Linear-Quadratic Approximation and Value-Function Iteration: A Comparison
比较了Kydland和Prescott的线性二次近似方法与值函数迭代法在非线性和非二次型经济模型中的准确性，发现两者得出的决策规则非常相似。
This article studies the accuracy of two versions of Kydland and Prescott's (1980, 1982) procedure for approximating optimal decision rules in problems in which the objective fails to be quadratic and the constraints fail to be linear. The analysis is carried out using a version of the Brock–Mirman (1972) model of optimal economic growth. Although the model is not linear quadratic, its solution can, nevertheless, be computed with arbitrary accuracy using a variant of existing value-function iteration procedures. I find that the Kydland–Prescott approximate decision rules are very similar to those implied by value-function iteration.