The University of Southampton
University of Southampton Institutional Repository

Nonparametric specification testing for nonlinear time series with nonstationarity

Nonparametric specification testing for nonlinear time series with nonstationarity
Nonparametric specification testing for nonlinear time series with nonstationarity
This paper considers a nonparametric time series regression model with a nonstationary regressor. We construct a nonparametric test for whether the regression is of a known parametric form indexed by a vector of unknown parameters. We establish the asymptotic distribution of the proposed test statistic. Both the setting and the results differ from earlier work on nonparametric time series regression with stationarity. In addition, we develop a bootstrap simulation scheme for the selection of suitable bandwidth parameters involved in the kernel test as well as the choice of simulated critical values. An example of implementation is given to show that the proposed test works in practice.
1869-1892
Gao, Jiti
fb907009-eef0-4e30-aca7-b484324f4955
King, Maxwell
412b549a-8886-4346-84ec-5bfab1081eaa
Lu, Zudi
4aa7d988-ac2b-4150-a586-ca92b8adda95
Tjøstheim, Dag
13b95e48-8f1f-44e8-95dd-8527a1897ff6
Gao, Jiti
fb907009-eef0-4e30-aca7-b484324f4955
King, Maxwell
412b549a-8886-4346-84ec-5bfab1081eaa
Lu, Zudi
4aa7d988-ac2b-4150-a586-ca92b8adda95
Tjøstheim, Dag
13b95e48-8f1f-44e8-95dd-8527a1897ff6

Gao, Jiti, King, Maxwell, Lu, Zudi and Tjøstheim, Dag (2009) Nonparametric specification testing for nonlinear time series with nonstationarity. Econometric Theory, 25 (6), 1869-1892. (doi:10.1017/S0266466609990363).

Record type: Article

Abstract

This paper considers a nonparametric time series regression model with a nonstationary regressor. We construct a nonparametric test for whether the regression is of a known parametric form indexed by a vector of unknown parameters. We establish the asymptotic distribution of the proposed test statistic. Both the setting and the results differ from earlier work on nonparametric time series regression with stationarity. In addition, we develop a bootstrap simulation scheme for the selection of suitable bandwidth parameters involved in the kernel test as well as the choice of simulated critical values. An example of implementation is given to show that the proposed test works in practice.

This record has no associated files available for download.

More information

Published date: 2009
Organisations: Mathematical Sciences

Identifiers

Local EPrints ID: 360466
URI: http://eprints.soton.ac.uk/id/eprint/360466
PURE UUID: 9c2caf29-057d-483e-b526-e851dcdc0c65
ORCID for Zudi Lu: ORCID iD orcid.org/0000-0003-0893-832X

Catalogue record

Date deposited: 10 Dec 2013 11:59
Last modified: 15 Mar 2024 03:49

Export record

Altmetrics

Contributors

Author: Jiti Gao
Author: Maxwell King
Author: Zudi Lu ORCID iD
Author: Dag Tjøstheim

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×