.clang-format

@@ -8,6 +8,12 @@
 #  https://clang.llvm.org/docs/ClangFormatStyleOptions.html
 # Effective configuration can be obtained with:
 #  clang-format --dump-config
+
+# The RemoveParentheses and RemoveSemicolon option are not permanently set,
+# because the clang-format manual (as of version 19) states that these
+# options can lead to incorrect formatting and thus their result should be
+# carefully reviewed.
+
 Language: Cpp
 Standard: c++20
 ColumnLimit: 100
@@ -19,9 +25,12 @@ BreakInheritanceList: AfterColon
 Cpp11BracedListStyle: true
 DeriveLineEnding: false
 IndentPPDirectives: AfterHash
+InsertNewlineAtEOF: true
 PackConstructorInitializers: NextLine
 PPIndentWidth: 1
 PointerAlignment: Left
+# RemoveParentheses: ReturnStatement
+# RemoveSemicolon: true
 SpaceAfterTemplateKeyword: false
 SpaceBeforeParens: ControlStatements
 SpaceBeforeCpp11BracedList: true

.gitlab-ci.yml

@@ -107,7 +107,7 @@ pkg_macOS_x86_64:
   script:
     # Enforce the arm64 meson for rewrite, as a workaround to https://github.com/mesonbuild/meson/issues/12282
     - env PATH="/opt/homebrew/bin:$PATH" meson rewrite kwargs set project / version "$VERSION"
-    - ln -s ~/tarballs macOS/deps/x86_64
+    - ln -s ~/tarballs macOS/deps/
     - make -C macOS build-x86_64
   cache:
     key: "$CI_JOB_NAME-$CI_COMMIT_REF_SLUG"
@@ -127,7 +127,7 @@ pkg_macOS_arm64:
   script:
     # Enforce the arm64 meson for rewrite, as a workaround to https://github.com/mesonbuild/meson/issues/12282
     - env PATH="/opt/homebrew/bin:$PATH" meson rewrite kwargs set project / version "$VERSION"
-    - ln -s ~/tarballs macOS/deps/arm64
+    - ln -s ~/tarballs macOS/deps/
     - make -C macOS build-arm64
   cache:
     key: "$CI_JOB_NAME-$CI_COMMIT_REF_SLUG"
@@ -184,6 +184,17 @@ test_clang_format:
     - ninja -C build-clang-format clang-format-check
   needs: []
 
+test_clang_tidy:
+  stage: test
+  script:
+    # Hack needed for meson < 1.6.0 which only looks for unversioned clang-tidy
+    - mkdir -p ~/.local/bin && ln -s /usr/bin/clang-tidy-19 ~/.local/bin/clang-tidy
+    - export PATH="$HOME/.local/bin:$PATH"
+    - meson setup -Dbuild_for=octave build-clang-tidy
+    - ninja -C build-clang-tidy clang-tidy
+  needs: []
+  when: manual
+
 # For the sign and deploy jobs, we don’t use the “needs” keyword, since we
 # don’t want those jobs to start before the “test” and “pkg” stages have
 # succeeded. Hence we stick to the “dependencies” keyword.

NEWS.md

+Announcement for Dynare 6.3 (on 2025-02-19)
+===========================================
+
+We are pleased to announce the release of Dynare 6.3.
+
+This maintenance release fixes various bugs.
+
+The Windows, macOS, MATLAB online and source packages are available for
+download at [the Dynare website](https://www.dynare.org/download/).
+
+This release is compatible with MATLAB versions ranging from 9.5 (R2018b) to
+24.2 (R2024b), and with GNU Octave versions ranging from 7.1.0 to 9.4.0 (NB:
+the Windows package requires version 9.4.0 specifically).
+
+Here is a list of the problems identified in version 6.2 and that have been
+fixed in version 6.3:
+
+* OccBin with option `smoother_inversion_filter` would crash the MCMC
+  estimation if the `filtered_variables` or `filter_step_ahead` options were
+  used
+* OccBin with option `smoother_inversion_filter` would use the PKF if
+  `mh_replic>0`
+* OccBin with option `smoothed_state_uncertainty` would crash Dynare if the
+  MCMC smoother was run after the classical one
+* OccBin's smoother would crash when encountering an internal error due to the
+  output of the linear smoother not having been computed
+* Calling `model_info` with `differentiate_forward_vars` would crash
+* The `identification` command would compute the asymptotic Hessian via
+  simulation instead of via moments as intended
+* The `identification` command would crash during prior sampling if the initial
+  draw did not solve the model
+* The `gsa_sample_file` was broken
+* Optimization algorithm `mode_compute=5` (`newrat`) would crash with
+  `analytic_derivation`
+* The `discretionary_policy` command would crash if the model was purely
+  forward-looking
+* The `dsample` command would crash
+* The `conditional_forecast_paths` block did not accept vector inputs
+* For MCMC chains with fewer than 6000 draws, the default number of `sub_draws`
+  used to compute posterior moments was incorrect
+* Bi-annual dates (e.g. `2024S1` or `2024H1`) were not accepted within Dynare
+  statements
+* Plotting `dseries` did not correctly show dates on the x-axis
+
+
 Announcement for Dynare 6.2 (on 2024-09-25)
 ===========================================
 

README.md

@@ -104,13 +104,13 @@ If you want a certain version (e.g. 5.x) , then add `--single-branch --branch 5.
 
 If you want to compile for MATLAB, please run the following (after adapting the path to MATLAB):
 ```sh
-meson setup -Dmatlab_path=/usr/local/MATLAB/R2023b -Dbuildtype=debugoptimized build-matlab
+meson setup -Dmatlab_path=/usr/local/MATLAB/R2023b --buildtype=debugoptimized build-matlab
 ```
 The build directory will thus be `build-matlab`.
 
 Or for Octave:
 ```sh
-meson setup -Dbuild_for=octave -Dbuildtype=debugoptimized build-octave
+meson setup -Dbuild_for=octave --buildtype=debugoptimized build-octave
 ```
 The build directory will thus be `build-octave`.
 
