The Effects of Additive Outliers and Measurement Errors when Testing for Structural Breaks in Variance

Paulo Rodrigues and Antonio Rubia

Working Papers from Banco de Portugal, Economics and Research Department

Abstract: This paper discusses the asymptotic and finite-sample properties of CUSUM-based tests for detecting structural breaks in volatility in the presence of stochastic contamination, such as additive outliers or measurement errors. This analysis is particularly relevant for financial data, on which these tests are commonly used to detect variance breaks. In particular, we focus on the tests by Inclán and Tiao [IT] (1994) and Kokoszka and Leipus [KL] (1998, 2000), which have been intensively used in the applied literature. Our results are extensible to related procedures. We show that the asymptotic distribution of the IT test can largely be affected by sample contamination, whereas the distribution of the KL test remains invariant. Furthermore, the break-point estimator of the KL test renders consistent estimates. In spite of the good large-sample properties of this test, large additive outliers tend to generate power distortions or wrong break-date estimates in small samples.

JEL-codes: C12 C15 C52 (search for similar items in EconPapers)
Date: 2010
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.bportugal.pt/sites/default/files/anexos/papers/wp201011.pdf

Related works:
Journal Article: The Effects of Additive Outliers and Measurement Errors when Testing for Structural Breaks in Variance (2011)
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:ptu:wpaper:w201011

Access Statistics for this paper

More papers in Working Papers from Banco de Portugal, Economics and Research Department Contact information at EDIRC.
Bibliographic data for series maintained by DEE-NTD ().