Everything was already in place (since ages!), except that the parser interface
was missing.
Also fix the derivation formula for atanh, which was incorrect.
The implementation of PacExpectationNode::toStatic() did not make sense. It
should normally never be called, hence we error out at this point.
Also do a cosmetic change in the PacExpectationNode::clone() methode.
In particular, this implies that steady state values of endogenous in the
“occbin_constraints” block must now be specified using the STEADY_STATE()
operator (and not with a “_ss” suffix).
Moreover:
– make various simplifications to the fields generated under M_
– in the driver file, replace the call to occbin.initialize() by a few explicit operations
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
Introduce a new method for decomposing a product of factors, so that we can
identify expressions of the form (1-optim_share)*A*B.
Also enforce that the optim_share parameter be in a factor of the form
1-optim_share (previously it would accept any expression containing the
parameter).
Note that this fix does not yet allow to actually write non-optimizing parts of
the form (1-optim_share)*A*B, since at a later point the preprocessor imposes
that this part be a linear combination of variables (but in the future we could
think of expanding the A*B product into a linear combination if, for example, A
is a paramater or a constant and B is a linear combination).
Closes: #50
– 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.
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.
Sébastien Villemot
MichelJuillard
Houtan Bastani
