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Announcement for Dynare 4.5.6 (on 2018-07-25)
=============================================

We are pleased to announce the release of Dynare 4.5.6.

This is a bugfix release.

The Windows packages are already available for download at:

 http://www.dynare.org/download/dynare-stable

The Mac and GNU/Linux packages (for Debian and Ubuntu LTS) should follow soon.

This release is compatible with MATLAB versions 7.5 (R2007b) to 9.3 (R2018a)
and with GNU Octave versions 4.4.

Here is a list of the problems identified in version 4.5.5 and that have been
fixed in version 4.5.6:

 - TaRB sampler: incorrect last posterior was returned if the last draw was
   rejected.

 - Fixed online particle filter by drawing initial conditions in the prior
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   distribution.

 - Fixed evaluation of the likelihood in non linear / particle filters.

 - Added missing documented `montecarlo` option in Gaussian Filter and
   Nonlinear Kalman Filter.

 - Added back a flag to deal with errors on Cholesky decomposition in the
   Conditional Particle Filter.

 - Macroprocessor `length()` operator was returning 1 when applied to a
   string. Macroprocessor now raises an error when `length()` operator is
   called on an integer and return the number of characters when applied to a
   string.

 - `mode_compute=8`: the error code during mode-finding was not correctly
   handled, resulting in crashes.

 - Identification was not correctly displaying a message for collinear parameters
   if there was no unidentified parameter present.



Announcement for Dynare 4.5.5 (on 2018-06-08)
=============================================

We are pleased to announce the release of Dynare 4.5.5.

This is a bugfix release.

The Windows packages are already available for download at:

 http://www.dynare.org/download/dynare-stable

The Mac and GNU/Linux packages (for Debian and Ubuntu LTS) should follow soon.

This release is compatible with MATLAB versions 7.5 (R2007b) to 9.3 (R2018a)
and with GNU Octave versions 4.2.

Here is a list of the problems identified in version 4.5.4 and that have been
fixed in version 4.5.5:

 - Identification was crashing during prior sampling if `ar` was initially too
   low.

 - The `align` method on `dseries` did not return a functional second `dseries`
   output.

 - Predetermined variables were not properly set when used in model local
   variables.

 - `perfect_foresight_solver` with option `stack_solve_algo=7` was not working
   correctly when an exogenous variable has a lag greater than 1.

 - `identification` with `prior_mc` option would crash if the number of moments
   with non-zero derivative is smaller than the number of parameters.

 - Calling several times `normcdf` or `normpdf` with the same arguments in a
   model with block decomposition (but not bytecode) was leading to incorrect
   results.



Announcement for Dynare 4.5.4 (on 2018-01-29)
=============================================

We are pleased to announce the release of Dynare 4.5.4.

This is a bugfix release.

The Windows packages are already available for download at:

 http://www.dynare.org/download/dynare-stable

The Mac and GNU/Linux packages (for Debian and Ubuntu LTS) should follow soon.

This release is compatible with MATLAB versions 7.5 (R2007b) to 9.3 (R2017b)
and with GNU Octave versions 4.2.

Here is a list of the problems identified in version 4.5.3 and that have been
fixed in version 4.5.4:

 - The `type` option of `plot_shock_decomposition` was always set to `qoq` regardless of what is specified.

 - Bug in GSA when no parameter was detected below pvalue threshold.

 - Various bug fixes in shock decompositions.

 - Bug in reading in macro arrays passed on `dynare` command line via the `-D` option.

 - Estimation with missing values was crashing if the `prefilter` option was used.

 - Added a workaround for a difference in behaviour between Octave and Matlab regarding the creation
   of function handles for functions that do not exist in the path. With Octave 4.2.1, steady state
   files did not work if no auxiliary variables were created.

 - The `stoch_simul` command was crashing with a cryptic message if option `order=3` was used without
   setting `k_order_solver`.

