Consequently drop “occbin” option to “model”.
Incidentally, allow more values in equation tag names (previously some keywords
such as “alpha” were disallowed).
Ref. #68
As the name implies, this option allows contemporaneous variables on the RHS.
The A0 matrix for contemporaneous variables is added as a second (optional)
output to the generated var_ar.m file. Note that for reduced-form VAR, this
matrix will be the identity.
Also, the user is now allowed to write the VAR models in a more flexible form:
the LHS must still be a single variable, but the RHS can be an arbitrary
expression (as long as it is linear, obviously). Internally, the preprocessor
now uses derivation to compute the coefficients of the AR and A0. This change
applies to both reduced-form and structural VAR models.
Ref. dynare#1785
For the time being, the preprocessor will refuse that this option be used with
any command other than estimation.
By the way, remove occbin_likelihood and occbin_smoother options to estimation.
Ref. dynare#569
— rename the files with camel case
— encapsulate the functions with modules
— change the signature of function <MODFILE>_dynamic_set_series!, by removing
the output argument and appending the exclamation mark, since this function
modifies one of its arguments, and for symmetry with the static version
Ref. DynareJulia/Dynare.jl#1
– Fix order of items in this structure. Previously, items were ordered
according to the declaration order of parameters. Now, items are order
according to lag order (first lag appears first)
– Gracefully handle the case where there is no autoregressive part
(Closes: #52)
Also be more strict on the form of the target (must now be X(-1) or log(X(-1))
where X is *not* an auxiliary variable).
By the way, improve some comments in SymbolTable.
The detection of the target EC variable to be used when constructing the
forward-looking expectation variable is rather fragile.
When the PAC model is written with an (non-)optimizing share of agents,
restrict the identification of the target variable to the optimizing
expression, to minimize the risk of wrong identification.
By the way, add a few comments, and a small simplification.
By default, the preprocessor is supposed to only do the “unary ops”
transformation in the equations of VAR/PAC/trend component models.
However, the implementation was slightly different so far. It would detect
candidates to this transformation in the chosen equations, but it would then
perform the substitution in *all* equations.
This could lead for crashes, for example if the chosen equation contains
log(X(-1)), but another (non-chosen) equation has log(X(-2)). Then this latter
expression, even though it belongs to the same lag-equivalence class, is not
properly handled, causing a segfault.
Also do a few related cosmetic changes.
Use 3-column format before calling sparse().
Ensure that the 3-column matrix is constructed in column-major order: data
locality will greatly improve performance once we implement use_dll.
Rather use a single vector as in non-block mode.
By the way, change the order of output arguments in static functions, to be
closer to the dynamic ones.
Temporary terms need to be computed per equation (as was done previously), and
not simply per block.
It’s necessary to track temporary terms per equation, because some equations
are evaluated instead of solved, and an equation E1 may depend on the value of
an endogenous Y computed by a previously evaluated equation E2; in this case,
if some temporary term TT of equation E2 contains Y, then TT needs to be
computed after E1, but before E2.
In particular, in dynamic models, temporary terms are now computed for
derivatives w.r.t. exogenous, and also w.r.t. endogenous variables that do not
belong to the block.
Also remove a message about elements below the cutoff that was no longer
correct (elements below the cutoff have no impact on the incidence matrix
outside of normalization).
By the way, remove the BlockType stuff which was purely informative (and it’s
not worth carrying over prologue and epilogue information just for that).
Previously, the cutoff option would also impact the block decomposition itself,
since it would had an influence on the incidence matrix used for computing the
blocks and their derivatives.
The problem is that, in the general case, it’s quite possible that an element
of the numerical Jacobian be zero at the evaluation point, while being quite
different from zero along the simulation path. A typical example is an
expression of the type x*y, where y is an endogenous and x is an exogenous not
present in the initval block (and hence initialized to zero).
It has been superseded by ModelTree::blocks_derivatives.
By the way, fix the initial number of non-zero elements in sparse Jacobian.
Also avoid computing suboptimal temporary terms.
— use a std::map for storing block derivatives
— remove redundant ModelTree::first_chain_rule_derivatives structure
— remove unused codepaths in StaticModel
— DynamicModel: simplify code that determines the type of derivatives in a
block. We now use a slightly different categorization.
— by the way, fix the max lead/lag information for blocks that are obtained via
merging. A workaround was previously implemented in
DynamicModel::get_Derivative(), but it is no longer needed with this fix.
