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Modelling circular time series

Author

Listed:
  • Harvey, Andrew
  • Hurn, Stan
  • Palumbo, Dario
  • Thiele, Stephen

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.

Suggested Citation

  • Harvey, Andrew & Hurn, Stan & Palumbo, Dario & Thiele, Stephen, 2024. "Modelling circular time series," Journal of Econometrics, Elsevier, vol. 239(1).
    • Handle: RePEc:eee:econom:v:239:y:2024:i:1:s0304407623001446
    DOI: 10.1016/j.jeconom.2023.02.016
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    More about this item

    Keywords

    Directional statistics; Dynamic conditional score model; Nonstationarity; von Mises distribution; Wind direction;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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