 - In cases where the prior bounds are infinite and the mode is estimated at exactly 0, no `mode_check`
   graphs were displayed.

 - Parallel execution of MCMC was broken in models without auxiliary variables.

 - Reading data with column names from Excel might crash.

 - The multivariate Kalman smoother was crashing in case of missing data in the observations and
   `Finf` became singular.

 - The `plot_shock_decomposition` command ignored various user-defined options like `fig_name`,
   `use_shock_groups` or `interactive` and instead used the default options.

 - Nested `@#ifdef` and `@#ifndef` statements don't work in the macroprocessor.



Announcement for Dynare 4.5.3 (on 2017-10-19)
=============================================

We are pleased to announce the release of Dynare 4.5.3.

This is a bugfix release. It comes less than 24 hours after the previous release,
because version 4.5.2 was affected by a critical bug for MATLAB older than R2016b.

The Windows packages are already available for download at:

 http://www.dynare.org/download/dynare-stable

The Mac and GNU/Linux packages (for Debian and Ubuntu LTS) should follow soon.

This release is compatible with MATLAB versions 7.5 (R2007b) to 9.3 (R2017b)
and with GNU Octave versions 4.2.

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Here is a list of the problems identified in version 4.5.2 and that have been
fixed in version 4.5.3:


 - `isfile` routine was failing with matlab older than R2016b. This bug did not
   affect Octave.



Announcement for Dynare 4.5.2 (on 2017-10-19)
=============================================

We are pleased to announce the release of Dynare 4.5.2.

This is a bugfix release.

The Windows packages are already available for download at:

 http://www.dynare.org/download/dynare-stable

The Mac and GNU/Linux packages (for Debian and Ubuntu LTS) should follow soon.

This release is compatible with MATLAB versions 7.5 (R2007b) to 9.3 (R2017b)
and with GNU Octave versions 4.2.

Here is a list of the problems identified in version 4.5.1 and that have been
fixed in version 4.5.2:


 - Fixed bug in perfect foresight solver:

   + If expected shocks were declared after the terminal period, as specified
   by the `periods` option, Dynare was crashing.

   + Models declared with the `linear` option were crashing if exogenous
   variables were present with a lead or lag.

 - After ML or Bayesian estimation when the smoother option or `mh_replic=0`
   were not specified, not all smoothed measurement errors were displayed.

 - Fixed error in reference manual about the `conditional_forecasts` command.

 - Fixed smoother behaviour, provide informative error instead of crashing when
   model cannot be solved.

 - The `nopathchange` preprocessor option was always triggered, regardless of
   whether it was passed or not.

 - When `ramsey_policy` is used, allow state variables to be set in `histval`
   block.

 - `histval` erroneously accepted leads, leading to cryptic crashes.

 - The prior MC draws from previous runs were not deleted, potentially
   resulting in loading stale files.

 - `estim_params_` was being declared `global` more than once.

 - Fixed crashes happening when simulating linear models with order>1.

 - Make empirical moments independent of `simul_replic`, as stated in the
   reference manual, by outputting moments computed with the first simulated
   sample.

 - The `prior_function` required a preceding `estimation`-command to properly
   set up the prior.

 - If the mode for a parameter was at exactly 0, `mode_check` was crashing.

 - Fixed `get_posterior_parameters`-routine which should not do more than
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   getting parameters. As a consequense, the `shock_decomposition`-command
   did not correctly set the `parameter_set` for use in subsequent function
   calls if shocks are correlated or measurement error is present.

 - Fixed bug in Ramsey problem with constraints both on a policy instrument and
   another variable. Note that the constraint on a variable that is not an
   instrument of the Ramsey problem must be written with an equation tag in the
   model block.
 - Fixed bug in Ramsey problem with constraints on policy instrument.

 - Fixed crash with optimizer 5 when not used with DSGE model at order 1.

 - Fixed mex file used for third order approximation (was crashing on
   Matlab/Windows 7).



