diff --git a/matlab/ep/extended_path.m b/matlab/ep/extended_path.m
index c4a590d0cb749aa5da5c5e458293c271dd9f1653..1072698f313d217a4866ab217e9afbdacf0dd1f5 100644
--- a/matlab/ep/extended_path.m
+++ b/matlab/ep/extended_path.m
@@ -68,23 +68,25 @@ while (t <= samplesize)
initialguess = [];
end
if t>2
- [endogenous_variables_paths(:,t), info_convergence, endogenousvariablespaths] = extended_path_core(innovations.positive_var_indx, ...
+ [endogenous_variables_paths(:,t), info_convergence, endogenousvariablespaths, y] = extended_path_core(innovations.positive_var_indx, ...
spfm_exo_simul, ...
endogenous_variables_paths(:,t-1), ...
pfm, ...
M_, ...
options_, ...
oo_, ...
- initialguess);
+ initialguess, ...
+ y);
else
- [endogenous_variables_paths(:,t), info_convergence, endogenousvariablespaths, pfm, options_] = extended_path_core(innovations.positive_var_indx, ...
+ [endogenous_variables_paths(:,t), info_convergence, endogenousvariablespaths, y, pfm, options_] = extended_path_core(innovations.positive_var_indx, ...
spfm_exo_simul, ...
endogenous_variables_paths(:,t-1), ...
pfm, ...
M_, ...
options_, ...
oo_, ...
- initialguess);
+ initialguess, ...
+ []);
end
if ~info_convergence
msg = sprintf('No convergence of the (stochastic) perfect foresight solver (in period %s)!', int2str(t));
diff --git a/matlab/ep/extended_path_core.m b/matlab/ep/extended_path_core.m
index 237d99b801ab3b5fbcf96ccb4f6529b4e3d70786..ec0aa4736ba8b650644af672e6ab931aae343310 100644
--- a/matlab/ep/extended_path_core.m
+++ b/matlab/ep/extended_path_core.m
@@ -1,11 +1,12 @@
-function [y, info_convergence, endogenousvariablespaths, pfm, options_] = extended_path_core(positive_var_indx, ...
+function [y1, info_convergence, endogenousvariablespaths, y, pfm, options_] = extended_path_core(positive_var_indx, ...
exo_simul, ...
initial_conditions ,...
pfm, ...
M_, ...
options_, ...
oo_, ...
- initialguess)
+ initialguess, ...
+ y)
% Copyright © 2016-2025 Dynare Team
%
@@ -41,7 +42,7 @@ stack_solve_algo = ep.stack_solve_algo;
if init% Compute first order solution (Perturbation)...
endo_simul = simult_(M_,options_,initial_conditions,oo_.dr,exo_simul(2:end,:),1);
else
- if nargin==8 && ~isempty(initialguess)
+ if nargin>7 && ~isempty(initialguess)
% Note that the first column of initialguess should be equal to initial_conditions.
endo_simul = initialguess;
else
@@ -49,6 +50,10 @@ else
end
end
+if nargin~=9
+ y = [];
+end
+
oo_.endo_simul = endo_simul;
if debug
@@ -77,17 +82,17 @@ else
switch(algo)
case 0
% Full tree of future trajectories.
- if nargout>3
- [flag, endogenousvariablespaths, errorcode, ~, pfm, options_] = solve_stochastic_perfect_foresight_model_0(endo_simul, exo_simul, options_, M_, pfm);
+ if nargout>4
+ [flag, endogenousvariablespaths, errorcode, y, pfm, options_] = solve_stochastic_perfect_foresight_model_0(endo_simul, exo_simul, y, options_, M_, pfm);
else
- [flag, endogenousvariablespaths, errorcode] = solve_stochastic_perfect_foresight_model_0(endo_simul, exo_simul, options_, M_, pfm);
+ [flag, endogenousvariablespaths, errorcode, y] = solve_stochastic_perfect_foresight_model_0(endo_simul, exo_simul, y, options_, M_, pfm);
end
case 1
% Sparse tree of future histories.
- if nargout>3
- [flag, endogenousvariablespaths, errorcode, ~, pfm, options_] = solve_stochastic_perfect_foresight_model_1(endo_simul, exo_simul, options_, M_, pfm);
+ if nargout>4
+ [flag, endogenousvariablespaths, errorcode, y, pfm, options_] = solve_stochastic_perfect_foresight_model_1(endo_simul, exo_simul, y, options_, M_, pfm);
else
- [flag, endogenousvariablespaths, errorcode] = solve_stochastic_perfect_foresight_model_1(endo_simul, exo_simul, options_, M_, pfm);
+ [flag, endogenousvariablespaths, errorcode, y] = solve_stochastic_perfect_foresight_model_1(endo_simul, exo_simul, y, options_, M_, pfm);
end
end
info_convergence = ~flag;
@@ -98,7 +103,7 @@ if ~info_convergence && ~options_.no_homotopy
end
if info_convergence
- y = endogenousvariablespaths(:,2);
+ y1 = endogenousvariablespaths(:,2);
else
- y = NaN(size(endo_nbr,1));
+ y1 = NaN(size(endo_nbr,1));
end
diff --git a/matlab/ep/solve_stochastic_perfect_foresight_model_0.m b/matlab/ep/solve_stochastic_perfect_foresight_model_0.m
index 19e77a8315a6b2afdb96b742f01c66be4c9ed515..efdaf624721374a5855595a6c003ee0882145621 100644
--- a/matlab/ep/solve_stochastic_perfect_foresight_model_0.m
+++ b/matlab/ep/solve_stochastic_perfect_foresight_model_0.m
@@ -1,4 +1,4 @@
-function [errorflag, endo_simul, errorcode, y, pfm, options_] = solve_stochastic_perfect_foresight_model_0(endo_simul, exo_simul, options_, M_, pfm)
+function [errorflag, endo_simul, errorcode, y, pfm, options_] = solve_stochastic_perfect_foresight_model_0(endo_simul, exo_simul, y, options_, M_, pfm)
% Copyright © 2025 Dynare Team
%
@@ -148,7 +148,9 @@ end
pfm.Y = repmat(endo_simul(:),1,pfm.world_nbr);
-y = repmat(pfm.steady_state, pfm.dimension/pfm.ny, 1);
+if isempty(y)
+ y = repmat(pfm.steady_state, pfm.dimension/pfm.ny, 1);
+end
if update_options_struct
% Set algorithm
diff --git a/matlab/ep/solve_stochastic_perfect_foresight_model_1.m b/matlab/ep/solve_stochastic_perfect_foresight_model_1.m
index ccdc882f61ae42003c44eb19e3761bf80d05bebf..19eb0673804beb1101b3a5fc3c0a15112e8694de 100644
--- a/matlab/ep/solve_stochastic_perfect_foresight_model_1.m
+++ b/matlab/ep/solve_stochastic_perfect_foresight_model_1.m
@@ -1,4 +1,4 @@
-function [errorflag, endo_simul, errorcode, y, pfm, options_] = solve_stochastic_perfect_foresight_model_1(endo_simul, exo_simul, options_, M_, pfm)
+function [errorflag, endo_simul, errorcode, y, pfm, options_] = solve_stochastic_perfect_foresight_model_1(endo_simul, exo_simul, y, options_, M_, pfm)
% Copyright © 2012-2025 Dynare Team
%
@@ -113,7 +113,9 @@ if update_pfm_struct
end
-y = repmat(pfm.steady_state, pfm.block_nbr, 1);
+if isempty(y)
+ y = repmat(pfm.steady_state, pfm.block_nbr, 1);
+end
if update_options_struct
% Set algorithm