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Stochastic level shifts and outliers and the dynamics of oil price movements

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  • Trimbur, Thomas M.

Abstract

Oil prices clearly play an important role in the macroeconomy. The dynamics of oil prices have, however, been difficult to pin down because of the frequent occurrence of large shocks. In this paper, we propose a time series model with heavy-tailed disturbances to analyze the dynamics of the oil price. The model has the form of a generalized local linear trend, and we show that it successfully captures outliers and level shifts as empirical regularities in the oil price, including known historical price shocks. Further, the results of a forecast exercise are given, and we study extensions that examine the effect of the GDP cycle on the oil price.

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  • Trimbur, Thomas M., 2010. "Stochastic level shifts and outliers and the dynamics of oil price movements," International Journal of Forecasting, Elsevier, vol. 26(1), pages 162-179, January.
    • Handle: RePEc:eee:intfor:v:26:y::i:1:p:162-179
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    References listed on IDEAS

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    Cited by:

    1. Tucker McElroy & Thomas Trimbur, 2015. "Signal Extraction for Non-Stationary Multivariate Time Series with Illustrations for Trend Inflation," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(2), pages 209-227, March.
    2. Yu, Lean & Zhao, Yaqing & Tang, Ling & Yang, Zebin, 2019. "Online big data-driven oil consumption forecasting with Google trends," International Journal of Forecasting, Elsevier, vol. 35(1), pages 213-223.
    3. Cosentino, Valentina & Favuzza, Salvatore & Graditi, Giorgio & Ippolito, Mariano Giuseppe & Massaro, Fabio & Riva Sanseverino, Eleonora & Zizzo, Gaetano, 2012. "Smart renewable generation for an islanded system. Technical and economic issues of future scenarios," Energy, Elsevier, vol. 39(1), pages 196-204.

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