TROLL - Impression.be

State of the art simulation methods:
• Standard backward (NEWTON, relaxation),
• Forward looking simulation (FAIR-
TAYLOR, stack-time),
• Simulate dynamic,
dynamic equation by equation,
static
semi-static,
• Losts of parameters to tune the simulation
progress, more possibilities to go
through non-convergence events.
With TROLL, just pay attention to the system
of equations and use all the integrated tools
available to you. It is simply beautiful: flexible,
efficient, with state of the art algorithms (see
below).
All kinds of simulations are possible: static every
period or ‘semi-static’, dynamic equationby-equation,
dynamic on the full system.
By switching from static to dynamic step-bystep,
you may avoid a lot of trouble in the
convergence process; therefore, you will save
time.
SofTwaRe/oVeRView
Optimisation
Advanced techniques to complement regressions and simulation
Find out the stability of you model’s parameters,
the best estimators of complex systems
by defining your own objective function. Optimising
on a maximum log-likelihood function
is possible and thanks to the TROLL Programming
Language, you will control any kind of
surrounding effects.
Efficiency:
• Intensive use of RAM for speed,
• Exogenise a variable in the simulation,
• Tools for model structure analysis,
• Selective storage of variables in databanks,
• DEFINITION to avoid preparing a database
for all symbols of the system.
Don’t forget TROLL also has a stochastic simulator.
Even if these kinds of simulations are
costly, both with regard to the volume of output
stored as well as RAM requirements, the
simulator is optimised enough in terms of performance
to make many exercises feasible on
your computer.
TROLL also contains a famous module for advanced
modellers, called LKROOTS. Its aim is
to perform eigenanalysis on a linearized version
of the model, for both backward and forward-looking
models. Analysis of the number
of roots and their modulus will indicate perhaps
an explosive growth mode on some variables
of a backward model, or, for a forward-looking
model, you will immediately verify if the system
follows the “Blanchard-Khan” condition.
This approach is for example applied in determining
a set of coefficients, where some
of them are constrained. The variance/covariance
matrix may be produced as an output
of the process. TROLL becomes a powerful research
environment.
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