Release notes for 4.4.0 release
Sébastien Villemot
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NEWS
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NEWS
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Announcement for Dynare 4.4.0 (on 2013-12-11)
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=============================================
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We are pleased to announce the release of Dynare 4.4.0.
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This major release adds new features and fixes various bugs.
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The Windows package is already available for download. The Mac and
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Debian/Ubuntu packages should follow soon.
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All users are strongly encouraged to upgrade.
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This release is compatible with MATLAB versions ranging from 7.3 (R2006b) to
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8.1 (R2013b) and with GNU Octave version 3.6.
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Here is the list of major user-visible changes:
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* New major algorithms:
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- Extended path at order 1 and above, also known as “stochastic extended
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path”. This method is triggered by setting the `order' option of the
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`extended_path' command to a value greater than 0. Dynare will then use a
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Gaussian quadrature to take into account the effects of future uncertainty.
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The time series for the endogenous variables are generated by assuming that
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the agents believe that there will no more shocks after period t+order.
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- Alternative algorithms for computing decision rules of a stochastic model,
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based on the cycle reduction and logarithmic reduction algorithms. These
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methods are respectively triggered by giving `dr = cycle_reduction' or 'dr
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= logarithmic_reduction' as an option to the `stoch_simul' command.
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- Pruning now works with 3rd order approximation, along the lines of
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Andreasen, Fernández-Villaverde and Rubio-Ramírez (2013).
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- Computation of conditional forecast using an extended path method. This is
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triggered by the new option `simulation_type = deterministic' in the
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`conditional_forecast' command. In this case, the `expectation' command in
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the `conditional_forecast_paths' block has to be used to indicate the nature
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of expectations (whether shocks are a surprise or are perfectly
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anticipated).
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- Endogenous priors as in Christiano, Trabandt and Walentin (2011). Those are
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triggered by the new option `endogenous_prior' of the `estimation' command.
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* Other algorithmic improvements:
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- New command `model_diagnostics' to perform various sanity checks on the
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model. Note: in the past, some users may have used a preliminary MATLAB
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function implementing this; the new command has the same syntax, except that
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you shouldn't pass any argument to it.
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- Terminal conditions of perfect foresight simulations can now be specified in
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growth rates. More specifically, the new option `differentiate_forward_vars'
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of the `model' block will create auxiliary forward looking variables
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expressed in first differences or growth rates of the actual forward looking
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variables defined in the model. These new variables have obvious zero
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terminal conditions whatever the simulation context and this in many cases
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helps convergence of simulations.
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- Convergence diagnostics for single chain MCMC à la Geweke (1992, 1999).
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- New optimizer for the posterior mode (triggered by `mode_compute=10'): it
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uses the simpsa algorithm, based on the combination of the non-linear
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simplex and simulated annealing algorithms and proposed by Cardoso, Salcedo
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and Feyo de Azevedo (1996).
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- The automatic detrending engine has been extended to work on models written
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in logs. The corresponding trend variable type is `log_trend_var', and the
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corresponding deflator type is `log_deflator'.
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* New features in the user interface:
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- New set of functions for easily creating PDF reports including figures and
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tables. See the “Reporting” section in the reference manual for more
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details.
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- New MATLAB/Octave classes for handling time series. See the “Time series”
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section in the reference manual for more details.
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- Datafiles in CSV format can now be used for estimation.
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- New macro processor `length' operator, returns the length of an array.
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- New option `all_values_required' of `initval' and `endval' blocks: enforces
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initialization of all endogenous and exogenous variables within the block.
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- Option `ar' can now be given to the `estimation' command.
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- New options `nograph', `nointeractive', `nostrict' and `nowarn' to the
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`dynare' command.
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- The information on MCMC acceptance rates, seeds, last log posterior
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likelihood, and last parameter draw are now saved in `oo_.MC_record'.
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- New options `mode_check_neighbourhood_size', `mode_check_symmetric_plots'
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and `mode_check_number_of_points', for a better control of the diagnostic
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plots.
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- New option `parallel_local_files' of `model' block, for transferring extra
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files during parallel computations.
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- New option `clock' of `set_dynare_seed', for setting a different seed at
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each run.
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- New option `qz_zero_threshold' of the `check', `stoch_simul' and
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`estimation' commands, for a better control of the situation where a
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generalized eigenvalue is close to 0/0.
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- New `verbatim' block for inclusion of text that should pass through the
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preprocessor and be placed as is in the `modfile.m' file.
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- New option `mcmc_jumping_covariance' of the `estimation' command, for a
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better control of the covariance matrix used for the proposal density of the
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MCMC sampler.