@@ -273,7 +273,7 @@ Now use the following commands if using MATLAB (adapt them for Octave, see above
 cd /home/$USER/dynare
 git clone --recurse-submodules https://git.dynare.org/dynare/dynare.git unstable
 cd unstable
-meson setup -Dmatlab_path=/usr/local/MATLAB/R2023b -Dfortran_args="[ '-B', '/home/$USER/dynare/slicot']" -Dbuildtype=debugoptimized build-matlab
+meson setup -Dmatlab_path=/usr/local/MATLAB/R2023b -Dfortran_args="[ '-B', '/home/$USER/dynare/slicot']" --buildtype=debugoptimized build-matlab
 meson compile -C build-matlab
 ```
 
@@ -318,7 +318,7 @@ cd dynare
 ```
 - Configure Dynare from the source directory (adjust `matlab_path` if you use a different version than R2024a):
 ```sh
-meson setup -Dmatlab_path=/usr/local/MATLAB/R2024a -Dbuildtype=debugoptimized build-matlab  
+meson setup -Dmatlab_path=/usr/local/MATLAB/R2024a --buildtype=debugoptimized build-matlab
 ```
 - Compile:
 ```sh
@@ -362,7 +362,7 @@ cd dynare
 ```
 - Configure Dynare from the source directory:
 ```sh
-meson setup -Dmatlab_path=<…> -Dbuildtype=debugoptimized -Dprefer_static=true -Dfortran_args="['-B','/usr/local/lib']" build-matlab
+meson setup -Dmatlab_path=<…> --buildtype=debugoptimized --prefer-static -Dfortran_args="['-B','C:/msys64/usr/local/lib']" build-matlab
 ```
 where the path of MATLAB is specified. Note that you should use
 the MSYS2 notation and not put spaces in the MATLAB path, so you probably want
@@ -520,7 +520,7 @@ If you want a certain version (e.g. 5.x) , then add `--single-branch --branch 5.
 ```sh
 export BUILDDIR=build-matlab
 export MATLABPATH=/Applications/MATLAB_R2023b.app
-arch -$ARCH meson setup --native-file macOS/homebrew-native-$ARCH.ini -Dmatlab_path=$MATLABPATH -Dbuildtype=debugoptimized -Dfortran_args="['-B','$DYNAREDIR/slicot/lib']" $BUILDDIR
+arch -$ARCH meson setup --native-file macOS/homebrew-native-$ARCH.ini -Dmatlab_path=$MATLABPATH --buildtype=debugoptimized -Dfortran_args="['-B','$DYNAREDIR/slicot/lib']" $BUILDDIR
 ```
 where you need to adapt the path to MATLAB.
 Similarly, if you want to compile for Octave, replace the `-Dmatlab_path` option by `-Dbuild_for=octave`, and change the build directory to `build-octave`.

doc/manual/source/bibliography.rst

@@ -65,7 +65,7 @@ Bibliography
 * Koopman, S. J. and J. Durbin (2003): “Filtering and Smoothing of State Vector for Diffuse State Space Models,” *Journal of Time Series Analysis*, 24(1), 85–98.
 * Kuntsevich, Alexei V. and Franz Kappel (1997): “SolvOpt - The solver for local nonlinear optimization problems (version 1.1, Matlab, C, FORTRAN)”, University of Graz, Graz, Austria.
 * Laffargue, Jean-Pierre (1990): “Résolution d’un modèle macroéconomique avec anticipations rationnelles”, *Annales d’Économie et Statistique*, 17, 97–119.
-* Liu, Jane and Mike West (2001): “Combined parameter and state estimation in simulation-based filtering”, in *Sequential Monte Carlo Methods in Practice*, Eds. Doucet, Freitas and Gordon, Springer Verlag.
+* Liu, Jane and Mike West (2001): “Combined parameter and state estimation in simulation-based filtering”, in *Sequential Monte Carlo Methods in Practice*, Eds. Doucet, Freitas and Gordon, Springer Verlag, Chapter 10, 197-223.
 * Murray, Lawrence M., Emlyn M. Jones and John Parslow (2013): “On Disturbance State-Space Models and the Particle Marginal Metropolis-Hastings Sampler”, *SIAM/ASA Journal on Uncertainty Quantification*, 1, 494–521.
 * Mutschler, Willi (2015): “Identification of DSGE models - The effect of higher-order approximation and pruning“, *Journal of Economic Dynamics & Control*, 56, 34-54.
 * Mutschler, Willi (2018): “Higher-order statistics for DSGE models”, *Econometrics and Statistics*, 6(C), 44-56.

doc/manual/source/conf.py

 # -*- coding: utf-8 -*-
 
-# Copyright © 2018-2024 Dynare Team
+# Copyright © 2018-2025 Dynare Team
 #
 # This file is part of Dynare.
 #
@@ -34,7 +34,7 @@ html_static_path = ['_static']
 master_doc = 'index'
 
 project = u'Dynare'
-copyright = u'1996–2024 Dynare Team'
+copyright = u'1996–2025 Dynare Team'
 author = u'Dynare Team'
 
 add_function_parentheses = False

doc/manual/source/index.rst

@@ -26,7 +26,7 @@ The following people used to be members of the team:
 * Ferhat Mihoubi
 * George Perendia
 
-Copyright © 1996-2024, Dynare Team.
+Copyright © 1996-2025, Dynare Team.
 
 Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.
 

doc/manual/source/installation-and-configuration.rst

@@ -15,7 +15,7 @@ compilation steps are necessary in that case.
 In order to run Dynare, you need one of the following:
 
 * MATLAB, any version ranging from 9.5 (R2018b) to 24.2 (R2024b);
-* GNU Octave, any version ranging from 7.1.0 to 9.2.0, with the ``statistics`` package
+* GNU Octave, any version ranging from 7.1.0 to 9.4.0, with the ``statistics`` package
   from `Octave-Forge`_. Note however that the Dynare installer for Windows
   requires a more specific version of Octave, as indicated on the download
   page.
@@ -23,8 +23,17 @@ In order to run Dynare, you need one of the following:
 The following optional extensions are also useful to benefit from
 extra features, but are in no way required:
 
-* If under MATLAB: the Optimization Toolbox, the Statistics Toolbox,
-  the Control System Toolbox;
+* If under MATLAB: the 
+
+  * Optimization Toolbox (providing various optimizers 
+    like ``fminsearch``, ``fmincon``, or ``fminunc``, used in e.g. ``mode_compute``,
+    ``opt_algo`` or ``ALGO``), 
+  * Statistics Toolbox (for faster and sometimes more robust implementations of 
+    statistical distributions), 
+  * Global Optimization Toolbox (for ``particleswarm`` and ``simulannealbnd``, used in 
+    e.g. ``mode_compute``, ``opt_algo`` or ``ALGO``)
+  * Control System Toolbox (for the Lyapunov solver ``dlyapchol`` triggered with ``lyapunov=square_root_solver``)
+  * Parallel Computing Toolbox (to speed up the ``dime`` sampler)
 
 * If under Octave, the following `Octave-Forge`_ packages: ``optim``, ``io``,
   ``control``.
@@ -91,6 +100,18 @@ Debian, Ubuntu and Linux Mint).
 On macOS
 --------
 
+.. warning::
+
+   Installing into ``/Applications/dynare`` might fail if you have older versions of Dynare already installed in ``/Applications/Dynare``.
+   To fix this, modify the ownership by executing the following command in Terminal.app::
+
+     sudo chown -R "$USER":staff /Applications/Dynare
+
+   Alternatively, you can modify the installation path in the automated installed using *Customize* and *Location*.
+   After installation, the folder will contain several sub-directories, among which are ``matlab``, ``mex``, and ``doc``.
+   Several versions of Dynare can coexist (by default in ``/Applications/Dynare``),
+   as long as you correctly adjust your path settings (see :ref:`words-warning`).
+
 With MATLAB
 ^^^^^^^^^^^
 
@@ -100,15 +121,6 @@ and follow the instructions.
 This installation does not require administrative privileges.
 If for some reason admin rights are requested, use *Change Install Location* and select *Install for me only*.
 The default installation directory is ``/Applications/Dynare/x.y-arch``.
-Installing into ``/Applications/dynare`` might fail if you have older versions of Dynare already installed in ``/Applications/Dynare``.
-To fix this, modify the ownership by executing the following command in Terminal.app::
-
-  sudo chown -R "$USER":staff /Applications/Dynare
-
-Alternatively, you can modify the installation path in the automated installed using *Customize* and *Location*.
-After installation, the folder will contain several sub-directories, among which are ``matlab``, ``mex``, and ``doc``.
-Several versions of Dynare can coexist (by default in ``/Applications/Dynare``),
-as long as you correctly adjust your path settings (see :ref:`words-warning`).
 
