximum_lag, T, ny, i_cols, ...
+ i_cols_J1, i_cols_1, i_cols_T, ...
+ i_cols_j,nnzJ,jendo,jexog)
+% function [residuals,JJacobian] = perfect_foresight_problem(x, model_dynamic, Y0, YT,exo_simul,
+% params, steady_state, maximum_lag, periods, ny, i_cols,i_cols_J1, i_cols_1,
+% i_cols_T, i_cols_j, nnzA)
+% computes the residuals and th Jacobian matrix
+% for a perfect foresight problem over T periods.
+%
+% INPUTS
+% ...
+% OUTPUTS
+% ...
+% ALGORITHM
+% ...
+%
+% SPECIAL REQUIREMENTS
+% None.
+
+% Copyright (C) 2015 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 .
+
+
+YY = [Y0; y; YT];
+
+residuals = zeros(T*ny,1);
+
+z = zeros(columns(dynamicjacobian), 1);
+
+if nargout == 2
+ JJacobian = sparse([],[],[],T*ny,T*ny,T*nnzJ);
+end
+
+i_rows = 1:ny;
+i_cols_J = i_cols;
+
+for it = maximum_lag+(1:T)
+ z(jendo) = YY(i_cols);
+ z(jexog) = transpose(exo_simul(it,:));
+ residuals(i_rows) = dynamicjacobian*z;
+ if nargout == 2
+ if it == 2
+ JJacobian(i_rows,i_cols_J1) = dynamicjacobian(:,i_cols_1);
+ elseif it == T + 1
+ JJacobian(i_rows,i_cols_J(i_cols_T)) = dynamicjacobian(:,i_cols_T);
+ else
+ JJacobian(i_rows,i_cols_J) = dynamicjacobian(:,i_cols_j);
+ i_cols_J = i_cols_J + ny;
+ end
+ end
+ i_rows = i_rows + ny;
+ i_cols = i_cols + ny;
+end
\ No newline at end of file
diff --git a/matlab/perfect-foresight-models/private/simulation_core.m b/matlab/perfect-foresight-models/private/simulation_core.m
index dad7ceacd..e30158794 100644
--- a/matlab/perfect-foresight-models/private/simulation_core.m
+++ b/matlab/perfect-foresight-models/private/simulation_core.m
@@ -18,7 +18,7 @@ function [oo_, maxerror] = simulation_core(options_, M_, oo_)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see .
-if options_.linear_approximation && ~isequal(options_.stack_solve_algo,0)
+if options_.linear_approximation && ~(isequal(options_.stack_solve_algo,0) || isequal(options_.stack_solve_algo,7))
error('perfect_foresight_solver: Option linear_approximation is only available with option stack_solve_algo equal to 0.')
end
@@ -91,12 +91,41 @@ else
illi = illi(:,2:3);
[i_cols_J1,junk,i_cols_1] = find(illi(:));
i_cols_T = nonzeros(M_.lead_lag_incidence(1:2,:)');
- [y,info] = dynare_solve(@perfect_foresight_problem,z(:),options_, ...
- str2func([M_.fname '_dynamic']),y0,yT, ...
- oo_.exo_simul,M_.params,oo_.steady_state, ...
- M_.maximum_lag,options_.periods,M_.endo_nbr,i_cols, ...
- i_cols_J1, i_cols_1, i_cols_T, i_cols_j, ...
- M_.NNZDerivatives(1));
+ if options_.linear_approximation
+ y_steady_state = oo_.steady_state;
+ x_steady_state = transpose(oo_.exo_steady_state);
+ ip = find(M_.lead_lag_incidence(1,:)');
+ ic = find(M_.lead_lag_incidence(2,:)');
+ in = find(M_.lead_lag_incidence(3,:)');
+ % Evaluate the Jacobian of the dynamic model at the deterministic steady state.
+ model_dynamic = str2func([M_.fname,'_dynamic']);
+ [d1,jacobian] = model_dynamic(y_steady_state([ip; ic; in]), x_steady_state, M_.params, y_steady_state, 1);
+ % Check that the dynamic model was evaluated at the steady state.
+ if max(abs(d1))>1e-12
+ error('Jacobian is not evaluated at the steady state!')
+ end
+ nyp = nnz(M_.lead_lag_incidence(1,:)) ;
+ ny0 = nnz(M_.lead_lag_incidence(2,:)) ;
+ nyf = nnz(M_.lead_lag_incidence(3,:)) ;
+ nd = nyp+ny0+nyf; % size of y (first argument passed to the dynamic file).
+ jexog = transpose(nd+(1:M_.exo_nbr));
+ jendo = transpose(1:nd);
+ z = bsxfun(@minus,z,y_steady_state);
+ x = bsxfun(@minus,oo_.exo_simul,x_steady_state);
+ [y,info] = dynare_solve(@linear_perfect_foresight_problem,z(:), options_, ...
+ jacobian, y0-y_steady_state, yT-y_steady_state, ...
+ x, M_.params, y_steady_state, ...
+ M_.maximum_lag, options_.periods, M_.endo_nbr, i_cols, ...
+ i_cols_J1, i_cols_1, i_cols_T, i_cols_j, ...
+ M_.NNZDerivatives(1),jendo,jexog);
+ else
+ [y,info] = dynare_solve(@perfect_foresight_problem,z(:),options_, ...
+ str2func([M_.fname '_dynamic']),y0,yT, ...
+ oo_.exo_simul,M_.params,oo_.steady_state, ...
+ M_.maximum_lag,options_.periods,M_.endo_nbr,i_cols, ...
+ i_cols_J1, i_cols_1, i_cols_T, i_cols_j, ...
+ M_.NNZDerivatives(1));
+ end
if all(imag(y)<.1*options_.dynatol.f)
if ~isreal(y)
y = real(y);
@@ -104,7 +133,11 @@ else
else
info = 1;
end
- oo_.endo_simul = [y0 reshape(y,M_.endo_nbr,periods) yT];
+ if options_.linear_approximation
+ oo_.endo_simul = [y0 bsxfun(@plus,reshape(y,M_.endo_nbr,periods),y_steady_state) yT];
+ else
+ oo_.endo_simul = [y0 reshape(y,M_.endo_nbr,periods) yT];
+ end
if info == 1
oo_.deterministic_simulation.status = false;
else