Announcement for Dynare 4.5.1 (on 2017-08-24)
=============================================

We are pleased to announce the release of Dynare 4.5.1.

This is a bugfix release.

The Windows packages are already available for download at:

 http://www.dynare.org/download/dynare-stable

The Mac and GNU/Linux packages (for Debian and Ubuntu LTS) should follow soon.

This release is compatible with MATLAB versions 7.5 (R2007b) to 9.2 (R2017a)
and with GNU Octave versions 4.2.

Here is a list of the problems identified in version 4.5.0 and that have been
fixed in version 4.5.1:


 - Fixed out of memory issue with simpsa optimization algorithm.

 - Added missing plots for measurement errors with `generate_trace_plot`
   command.

 - Posterior moments after MCMC for very big models were not correctly computed
   and their plotting might crash Dynare.

 - Results of the posterior conditional variance decomposition after MCMC were
   not correctly computed.

 - Options `use_shock_groups` and `colormap` of the `shock_decomposition`
   command were not working.

 - Added a clean error message if sensitivity toolbox is used with recursive
   estimation.

 - Computation of posterior filtered variables was crashing in models with only
   one variable.

 - Fixed various typos and errors in the reference manual.



Announcement for Dynare 4.5.0 (on 2017-06-11)
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=============================================

We are pleased to announce the release of Dynare 4.5.0.

This major release adds new features and fixes various bugs.

The Windows packages are already available for download at:

 http://www.dynare.org/download/dynare-stable

The Mac and Debian/Ubuntu packages should follow soon.

All users are strongly encouraged to upgrade.

This release is compatible with MATLAB versions ranging from 7.5 (R2007b) to
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9.2 (R2017a) and with GNU Octave version 4.2.

Here is the list of major user-visible changes:


 - Ramsey policy

   + Added command `ramsey_model` that builds the expanded model with
     FOC conditions for the planner's problem but doesn't perform any
     computation. Usefull to compute Ramsey policy in a perfect
     foresight model,
   + `ramsey_policy` accepts multipliers in its variable list and
     displays results for them.
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 - Perfect foresight models

   + New commands `perfect_foresight_setup` (for preparing the
     simulation) and `perfect_foresight_solver` (for computing it). The
     old `simul` command still exist and is now an alias for
     `perfect_foresight_setup` + `perfect_foresight_solver`. It is no
     longer possible to manipulate by hand the contents of
     `oo_.exo_simul` when using `simul`. People who want to do
     it must first call `perfect_foresight_setup`, then do the
     manipulations, then call `perfect_foresight_solver`,
   + By default, the perfect foresight solver will try a homotopy
     method if it fails to converge at the first try. The old behavior
     can be restored with the `no_homotopy` option,
   + New option `stack_solve_algo=7` that allows specifying a
     `solve_algo` solver for solving the model,
   + New option `solve_algo` that allows specifying a solver for
     solving the model when using `stack_solve_algo=7`,
   + New option `lmmcp` that solves the model via a Levenberg-Marquardt
     mixed complementarity problem (LMMCP) solver,
   + New option `robust_lin_solve` that triggers the use of a robust
     linear solver for the default `solve_algo=4`,
   + New options `tolf` and `tolx` to control termination criteria of
     solvers,
   + New option `endogenous_terminal_period` to `simul`,
   + Added the possibility to set the initial condition of the
     (stochastic) extended path simulations with the histval block.
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 - Optimal simple rules

   + Saves the optimal value of parameters to `oo_.osr.optim_params`,
   + New block `osr_params_bounds` allows specifying bounds for the
     estimated parameters,
   + New option `opt_algo` allows selecting different optimizers while
     the new option `optim` allows specifying the optimizer options,
   + The `osr` command now saves the names, bounds, and indices for the
     estimated parameters as well as the indices and weights of the
     variables entering the objective function into `M_.osr`.
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 - Forecasts and Smoothing