 It is recommended to install the Xcode Command Line Tools (this is an Apple product)
 and GCC via Homebrew_ (see :ref:`prerequisites-macos`).
@@ -133,6 +145,8 @@ once)::
 
   octave:1> pkg install -forge io statistics control struct optim
 
+If you want to use the `x13` functionality of `dseries`, you also need to build the `x13as` binary. [#fx13]_
+
 On FreeBSD
 ----------
 
@@ -325,3 +339,8 @@ Dynare unusable.
 .. _Dynare wiki: https://git.dynare.org/Dynare/dynare/wikis
 .. _Octave-Forge: https://octave.sourceforge.io/
 .. _Homebrew: https://brew.sh
+
+
+.. rubric:: Footnotes
+
+.. [#fx13] See the instructions at `<https://forum.dynare.org/t/missing-installation-package/27350/4>`__.
\ No newline at end of file

doc/manual/utils/dynare_dom.py

@@ -97,7 +97,7 @@ class DynObject(ObjectDescription):
                 self.state_machine.reporter.warning(
                     'duplicate object description of %s, ' % fullname +
                     'other instance in ' +
-                    self.env.doc2path(objects[fullname][0]),line=self.lineno)
+                    str(self.env.doc2path(objects[fullname][0])),line=self.lineno)
             objects[fullname] = (self.env.docname, self.objtype)
 
         indextext = self.get_index_text(fullname,name_obj)
@@ -242,7 +242,7 @@ class DynSimpleObject(ObjectDescription):
                 self.state_machine.reporter.warning(
                     'duplicate object description of %s, ' % fullname +
                     'other instance in ' +
-                    self.env.doc2path(objects[fullname][0]), line=self.lineno)
+                    str(self.env.doc2path(objects[fullname][0])), line=self.lineno)
             objects[fullname] = self.env.docname, self.objtype
 
         indextext = self.get_index_text(fullname,name_obj)

license.txt

 Format: https://www.debian.org/doc/packaging-manuals/copyright-format/1.0/
 Upstream-Name: Dynare
-Upstream-Contact: Dynare Team, whose members in 2024 are:
+Upstream-Contact: Dynare Team, whose members in 2025 are:
                   - Stéphane Adjemian <stephane.adjemian@univ-lemans.fr>
                   - Michel Juillard <michel.juillard@mjui.fr>
                   - Frédéric Karamé <frederic.karame@univ-lemans.fr>
@@ -23,7 +23,7 @@ Upstream-Contact: Dynare Team, whose members in 2024 are:
 Source: https://www.dynare.org
 
 Files: *
-Copyright: 1996-2024 Dynare Team
+Copyright: 1996-2025 Dynare Team
 License: GPL-3+
 
 Files: matlab/+occbin/IVF_core.m
@@ -97,7 +97,7 @@ License: GPL-3+
 
 Files: matlab/optimization/cmaes.m
 Copyright: 2001-2012 Nikolaus Hansen
-           2012-2017 Dynare Team
+           2012-2023 Dynare Team
 License: GPL-3+
 
 Files: matlab/optimization/solvopt.m
@@ -173,7 +173,7 @@ Comment: The author gave authorization to redistribute
 Files: matlab/+gsa/Morris_Measure_Groups.m
        matlab/+gsa/Sampling_Function_2.m
 Copyright: 2005 European Commission
-           2012-2013 Dynare Team
+           2012-2023 Dynare Team
 License: GPL-3+
 Comment: Written by Jessica Cariboni and Francesca Campolongo
  Joint Research Centre, The European Commission,
@@ -220,14 +220,14 @@ License: GPL-3+
 
 Files: matlab/missing/stats/quantile.m
 Copyright: 2014-2016 Christopher Hummersone
-           2016-2017 Dynare Team
+           2016-2023 Dynare Team
 License: GPL-3+
 
 Files: matlab/missing/stats/corr.m
 Copyright: 1993-1996 Kurt Hornik
            1996-2015 John W. Eaton
            2013-2015 Julien Bect
-           2016-2017 Dynare Team
+           2016-2023 Dynare Team
 License: GPL-3+
 
 Files: matlab/lmmcp/catstruct.m
@@ -260,7 +260,7 @@ Copyright: 2000-2022 Frank Schorfheide
 License: CC-BY-SA-4.0
 
 Files: doc/*.rst doc/*.tex doc/*.svg doc/*.pdf doc/*.bib
-Copyright: 1996-2022 Dynare Team
+Copyright: 1996-2025 Dynare Team
 License: GFDL-NIV-1.3+
 
 Files: doc/dr.tex doc/dr.bib
@@ -278,14 +278,14 @@ License: GPL-3+
 
 Files: scripts/dynare.el
 Copyright: 2010 Yannick Kalantzis
-           2019-2023 Dynare Team
+           2019-2025 Dynare Team
 License: GPL-3+
 
 Files: mex/sources/gensylv/gensylv.cc
        mex/sources/libkorder/kord/* mex/sources/libkorder/sylv/*
        mex/sources/libkorder/tl/* mex/sources/libkorder/utils/*
 Copyright: 2004-2011 Ondra Kamenik
-           2019-2023 Dynare Team
+           2019-2025 Dynare Team
 License: GPL-3+
 
 Files: mex/sources/sobol/sobol.f08
@@ -294,11 +294,11 @@ Copyright: 2004-2009 John Burkardt
 License: LGPL-3+
 
 Files: preprocessor/doc/macroprocessor/*
-Copyright: 2008-2021 Dynare Team
+Copyright: 2008-2024 Dynare Team
 License: CC-BY-SA-4.0
 
 Files: preprocessor/doc/preprocessor/*
-Copyright: 2007-2019 Dynare Team
+Copyright: 2007-2023 Dynare Team
 License: CC-BY-SA-4.0
 
 Files: contrib/ms-sbvar/utilities_dw/*

macOS/build.sh

@@ -70,7 +70,7 @@ ln -s "$BREWDIR"/opt/gcc/lib/gcc/"$GCC_VERSION"/libquadmath.a "$QUADMATH_DIR"
 cd "$ROOTDIR"
 
 # NB: the addition of -Wl,-ld_classic is a workaround for https://github.com/mesonbuild/meson/issues/12282 (see also the native file)
-common_meson_opts=(-Dbuild_for=matlab -Dbuildtype=release -Dprefer_static=true -Dfortran_args="[ '-B', '$LIB64/Slicot/' ]" \
+common_meson_opts=(-Dbuild_for=matlab --buildtype=release --prefer-static -Dfortran_args="[ '-B', '$LIB64/Slicot/' ]" \
                    -Dc_link_args="[ '-Wl,-ld_classic', '-L$QUADMATH_DIR' ]" -Dcpp_link_args="[ '-Wl,-ld_classic', '-L$QUADMATH_DIR' ]" -Dfortran_link_args="[ '-Wl,-ld_classic', '-L$QUADMATH_DIR' ]" \
                    --native-file macOS/homebrew-native-$PKG_ARCH.ini)
 

matlab/+bgp/write.m

@@ -15,7 +15,7 @@ function write(M_)
 % REMARKS
 % - The trends are assumed to be multiplicative.
 
