TY  - JOUR
AU  - Judd,Kenneth
AU  - Maliar,Lilia
AU  - Maliar,Serguei
TI  - Numerically Stable Stochastic Simulation Approaches for Solving Dynamic Economic Models
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 15296
PY  - 2009
Y2  - August 2009
UR  - http://www.nber.org/papers/w15296
L1  - http://www.nber.org/papers/w15296.pdf
N1  - Author contact info:
Kenneth L. Judd
Hoover Institution
Stanford University
Stanford, CA  94305-6010
Tel: 650/723-5866
Fax: 650/723-1687
E-Mail: kennethjudd@mac.com

Lilia Maliar
Office T-24 Hoover Institution
Stanford University
CA 94305-6010, USA
Tel: 6507253416
Fax: 6507231687
E-Mail: maliarl@stanford.edu

Serguei Maliar
Office T-24 Hoover Institution
Stanford University
CA 94305-6010, USA
Tel: 6507253416
Fax: 6507231687
E-Mail: maliars@stanford.edu
AB  - 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.
ER  -