   + The smoother and forecasts take uncertainty about trends and means
     into account,
   + Forecasts accounting for measurement error are now saved in fields
     of the form `HPDinf_ME` and `HPDsup_ME`,
   + New fields `oo_.Smoother.Trend` and `oo_.Smoother.Constant` that
     save the trend and constant parts of the smoothed variables,
   + new field `oo_.Smoother.TrendCoeffs` that stores the trend
     coefficients.
   + Rolling window forecasts allowed in `estimation` command by
     passing a vector to `first_obs`,
   + The `calib_smoother` command now accepts the `loglinear`,
     `prefilter`, `first_obs` and `filter_decomposition` options.
   + New options: `logdata`, `consider_all_endogenous`,
     `consider_only_observed`, `posterior_max_subsample_draws`,
     `mh_conf_sig`, `diffuse_kalman_tol`, `dirname`, `nodecomposition`
   + `load_mh_file` and `mh_recover` now try to load chain's proposal density,
   + New option `load_results_after_load_mh` that allows loading some
     posterior results from a previous run if no new MCMC draws are
     added,
   + New option `posterior_nograph` that suppresses the generation of
     graphs associated with Bayesian IRFs, posterior smoothed objects,
     and posterior forecasts,
   + Saves the posterior density at the mode in
     `oo_.posterior.optimization.log_density`,
   + The `filter_covariance` option now also works with posterior
     sampling like Metropolis-Hastings,
   + New option `no_posterior_kernel_density` to suppress computation
     of kernel density of posterior objects,
   + Recursive estimation and forecasting now provides the individual
     `oo_` structures for each sample in `oo_recursive_`,
   + The `trace_plot` command can now plot the posterior density,
   + New command `generate_trace_plots` allows generating all trace
     plots for one chain,
   + New commands `prior_function` and `posterior_function` that
     execute a user-defined function on parameter draws from the
     prior/posterior distribution,
   + New option `huge_number` for replacement of infinite bounds with
     large number during `mode_compute`,
   + New option `posterior_sampling_method` allows selecting the new
     posterior sampling options:
     `tailored_random_block_metropolis_hastings` (Tailored randomized
     block (TaRB) Metropolis-Hastings), `slice` (Slice sampler),
     `independent_metropolis_hastings` (Independent
     Metropolis-Hastings),
   + New option `posterior_sampler_options` that allow controlling the
     options of the `posterior_sampling_method`, its `scale_file`-option
     pair allows loading the `_mh_scale.mat`-file storing the tuned
     scale factor from a previous run of `mode_compute=6`,
   + New option `raftery_lewis_diagnostics` that computes Raftery/Lewis
     (1992) convergence diagnostics,
   + New option `fast_kalman_filter` that provides fast Kalman filter
     using Chandrasekhar recursions as described in Ed Herbst (2015),
   + The `dsge_var` option now saves results at the posterior mode into
     `oo_.dsge_var`,
   + New option `smoothed_state_uncertainty` to provide the uncertainty
     estimate for the smoothed state estimate from the Kalman smoother,
   + New prior density: generalized Weibull distribution,
   + Option `mh_recover` now allows continuing a crashed chain at the
     last save mh-file,
   + New option `nonlinear_filter_initialization` for the
     `estimation` command. Controls the initial covariance matrix
     of the state variables in nonlinear filters.
   + The `conditional_variance_decomposition` option now displays
     output and stores it as a LaTeX-table when the `TeX` option is
     invoked,
   + The `use_calibration` to `estimated_params_init` now also works
     with ML,
   + Improved initial estimation checks.
   + The default solver for finding the steady state is now a
     trust-region solver (can be triggered explicitly with option
     `solve_algo=4`),
   + New options `tolf` and `tolx` to control termination criteria of
     solver,
   + The debugging mode now provides the termination values in steady
     state finding.
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 - Stochastic simulations