-% Copyright © 2019-2023 Dynare Team
+% Copyright © 2019-2024 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -84,37 +84,40 @@ fprintf(fid, 'y = z(1:%u);\n\n', M_.endo_nbr);
 fprintf(fid, 'g = z(%u:%u);\n', M_.endo_nbr+1, 2*M_.endo_nbr);
 
 % Define the point where the dynamic model is to be evaluated.
-fprintf(fid, 'Y = zeros(%u, 1);\n', 2*(n0+n1+n2));
+% In period t, then in period t+1
+fprintf(fid, 'Y0 = NaN(%u, 1);\n', 3*M_.endo_nbr);
+fprintf(fid, 'Y1 = NaN(%u, 1);\n', 3*M_.endo_nbr);
 for i=1:length(I0) % period t equations, lagged variables.
     if I0(i)
-        fprintf(fid, 'Y(%u) = y(%u);\n', I0(i), i);
+        fprintf(fid, 'Y0(%u) = y(%u);\n', i+(purely_forward_model*M_.endo_nbr), i);
     end
 end
 for i=1:length(I1) % period t equations, current variables.
     if I1(i)
-        fprintf(fid, 'Y(%u) = y(%u)*g(%u);\n', I1(i), i, i);
+        fprintf(fid, 'Y0(%u) = y(%u)*g(%u);\n', i+M_.endo_nbr+(purely_forward_model*M_.endo_nbr), i, i);
     end
 end
 for i=1:length(I2) % period t equations, leaded variables.
     if I2(i)
-        fprintf(fid, 'Y(%u) = y(%u)*g(%u)*g(%u);\n', I2(i), i, i, i);
+        fprintf(fid, 'Y0(%u) = y(%u)*g(%u)*g(%u);\n', i+2*M_.endo_nbr, i, i, i);
     end
 end
 for i=1:length(I0) % period t+1 equations lagged variables.
     if I0(i)
-        fprintf(fid, 'Y(%u) = y(%u)*g(%u);\n', n0+n1+n2+I0(i), i, i);
+        fprintf(fid, 'Y1(%u) = y(%u)*g(%u);\n', i+(purely_forward_model*M_.endo_nbr), i, i);
     end
 end
 for i=1:length(I1) % period t+1 equations current variables.
     if I1(i)
-        fprintf(fid, 'Y(%u) = y(%u)*g(%u)*g(%u);\n', n0+n1+n2+I1(i), i, i, i);
+        fprintf(fid, 'Y1(%u) = y(%u)*g(%u)*g(%u);\n', i+M_.endo_nbr+(purely_forward_model*M_.endo_nbr), i, i, i);
     end
 end
 for i=1:length(I2) % period t+1 equations leaded variables.
     if I2(i)
-        fprintf(fid, 'Y(%u) = y(%u)*g(%u)*g(%u)*g(%u);\n', n0+n1+n2+I2(i), i, i, i, i);
+        fprintf(fid, 'Y1(%u) = y(%u)*g(%u)*g(%u)*g(%u);\n', i+2*M_.endo_nbr, i, i, i, i);
     end
 end
+
 fprintf(fid, '\n');
 
 % Define the vector of parameters.
@@ -131,19 +134,36 @@ fprintf(fid, 'F = NaN(%u, 1);\n', 2*M_.endo_nbr);
 fprintf(fid, 'x = zeros(1, %u);\n\n', M_.exo_nbr);
 
 % Evaluate the residuals and jacobian of the dynamic model in periods t and t+1.
+fprintf(fid, '[F(1:%u), T0_order, T0] = %s.sparse.dynamic_resid(Y0, x, p, y);\n', M_.endo_nbr, M_.fname);
+fprintf(fid, '[F(%u:%u), T1_order, T1] = %s.sparse.dynamic_resid(Y1, x, p, y);\n', M_.endo_nbr+1, 2*M_.endo_nbr, M_.fname);
 fprintf(fid, 'if nargout>1\n');
+fprintf(fid, '    sparse_rowval = [');
+fprintf(fid, '%u ', M_.dynamic_g1_sparse_rowval);
+fprintf(fid, '];\n');
+fprintf(fid, '    sparse_colval = [');
+fprintf(fid, '%u ', M_.dynamic_g1_sparse_colval);
+fprintf(fid, '];\n');
+fprintf(fid, '    sparse_colptr = [');
+fprintf(fid, '%u ', M_.dynamic_g1_sparse_colptr);
+fprintf(fid, '];\n');
+fprintf(fid, '    J0 = %s.sparse.dynamic_g1(Y0, x, p, y, sparse_rowval, sparse_colval, sparse_colptr, T0_order, T0);\n', M_.fname);
+fprintf(fid, '    J1 = %s.sparse.dynamic_g1(Y1, x, p, y, sparse_rowval, sparse_colval, sparse_colptr, T1_order, T1);\n', M_.fname);
+
+% Transform back the Jacobians J0 and J1 in the legacy format (non-sparse)
+% NB: it is probably possible to simplify the rest of this file, but maintaining
+% decent performance does not seem straightforward.
+lli = find(M_.lead_lag_incidence');
+if purely_forward_model
+    lli = lli + M_.endo_nbr;
+end
+fprintf(fid, '    lli = [');
+fprintf(fid, '%u ', lli);
+fprintf(fid, '];\n');
+
 fprintf(fid, '    J = zeros(%u, %u);\n', 2*M_.endo_nbr, n0+n1+n2+M_.endo_nbr);
-fprintf(fid, '    [F(1:%u), tmp] = %s.dynamic(Y(1:%u), x, p, y, 1);\n', M_.endo_nbr, M_.fname, n0+n1+n2);
-fprintf(fid, '    J(1:%u,1:%u) = tmp(:,1:%u);\n', M_.endo_nbr, n0+n1+n2, n0+n1+n2);
-fprintf(fid, '    [F(%u:%u), tmp] = %s.dynamic(Y(1+%u:%u), x, p, y, 1);\n', M_.endo_nbr+1, 2*M_.endo_nbr, M_.fname, n0+n1+n2, 2*(n0+n1+n2));
-fprintf(fid, '    J(%u:%u,1:%u) = tmp(:,1:%u);\n', M_.endo_nbr+1, 2*M_.endo_nbr, n0+n1+n2, n0+n1+n2);
-fprintf(fid, 'else\n');
-fprintf(fid, '    F(1:%u) = %s.dynamic(Y(1:%u), x, p, y, 1);\n', M_.endo_nbr, M_.fname, n0+n1+n2);
-fprintf(fid, '    F(%u:%u) = %s.dynamic(Y(1+%u:%u), x, p, y, 1);\n', M_.endo_nbr+1, 2*M_.endo_nbr, M_.fname, n0+n1+n2, 2*(n0+n1+n2));
-fprintf(fid, 'end\n\n');
+fprintf(fid, '    J(1:%u,1:%u) = full(J0(:,lli));\n', M_.endo_nbr, n0+n1+n2);
+fprintf(fid, '    J(%u:%u,1:%u) = full(J1(:,lli));\n', M_.endo_nbr+1, 2*M_.endo_nbr, n0+n1+n2);
 
