Change search
ReferencesLink to record
Permanent link

Direct link
Testing Seasonal Unit Roots in Data at Any Frequency, an HEGY approach
Dalarna University, School of Technology and Business Studies, Statistics.ORCID iD: 0000-0003-2970-9622
Dalarna University, School of Technology and Business Studies, Statistics.
2012 (English)Report (Other academic)
Abstract [en]

This paper generalizes the HEGY-type test to detect seasonal unit roots in data at any frequency, based on the seasonal unit root tests in univariate time series by Hylleberg, Engle, Granger and Yoo (1990). We introduce the seasonal unit roots at first, and then derive the mechanism of the HEGY-type test for data with any frequency. Thereafter we provide the asymptotic distributions of our test statistics when different test regressions are employed. We find that the F-statistics for testing conjugation unit roots have the same asymptotic distributions. Then we compute the finite-sample and asymptotic critical values for daily and hourly data by a Monte Carlo method. The power and size properties of our test for hourly data is investigated, and we find that including lag augmentations in auxiliary regression without lag elimination have the smallest size distortion and tests with seasonal dummies included in auxiliary regression have more power than the tests without seasonal dummies. At last we apply the our test to hourly wind power production data in Sweden and shows there are no seasonal unit roots in the series.

Place, publisher, year, edition, pages
2012. , 34 p.
Working papers in transport, tourism, information technology and microdata analysis, ISSN 1650-5581 ; 08
Keyword [en]
HEGY test, Any Frequency, Seasonlity, Seasonal Unit Root, Asymptotic distribution of F-statistics
National Category
Probability Theory and Statistics
Research subject
Komplexa system - mikrodataanalys, General Microdata Analysis - methods
URN: urn:nbn:se:du-11399OAI: diva2:574806
Available from: 2012-12-10 Created: 2012-12-06 Last updated: 2015-05-07Bibliographically approved

Open Access in DiVA

fulltext(473 kB)1725 downloads
File information
File name FULLTEXT02.pdfFile size 473 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Meng, XiangliHe, Changli
By organisation
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar
Total: 1725 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 607 hits
ReferencesLink to record
Permanent link

Direct link