Numerical Distribution Functions for Seasonal Unit Root Tests

Ignacio Díaz-Emparanza

No 1134-8984, BILTOKI from Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística)

Abstract: When working with time series data observed at intervals smaller than a year, it is often necessary to test for the presence of seasonal unit roots. One of the most widely used methods for testing seasonal unit roots is that of HEGY, which provides test statistics with non-standard distributions. This paper describes a generalisation of this method for any periodicity and uses a response surface regressions approach to calculate the critical values and P values of the HEGY statistics whatever the periodicity and sample size of the data. The algorithms are prepared with the Gretl open source econometrics package and some new tables of critical values for daily, hourly and half-hourly data are presented.

Keywords: seasonality; unit roots; surface response analysis (search for similar items in EconPapers)
Date: 2011-12
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: View citations in EconPapers (1)

Downloads: (external link)
https://addi.ehu.eus/handle/10810/5568 (application/pdf)

Related works:
Journal Article: Numerical distribution functions for seasonal unit root tests (2014)
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:ehu:biltok:5568

Ordering information: This working paper can be ordered from
Dpto. de Econometría y Estadística, Facultad de CC. Económicas y Empresariales, Universidad del País Vasco, Avda. Lehendakari Aguirre 83, 48015 Bilbao, Spain

Access Statistics for this paper

More papers in BILTOKI from Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística) Contact information at EDIRC.
Bibliographic data for series maintained by Alcira Macías ().