Creator: Christiano, Lawrence J. Series: Working paper (Federal Reserve Bank of Minneapolis. Research Department) Number: 415 Abstract:
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 the Kydland-Prescott approximate decision rules are very similar to those implied by value-function iteration.
关键词: Production function, Optimization, Growth model, Markov chain, State space, and Decision rule 学科: C40 - Econometric and Statistical Methods: Special Topics: General
Creator: McGrattan, Ellen R. Series: Staff report (Federal Reserve Bank of Minneapolis. Research Department) Number: 164 Abstract:
Since it is the dominant paradigm of the business cycle and growth literatures, the stochastic growth model has been used to test the performance of alternative numerical methods. This paper applies the finite element method to this example. I show that the method is easy to apply and, for examples such as the stochastic growth method, gives accurate solutions within a second or two on a desktop computer. I also show how inequality constraints can be handled by redefining the optimization problem with penalty functions.
关键词: Growth model and Finite element method 学科: C68 - Computable General Equilibrium Models and C63 - Computational Techniques; Simulation Modeling