-% Compute the jacobian if required.
-fprintf(fid, 'if nargout>1\n');
 fprintf(fid, '    JAC = zeros(%u,%u);\n', 2*M_.endo_nbr, 2*M_.endo_nbr);
 
 % Compute the derivatives of the first block of equations (period t)
@@ -279,7 +299,7 @@ else
 end
 
 % Compute the derivatives of the second block of equations (period t+1)
-% with respect to the endogenous variables.
+% with respect to the growth factors.
 if purely_backward_model || purely_forward_model
     for i=M_.eq_nbr+1:2*M_.eq_nbr
         for j=1:M_.endo_nbr
@@ -328,4 +348,4 @@ end
 fprintf(fid, '    JAC(:,%u:%u) = J(:,%u:%u);\n', M_.endo_nbr+1, 2*M_.endo_nbr, n0+n1+n2+1, n0+n1+n2+M_.endo_nbr);
 
 fprintf(fid,'end\n');
-fclose(fid);
\ No newline at end of file
+fclose(fid);

matlab/+gsa/run.m

@@ -360,7 +360,7 @@ if options_gsa.redform && ~isempty(options_gsa.namendo)
         if isempty(options_gsa.threshold_redform) && ~(exist('gsa_sdp','file')==6 || exist('gsa_sdp','file')==2)
             fprintf('\nThe "SS-ANOVA-R: MATLAB Toolbox for the estimation of Smoothing Spline ANOVA models with Recursive algorithms" is missing.\n')
             fprintf('To obtain it, go to:\n\n')
-            fprintf('https://ec.europa.eu/jrc/en/macro-econometric-statistical-software/ss-anova-r-downloads \n\n')
+            fprintf('https://joint-research-centre.ec.europa.eu/system/files/2025-01/ss_anova_recurs.zip \n\n')
             fprintf('and follow the instructions there.\n')
             fprintf('After obtaining the files, you need to unpack them and set a Matlab Path to those files.\n')
             error('SS-ANOVA-R Toolbox missing!')

matlab/+gsa/stability_mapping.m

@@ -92,6 +92,10 @@ xparam1=[];
 [~,~,~,lb,ub] = set_prior(estim_params_,M_,options_); %Prepare bounds
 if ~isempty(bayestopt_) && any(bayestopt_.pshape > 0)
     % Set prior bounds
+    if options_.prior_trunc==0
+        fprintf('\nstability_mapping: GSA with priors requires bounded support. Setting options_.prior_trunc=1e-10.\n')
+        options_.prior_trunc=1e-10;
+    end
     bounds = prior_bounds(bayestopt_, options_.prior_trunc);
     bounds.lb = max(bounds.lb,lb);
     bounds.ub = min(bounds.ub,ub);

matlab/+gui/+perfect_foresight/run.m

@@ -13,7 +13,7 @@ function run(json)
 % SPECIAL REQUIREMENTS
 %   none
 
-% Copyright © 2019-2023 Dynare Team
+% Copyright © 2019-2024 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -103,7 +103,6 @@ if ~isempty(jm.anticipated_transitory_shocks)
             'periods', s.start_date:s.end_date, ...
             'value', s.value)];
     end
-    M_.exo_det_length = 0;
 end
 
 %% Make unanticipated shock map

matlab/+gui/+stochastic-simulation/read.m

@@ -13,7 +13,7 @@ function read(json)
 % SPECIAL REQUIREMENTS
 %   none
 
-% Copyright © 2019-2020 Dynare Team
+% Copyright © 2019-2024 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -36,7 +36,6 @@ global M_ options_ oo_
 jm = loadjson_(json, 'SimplifyCell', 1);
 data2json=struct();
 
-M_.exo_det_length = 0;
 for nshocks = 1:length(jm.stochasticshocksdescription)
 	covartype=jm.stochasticshocksdescription{nshocks}.shockattributevalue;
 	thisshock=(jm.stochasticshocksdescription{nshocks}.shockindex)+1;

