diff --git a/NEWS b/NEWS
index 796078725429c0b1f31f64b5e6dba7068d5ff6ea..71e9b45d4e07515eb4c7d42e53ead781e81abbf1 100644
--- a/NEWS
+++ b/NEWS
@@ -19,367 +19,374 @@ This release is compatible with MATLAB versions ranging from 7.3 (R2006b) to
Here is the list of major user-visible changes:
+
+Dynare 4.5
+==========
+
+
- 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,
+ + 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.
+ + `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`,
+ + 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,
+ + 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 `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 `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 `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 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 options `tolf` and `tolx` to control termination criteria of
+ solvers,
- + New option `endogenous_terminal_period` to `simul`,
+ + 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.
+ + 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`,
+ + Saves the optimal value of parameters to `oo_.osr.optim_params`,
- + New block `osr_params_bounds` allows specifying bounds for the
- estimated parameters,
+ + 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,
+ + 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`.
+ + 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,
+ + 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`,
+ + 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 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.
+ + new field `oo_.Smoother.TrendCoeffs` that stores the trend
+ coefficients.
- + Rolling window forecasts allowed in `estimation` command by
- passing a vector to `first_obs`,
+ + 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.
+ + 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`
+ + 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,
+ + `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 `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,
+ + 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`,
+ + 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,
+ + 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,
+ + 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_`,
+ + 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,
+ + The `trace_plot` command can now plot the posterior density,
- + New command `generate_trace_plots` allows generating all trace
- plots for one chain,
+ + 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 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 `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_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 `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 `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),
+ + 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`,
+ + 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 option `smoothed_state_uncertainty` to provide the uncertainty
+ estimate for the smoothed state estimate from the Kalman smoother,
- + New prior density: generalized Weibull distribution,
+ + New prior density: generalized Weibull distribution,
- + Option `mh_recover` now allows continuing a crashed chain at the
- last save mh-file,
+ + 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.
+ + 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 `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,
+ + The `use_calibration` to `estimated_params_init` now also works
+ with ML,
- + Improved initial estimation checks.
+ + 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`),
+ + 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,
+ + New options `tolf` and `tolx` to control termination criteria of
+ solver,
- + The debugging mode now provides the termination values in steady
- state finding.
+ + The debugging mode now provides the termination values in steady
+ state finding.
- Stochastic simulations
- + New options `nodecomposition`,
+ + New options `nodecomposition`,
- + New option `bandpass_filter` to compute bandpass-filtered
- theoretical and simulated moments,
+ + 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,
+ + 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` 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 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`,
+ + `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,
+ + 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 `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,
+ + 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 `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.
+ + New option `contemporaneous_correlation` that allows saving
+ contemporaneous correlations in addition to the covariances.
- Identification
- + New options `diffuse_filter` and `prior_trunc`,
+ + New options `diffuse_filter` and `prior_trunc`,
- + The `identification` command now supports correlations via
- simulated moments,
+ + The `identification` command now supports correlations via
+ simulated moments,
- Sensitivity analysis
- + New blocks `irf_calibration` and `moment_calibration`,
+ + New blocks `irf_calibration` and `moment_calibration`,
- + Outputs LaTeX tables if the new `TeX` option is used,
+ + Outputs LaTeX tables if the new `TeX` option is used,
- + New option `relative_irf` to `irf_calibration` block.
+ + New option `relative_irf` to `irf_calibration` block.
- Conditional forecast
- + Command `conditional_forecast` now takes into account `histval`
- block if present.
+ + 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,
+ + New option `colormap` to `shocks_decomposition` for controlling
+ the color map used in the shocks decomposition graphs,
- + `shocks_decomposition` now accepts the `nograph` option,
+ + `shocks_decomposition` now accepts the `nograph` option,
- + New command `realtime_shock_decomposition` that for each period `T= [presample,...,nobs]`
- allows computing the:
+ + New command `realtime_shock_decomposition` that for each period `T= [presample,...,nobs]`
+ allows computing the:
- o realtime historical shock decomposition `Y(t|T)`, i.e. without observing data in `[T+1,...,nobs]`
- o forecast shock decomposition `Y(T+k|T)`
- o realtime conditional shock decomposition `Y(T+k|T+k)-Y(T+k|T)`
+ * realtime historical shock decomposition `Y(t|T)`, i.e. without observing data in `[T+1,...,nobs]`
- + New block `shock_groups` that allows grouping shocks for the
- `shock_decomposition` and `realtime_shock_decomposition` commands,
+ * forecast shock decomposition `Y(T+k|T)`
- + New command `plot_shock_decomposition` that allows plotting the
- results from `shock_decomposition` and
- `realtime_shock_decomposition` for different vintages and shock
- groupings.
+ * 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,
+ + Can now pass a macro-variable to the `@#include` macro directive,
- + New preprocessor flag `-I`, macro directive `@#includepath`, and
- dynare config file block `[paths]` to pass a search path to the
- macroprocessor to be used for file inclusion via `@#include`.
+ + New 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 `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 `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 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`.
+ + 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 methods `abs`, `cumprod` and `chain`,
- + New option `tableRowIndent` to `addTable`,
+ + New option `tableRowIndent` to `addTable`,
- + Reporting system revamped and made more efficient, dependency on
- matlab2tikz has been dropped.
