Robustness of alternative non-linearity tests for SETAR models

Man-Wai Ng and Wai-Sum Chan
Additional contact information
Man-Wai Ng: Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong, Postal: Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong
Wai-Sum Chan: Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong, Postal: Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong

Journal of Forecasting, 2004, vol. 23, issue 3, 215-231

Abstract: In recent years there has been a growing interest in exploiting potential forecast gains from the non-linear structure of self-exciting threshold autoregressive (SETAR) models. Statistical tests have been proposed in the literature to help analysts check for the presence of SETAR-type non-linearities in an observed time series. It is important to study the power and robustness properties of these tests since erroneous test results might lead to misspecified prediction problems. In this paper we investigate the robustness properties of several commonly used non-linearity tests. Both the robustness with respect to outlying observations and the robustness with respect to model specification are considered. The power comparison of these testing procedures is carried out using Monte Carlo simulation. The results indicate that all of the existing tests are not robust to outliers and model misspecification. Finally, an empirical application applies the statistical tests to stock market returns of the four little dragons (Hong Kong, South Korea, Singapore and Taiwan) in East Asia. The non-linearity tests fail to provide consistent conclusions most of the time. The results in this article stress the need for a more robust test for SETAR-type non-linearity in time series analysis and forecasting. Copyright © 2004 John Wiley & Sons, Ltd.

Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://hdl.handle.net/10.1002/for.915 Link to full text; subscription required (text/html)

Related works:
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:jof:jforec:v:23:y:2004:i:3:p:215-231

DOI: 10.1002/for.915

Access Statistics for this article

Journal of Forecasting is currently edited by Derek W. Bunn

More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().