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Release announcement for 5.0

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Announcement for Dynare 5.0 (on 2022-01-07)
===========================================
We are pleased to announce the release of Dynare 5.0.
This major release adds new features and fixes various bugs.
The Windows, macOS and source packages are already available for download at
[the Dynare website](https://www.dynare.org/download/).
All users are strongly encouraged to upgrade.
This release is compatible with MATLAB versions ranging from 8.3 (R2014a) to
9.11 (R2021b), and with GNU Octave version 6.4.0 (under Windows).
The new tools for semi-structural models and the improvements on the nonlinear
solvers were funded by the ECB. Special thanks to Nikola Bokan (ECB) for his
contributions and numerous bug reports and fixes.
Major user-visible changes
--------------------------
- New routines for simulating semi-structural (backward) models where
some equations incorporate expectations based on future values of a VAR or
trend component model. See the `var_model`, `trend_component_model` and
`var_expectation_model` commands, and the `var_expectation` operator.
- New routines for simulating semi-structural models where some equations are
specified using the polynomial adjustment costs (PAC) approach, as in the
FRB/US model (see Brayton et al., 2014 and Brayton et al., 2000) and the
ECB-BASE model (see Angelini et al., 2019). The forward-looking terms of the
PAC equations can be computed either using a satellite VAR model, or using
full model-consistent expectations. See the `pac_model` command and the
`pac_expectation` operator.
- New Method of Moments toolbox that provides functionality to estimate
parameters by (i) Generalized Method of Moments (GMM) up to 3rd-order pruned
perturbation approximation or (ii) Simulated Method of Moments (SMM) up to
any perturbation approximation order. The toolbox is inspired by replication
codes accompanied to Andreasen et al. (2018), Born and Pfeifer (2014), and
Mutschler (2018). It is accessible via the new `method_of_moments` command
and the new `matched_moments` block. Moreover, by default, a new non-linear
least squares optimizer based on `lsqnonlin` is used for minimizing the
method of moments objective function (available under `mode_compute=13`).
GMM can further benefit from using Gradient-based optimizers (using
`analytic_standard_errors` option and/or passing `'Jacobian','on'` to the
optimization options) as the Jacobian of the moment conditions can be
computed analytically.
- Implementation of the Occbin algorithm by Guerrieri and Iacoviello (2015),
together with the inversion filter of Cuba-Borda, Guerrieri, Iacoviello, and
Zhong (2019) and the piecewise Kalman filter of Giovannini, Pfeiffer, and
Ratto (2021). It is available via the new block `occbin_constraints` and the
new commands `occbin_setup`, `occbin_solver`, `occbin_graph` and
`occbin_write_regimes`.
- Stochastic simulations
- `stoch_simul` now supports theoretical moments at `order=3` with
`pruning`.
- `stoch_simul` now reports second moments based on the pruned state space
if the `pruning` option is set (in previous Dynare releases it would
report a second-order accurate result based on the linear solution).
- Estimation
- Performance optimization to pruned state space system and Lyapunov
solvers.
- New option `mh_posterior_mode_estimation` to `estimation` to perform
mode-finding by running the MCMC.
- New heteroskedastic filter and smoother, where shocks standard error may
*unexpectedly* change in every period. Triggered by
`heteroskedastic_filter` option of the `estimation` command, and
configured via the `heteroskedastic_shocks` block.
- New option `mh_tune_guess` for setting the initial value for
`mh_tune_jscale`.
- New option `smoother_redux` to `estimation` and `calib_smoother` to
trigger computing the Kalman smoother on a restricted state space instead
of the full one.
- New block `filter_initial_state` for setting the initial condition of the
Kalman filter/smoother.
- New option `mh_initialize_from_previous_mcmc` to the `estimation` command
that allows to pick initial values for a new MCMC from a previous one.
- The `xls_sheet` option of the `estimation` command now takes a quoted
string as value. The former unquoted syntax is still accepted, but no
longer recommended.
- New option `particle_filter_options` to set various particle filter options
- Perfect foresight and extended path
- New specialized algorithm in `perfect_foresight_solver` to deal with
purely static problems.
- The `debug` option of `perfect_foresight_solver` provides debugging
information if the Jacobian is singular.
- In deterministic models (perfect foresight or extended path), exogenous
variables with lead/lags are now replaced by auxiliary variables. This
brings those models in line with the transformation done on stochastic
models. However note that transformation is still not exactly the same
between the two classes of models, because there is no need to take into
account the Jensen inequality on the latter. In deterministic models,
there is a one-to-one mapping between exogenous with lead/lags and
auxiliaries, while in stochastic models, an auxiliary endogenous may
correspond to a more complex nonlinear expression.