+ + 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=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=101` Uses SOLVEOPT as described by Kuntsevich and
+ Kappel (1997),
- + `mode_compute=102` Uses `simulannealbnd` from Matlab's Global
- Optimization Toolbox (if available),
+ + `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 option `silent_optimizer` to shut off output from mode
+ computing/optimization,
- + New options `verbosity` and `SaveFiles` to control output and
- saving of files during mode computing/optimization.
+ + New options `verbosity` and `SaveFiles` to control output and
+ saving of files during mode computing/optimization.
- LaTeX output
- + New command `write_latex_original_model`,
+ + 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 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_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 `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.
+ + New command `collect_latex_files` that creates one compilable LaTeX
+ file containing all TeX-output.
- Misc.
- + Provides 64bit preprocessor,
+ + Provides 64bit preprocessor,
- + Introduces new path management to avoid conflicts with other
- toolboxes,
+ + Introduces new path management to avoid conflicts with other
+ toolboxes,
- + Full compatibility with Matlab 2014b's new graphic interface,
+ + Full compatibility with Matlab 2014b's new graphic interface,
- + When using `model(linear)`, Dynare automatically checks
- whether the model is truly linear,
+ + When using `model(linear)`, Dynare automatically checks
+ whether the model is truly linear,
- + `usedll`, the `msvc` option now supports `normcdf`, `acosh`,
- `asinh`, and `atanh`,
+ + `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,
+ + 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,
+ + Improved numerical performance of
+ `schur_statespace_transformation` for very large models,
- + The `all_values_required` option now also works with `histval`,
+ + The `all_values_required` option now also works with `histval`,
- + Add missing `horizon` option to `ms_forecast`,
+ + 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`.
+ + 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`.
@@ -388,355 +395,355 @@ Here is the list of major user-visible changes:
- BVAR models
- + `bvar_irf` could display IRFs in an unreadable way when they moved from
- negative to positive values,
+ + `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.
+ + 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 `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 `plot_conditional_forecast` option could produce unreadable figures if
+ the areas overlap,
- + The `conditional_forecast` command after MLE crashed,
+ + 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.
+ + 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.
+ + 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 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,
+ + 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.
+ + 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.
+ + 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,
+ + 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.
+ + 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,
+ + 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,
+ + 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`,
+ + 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`,
+ + 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,
+ + 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`,
+ + 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,
+ + 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,
+ + 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_*`,
+ + 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,
+ + Using a user-defined `mode_compute` crashed estimation,
- + Option `mode_compute=10` did not work with infinite prior bounds,
+ + 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,
+ + 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,
+ + 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,
+ + 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,
+ + 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,
+ + 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,
+ + 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,
+ + 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,
+ + 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),
+ + 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,
+ + The estimation option `lyapunov=fixed_point` was broken,
- + Computation of `filtered_vars` with only one requested step crashed Dynare,
+ + Computation of `filtered_vars` with only one requested step crashed Dynare,
- + Option `kalman_algo=3` was broken with non-diagonal measurement error,
+ + 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,
+ + 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,
+ + 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,
+ + 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,
+ + 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,
+ + 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,
+ + 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,
+ + 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,
+ + `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`,
+ + 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,
+ + 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`,
+ + 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,
+ + 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,
+ + 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 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.
+ + 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 `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,
+ + 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 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 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 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,
+ + 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.
+ + 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 provided wrong decision
+ rules, yielding wrong forecasts.
- + Forecasting with exogenous deterministic variables crashed when the
- `periods` option was not explicitly specified,
+ + 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.
+ + 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,
+ + Sensitivity with ML estimation could result in crashes,
- + Option `mc` must be forced if `neighborhood_width` is used,
+ + Option `mc` must be forced if `neighborhood_width` is used,
- + Fixed dimension of `stock_logpo` and `stock_ys`,
+ + Fixed dimension of `stock_logpo` and `stock_ys`,
- + Incomplete variable initialization could lead to crashes with `prior_range=1`.
+ + 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,
+ + 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,
+ + 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
+ + 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,
+ + When using ML, the asymptotic Hessian was not computed,
- + Checking for singular values when the eigenvectors contained only
- one column did not work correctly,
+ + Checking for singular values when the eigenvectors contained only
+ one column did not work correctly,
- Model comparison
- + Selection of the `modifiedharmonicmean` estimator was broken,
+ + 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,
+ + 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,
+ + 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,
+ + Using only one (co)variance in the objective function resulted in crashes,
- + For models with non-stationary variables the objective function was computed wrongly.
+ + 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.
+ + 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, 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 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 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,
+ + 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,
+ + 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,
+ + Did not work with the `parameter_set=calibration` option if an
+ `estimated_params` block is present,
- + Crashed after MLE.
+ + 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 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 only accepted column and not row vectors,
- + The `initval_file` command did not work with Excel files,
+ + 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 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,
+ + 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,
+ + 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`/`bytecode`, relational operators could not be enforced,
- + When using `block` some exceptions were not properly handled,
- leading to code crashes,
+ + When using `block` some exceptions were not properly handled,
+ leading to code crashes,
- + Using `periods=1` crashed the solver (bug only partially fixed).
+ + 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 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.
+ + 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`,
+ + 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,
+ + 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,
+ + 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.
+ + 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.
+ + 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
@@ -787,6 +794,7 @@ Here is the list of major user-visible changes:
variables and parameters.
+
Announcement for Dynare 4.4.3 (on 2014-07-31)
=============================================