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Announcement for Dynare 4.5.7 (on 2019-02-06)
=============================================
We are pleased to announce the release of Dynare 4.5.7.
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 9.4 (R2018b)
and with GNU Octave versions 4.4.1.
Here is a list of the problems identified in version 4.5.6 and that have been
fixed in version 4.5.7:
- The mex-file conducting the QZ decomposition erroneously applied
the `qz_criterium` to the square absolute value of eigenvalues
instead of the absolute value itself (as done in mjdgges.m and the
AIM solver).
- In pathological cases, `mode_compute=5` (`newrat`) might enter an
infinite loop.
- `discretionary_policy` might erroneously state that the derivatives
of the objective function are non-zero if there are NaN present.
- Dynare++, when conducting the QZ decomposition, erroneously applied
the `qz_criterium` to the square absolute value of eigenvalues
instead of the absolute value itself.
- Dynare++: IRFs were incorrectly computed.
- `dynare_sensitivity` did not display the figures of
`irf_calibration`, it only stored them on the disk.
- Scatter plots generated by `dynare_sensitivity` did not correctly
display LaTeX names.
- Parameter updating via steady state files did not correctly work in
case of using [static]/[dynamic] equation tags.
- Memory leaks in `k_order_pert` (used by higher order stochastic
simulations) could lead to crashes.
- Predetermined variables were not properly set when used in model
local variables.
- Posterior moment computation did not correctly update the
covariance matrix of exogenous shocks during posterior sampling.
- Dynare was crashing with a cryptic message if a non estimated
parameter was initialized in the `estimated_params_init` block.
- The `forecast` command crashed if the model was declared as linear
and contained deterministic exogenous variables.
- Block decomposition is broken when used in conjunction with
`varexo_det`.
- The model was not correctly specified when `identification` was run
without another stochastic command in the `.mod` file
(e.g. `estimation`, `stoch_simul`, etc.).
- Realtime annualized shock decompositions added the wrong steady state
value.
- `mh_recover` option crashed when using slice sampler.
- x-axis values in plots of moment restrictions were wrong for
autocovariances.
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 9.4 (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
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 9.4 (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.
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
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)
=============================================
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
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.
- 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.
- 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`.
- 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.
- Estimation
+ 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.
- Steady state
+ 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.
- 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.
- Identification
+ New options `diffuse_filter` and `prior_trunc`,
+ The `identification` command now supports correlations via
simulated moments,
- 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.
- Conditional forecast
+ Command `conditional_forecast` now takes into account `histval`
block if present.
- 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.
- 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`.
- Command line
+ 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`.
- 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.
- 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.
- LaTeX output
+ 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.
- Misc.
+ 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`.
* 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.
- 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.
- 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.
- dseries class
+ When subtracting a dseries object from a number, the number was instead
subtracted from the dseries object.
- 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.
- 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.
- 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,
- Forecats
+ 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.
- 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`.
- 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,