Modelling circular time series

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, develope...

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Bibliographic Details
Published inJournal of econometrics Vol. 239; no. 1; p. 105450
Main Authors Harvey, Andrew, Hurn, Stan, Palumbo, Dario, Thiele, Stephen
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.02.2024
Subjects
Directional statistics
Dynamic conditional score model
Nonstationarity
von Mises distribution
Wind direction
Nonstationarity
Wind direction
C22
Dynamic conditional score model
Directional statistics
von Mises distribution
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Summary: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.
ISSN:0304-4076
1872-6895
DOI:10.1016/j.jeconom.2023.02.016