Tempered Particle Filtering

Edward Herbst and Frank Schorfheide

No 23448, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: The accuracy of particle filters for nonlinear state-space models crucially depends on the proposal distribution that mutates time t-1 particle values into time t values. In the widely-used bootstrap particle filter, this distribution is generated by the state-transition equation. While straightforward to implement, the practical performance is often poor. We develop a self-tuning particle filter in which the proposal distribution is constructed adaptively through a sequence of Monte Carlo steps. Intuitively, we start from a measurement error distribution with an inflated variance, and then gradually reduce the variance to its nominal level in a sequence of tempering steps. We show that the filter generates an unbiased and consistent approximation of the likelihood function. Holding the run time fixed, our filter is substantially more accurate in two DSGE model applications than the bootstrap particle filter.

JEL-codes: C11 C32 E32 (search for similar items in EconPapers)
Date: 2017-05
New Economics Papers: this item is included in nep-dcm, nep-ets and nep-mac
Note: EFG ME
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Published as Edward Herbst & Frank Schorfheide, 2018. "Tempered particle filtering," Journal of Econometrics, .

Downloads: (external link)
http://www.nber.org/papers/w23448.pdf (application/pdf)

Related works:
Journal Article: Tempered particle filtering (2019)
Working Paper: Tempered Particle Filtering (2016)
Working Paper: Tempered Particle Filtering (2016)
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:nbr:nberwo:23448

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w23448

Access Statistics for this paper

More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().