- Optimal policy
- Several improvements to `evaluate_planner_objective`:
- it now applies a consistent approximation order when doing the
computation;
- in addition to the conditional welfare, it now also provides the
unconditional welfare;
- in a stochastic context, it now works with higher order approximation
(only the conditional welfare is available for order ⩾ 3);
- it now also works in a perfect foresight context.
- `discretionary_policy` is now able to solve nonlinear models (it will
then use their first-order approximation, and the analytical steady state
must be provided).
- Identification
- New option `schur_vec_tol` to the `identification` command, for setting
the tolerance level used to find nonstationary variables in Schur
decomposition of the transition matrix.
- The `identification` command now supports optimal policy.
- Shock decomposition
- The `fast_realtime` option of the `realtime_shock_decomposition` command
now accepts a vector of integers, which runs the smoother for all the
specified data vintages.
- Macro processor
- Macroprocessor variables can be defined without a value (they are
assigned integer 1).
- LaTeX and JSON outputs
- New `nocommutativity` option to the `dynare` command. This option tells
the preprocessor not to use the commutativity of addition and
multiplication when looking for common subexpressions. As a consequence,
when using this option, equations in various outputs (LaTeX, JSON…) will
appear as the user entered them (without terms or factors swapped). Note
that using this option may have a performance impact on the preprocessing
stage, though it is likely to be small.
- Model-local variables are now substituted out as part of the various
model transformations. This means that they will no longer appear in
LaTeX or in JSON files (for the latter, they are still visible with
`json=parse` or `json=check`).
- Compilation of the model (`use_dll` option)
- Block decomposition (option `block` of `model`) can now be used in
conjunction with the `use_dll` option.
- The `use_dll` option can now directly be given to the `dynare` command.
- dseries classes
- Routines for converting between time series frequencies (e.g. daily to
monthly) have been added.
- dseries now support bi-annual and daily frequency data.
- dseries can now import data from [DBnomics](https://db.nomics.world), via
the [mdbnomics](https://git.dynare.org/dbnomics/mdbnomics) plugin. Note
that this does not yet work under Octave. For the time being, the
DBnomics plugin must be installed separately.
- Misc improvements
- The `histval_file` and `initval_file` commands have been made more
flexible and now have functionalities similar to the `datafile` option of
the `estimation` command.
- When using the `loglinear` option, the output from Dynare now clearly
shows that the results reported concern the log of the original variable.
- Options `block` and `bytecode` of `model` can now be used in conjunction
with model-local variables (variables declared with a pound-sign `#`).
- The `model_info` command now prints the typology of endogenous variables
for non-block decomposed models.
- The total computing time of a run (in seconds) is now saved to `oo_.time`.
- New `notime` option to the `dynare` command, to disable the printing and
the saving of the total computing time.
- New `parallel_use_psexec` command-line Windows-specific option for
parallel local clusters: when `true` (the default), use `psexec` to spawn
processes; when `false`, use `start`.
- when compiling from source, it is no longer necessary to pass the
`MATLAB_VERSION` version to the configure script; the version is now
automatically detected.
Incompatible changes
--------------------
- Dynare will now generally save its output in the `MODFILENAME/Output` folder
(or the `DIRNAME/Output` folder if the `dirname` option was specified)
instead of the main directory. Most importantly, this concerns the
`_results.mat` and the `_mode.mat` files.
- The structure of the `oo_.planner_objective` field has been changed, in
relation to the improvements to `evaluate_planner_objective`.
- The preprocessor binary has been renamed to `dynare-preprocessor`, and is
now located in a dedicated `preprocessor` subdirectory.
- The `dynare` command no longer accepts `output=dynamic` and `output=first`
(those options actually had no effect).
- The minimal required MATLAB version is now R2014a (8.3).
- The 32-bit support has been dropped for Windows.
Bugs that were present in 4.6.4 and that have been fixed in 5.0
---------------------------------------------------------------
* Equations marked with `static`-tags were not detrended when a `deflator` was
specified
* Parallel execution of `dsge_var` estimation was broken
* The preprocessor would incorrectly simplify forward-looking constant
equations of the form `x(+1)=0` to imply `x=0`
* Under some circumstances, the use of the `model_local_variable` statement
would lead to a crash of the preprocessor
* When using the `block`-option without `bytecode` the residuals of the static
model were incorrectly displayed
* When using `k_order_solver`, the `simult_` function ignored requested
approximation orders that differed from the one used to compute the decision
rules
* Stochastic simulations of the `k_order_solver` without `pruning` iterated on
the policy function with a zero shock vector for the first (non-endogenous)
period
* `estimation` would ignore the mean of non-zero observables if the mean was 0
for the initial parameter vector
* `mode_check` would crash if a parameter was estimated to be exactly 0
* `load_mh_file` would not be able to load proposal density if the previous run
was done in parallel
* `load_mh_file` would not work with MCMC runs from Dynare versions before
4.6.2
* `ramsey_model` would not correctly work with `lmmcp`
* `ramsey_model` would crash if a non-scalar error code was encountered during
steady state finding.
