– Temporary terms were not correctly passed between blocks
– solve_algo ⩾ 9 was incorrectly passed through bytecode own’s solver instead
of through dynare_solve
In 3025a14ed9, the call to the deprecated “luinc”
has been replaced by a call to “ilu”.
However, the type of “ilu” decomposition had not been specified. The default,
“nofill”, does not make use of the “droptol” option which was used with
“luinc”. Also, under Octave, it does not work when there is a zero on the
diagonal of the input matrix.
Rather use the “crout” type, which addresses these two issues.
These options were implemented and described in the reference manual, but their
interface was missing.
By the way, make various minor improvements to the description of “model_info”
in the reference manual. In particular, remove the single quotes around the two
aforementioned options (which are a remnant from an older interface).
The cherrypick was failing if the selected equations were not about a PAC equation (e.g. a VAR expectation
model), because the code was assuming the existence of the pac field in M_.
Also adjust the periods in Simulated_time_series (output of the perfect
foresight solver in the workspace). Note that this dseries object contains the
observations for the initial condition (M_.orig_maximum_lag observations) and
for the terminal condition (M_.orig_maximum_lead observations).
See #1838.
Fix testsuite (wrong file name)
Auxiliary variables were still present in the growth neutrality correction. This
commit remove the auxiliaries, so that the user doesn't need to update the
database with the auxiliary variable definitions.
Also adds integration test.
TODO Check that it works with log unary op
TODO Complete tests by checking that the written evaluate routine works
By the same token, improve the logical expression for determining whether all
values are infinite (it was nevertheless giving the right result, because an
“all()” is implicit when an array of booleans is passed to an “if” statement).
The print_expectations routine was previously only considering the
aggregate expectation (for the target). Now it updates the
database (dseries) with each component of the PAC model. The growth
neutrality correction is included in the aggregate expectation but not
in the expectations of the components.
Sébastien Villemot
Johannes Pfeifer
Stéphane Adjemian (Charybdis)
Marco Ratto
Willi Mutschler