   + New options `nodecomposition`,
   + New option `bandpass_filter` to compute bandpass-filtered
     theoretical and simulated moments,
   + New option `one_sided_hp_filter` to compute one-sided HP-filtered
     simulated moments,
   + `stoch_simul` displays a simulated variance decomposition when
     simulated moments are requested,
   + `stoch_simul` saves skewness and kurtosis into respective fields
     of `oo_` when simulated moments have been requested,
   + `stoch_simul` saves the unconditional variance decomposition in
     `oo_.variance_decomposition`,
   + New option `dr_display_tol` that governs omission of small terms
     in display of decision rules,
   + The `stoch_simul` command now prints the displayed tables as LaTeX
     code when the new `TeX` option is enabled,
   + The `loglinear` option now works with lagged and leaded exogenous
     variables like news shocks,
   + New option `spectral_density` that allows displaying the spectral
     density of (filtered) endogenous variables,
   + New option `contemporaneous_correlation` that allows saving
     contemporaneous correlations in addition to the covariances.
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 - Identification

   + New options `diffuse_filter` and `prior_trunc`,
   + The `identification` command now supports correlations via
     simulated moments,
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 - Sensitivity analysis

   + New blocks `irf_calibration` and `moment_calibration`,
   + Outputs LaTeX tables if the new `TeX` option is used,
   + New option `relative_irf` to `irf_calibration` block.
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 - Conditional forecast

   + Command `conditional_forecast` now takes into account `histval`
     block if present.
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 - Shock decomposition

   + New option `colormap` to `shocks_decomposition` for controlling
     the color map used in the shocks decomposition graphs,
   + `shocks_decomposition` now accepts the `nograph` option,
   + New command `realtime_shock_decomposition` that for each period `T= [presample,...,nobs]`
     allows computing the:
     * realtime historical shock decomposition `Y(t|T)`, i.e. without observing data in `[T+1,...,nobs]`
     * forecast shock decomposition `Y(T+k|T)`
     * realtime conditional shock decomposition `Y(T+k|T+k)-Y(T+k|T)`

   + New block `shock_groups` that allows grouping shocks for the
     `shock_decomposition` and `realtime_shock_decomposition` commands,

   + New command `plot_shock_decomposition` that allows plotting the
     results from `shock_decomposition` and
     `realtime_shock_decomposition` for different vintages and shock
     groupings.
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 - Macroprocessor

   + Can now pass a macro-variable to the `@#include` macro directive,
   + New preprocessor flag `-I`, macro directive `@#includepath`, and
     dynare config file block `[paths]` to pass a search path to the
     macroprocessor to be used for file inclusion via `@#include`.
   + New option `onlyclearglobals` (do not clear JIT compiled functions
     with recent versions of Matlab),
   + New option `minimal_workspace` to use fewer variables in the
     current workspace,
   + New option `params_derivs_order` allows limiting the order of the
     derivatives with respect to the parameters that are calculated by
     the preprocessor,
   + New command line option `mingw` to support the MinGW-w64 C/C++
     Compiler from TDM-GCC for `use_dll`.
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 - dates/dseries/reporting classes

   + New methods `abs`, `cumprod` and `chain`,
   + New option `tableRowIndent` to `addTable`,
   + Reporting system revamped and made more efficient, dependency on
     matlab2tikz has been dropped.
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 - Optimization algorithms