This was only adding unneeded complexity, for no clear reason (we’re very far
from reaching 2³¹ equations, and if we wanted to support models that large, it
would be better to use long integers to avoid being limited to 2³²).
— return output arguments on the left-hand side
— do not pass class members as input/output arguments
By the way, fix a (benign) vector allocation bug in
{Static,Dynamic}Model::computeChainRuleJacobian().
Since commit 9c9e8f816f, it’s the information
from the original model which was in this field, which is not what is expected.
By the way, do not output this field (and the related M_.hessian_eq_zero) when
the Hessian is not computed by the preprocessor (i.e. in practice for perfect
foresight), since they would otherwise contain incorrect information.
Ref. dynare#1681
Auxiliary equations appearing in set_auxiliary_variables.m and
dynamic_set_auxiliary_series.m need to appear in recursive ordering, since
those files are used for sequential evaluation.
Previously, the recursive ordering was guaranteed by a set of ad hoc rules and
workarounds, but that would not cover certain edge cases.
With this commit, the recursive ordering is systematically computed, using a
topological sort on the directed acyclic graph whose vertices are auxiliary
equations and whose edges are dependency relationships.
Closes: #22
Allows for the inclusion/exclusion of a set of equations, specified either on the command line or in a text file.
If the equation has a single endogenous variable on the LHS, then the equation is moved. If not, if the equation has an `endogenous` tag then that variable is removed along with this equation. If not, then an error is thrown.
As a command line argument, `exclude_eqs` can take the form (same syntax for `include_eqs`):
* `exclude_eqs=eq1 to remove all equations declared as `[name=eq1]`
* `exclude_eqs=[eq 1, eq 2]` to remove all equations declared as `[name=eq 1]` or `[name=eq 2]`
* `exclude_eqs=[tagname=X]` to remove all equations declared as `[tagname=X]`
* `exclude_eqs=[tagname=(X, Y)]` to remove all equations declared as `[tagname=X]` or `[tagname=Y]`
When declared in a file, the file should be of the form:
```
eq 1
eq 2
```
to remove all equations declared as `[name=eq 1]` or `[name=eq 2]`.
It should be of the form:
```
tagname=
X
Y
```
to remove all equations declared as `[tagname=X]` or `[tagname=Y]`.
— Raise the default tolerance for cross-derivatives to 1e-6, to reduce the
number of false positives
— New option “balanced_growth_test_tol” to the “model” block for changing that
tolerance
— Turn back test failures into errors. Since there is now an option for
controlling the tolerance, the user always has the possibility of making the
test pass.
Closes: dynare#1389
In many cases, they can be replaced by the curly braces syntax.
Otherwise, we can now use the pair() and tuple() constructors, without the need
to specify template parameters, thanks to class template argument
deduction (new in C++17).
This is made possible by the getLagEquivalenceClass() method introduced in the
previous commit.
Previously, the static version of the LHS expressions was used.
As a consequence, drop ModFile::diff_static_model, now useless.
Previously, for testing whether two diff() expressions or two unary ops were
the lead/lag of each other, the preprocessor would test whether they have the
same static representation. This is ok for simple expressions (e.g.
diff(x(-1))), but not for more complex ones (e.g. diff(x-y) and diff(x(-1)-y)
should not be given the same auxiliary variable).
This commit fixes this by properly constructing the equivalence relationship
and choosing a representative within each equivalence class. See the comments
above lag_equivalence_table_t in ExprNode.hh for more details.
Closes#27
Furthermore, modifications to model local variables were not taken into account.
To fix, take checksum of model local variables, temporary terms, and equations
Also, use existing functions to print these to a stringstream instead of repeating print functionality in this function
Backward incompatible change: the temporary terms for 3rd order are now stored
in "temporary_terms_third_derivative" (without the final "s"; same for external
functions), for consistency with the name of the slot for the derivatives
themselves ("third_derivative").
Ref dynare#217
Does not work for Julia mode, neither with block and bytecode.
Note: in DLL mode, the number of temporary terms in no longer given in the
‘ntt’ symbol; it must be computed using ‘M_.dynamic_tmp_nbr’.
Ref dynare#217
The idea is to make use of the dynamic_set_auxiliary_dseries.m file to generate
the initial conditions for all auxiliary variables, including the diffs.
Also remove the check done by the preprocessor for the lags in histval, since
it does not work correctly with the diff operator.
Sébastien Villemot
MichelJuillard
Stéphane Adjemian (Charybdis)
Michel Juillard
Houtan Bastani
Dóra Kocsis
Stéphane Adjemian (Charybdis)