Economics at your fingertips  

Can the SupLR test discriminate between different switching

Lanouar Charfeddine ()

International Finance from University Library of Munich, Germany

Abstract: In recent years two classes of switching models have been proposed, the Markov switching models, Hamilton (1989) and the Threshold Auto- Regressive Models (TAR), Lim and Tong (1980). These two models have the advantage of being able to modelize and capture asymmetry, sudden changes and irreversibility time observed in many economic and financial time series. Despite these similarities and common points, these models have been envolved, in the literature, largely independently. In this paper, using the $SupLR$ test, we study the possibility of discrimination between these two models. This approach is motivated by the fact that the majority of authors, in applications, use switching models without any statistical justification. We show that when the null hypothesis is rejected it appears that different switching models are significant. Then, using simulation experiments we show that it is very difficult to differenciate between MSAR and SETAR models specially with large samples. The power of the $SupLR$ test seems to be sensitive to the mean, the noise variance and the delay parameter which appear in each model. Finally, we apply this methodology to the US GNP growth rate and the US/UK exchange rate.

Keywords: Switching Models; SETAR processes SupLR test; Empirical power; exchange rates (search for similar items in EconPapers)
JEL-codes: C12 C15 F31 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2005-11-04
Note: Type of Document - pdf; pages: 26
References: Add references at CitEc
Citations Track citations by RSS feed

Downloads: (external link) (application/pdf)

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:

Access Statistics for this paper

More papers in International Finance from University Library of Munich, Germany
Bibliographic data for series maintained by EconWPA ().

Page updated 2019-01-19
Handle: RePEc:wpa:wuwpif:0511002