It is now supported by the MATLAB editor (as of R2022a).
The old ASCII notation is left in some files that we copy as-is from other
sources (e.g. in the contrib/ and m4/ subdirectories).
The particles submodule is not updated at this point, because it is in an
inconsistent state.
[skip ci]
There was no user interface, and the feature that it provides has lost
relevance over time.
Note that algorithms for block and/or bytecode still internally use some
equivalent of this parameter, but its initial value will no longer be
modifiable (which could lead to bugs, see commit
e49e7e906f).
These command solve the problem where agents think they know perfectly the
future (they behave as in perfect foresight), but make expectation errors.
Hence they can potentially be surprised in every period, and their expectations
about the future (incl. the final steady state) may change.
Currently the sequence of information sets needs to be passed through a CSV
file. Another interface may be added in the future.
The algorithm uses a sequence of (true) perfect foresight simulations (not
necessarily as many as there are periods, because if the information set does
not change between two periods, there is no need to do a new computation).
There are two possibilities for guess values:
— the default is to use the initial steady state for the simulation using the
first-period information set; then use previously simulated values as guess
values
— alternatively, with the terminal_steady_state_as_guess_value option, use the
terminal steady state as guess value for all future periods (this is actually
what the “true” perfect foresight solver does by default)
Contains improvements, in order to recover as much as possible static unobserved (filtered, smoothed, updated, k-step ahead), Variance, State_uncertainty, k-step ahead variances trying to map lagged states onto current ones using pinv(T). This has exceptions (namely lagged shocks which are ONLY used to recover static NON observed variables). this exception is also trapped.
For such extensions we can only recover smoothed variables starting from d+1. Variances CANNOT be recovered for such variables (the smoother gives ZERO.)
Incidently, remove the possibility of passing model derivatives as arguments to
the k_order_perturbation. That possibility was only used by the risky steady
state code.
Closes: #1338
It applies the approximated policy function to a set of particles, using
Dynare++ routines.
There is support for parallelization, using Dynare++ multithreading
model (itself based on C++11 threads; we don’t use OpenMP because it is
incompatible with MKL). For the time being, default to a single thread. This
should be later refined through empirical testing.
In case the epilogue formula is non-linear, the non additive non-linear term is distributed proportionally to the size of the individual shock contribution.
It is triggered by new option with_epilogue, applicable to commands:
1) shock_decomposition, realtime_shock_decomposition,
where preprocessor should trigger
options_.shock_decomp.with_epilogue=true;
2) initial_condition_decomposition
where preprocessor should trigger
options_.initial_condition_decomp.with_epilogue=true;
Stéphane Adjemian (Ryûk)
Johannes Pfeifer
Normann Rion
Frédéric Karamé
Sébastien Villemot
Marco Ratto
Houtan Bastani