Solving the Stochastic Growth Model by Policy-Function Iteration
描述了一种计算机算法，通过迭代决策规则中的不动点方程来求解随机增长模型，该算法不离散化状态空间，而是保留资本存量和生产率冲击的连续域，适用于无法由中央计划者求解的动态经济。
This article describes a computer algorithm that solves the stochastic growth model by iterating on a fixed-point equation in the decision rule determining consumption as a function of the state variables. This algorithm does not discretize the state space, but rather it preserves the continuous domain of the capital stock and the productivity shock. The main advantage of this algorithm is that it is based on a Euler equation and thus it has a straightforward generalization to dynamic economies that cannot be solved by a central planner, such as a non-Pareto optimal competitive economy.