Economics at your fingertips  


Frédéric Docquier () and Philippe Ligeois
Additional contact information
Philippe Ligeois: ECARES, Universite Libre de Bruxelles, Belgium

No 246, Computing in Economics and Finance 2000 from Society for Computational Economics

Abstract: In this paper, we examine the performance of the Troll Stacked- time algorithm in the simulation of large scale overlapping generations (OLG) models. At each period of time, the number of equations is proportional to the individual length of lifetime. The model size and the data requirements may thus be very large. Given the repetitive structure of the equations, we show how Troll specific macrocommands can be used to explode a generic version (in which the lifetime is parameterized) into a complete model. A similar technique applies to explode the initial dataset on the whole simulation horizon. The stability properties of the model are derived and the Stacked-time algorithm performances are checked for a large scale model with endogenous labour supply and uncertain lifetime. It turns out that Troll performances are very attractive even for a system of 300000 simultaneous equations."

Date: 2000-07-05
References: Add references at CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Working Paper: Simulating computable overlapping generations models with TROLL (2004)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in Computing in Economics and Finance 2000 from Society for Computational Economics CEF 2000, Departament d'Economia i Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas, 25,27, 08005, Barcelona, Spain. Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().

Page updated 2019-05-29
Handle: RePEc:sce:scecf0:246