Solving the Stochastic Growth Model by Linear-Quadratic Approximation

1 January 1990

journal article
research article
Published by Taylor & Francis in Journal of Business & Economic Statistics

Vol. 8 (1) , 41-44
https://doi.org/10.1080/07350015.1990.10509774

Abstract

I describe a method that can be used to approximate the solution of the stochastic growth model. The method relies on approximating the return and transition functions of the original problem by taking second-order and first-order Taylor expansions around the steady state of the system. The result is the optimal linear regulator problem.

Keywords

ALGORITHMS
OPTIMAL CONTROL
RICCATI EQUATION

This publication has 3 references indexed in Scilit:

Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods
Journal of Business & Economic Statistics, 1990
Time to Build and Aggregate Fluctuations
Econometrica, 1982
A nonrecursive algebraic solution for the discrete Riccati equation
IEEE Transactions on Automatic Control, 1970