Solving a particular growth model by linear quadratic approximation and by value function iteration

This paper studies the accuracy of two versions of the procedure proposed by Kydland and Prescott (1980, 1982) for approximating the optional decision rules in problems in which the objective fails to be quadratic and the constraints linear. The analysis is carried out in the context of a particular example: 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 the value function iteration procedures described in Bertsekas (1976). I find that the Kydland-Prescott approximate decision rules are very similar to those implied by value function iteration.