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.