matlab/+hank/check_steady_state_input.m

+% Copyright © 2025 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 <https://www.gnu.org/licenses/>.
+%
+% Compute the stochastic simulations of heterogeneus-agent models
+%
+% INPUTS
+% - M_       [structure] Matlab's structure describing the model
+% - options_ [structure] Matlab's structure describing the current options
+% - ss       [structure] Matlab's structure with the model steady-state
+%                       information. It contains the following fields:
+%    - pol [structure] Matlab's structure containing the policy functions
+%                      discretization
+%       - pol.grids [structure]: Matlab's structure containing the nodes of the
+%                                state grids as column vectors.
+%       - pol.values [structure]: Matlab's structure containing the policy
+%                                 function as matrices. Row indices and column
+%                                 indices follow the lexicographic order
+%                                 specified in pol.shocks and pol.states
+%       - pol.shocks [array]: a list containing the order of shock/innovation
+%                             variables used for the rows of pol.values. If not
+%                             specified, it follows the declaration order in the
+%                             var(heterogeneity=) statement (resp. varexo(heterogeneity=)
+%                             statement) for discretizes AR(1) processes (resp.
+%                             discretized gaussian i.i.d innovations).
+%       - pol.states [array]: a list containing the order of state variables
+%                             used for the columns of pol.values. If not
+%                             specified, it follows the declaration order in the
+%                             var(heterogeneity=) statement.
+%    - shocks [structure]: Matlab's stucture describing the discretization of
+%                          individual shocks or innovations:
+%       - shocks.grids [structure]: Matlab's structure containing the nodes of
+%                                   the shock grids
+%       - shocks.Pi [structure]: Matlab's structure containing the Markov
+%                                matrices if the shock processes are discretized
+%                                AR(1) processes. The field should be absent
+%                                otherwise.
+%       - shocks.w [structure]: Matlab's structure containing the Gauss-Hermite
+%                               weights if the i.i.d gaussian innovation
+%                               processes are discretized
+%    - d [structure]: Matlab's structure describing the steady-state
+%                     distribution
+%       - d.grids [structure]: structure containing the states grids as column
+%                              vectors. If one of the states grid is not
+%                              specified, it is assumed to be identical to
+%                              its policy-function value stored in pol.grids
+%       - d.hist [matrix]: the histogram of the distribution as a matrix with
+%                          shocks/innovation indices as rows and state indices
+%                          as columns. Row and column indices follow the
+%                          lexicographic order specified in d.shocks and
+%                          d.states
+%       - d.shocks [array]: a list containing the order of shock/innovation
+%                           variables used for the rows of d.hist. If it is not
+%                           specified, it falls back to the value induced by
+%                           pol.shocks.
+%       - d.states [array]: a list containing the order of state variables used
+%                           for the columns of d.hist. If it is not
+%                           specified, it falls back to the value induced by
+%                           pol.states.
+%    - agg [structure]: Matlab's tructure containing the steady-state values of
+%                       aggregate variables
+% OUTPUTS
+% - out_ss [structure]: validated and normalized steady-state input structure.
+%                       It has a similar structure as the ss structure in inputs.
+% - sizes [structure]: structure containing sizes information
+%    - n_e [integer]: number of shocks
+%    - N_e [integer]: total number of nodes in the shocks grids
+%    - shocks [structure]: number of nodes for each shock grid
+%    - n_a [integer]: number of states
+%    - pol [structure]: 
+%       - pol.N_a [integer]: total number of nodes in the policy state grids
+%       - pol.states [structure]: number of nodes for each state grid
+%    - d [structure]:
+%       - d.states [structure]: number of nodes for each distribution state grid
+%       - d.N_a [integer]: total number of nodes in the distribution grids
+%    - n_pol [integer]: number of policy variables
+%    - agg [integer]: number of aggregate variables
+function [out_ss, sizes] = check_steady_state_input(M_, options_, ss)
+   %% Checks
+   % Retrieve variables information from M_
+   state_symbs = M_.heterogeneity(1).endo_names(M_.heterogeneity(1).state_var);
+   pol_symbs= M_.heterogeneity(1).endo_names;
+   inn_symbs = M_.heterogeneity(1).exo_names;
+   agg_symbs = M_.endo_names(1:M_.orig_endo_nbr);
+   % Initialize output variables
+   sizes = struct;
+   out_ss = struct;
+   if ~isstruct(ss)
+      error('Misspecified steady-state input `ss`: the steady-state input `ss` is not a structure.')
+   end
+   %% Shocks
+   % Check that the field `ss.shocks` exists
+   check_isfield('shocks', ss, 'ss.shocks', ' Models without idiosyncratic shocks but with ex-post heterogeneity over individual state variables cannot be solved yet.')
+   shocks = ss.shocks;
+   % Check that `ss.shocks` is a structure
+   check_isstruct(shocks, 'ss.shocks');
+   % Check that the field `ss.shocks.grids` exists
+   check_isfield('grids', ss.shocks, 'ss.shocks.grids');
+   % Check that `ss.shocks.grids` is a structure
+   check_isstruct(shocks.grids, 'ss.shocks.grids');
+   shock_symbs = fieldnames(shocks.grids);
+   % Check the types of `ss.shocks.grids` values
+   check_fun(shocks.grids, 'ss.shocks.grids', shock_symbs, @(x) isnumeric(x) && isreal(x) && isvector(x) && ~issparse(x), 'are not dense real vectors');
+   % Make `ss.shocks.grids` values column vector in the output steady-state
+   % structure
+   for i=1:numel(shock_symbs)
+      s = shock_symbs{i};
+      if isrow(ss.shocks.grids.(s))
+         out_ss.shocks.grids.(s) = ss.shocks.grids.(s)';
+      else
+         out_ss.shocks.grids.(s) = ss.shocks.grids.(s);
+      end
+   end
+   % Check shock discretization
+   flag_ar1 = isfield(shocks, 'Pi');
+   flag_gh = isfield(shocks, 'w');
+   if ~flag_ar1 && ~flag_gh
+      error('Misspecified steady-state input `ss`: the `ss.shocks.Pi` and `ss.shocks.w` fields are both non-specified, while exactly one of them should be set.');
+   end
+   % Check that either individual AR(1) processes or i.i.d gaussion innovation
+   % processes are discretized
+   if flag_ar1 && flag_gh
+      error('Misspecified steady-state input `ss`: the `ss.shocks.Pi` and `ss.shocks.w` fields are both specified, while only one of them should be.');
+   end
+   % Case of discretized AR(1) exogenous processes
+   if flag_ar1
+      % Check that the grids specification for AR(1) shocks and the
+      % var(heterogeneity=) statement are compatible
+      check_consistency(shock_symbs, pol_symbs, 'ss.shocks.grids', 'M_.heterogeneity(1).endo_names');
+      % Check that shocks.Pi is a structure
+      check_isstruct(shocks.Pi, 'ss.shocks.Pi');
+      % Check that the grids specification for individual AR(1) shocks, the
+      % information in the M_ structure and the Markov transition matrices
+      % specification are compatible and display a warning if redundancies are
+      % detected
+      check_missingredundant(shocks.Pi, 'ss.shocks.Pi', shock_symbs, options_.hank.nowarningredundant);
+      % Store:
+      %    - the number of shocks
+      sizes.n_e = numel(shock_symbs);
+      %    - the size of the tensor product of the shock grids
+      grid_nb = cellfun(@(s) numel(shocks.grids.(s)), shock_symbs); 
+      sizes.N_e = prod(grid_nb);
+      %    - the size of each shock grid
+      for i=1:numel(shock_symbs)
+         s = shock_symbs{i};
+         sizes.shocks.(s) = numel(shocks.grids.(s));
+      end
+      % Check the type of shocks.Pi field values
+      check_fun(shocks.Pi, 'ss.shocks.Pi', shock_symbs, @(x) ismatrix(x) && isnumeric(x) && isreal(x) && ~issparse(x), 'are not dense real matrices');
+      % Check the internal size compatibility of discretized shocks processes
+      check_fun(shocks.Pi, 'ss.shocks.Pi', shock_symbs, @(x) size(x,1), 'have a number of rows that is not consistent with the size of their counterparts in `ss.shocks.grids`', grid_nb);
+      check_fun(shocks.Pi, 'ss.shocks.Pi', shock_symbs, @(x) size(x,2), 'have a number of columns that is not consistent with the size of their counterparts in `ss.shocks.grids`', grid_nb);
+      % Check that the matrices provided in shocks.Pi are Markov matrices:
+      %     - all elements are non-negative
+      check_fun(shocks.Pi, 'ss.shocks.Pi', shock_symbs, @(x) all(x >= 0, 'all'), 'contain negative elements')
+      %     - the sum of each row equals 1.
+      check_fun(shocks.Pi, 'ss.shocks.Pi', shock_symbs, @(x) all(abs(sum(x,2)-1) < options_.hank.tol_check_sum), 'have row sums different from 1.')
+      % Remove AR(1) shock processes from state and policy variables
+      state_symbs = setdiff(state_symbs, shock_symbs);
+      pol_symbs = setdiff(pol_symbs, shock_symbs);
+      % Copy relevant shock-related elements in out_ss 
+      out_ss.shocks.Pi = ss.shocks.Pi;
+   end
+   % Case of discretized i.i.d gaussian innovations
+   if flag_gh
+      % Check that shocks.w is a structure
