Dynare 6.1 Released
Posted on 02 May 2024We are pleased to announce the release of Dynare 6.1.
This maintenance release fixes various bugs.
The Windows, macOS, MATLAB online and source packages are already available for download at the Dynare website.
This release is compatible with MATLAB versions ranging from 9.5 (R2018b) to 24.1 (R2024a), and with GNU Octave versions ranging from 7.1.0 to 9.1.0 (NB: the Windows package requires version 9.1.0 specifically).
Here is a list of the problems identified in version 6.0 and that have been fixed in version 6.1:
- Identification: simulated moments were triggered instead of theoretical ones
- Variance decompositions would crash with measurement errors when zero variance shocks were present
- The handling of Lagrange multipliers in the display of problems with the Jacobian was wrong
- The option
auxnamewas missing in the documentation of thepac_modelcommand - PAC equation estimation/simulation was crashing in the case of composite target
- The PAC equation estimation would crash if the PAC target was a transformed variable
- The
perfect_foresight_with_expectation_errors_solvercommand could return incorrect results when used in conjunction withhomotopy_linearization_fallbackorhomotopy_marginal_linearization_fallbackoptions - For scalar values, the description of the
horizonoption of thevar_expectation_modelcommand was incorrect - The steady state computation with the
bytecodeoption in a Ramsey model was broken - OccBin: the piecewise Kalman filter would crash in case of a periodic solution
- The
heteroskedastic_filteroption of theestimationcommand would cause a crash if there was only one shock - The
method_of_momentscommand would crash during the J-test for just and underidentified models - User-defined
warningsettings were internally overwritten with themethod_of_momentscommand or the piecewise Kalman filter - The SMC sampler would crash if any of the
bayesian_irf,moments_varendo, orsmootheroptions of theestimationcommand had been specified - The
bvar_irfcommand would ignore theSquareRootoption and instead employ a Cholesky decomposition - The univariate Kalman filter erroneously treated observations with negative prediction variances due to numerical issues as missing values instead of discarding the parameter draw
Moreover, a new homotopy_exclude_varexo option to the
perfect_foresight_solver command has been added, to exclude some exogenous
variables from the homotopy procedure (i.e. to keep them at their value
corresponding to 100% of the shock during all homotopy iterations).
As a reminder, the list of new features introduced in versions 6.x can be found in the release notes for 6.0.