Solving the Stochastic Growth Model by Deterministic Extended Path
介绍用确定性扩展路径算法求解简单随机增长模型，讨论两种近似误差来源，发现数值迭代误差小，但期望处理误差在特定情形下也小。
This article describes the use of the deterministic version of the extended-path algorithm to solve the simple stochastic growth model. The article also discusses the two sources of approximation error inherent in this method. It is demonstrated that the error due to numerical iterations is small. No general conclusion can be reached on the error that arises from the algorithm's treatment of expectations. In at least two specific cases, however, this error appears to be small.