Nonlinear and Non-Gaussian State-Space Modeling with Monte-Carlo Simulations

Author

Roberto S. Mariano, Singapore Management UniversityFollow
Hisashi Tanizaki

Publication Type

Journal Article

Publication Date

1998

Abstract

We propose two nonlinear and nonnormal filters based on Monte Carlo simulation techniques. In terms of programming and computational requirements both filters are more tractable than other nonlinear filters that use numerical integration, Monte Carlo integration with importance sampling or Gibbs sampling. The proposed filters are extended to prediction and smoothing algorithms. Monte Carlo experiments are carried out to assess the statistical merits of the proposed filters.

Discipline

Economics

Research Areas

Econometrics

Publication

Journal of Econometrics

Volume

83

Issue

1-2

First Page

263

Last Page

290

ISSN

0304-4076

Identifier

10.1016/s0304-4076(97)80226-6

Publisher

Elsevier

Citation

Mariano, Roberto S. and Tanizaki, Hisashi. Nonlinear and Non-Gaussian State-Space Modeling with Monte-Carlo Simulations. (1998). Journal of Econometrics. 83, (1-2), 263-290.
Available at: https://ink.library.smu.edu.sg/soe_research/272

Additional URL

https://doi.org/10.1016/s0304-4076(97)80226-6