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Modelling circular time series☆
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DOI：10.1016/j.jeconom.2023.02.016.png)
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Abstract
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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. (c) 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords:
Directional statistics
Dynamic conditional score model
Nonstationarity
von Mises distribution
Wind direction
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