Simulating computable overlapping generations models with troll

摘要

In this note, we examine the performance of Troll new 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 individuals' lifetime. The model size and the data requirements may thus be very large. Given the repetitive structure of the model equations, it is possible to explode a generic version of them and the initial dataset, using a macrofile in which the time horizon and the lifetime are completely parameterized. We provide a generic instance of such a model and useful macrofiles for a basic consumption model. The Stacked-time algorithm performances are checked for this basic model as well as for a very large scale model with endogenous labour supply and uncertain lifetime. It turns out that Troll performances are very attractive even for a system with more than 300000 simultaneous equations (600 equations × 500 periods).