   + `mode_compute=2` Uses the simulated annealing as described by
     Corana et al. (1987),
   + `mode_compute=101` Uses SOLVEOPT as described by Kuntsevich and
     Kappel (1997),
   + `mode_compute=102` Uses `simulannealbnd` from Matlab's Global
     Optimization Toolbox (if available),
   + New option `silent_optimizer` to shut off output from mode
     computing/optimization,
   + New options `verbosity` and `SaveFiles` to control output and
     saving of files during mode computing/optimization.
   + New command `write_latex_original_model`,
   + New option `write_equation_tags` to `write_latex_dynamic_model`
     that allows printing the specified equation tags to the generate
     LaTeX code,
   + New command `write_latex_parameter_table` that writes the names and
     values of model parameters to a LaTeX table,
   + New command `write_latex_prior_table` that writes the descriptive
     statistics about the prior distribution to a LaTeX table,
   + New command `collect_latex_files` that creates one compilable LaTeX
     file containing all TeX-output.
   + Provides 64bit preprocessor,
   + Introduces new path management to avoid conflicts with other
     toolboxes,
   + Full compatibility with Matlab 2014b's new graphic interface,
   + When using `model(linear)`, Dynare automatically checks
     whether the model is truly linear,
   + `usedll`, the `msvc` option now supports `normcdf`, `acosh`,
     `asinh`, and `atanh`,
   + New parallel option `NumberOfThreadsPerJob` for Windows nodes that
     sets the number of threads assigned to each remote MATLAB/Octave
     run,
   + Improved numerical performance of
     `schur_statespace_transformation` for very large models,
   + The `all_values_required` option now also works with `histval`,
   + Add missing `horizon` option to `ms_forecast`,
   + BVAR now saves the marginal data density in
     `oo_.bvar.log_marginal_data_density` and stores prior and
     posterior information in `oo_.bvar.prior` and
     `oo_.bvar.posterior`.
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* Bugs and problems identified in version 4.4.3 and that have been fixed in version 4.5.0:


 - BVAR models

   + `bvar_irf` could display IRFs in an unreadable way when they moved from
     negative to positive values,
   + In contrast to what is stated in the documentation, the confidence interval
     size `conf_sig` was 0.6 by default instead of 0.9.
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 - Conditional forecasts

   + The `conditional_forecast` command produced wrong results in calibrated
     models when used at initial values outside of the steady state (given with
     `initval`),
   + The `plot_conditional_forecast` option could produce unreadable figures if
     the areas overlap,
   + The `conditional_forecast` command after MLE crashed,
   + In contrast to what is stated in the manual, the confidence interval size
     `conf_sig` was 0.6 by default instead of 0.8.
   + Conditional forecasts were wrong when the declaration of endogenous
     variables was not preceeding the declaration of the exogenous
     variables and parameters.
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 - Discretionary policy

   + Dynare allowed running models where the number of instruments did not match
     the number of omitted equations,
   + Dynare could crash in some cases when trying to display the solution,
   + Parameter dependence embedded via a `steady_state` was not taken into
     account, typically resulting in crashes.
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 - dseries class

   + When subtracting a dseries object from a number, the number was instead
     subtracted from the dseries object.
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 - DSGE-VAR models

   + Dynare crashed when estimation encountered non-finite values in the Jacobian
     at the steady state,
   + The presence of a constant was not considered for degrees of freedom
     computation of the Gamma function used during the posterior computation; due
     to only affecting the constant term, results should be be unaffected, except
     for model_comparison when comparing models with and without.
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 - Estimation command

