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Deterministic Seasonality In Dickey-Fuller Tests: Should We Care?

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  • Artur Da Silva Lopes

Abstract

This paper investigates the properties of Dickey-Fuller tests for seasonally unadjusted quarterly data when deterministic seasonality is present but it is neglected in the test regression. While for the random walk case the answer is straightforward, an extensive Monte Carlo study has to be performed for more realistic processes and testing strategies. The most important conclusion is that the common perception that deterministic seasonality has nothing to do with the long-run properties of the data is incorrect. Further numerical evidence on the shortcomings of the general-to-specific t-sig lag selection method is also presented.
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Suggested Citation

  • Artur Da Silva Lopes, 2004. "Deterministic Seasonality In Dickey-Fuller Tests: Should We Care?," Royal Economic Society Annual Conference 2004 75, Royal Economic Society.
    • Handle: RePEc:ecj:ac2004:75
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    Cited by:

    1. van Goor, Harm & Scholtens, Bert, 2014. "Modeling natural gas price volatility: The case of the UK gas market," Energy, Elsevier, vol. 72(C), pages 126-134.
    2. Deman, Laureen & Boucher, Quentin, 2023. "Impact of renewable energy generation on power reserve energy demand," Energy Economics, Elsevier, vol. 128(C).
    3. Matei Demetrescu & Uwe Hassler, 2007. "Effect of neglected deterministic seasonality on unit root tests," Statistical Papers, Springer, vol. 48(3), pages 385-402, September.
    4. B. da Silva Lopes, Artur C., 2005. "Finite sample effects of pure seasonal mean shifts on Dickey-Fuller tests," MPRA Paper 125, University Library of Munich, Germany, revised May 2006.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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