diff --git a/doc/manual/source/the-model-file.rst b/doc/manual/source/the-model-file.rst
index 7b1a62eba4771cfd949b6cc4cc26a8d952f0bd36..8b001673b6c4c76c6f0902591c3a7eea85baab52 100644
--- a/doc/manual/source/the-model-file.rst
+++ b/doc/manual/source/the-model-file.rst
@@ -4668,9 +4668,9 @@ that have been left free.
The ``perfect_foresight_controlled_paths`` block requires that the
:opt:`stack_solve_algo <stack_solve_algo = INTEGER>` option be equal to
- either ``0``, ``1``, ``2``, ``3`` or ``6``, and is incompatible with the
- :opt:`block`, :opt:`linear` and :opt:`bytecode` options of the :bck:`model`
- block.
+ either ``0``, ``1``, ``2``, ``3``, ``6`` or ``7``, and is incompatible with
+ the :opt:`block`, :opt:`linear` and :opt:`bytecode` options of the
+ :bck:`model` block.
*Options*
diff --git a/matlab/perfect-foresight-models/perfect_foresight_solver_core.m b/matlab/perfect-foresight-models/perfect_foresight_solver_core.m
index c7e376f29fdfa334efb4c6812453a09a1e60bdb8..c1977137cc03c5b745a6058cff2537351d634c9f 100644
--- a/matlab/perfect-foresight-models/perfect_foresight_solver_core.m
+++ b/matlab/perfect-foresight-models/perfect_foresight_solver_core.m
@@ -78,8 +78,11 @@ end
if ~isempty(controlled_paths_by_period)
assert(nargout >= 6); % Ensure modified exos are used
- if ~ismember(options_.stack_solve_algo, [0 1 2 3 6])
- error('perfect_foresight_controlled_paths is only available with stack_solve_algo option equal to 0, 1, 2, 3 or 6')
+ if ~ismember(options_.stack_solve_algo, [0 1 2 3 6 7])
+ error('perfect_foresight_controlled_paths is only available with stack_solve_algo option equal to 0, 1, 2, 3, 6 or 7')
+ end
+ if options_.stack_solve_algo == 7 && ismember(options_.solve_algo, [10, 11])
+ error('perfect_foresight_controlled_paths is not available for mixed-complementarity problems (LMMCP or PATH solvers)')
end
if options_.bytecode
error('perfect_foresight_controlled_paths is not available with the bytecode option')
@@ -157,7 +160,7 @@ else
end
[y, success] = solve_stacked_linear_problem(y, exo_simul, steady_state, exo_steady_state, M_, options_);
else
- [y, success, maxerror] = solve_stacked_problem(y, exo_simul, steady_state, M_, options_);
+ [y, success, maxerror, exo_simul] = solve_stacked_problem(y, exo_simul, steady_state, controlled_paths_by_period, M_, options_);
end
otherwise
error('Invalid value of stack_solve_algo option!')
diff --git a/matlab/perfect-foresight-models/solve_stacked_problem.m b/matlab/perfect-foresight-models/solve_stacked_problem.m
index 61a7b3294136de34150b71205749cdee62da3974..841b7c1ef72adbe387835905e2d9f15c781556d5 100644
--- a/matlab/perfect-foresight-models/solve_stacked_problem.m
+++ b/matlab/perfect-foresight-models/solve_stacked_problem.m
@@ -1,20 +1,23 @@
-function [endogenousvariables, success, maxerror] = solve_stacked_problem(endogenousvariables, exogenousvariables, steadystate, M_, options_)
+function [endogenousvariables, success, maxerror, exogenousvariables] = solve_stacked_problem(endogenousvariables, exogenousvariables, steadystate, controlled_paths_by_period, M_, options_)
% [endogenousvariables, success, maxerror] = solve_stacked_problem(endogenousvariables, exogenousvariables, steadystate, M_, options_)
% Solves the perfect foresight model using dynare_solve
%
% INPUTS
-% - endogenousvariables [double] N*T array, paths for the endogenous variables (initial guess).
-% - exogenousvariables [double] T*M array, paths for the exogenous variables.
+% - endogenousvariables [double] N*(T+M_.maximum_lag+M_.maximum_lead) array, paths for the endogenous variables (initial guess).
+% - exogenousvariables [double] (T+M_.maximum_lag+M_.maximum_lead)*M array, paths for the exogenous variables.
% - steadystate [double] N*1 array, steady state for the endogenous variables.
+% - controlled_paths_by_period [struct] data from perfect_foresight_controlled_paths block
% - M_ [struct] contains a description of the model.
% - options_ [struct] contains various options.
%
% OUTPUTS
-% - endogenousvariables [double] N*T array, paths for the endogenous variables (solution of the perfect foresight model).
+% - endogenousvariables [double] N*(T+M_.maximum_lag+M_.maximum_lead) array, paths for the endogenous variables (solution of the perfect foresight model).
% - success [logical] Whether a solution was found
% - maxerror [double] 1-norm of the residual
+% - exogenousvariables [double] (T+M_.maximum_lag+M_.maximum_lead)*M array, paths for the exogenous variables
+% (may be modified if perfect_foresight_controlled_paths present)
-% Copyright © 2015-2024 Dynare Team
+% Copyright © 2015-2025 Dynare Team
%
% This file is part of Dynare.
