Numerically Stable Stochastic Simulation Approaches for Solving Dynamic Economic Models / Kenneth Judd, Lilia Maliar, Serguei Maliar.

Format:

Book

Author/Creator:

Judd, Kenneth.

Contributor:

National Bureau of Economic Research.

Maliar, Lilia.

Maliar, Serguei.

Series:

Working Paper Series (National Bureau of Economic Research) no. w15296.

NBER working paper series no. w15296

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2009.

Summary:

We develop numerically stable stochastic simulation approaches for solving dynamic economic models. We rely on standard simulation procedures to simultaneously compute an ergodic distribution of state variables, its support and the associated decision rules. We differ from existing methods, however, in how we use simulation data to approximate decision rules. Instead of the usual least-squares approximation methods, we examine a variety of alternatives, including the least-squares method using SVD, Tikhonov regularization, least-absolute deviation methods, principal components regression method, all of which are numerically stable and can handle ill-conditioned problems. These new methods enable us to compute high-order polynomial approximations without encountering numerical problems. Our approaches are especially well suitable for high-dimensional applications in which other methods are infeasible.

Notes:

Print version record

August 2009.