Modelling circular time series
Andrew Harvey,
Stan Hurn,
Dario Palumbo and
Stephen Thiele
Journal of Econometrics, 2024, vol. 239, issue 1
Abstract:
Circular variables often play an important role in the construction of models for analysing and forecasting the consequences of climate change and its impact on the environment. Such variables pose special problems for time series modelling. This article shows how the score-driven approach, developed primarily in econometrics, provides a natural solution to the difficulties and leads to a coherent and unified methodology for estimation, model selection and testing. The new methods are illustrated with data on wind direction.
Keywords: Directional statistics; Dynamic conditional score model; Nonstationarity; von Mises distribution; Wind direction (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407623001446
Full text for ScienceDirect subscribers only
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:eee:econom:v:239:y:2024:i:1:s0304407623001446
DOI: 10.1016/j.jeconom.2023.02.016
Access Statistics for this article
Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson
More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().