Projection methods for solving aggregate growth models

We describe a general numerical approach, the projection method, to solve operator equations which arise in economic models. Principles from numerical analysis are then used to develop efficient implementations of the projection method for solving aggregate growth models. Since any numerical approach will involve error, we derive error measures which are related to optimization errors by agents and argue that the numerical approximations can be viewed as equilibria with boundedly rational agents. The results are programs which run hundreds of times faster than competing methods in the literature while achieving high accuracy.