+      check_isstruct(shocks.w, 'shocks.w');
+      % Verify that the grids specification for individual i.i.d innovations and
+      % the varexo(heterogeneity=) statement are compatible
+      check_consistency(shock_symbs, inn_symbs, 'ss.shocks.grids', 'M_.heterogeneity(1).exo_names');
+      % Verify that the grids specification for individual i.i.d innovations and
+      % the Gauss-Hermite weights specification are compatible and display a
+      % warning if redundancies are detected
+      check_missingredundant(shocks.w, 'ss.shocks.w', shock_symbs, options_.hank.nowarningredundant);
+      % Check the type of `ss.shocks.w` elements
+      check_fun(shocks.w, 'ss.shocks.w', shock_symbs, @(x) isvector(x) && isnumeric(x) && isreal(x) && ~issparse(x), 'are not dense real vectors');
+      % Store:
+      %    - the number of shocks
+      sizes.n_e = numel(shock_symbs);
+      %    - the size of the tensor product of the shock grids 
+      grid_nb = cellfun(@(s) numel(shocks.grids.(s)), shock_symbs); 
+      sizes.N_e = prod(grid_nb);
+      %    - the size of each shock grid
+      for i=1:numel(shock_symbs)
+         s = shock_symbs{i};
+         sizes.shocks.(s) = numel(shocks.grids.(s));
+      end
+      % Check the internal size compatibility of discretized shocks processes
+      check_fun(shocks.w, 'ss.shocks.w', shock_symbs, @(x) numel(x), 'have incompatible sizes with those of `ss.shocks.grids`', grid_nb);
+      % Check that the arrays provided in shocks.w have the properties of
+      % Gauss-Hermite weights:
+      %     - all elements are non-negative
+      check_fun(shocks.w, 'ss.shocks.w', shock_symbs, @(x) all(x >= 0.), 'contain negative elements');
+      %     - the sum of Gauss-Hermite weights is 1
+      check_fun(shocks.w, 'ss.shocks.w', shock_symbs, @(x) all(abs(sum(x)-1) < options_.hank.tol_check_sum), 'have sums different from 1.');
+      % Make `ss.shocks.w` values column vectors in the output steady-state
+      % structure
+      for i=1:numel(shock_symbs)
+         s = shock_symbs{i};
+         if isrow(ss.shocks.w.(s))
+            out_ss.shocks.w.(s) = ss.shocks.w.(s)';
+         else
+            out_ss.shocks.w.(s) = ss.shocks.w.(s);
+         end
+      end
+   end
+   %% Policy functions
+   % Check that the `ss.pol` field exists
+   check_isfield('pol', ss, 'ss.pol');
+   pol = ss.pol;
+   % Check that `ss.pol` is a structure
+   check_isstruct(ss.pol, 'ss.pol');
+   % Check that the `ss.pol`.grids field exists
+   check_isfield('grids', ss.pol, 'ss.pol.grids');
+   % Check that `ss.pol.grids` is a structure
+   check_isstruct(ss.pol.grids, 'ss.pol.grids');
+   % Check that the state grids specification and the var(heterogeneity=)
+   % statement are compatible
+   check_missingredundant(pol.grids, 'ss.pol.grids', state_symbs, options_.hank.nowarningredundant);
+   % Check that `ss.pol.grids` values are dense real vectors
+   check_fun(pol.grids, 'ss.pol.grids', state_symbs, @(x) isnumeric(x) && isreal(x) && isvector(x) && ~issparse(x), 'are not dense real vectors');
+   % Store:
+   %    - the number of states
+   sizes.n_a = numel(state_symbs);
+   %    - the size of the tensor product of the states grids 
+   grid_nb = cellfun(@(s) numel(pol.grids.(s)), state_symbs);
+   sizes.pol.N_a = prod(grid_nb);
+   %    - the size of each state grid
+   for i=1:numel(state_symbs)
+      s = state_symbs{i};
+      sizes.pol.states.(s) = numel(pol.grids.(s));
+   end
+   % Make `ss.shocks.grids` values column vector in the output steady-state
+   % structure
+   for i=1:numel(state_symbs)
+      s = state_symbs{i};
+      if isrow(ss.pol.grids.(s))
+         out_ss.pol.grids.(s) = ss.pol.grids.(s)';
+      else
+         out_ss.pol.grids.(s) = ss.pol.grids.(s);
+      end
+   end
+   % Check that the field `ss.pol.values` exists 
+   check_isfield('values', pol, 'ss.pol.values');
+   % Check that `ss.pol.values` is a struct
+   check_isstruct(pol.values, 'ss.pol.values');
+   % Check the missing and redundant variables in `ss.pol.values`
+   check_missingredundant(pol.values, 'ss.pol.values', pol_symbs, options_.hank.nowarningredundant);
+   % Check that `ss.pol.values` values are dense real matrices
+   check_fun(pol.values, 'ss.pol.values', pol_symbs, @(x) isnumeric(x) && isreal(x) && ismatrix(x) && ~issparse(x), 'are not dense real matrices'); 
+   % Check the internal size compatibility of `ss.pol.values`
+   sizes.n_pol = numel(pol_symbs);
+   check_fun(pol.values, 'ss.pol.values', pol_symbs, @(x) size(x,1), 'have a number of rows that is not consistent with the sizes of `ss.shocks.grids` elements', sizes.N_e);
+   check_fun(pol.values, 'ss.pol.values', pol_symbs, @(x) size(x,2), 'have a number of columns that is not consistent with the sizes of `ss.pol.grids` elements', sizes.pol.N_a);
+   % Copy `ss.pol.values` in `out_ss`
+   out_ss.pol.values = ss.pol.values;
+   % Check the permutation of state variables for policy functions
+   [out_ss.pol.states] = check_permutation(pol, 'states', 'ss.pol', state_symbs);
+   % Check the permutation of shock variables for policy functions
+   [out_ss.pol.shocks] = check_permutation(pol, 'shocks', 'ss.pol', shock_symbs);
+   %% Distribution
+   % Check that the field `ss.d` exists 
+   check_isfield('d', ss, 'ss.d');
+   d = ss.d;
+   % Check that the field `ss.d.hist` exists 
+   check_isfield('hist', ss.d, 'ss.d.hist');
+   % Check the type of `ss.d.hist`
+   if ~(ismatrix(d.hist) && isnumeric(d.hist) && isreal(d.hist) && ~issparse(d.hist))
+      error('Misspecified steady-state input `ss`: `ss.d.hist` is not a dense real matrix.');
+   end
+   % Check the consistency of `ss.d.grids` 
+   if ~isfield(d, 'grids')
+      if ~options_.hank.nowarningdgrids
+         warning('In the steady-state input `ss.d.grids`, no distribution-specific grid is set for states %s. The policy grids in `ss.pol.grids` shall be used.' , strjoin(state_symbs));
+      end
+      % Copy the relevant sizes from the pol field
+      sizes.d = sizes.pol;
+      out_ss.d.grids = out_ss.pol.grids;
+   else
+      % Check that `ss.d.grids` is a struct
+      check_isstruct(d.grids, 'ss.d.grids');
+      % Check redundant variables in `ss.d.grids`
+      d_grids_symbs = fieldnames(d.grids);
+      if isempty(d_grids_symbs)
+         if ~options_.hank.nowarningredundant
+            warning('In the steady-state input `ss.d.grids`, no distribution-specific grid is set for states %s. The policy grids in `ss.pol.grids` shall be used.' , strjoin(state_symbs));
+         end
+         % Copy the relevant sizes from the pol field
+         sizes.d = sizes.pol;
+         out_ss.d.grids = out_ss.pol.grids;
+      else
+         d_grids_symbs_in_states = ismember(d_grids_symbs, state_symbs);
+         if ~all(d_grids_symbs_in_states)
+            if ~options_.hank.nowarningredundant
+               warning('In the steady-state input `ss.d.states`, the following specification for the states grids in the distribution structure are not useful: %s', strjoin(d_grids_symbs(~d_grids_symbs_in_states)));
+            end
+            d_grids_symbs = d_grids_symbs(d_grids_symbs_in_states);
+         end
+         % Check the types of `ss.d.grids` elements
+         check_fun(pol.grids, 'ss.d.grids', d_grids_symbs, @(x) isnumeric(x) && isreal(x) && isvector(x) && ~issparse(x), 'are not dense real vectors');
+         % Store the size of the states grids for the distribution
+         for i=1:numel(d_grids_symbs)
+            s = d_grids_symbs{i};
+            sizes.d.states.(s) = numel(d.grids.(s));
+            out_ss.d.grids.(s) = d.grids.(s);
+         end
+         states_out_of_d = setdiff(state_symbs, d_grids_symbs);
+         if ~isempty(states_out_of_d)
+            if ~options_.hank.nowarningdgrids
+               warning('hank.bbeg.het_stoch_simul: in the steady-state structure, no distribution-specific grid set for states %s. The policy grids specified in pol.grids shall be used.', strjoin(states_out_of_d));
+            end
+            % Store the sizes of the unspecified states grids from the pol field
+            for i=1:numel(states_out_of_d)
+               s = states_out_of_d{i};
+               sizes.d.states.(s) = sizes.pol.states.(s);
+               out_ss.d.grids.(s) = pol.grids.(s);
+            end
+         end
+      end
+   end
+   % Check the internal size compatibility of the distribution histogram
+   if size(d.hist,1) ~= sizes.N_e
+      error('Misspecified steady-state input `ss`: the number of rows of the histogram matrix `ss.d.hist` is not consistent with the sizes of shocks grids `ss.shocks.grids`');
+   end
+   sizes.d.N_a = prod(structfun(@(x) x, sizes.d.states));
+   if size(d.hist,2) ~= sizes.d.N_a
+      error('Misspecified steady-state input `ss`: the number of columns of the histogram matrix `ss.d.hist` is not consistent with the sizes of states grids `ss.d.grids`/`ss.pol.grids`');
+   end
+   % Copy `ss.d.hist` in `out_ss` 
+   out_ss.d.hist = ss.d.hist;
+   % Check the permutation of state variables in the distribution
+   [out_ss.d.states] = check_permutation(d, 'states', 'ss.d', state_symbs);
+   % Check the permutation of shock variables in the distribution
+   [out_ss.d.shocks] = check_permutation(d, 'shocks', 'ss.d', shock_symbs);
+   %% Aggregate variables
+   % Check that the field `ss.agg` exists
+   check_isfield('agg', ss, 'ss.agg');
+   agg = ss.agg;
+   % Check that `ss.agg` is a structure
+   check_isstruct(agg, 'ss.agg');
+   % Check that the aggregate variables specification and the var statement are
+   % compatible
+   check_missingredundant(agg, 'ss.agg', agg_symbs, options_.hank.nowarningredundant);
+   % Store the number of aggregate variables
+   sizes.agg = numel(fieldnames(agg));
+   % Check the types of `ss.agg` values
+   check_fun(agg, 'ss.agg', agg_symbs, @(x) isreal(x) && isscalar(x), 'are not real scalars');
+   % Copy `ss.agg` into `out_ss`
+   out_ss.agg = agg;
+end