   + In contrast to what was stated in the manual, the confidence interval size
     `conf_sig` for `forecast` without MCMC was 0.6 by default instead of 0.9,
   + Calling estimation after identification could lead to crashes,
   + When using recursive estimation/forecasting and setting some elements of
     `nobs` to be larger than the number of observations T in the data,
     `oo_recursive_` contained additional cell entries that simply repeated the
     results obtained for `oo_recursive_T`,
   + Computation of Bayesian smoother could crash for larger models when
     requesting `forecast` or `filtered_variables`,
   + Geweke convergence diagnostics were not computed on the full MCMC chain when
     the `load_mh_file` option was used,
   + The Geweke convergence diagnostics always used the default `taper_steps` and
   `geweke_interval`,
   + Bayesian IRFs (`bayesian_irfs` option) could be displayed in an unreadable
     way when they move from negative to positive values,
   + If `bayesian_irfs` was requested when `mh_replic` was too low to compute
     HPDIs, plotting was crashing,
   + The x-axis value in `oo_.prior_density` for the standard deviation and
     correlation of measurement errors was written into a field
     `mearsurement_errors_*` instead of `measurement_errors_*`,
   + Using a user-defined `mode_compute` crashed estimation,
   + Option `mode_compute=10` did not work with infinite prior bounds,
   + The posterior variances and covariances computed by `moments_varendo` were
     wrong for very large models due to a matrix erroneously being filled up with
     zeros,
   + Using the `forecast` option with `loglinear` erroneously added the unlogged
     steady state,
   + When using the `loglinear` option the check for the presence of a constant
     was erroneously based on the unlogged steady state,
   + Estimation of `observation_trends` was broken as the trends specified as a
     function of deep parameters were not correctly updated during estimation,
   + When using `analytic_derivation`, the parameter values were not set before
     testing whether the steady state file changes parameter values, leading to
     subsequent crashes,
   + If the steady state of an initial parameterization did not solve, the
     observation equation could erroneously feature no constant when the
     `use_calibration` option was used,
   + When computing posterior moments, Dynare falsely displayed that moment
     computations are skipped, although the computation was performed correctly,
   + If `conditional_variance_decomposition` was requested, although all
     variables contain unit roots, Dynare crashed instead of providing an error
     message,
   + Computation of the posterior parameter distribution was erroneously based
     on more draws than specified (there was one additional draw for every Markov
     chain),
   + The estimation option `lyapunov=fixed_point` was broken,
   + Computation of `filtered_vars` with only one requested step crashed Dynare,
   + Option `kalman_algo=3` was broken with non-diagonal measurement error,
   + When using the diffuse Kalman filter with missing observations, an additive
     factor log(2*pi) was missing in the last iteration step,
   + Passing of the `MaxFunEvals` and `InitialSimplexSize` options to
     `mode_compute=8` was broken,
   + Bayesian forecasts contained initial conditions and had the wrong length in
     both plots and stored variables,
   + Filtered variables obtained with `mh_replic=0`, ML, or
     `calibrated_smoother` were padded with zeros at the beginning and end and
     had the wrong length in stored variables,
   + Computation of smoothed measurement errors in Bayesian estimation was broken,
   + The `selected_variables_only` option (`mh_replic=0`, ML, or
     `calibrated_smoother`) returned wrong results for smoothed, updated, and
     filtered variables,
   + Combining the `selected_variables_only` option with forecasts obtained
     using `mh_replic=0`, ML, or `calibrated_smoother` leaded to crashes,
   + `oo_.UpdatedVariables` was only filled when the `filtered_vars` option was specified,
   + When using Bayesian estimation with `filtered_vars`, but without
     `smoother`, then `oo_.FilteredVariables` erroneously also contained filtered
     variables at the posterior mean as with `mh_replic=0`,
   + Running an MCMC a second time in the same folder with a different number of
     iterations could result in crashes due to the loading of stale files,
   + Results displayed after Bayesian estimation when not specifying
     the `smoother` option were based on the parameters at the mode
     from mode finding instead of the mean parameters from the
     posterior draws. This affected the smoother results displayed, but
     also calls to subsequent command relying on the parameters stored
     in `M_.params` like `stoch_simul`,
   + The content of `oo_.posterior_std` after Bayesian estimation was based on
     the standard deviation at the posterior mode, not the one from the MCMC, this
     was not consistent with the reference manual,
   + When the initialization of an MCMC run failed, the metropolis.log file was
     locked, requiring a restart of Matlab to restart estimation,
   + If the posterior mode was right at the corner of the prior bounds, the
     initialization of the MCMC erroneously crashed,
   + If the number of dropped draws via `mh_drop` coincided with the number of
     draws in a `_mh'-file`, `oo_.posterior.metropolis.mean` and
     `oo_.posterior.metropolis.Variance` were NaN.
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 - Estimation and calibrated smoother

