Efficient likelihood evaluation of state-space representations

David DeJong (), Hariharan Dharmarajan, Roman Liesenfeld, Guilherme Moura () and Jean-Francois Richard

No 2009-02, Economics Working Papers from Christian-Albrechts-University of Kiel, Department of Economics

Abstract: We develop a numerical procedure that facilitates efficient likelihood evaluation in applications involving non-linear and non-Gaussian state-space models. The procedure approximates necessary integrals using continuous approximations of target densities. Construction is achieved via efficient importance sampling, and approximating densities are adapted to fully incorporate current information. We illustrate our procedure in applications to dynamic stochastic general equilibrium models.

Keywords: particle filter; adaption; efficient importance sampling; kernel density approximation; dynamic stochastic general equilibrium model (search for similar items in EconPapers)
Date: 2009
New Economics Papers: this item is included in nep-cba, nep-dge, nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/27737/1/598700846.PDF (application/pdf)

Related works:
Journal Article: Efficient Likelihood Evaluation of State-Space Representations (2013)
Working Paper: Efficient Likelihood Evaluation of State-Space Representations (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:cauewp:200902

Access Statistics for this paper

More papers in Economics Working Papers from Christian-Albrechts-University of Kiel, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().