* Using undefined objects in the `planner_objective` function would yield an
erroneous error message about the objective containing exogenous variables
* `model_diagnostics` did not correctly handle a previous `loglinear` option
* `solve_algo=3` (csolve) would ignore user-set `maxit` and `tolf` options
* The `planner_objective` values were not based on the correct initialization
of auxiliary variables (if any were present)
* The `nostrict` command line option was not ignoring unused endogenous
variables in `initval`, `endval` and `histval`
* `prior_posterior_statistics_core` could crash for models with eigenvalues
very close to 1
* The display of the equation numbers in `debug` mode related to issues in the
Jacobian would not correctly take auxiliary equations into account
* The `resid` command was not correctly taking auxiliary and missing equations
related to optimal policy (`ramsey_model`, `discretionary_policy`) into
account
* `bytecode` would lock the `dynamic.bin` file upon encountering an exception,
requiring a restart of MATLAB to able to rerun the file
* Estimation with the `block` model option would crash when calling the block
Kalman filter
* The `block` model option would crash if no `initval` statement was present
* Having a variable with the same name as the mod-file present in the base
workspace would result in a crash
* `oo_.FilteredVariablesKStepAheadVariances` was wrongly computed in the Kalman
smoother based on the previous period forecast error variance
* Forecasts after `estimation` would not work if there were lagged exogenous
variables present
* Forecasts after `estimation` with MC would crash if measurement errors were
present
* Smoother results would be infinity for auxiliary variables associated with
lagged exogenous variables
* In rare cases, the posterior Kalman smoother could crash due to previously
accepted draws violating the Blanchard-Kahn conditions when using an
unrestricted state space
* `perfect_foresight_solver` would crash for purely static problems
* Monte Carlo sampling in `identification` would crash if the minimal state
space for the Komunjer and Ng test could not be computed
* Monte Carlo sampling in `identification` would skip the computation of
identification statistics for all subsequent parameter draws if an error was
triggered by one draw
* The `--steps`-option of Dynare++ was broken
* `smoother2histval` would crash if variable names were too similar
* `smoother2histval` was not keeping track of whether previously stored results
were generated with `loglinear`
* The `initval_file` option was not supporting Dynare’s translation of a model
into a one lead/lag-model via auxiliary variables
References
----------
- Andreasen et al. (2018): “The Pruned State-Space System for Non-Linear DSGE
Models: Theory and Empirical Applications,” Review of Economic Studies,
85(1), 1–49
- Angelini, Bokan, Christoffel, Ciccarelli and Zimic (2019): “Introducing
ECB-BASE: The blueprint the new ECB semi-structural model for the euro area,”
ECB Working Paper no. 2315
- Born and Pfeifer (2014): “Policy risk and the business cycle,” Journal of
Monetary Economics, 68, 68–85
- Brayton, Davis and Tulip (2000): “Polynomial Adjustment Costs in FRB/US,”
Unpublished manuscript
- Brayton, Laubach and Reifschneider (2014): “The FRB/US Model: A Tool for
Macroeconomic Policy Analysis,” FEDS Notes. Washington: Board of Governors
of the Federal Reserve System, https://doi.org/10.17016/2380-7172.0012
- Cuba-Borda, Guerrieri, Iacoviello, and Zhong (2019): “Likelihood evaluation
of models with occasionally binding constraints,” Journal of Applied
Econometrics, 34(7), 1073–1085
- Giovannini, Pfeiffer and Ratto (2021): “Efficient and robust inference of
models with occasionally binding constraints,” Working Paper 2021-03, Joint
Research Centre, European Commission
- Guerrieri and Iacoviello (2015): “OccBin: A toolkit for solving dynamic
models with occasionally binding constraints easily,” Journal of Monetary
Economics, 70, 22–38
- Mutschler (2018): “Higher-order statistics for DSGE models,” Econometrics
and Statistics, 6(C), 44–56
Announcement for Dynare 4.6.4 (on 2021-03-18)
=============================================