Congratulations to the team for this major release full of new
features!
See you tomorrow for those who will be at the Summer School,
Le dimanche 11 juin 2017 à 00:58 +0200, Stéphane Adjemian a écrit :
> Dear Dynare users and friends,
>
> 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 7.3
> (R2006b) to 9.2 (R2017a) and with GNU Octave version 4.2.1.
>
>
> 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,
>
> + Checking for singular values when the eigenvectors contained
> only
> one column did not work correctly,
>
>
> - Model comparison
>
> + Selection of the `modifiedharmonicmean` estimator was broken,
>
>
> - 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.
>
>
> - Ramsey policy
>
> + 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,
>
>
> - Shock decomposition
>
> + Did not work with the `parameter_set=calibration` option if an
> `estimated_params` block is present,
>
> + Crashed after MLE.
>
>
> - 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,
>
> + Using `periods=1` crashed the solver (bug only partially fixed).
>
>
> - Smoothing
>
> + The univariate Kalman smoother returned wrong results when used
> with correlated measurement error,
>
> + The diffuse smoother sometimes returned linear combinations of
> the
> smoothed stochastic trend estimates instead of the original
> trend
> estimates.
>
> - Perturbation reduced form
>
> + In contrast to what is stated in the manual, the results of the
> unconditional variance decomposition were only stored in
> `oo_.gamma_y(nar+2)`, not in `oo_.variance_decomposition`,
>
> + Dynare could crash when the steady state could not be computed
> when using the `loglinear` option,
>
> + Using `bytcode` when declared exogenous variables were not
> used in the model leaded to crashes in stochastic simulations,
>
> + Displaying decision rules involving lags of auxiliary variables
> of
> type 0 (leads>1) crashed.
>
> + The `relative_irf` option resulted in wrong output at `order>1`
> as
> it implicitly relies on linearity.
>
>
> - Displaying of the MH-history with the `internals` command crashed
> if parameter names did not have same length.
>
> - Dynare crashed when the user-defined steady state file returned an
> error code, but not an conformable-sized steady state vector.
>
> - Due to a bug in `mjdgges.mex` unstable parameter draws with
> eigenvalues up to 1+1e-6 could be accepted as stable for the
> purpose of the Blanchard-Kahn conditions, even if
> `qz_criterium<1`.
>
> - The `use_dll` option on Octave for Windows required to pass a
> compiler flag at the command line, despite the manual stating this
> was not necessary.
>
> - Dynare crashed for models with `block` option if the Blanchard-
> Kahn
> conditions were not satisfied instead of generating an error
> message.
>
> - The `verbose` option did not work with `model(block)`.
>
> - When falsely specifying the `model(linear)` for nonlinear models,
> incorrect steady states were accepted instead of aborting.
>
> - The `STEADY_STATE` operator called on model local variables
> (so-called pound variables) did not work as expected.
>
> - The substring operator in macro-processor was broken. The
> characters of the substring could be mixed with random characters
> from the memory space.
>
> - Block decomposition could sometimes cause the preprocessor to
> crash.
>
> - A bug when external functions were used in model local variables
> that were contained in equations that required auxiliary
> variable/equations led to crashes of Matlab.
>
> - Sampling from the prior distribution for an inverse gamma II
> distribution when `prior_trunc>0` could result in incorrect
> sampling.
>
> - Sampling from the prior distribution for a uniform distribution
> when `prior_trunc>0` was ignoring the prior truncation.
>
> - Conditional forecasts were wrong when the declaration of
> endogenous
> variables was not preceeding the declaration of the exogenous
> variables and parameters.
>
>
> On behalf of the Dynare Team,
> Stéphane.
>
>
--
Sébastien Villemot
Économiste
Sciences Po, OFCE