%
@@ -46,6 +49,7 @@ end
z = endogenousvariables(:,M_.maximum_lag+(1:periods));
if (options_.solve_algo == 10 || options_.solve_algo == 11)% mixed complementarity problem
+ assert(isempty(controlled_paths_by_period))
[lb, ub] = feval(sprintf('%s.dynamic_complementarity_conditions', M_.fname), M_.params);
if options_.linear_approximation
lb = lb - steadystate_y;
@@ -70,10 +74,28 @@ if (options_.solve_algo == 10 || options_.solve_algo == 11)% mixed complementari
M_.dynamic_mcp_equations_reordering);
eq_to_ignore=find(isfinite(lb) | isfinite(ub));
-else
+elseif isempty(controlled_paths_by_period)
[y, check, res, ~, errorcode] = dynare_solve(@perfect_foresight_problem, z(:), ...
options_.simul.maxit, options_.dynatol.f, options_.dynatol.x, ...
options_, y0, yT, exogenousvariables, M_.params, steadystate, periods, M_, options_);
+else
+ for p = 1:periods
+ if isempty(controlled_paths_by_period(p).exogenize_id)
+ continue
+ end
+ z(controlled_paths_by_period(p).exogenize_id,p) = exogenousvariables(p+M_.maximum_lag,controlled_paths_by_period(p).endogenize_id);
+ end
+
+ % call the following in a wrapper, that is then passed to dynare_solve
+ % A = controlled_paths_substitute_stacked_jacobian(A, y, y0, yT, exogenousvariables, steadystate, controlled_paths_by_period, M_);
+
+ for p = 1:periods
+ if isempty(controlled_paths_by_period(p).exogenize_id)
+ continue
+ end
+ exogenousvariables(p+M_.maximum_lag,controlled_paths_by_period(p).endogenize_id) = y(controlled_paths_by_period(p).exogenize_id+p*M_.endo_nbr);
+ y(controlled_paths_by_period(p).exogenize_id+p*M_.endo_nbr) = controlled_paths_by_period(p).values;
+ end
end
if all(imag(y)<.1*options_.dynatol.x)
diff --git a/meson.build b/meson.build
index 05a4f6b6af075b92a5a7652748d509c29d05d3ce..f52e708e87abb9d09f6ae8355d7e5c209555eb49 100644
--- a/meson.build
+++ b/meson.build
@@ -1627,6 +1627,7 @@ mod_and_m_tests = [
'deprecated/ramst.mod' ] },
{ 'test' : [ 'deterministic_simulations/ramst_pf_controlled_paths.mod',
'deterministic_simulations/ramst_pf_controlled_paths_lbj.mod',
+ 'deterministic_simulations/ramst_pf_controlled_paths_ssa7.mod',
'deterministic_simulations/ramst_pf_controlled_paths_check.mod' ],
'extra' : [ 'deterministic_simulations/ramst_pf_controlled_paths_common.inc'] },
{ 'test' : [ 'deterministic_simulations/ramst_pfwee_controlled_paths.mod' ],
diff --git a/tests/deterministic_simulations/ramst_pf_controlled_paths_check.mod b/tests/deterministic_simulations/ramst_pf_controlled_paths_check.mod
index b370f6001d46f05df98ad52dc16b1320ed9e0a48..393e398c6fb2b90e794caabe351028f2a90faef4 100644
--- a/tests/deterministic_simulations/ramst_pf_controlled_paths_check.mod
+++ b/tests/deterministic_simulations/ramst_pf_controlled_paths_check.mod
@@ -1,4 +1,4 @@
-/* Checks that exogenous computed by ramst_pf_controlled_paths{,lbj}.mod actually give back the
+/* Checks that exogenous computed by ramst_pf_controlled_paths{,lbj,ssa7}.mod actually give back the
expected endogenous variables */
@#define shocks = false
@@ -33,3 +33,18 @@ perfect_foresight_solver;
if max(max(abs(oo_.endo_simul - S1.oo_.endo_simul))) > options_.dynatol.x
error('perfect_foresight_controlled_paths gives wrong result with stack_solve_algo=1')
end
+
+
+// stack_solve_algo=7
+
+S7 = load('ramst_pf_controlled_paths_ssa7/Output/ramst_pf_controlled_paths_ssa7_results.mat');
+
+perfect_foresight_setup(periods=30);
+
+oo_.exo_simul = S7.oo_.exo_simul;
+
+perfect_foresight_solver;
+
+if max(max(abs(oo_.endo_simul - S7.oo_.endo_simul))) > options_.dynatol.x
+ error('perfect_foresight_controlled_paths gives wrong result with stack_solve_algo=7')
+end
diff --git a/tests/deterministic_simulations/ramst_pf_controlled_paths_ssa7.mod b/tests/deterministic_simulations/ramst_pf_controlled_paths_ssa7.mod
new file mode 100644
index 0000000000000000000000000000000000000000..2fe4958a9d97373c45cc1856b947706e19e2423e
--- /dev/null
+++ b/tests/deterministic_simulations/ramst_pf_controlled_paths_ssa7.mod
@@ -0,0 +1,17 @@
+// Performs a simulation with a perfect_foresight_controlled_paths block
+// with the stack_solve_algo=7
+
+@#define shocks = true
+@#include "ramst_pf_controlled_paths_common.inc"
+
+perfect_foresight_setup(periods=30, first_simulation_period = 2001Y);
+perfect_foresight_solver(stack_solve_algo = 7);
+
+if ~oo_.deterministic_simulation.status
+ error('Perfect foresight simulation failed')
+end
+
+if oo_.endo_simul(1, 3) ~= 1.6 || any(oo_.endo_simul(1, 5:6) ~= 1.7) || any(oo_.endo_simul(2, 8:10) ~= 13) ...
+ || any(oo_.endo_simul(3, 4:6) ~= 0.5) || oo_.exo_simul(2, 1) ~= 1.2
+ error('Perfect foresight with controlled paths failed')
+end