   + When using `observation_trends` with the `prefilter` option, the mean shift
     due to the trend was not accounted for,
   + When using `first_obs`>1, the higher trend starting point of
     `observation_trends` was not taken into account, leading, among other things,
     to problems in recursive forecasting,
   + The diffuse Kalman smoother was crashing if the forecast error variance
     matrix becomes singular,
   + The multivariate Kalman smoother provided incorrect state estimates when
     all data for one observation are missing,
   + The multivariate diffuse Kalman smoother provided incorrect state estimates
     when the `Finf` matrix becomes singular,
   + The univariate diffuse Kalman filter was crashing if the initial covariance
     matrix of the nonstationary state vector is singular,
   + In contrast to what is stated in the manual, the confidence interval size
     `conf_sig` was 0.6 by default instead of 0.9.
   + Forecasting with exogenous deterministic variables provided wrong decision
     rules, yielding wrong forecasts.
   + Forecasting with exogenous deterministic variables crashed when the
     `periods` option was not explicitly specified,
   + Option `forecast` when used with `initval` was using the initial values in
     the `initval` block and not the steady state computed from these initial
     values as the starting point of forecasts.
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 - Global Sensitivity Analysis

   + Sensitivity with ML estimation could result in crashes,
   + Option `mc` must be forced if `neighborhood_width` is used,
   + Fixed dimension of `stock_logpo` and `stock_ys`,
   + Incomplete variable initialization could lead to crashes with `prior_range=1`.
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 - Indentification

   + Identification did not correctly pass the `lik_init` option,
     requiring the manual setting of `options_.diffuse_filter=1` in
     case of unit roots,
   + Testing identification of standard deviations as the only
     parameters to be estimated with ML leaded to crashes,
   + Automatic increase of the lag number for autocovariances when the
     number of parameters is bigger than the number of non-zero moments
     was broken,
   + When using ML, the asymptotic Hessian was not computed,
   + Checking for singular values when the eigenvectors contained only
     one column did not work correctly,
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 - Model comparison

   + Selection of the `modifiedharmonicmean` estimator was broken,
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 - Optimal Simple Rules

   + When covariances were specified, variables that only entered with
     their variance and no covariance term obtained a wrong weight,
     resulting in wrong results,
   + Results reported for stochastic simulations after `osr` were based
     on the last parameter vector encountered during optimization,
     which does not necessarily coincide with the optimal parameter
     vector,
   + Using only one (co)variance in the objective function resulted in crashes,
   + For models with non-stationary variables the objective function was computed wrongly.
   + If a Lagrange multiplier appeared in the model with a lead or a lag
     of more than one period, the steady state could be wrong.
   + When using an external steady state file, incorrect steady states
     could be accepted,
   + When using an external steady state file with more than one
     instrument, Dynare crashed,
   + When using an external steady state file and running `stoch_simul`
     after `ramsey_planner`, an incorrect steady state was used,
   + When the number of instruments was not equal to the number of
     omitted equations, Dynare crashed with a cryptic message,
   + The `planner_objective` accepted `varexo`, but ignored them for computations,
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 - Shock decomposition

   + Did not work with the `parameter_set=calibration` option if an
     `estimated_params` block is present,
   + Crashed after MLE.
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 - Perfect foresight models

   + The perfect foresight solver could accept a complex solution
     instead of continuing to look for a real-valued one,
   + The `initval_file` command only accepted column and not row vectors,
   + The `initval_file` command did not work with Excel files,
   + Deterministic simulations with one boundary condition crashed in
     `solve_one_boundary` due to a missing underscore when passing
     `options_.simul.maxit`,
   + Deterministic simulation with exogenous variables lagged by more
     than one period crashed,
   + Termination criterion `maxit` was hard-coded for `solve_algo=0`
     and could no be changed,
   + When using `block`/`bytecode`, relational operators could not be enforced,
   + When using `block` some exceptions were not properly handled,
     leading to code crashes,