matlab/perfect-foresight-models/linear_approximation_accuracy.m → matlab/+hank/private/check_consistency.m

-function err = linear_approximation_accuracy(options_, M_, oo_)
-% Evaluates the accuracy of the linear approximation when solving perfect foresight models, by
-% reporting the max absolute value of the dynamic residuals.
-%
-% INPUTS
-% - options_ [struct] contains various options.
-% - M_       [struct] contains a description of the model.
-% - oo_      [struct] contains results.
-%
-% OUTPUTS
-% - err      [double] n*1 vector, evaluation of the accuracy (n is the number of equations).
-
-% Copyright © 2015-2017 Dynare Team
+% Copyright © 2025 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -26,30 +14,24 @@ function err = linear_approximation_accuracy(options_, M_, oo_)
 %
 % You should have received a copy of the GNU General Public License
 % along with Dynare.  If not, see <https://www.gnu.org/licenses/>.
-
-lead_lag_incidence = M_.lead_lag_incidence;
-
-ny = M_.endo_nbr;
-
-maximum_lag = M_.maximum_lag;
-
-periods = options_.periods;
-steady_state = oo_.steady_state;
-params = M_.params;
-endo_simul = oo_.endo_simul;
-exo_simul = oo_.exo_simul;
-
-model_dynamic = str2func([M_.fname,'.dynamic']);
-
-residuals = zeros(ny,periods);
-
-Y = endo_simul(:);
-
-i_cols = find(lead_lag_incidence')+(maximum_lag-1)*ny;
-
-for it = (maximum_lag+1):(maximum_lag+periods)
-    residuals(:,it-1) = model_dynamic(Y(i_cols), exo_simul, params, steady_state,it);
-    i_cols = i_cols + ny;
-end
-
-err = transpose(max(abs(transpose(residuals))));
\ No newline at end of file
+%
+% Check consistency between two sets of variable names.
+%
+% INPUTS
+% - f1 [cell array of strings]: list of variable names to be checked for consistency
+% - f2 [cell array of strings]: reference list of valid variable names
+% - f1_name [char]: name of the first set (for error messages)
+% - f2_name [char]: name of the second set (for error messages)
+%
+% OUTPUTS
+% - (none) This function throws an error if there are elements in `f1` that are not present in `f2`.
+%
+% DESCRIPTION
+% Checks that all elements of `f1` are included in `f2`. If not, throws a descriptive error 
+% mentioning the missing variables and the corresponding structure names for easier debugging.
+function [] = check_consistency(f1, f2, f1_name, f2_name)
+   f1_in_f2 = ismember(f1,f2);
+   if ~all(f1_in_f2)
+      error('Misspecified steady-state input `ss`: the following variables are mentioned in `%s`, but are missing in `%s`: %s', f1_name, f2_name, strjoin(f1(~f1_in_f2)));
+   end
+end
\ No newline at end of file