Release of Dynare 5.3

[sebastien]

We are pleased to announce the release of Dynare 5.3.

This maintenance release fixes various bugs.

The Windows, macOS and source packages are already available for download at the Dynare website.

All users are strongly encouraged to upgrade.

This release is compatible with MATLAB versions ranging from 8.3 (R2014a) to 9.13 (R2022b), and with GNU Octave version 7.3.0 (under Windows).

Note for macOS users with an Apple Silicon processor, and who are also MATLAB users: the official MATLAB version for use on those processors is still the Intel version (running through Rosetta 2), so the official Dynare package for download on our website is built for Intel only. However, since Mathworks has
released a beta version of MATLAB for Apple Silicon, we created a beta package of Dynare that you can try with it. See this forum thread for more details:

[Testers Wanted] Release of Dynare 5.5-beta and 6.0-beta for Apple Silicon (M1/M2 chips)

We now provide native pkg installers for the unstable version of Dynare and for Dynare 5.5. Thanks to all! [UPDATED!] Dear users, MATLAB has finally released an Apple Silicon version (R2023b), so we are preparing native Apple Silicon packages of Dynare. Currently, I am the only member of the team with an Apple Silicon machine and therefore I would like other uses with M1 or M2 machines to test the compiled pkg. For this you have to: Install MATLAB R2023b for Apple Silicon following the th…

Here is a list of the problems identified in version 5.2 and that have been
fixed in version 5.3:

• The notmpterms option of the dynare command would trigger a crash if the block option of the model block was used
• When the use_dll option was passed to the model block, the operator abs in the model block incorrectly returned only the integer part of the absolute value
• Problems with OccBin (estimation and occbin_solver):
  • the piecewise linear Kalman filter (PKF) could crash if the model solution could not be computed for a parameter draw
  • the piecewise linear Kalman filter (PKF) could crash mode finding if an error was encountered
  • the piecewise linear Kalman filter (PKF) would crash in the one-constraint case if the fixed point algorithm did not converge
  • the smoother could crash due to the initial states being empty and when encountering errors
  • the smoother fields of oo_ contained wrong results if the piecewise linear Kalman smoother did not converge
  • in pathological cases, seemingly periodic solutions were incorrectly accepted as true solutions
• Problems related to Bayesian or ML estimation:
  • mh_recover and load_mh_file would not find the saved proposal density and had to rely on the _mode file
  • When requesting bayesian_irf together with loglinear, the resulting IRFs would be incorrect
  • the diffuse Kalman smoother initialization (lik_init=3) was wrong when the state transition matrix contained a column of zeros
  • the diffuse Kalman smoother initialization (lik_init=3) was wrong when the shock covariance matrix was not diagonal
• Problems with perfect foresight simulations (perfect_foresight_solver command):
  • when solving purely forward or backward models with the PATH solver (solve_algo=10), specified mcp tags were ignored
  • the linear_approximation option would ignore the nocheck option for not checking the correctness of the steady state
  • in the presence of a steady state file or a steady_state_model block, the contents of the last initval or endval block would be ignored and replaced by a steady state
• The identification and dynare_sensitivity commands would not pass a graph_format option to other subsequent commands
• Problems with sensitivity analysis (dynare_sensitivity command)
  • stability mapping incorrectly imposed a parameter limit of 52
  • prior sampling did not work with when a user specified prior_trunc=0* dynare++: the dynare_simul.m would not run
• The model_diagnostics command would not work with block_trust_region algorithms (solve_algo=13,14)

As a reminder, the list of new features introduced in versions 5.x can be found in the release notes for
5.0.