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- New option `use_calibration' of the `estimated_params_init', for using the
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calibration of deep parameters and the elements of the covariance matrix
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specified in the `shocks' block as starting values for the estimation.
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- New option `save_draws' of the `ms_simulation' command.
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- New option `irf_plot_threshold' of the `stoch_simul' and `estimation'
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commands, for a better control of the display of IRFs which are almost nil.
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- New option `long_name' for endogenous, exogenous and parameter declarations,
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which can be used to declare a long name for variables. That long name can
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be programmatically retrieved in `M_.endo_names_long'.
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* Miscellaneous changes
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- The deciles of some posterior moments were erroneously saved in a field
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`Distribution' under `oo_'. This field is now called `deciles', for
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consistency with other posterior moments and with the manual. Similarly, the
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fields `Mean', `Median', `HPDsup', `HPDinf', and `Variance' are now
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consistently capitalized.
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- The console mode now implies the `nodisplay' option.
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* Bugs and problems identified in version 4.3.3 and that have been fixed in
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version 4.4.0:
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- In an `endval' block, auxiliary variables were not given the right value.
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This would not result in wrong results, but could prevent convergence of
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the steady state computation.
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- Deterministic simulations with `stack_solve_algo=0' (the default value) were
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crashing if some exogenous had a lag strictly greater than 1.
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- When using the `mode_file' option, the initial estimation checks were not
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performed for the loaded mode, but for the original starting values. Thus,
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potential prior violations by the mode only appeared during estimation,
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leading to potentially cryptic crashes and error messages.
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- If a shock/measurement error variance was set to 0 in calibration, the
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correlation matrix featured a 0 instead of a 1 on the diagonal, leading to
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wrong estimation results.
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- In the presence of calibrated covariances, estimation did not enforce
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positive definiteness of the covariance matrix.
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- Estimation using the `diffuse_filter' option together with the univariate
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Kalman filter and a diagonal measurement error matrix was broken.
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- A purely backward model with `k_order_solver' was leading to crashes of
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MATLAB/Octave.
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- Non-linear estimation was not skipping the specified presample when
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computing the likelihood.
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- IRFs and theoretical moments at order > 1 were broken for purely
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forward-looking models.
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- Simulated moments with constant variables was leading to crashes when
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displaying autocorrelations.
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- The `osr' command was sometimes crashing with cryptic error messages because
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of some unaccounted error codes returned from a deeper routine.
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- The check for stochastic singularity during initial estimation checks was
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broken.
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- Recursive estimation starting with the pathological case of `nobs=1' was
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crashing.
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- Conditional variance decomposition within or after estimation was crashing
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when at least one shock had been calibrated to zero variance.
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- The `estimated_params_init' and `estimated_params_bounds' blocks were broken
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for correlations.
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- The `filter_step_ahead' option was not producing any output in Bayesian
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estimation.
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- Deterministic simulations were sometimes erroneously indicating convergence
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although the residuals were actually NaN or Inf.
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- Supplying a user function in the `mode_compute' option was leading to
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a crash.
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- Deterministic simulation of models without any exogenous variable was
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crashing.
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- The MS-SBVAR code was not updating files between runs on Windows. This means
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that if a MOD file was updated between runs in the same folder and a
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`file_tag' was not changed, then the results would not change.
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* References:
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- Andreasen, Martin M., Jesús Fernández-Villaverde, and Juan Rubio-Ramírez
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(2013): “The Pruned State-Space System for Non-Linear DSGE Models: Theory
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and Empirical Applications,” NBER Working Paper, 18983
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- Cardoso, Margarida F., R. L. Salcedo and S. Feyo de Azevedo (1996): “The
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simplex simulated annealing approach to continuous non-linear optimization,”
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Computers chem. Engng, 20(9), 1065-1080
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- Christiano, Lawrence J., Mathias Trabandt and Karl Walentin (2011):
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“Introducing financial frictions and unemployment into a small open economy
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model,” Journal of Economic Dynamics and Control, 35(12), 1999-2041
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- Geweke, John (1992): “Evaluating the accuracy of sampling-based approaches
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to the calculation of posterior moments,” in J.O. Berger, J.M. Bernardo,
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A.P. Dawid, and A.F.M. Smith (eds.) Proceedings of the Fourth Valencia
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International Meeting on Bayesian Statistics, pp. 169-194, Oxford University
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Press
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- Geweke, John (1999): “Using simulation methods for Bayesian econometric
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models: Inference, development and communication,” Econometric Reviews,
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18(1), 1-73
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Announcement for Dynare 4.3.3 (on 2013-04-12)
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=============================================
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