Solving the Stochastic Growth Model by Using a Recursive Mapping Based on Least Squares Projection
提出一种基于线性最小二乘投影算子的递归映射方法，用于求解标准随机增长模型的均衡解，使期末状态的边际估值满足正交条件。
A method to solve a standard version of a stochastic growth model is described. The method uses the equilibrium first-order condition (a Euler equation) and the linear least squares projection operator to construct a recursive mapping to compute the solution. At the solution, the marginal valuation of the end-of-period state (a dual price) satisfies certain orthogonality conditions.