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Aggregation of Seasonal Long-Memory Processes

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  • del Barrio Castro, Tomás
  • Rachinger, Heiko

Abstract

To understand the impact of temporal aggregation on the properties of a seasonal long-memory process, the effects of skip and cumulation sampling on both stationary and nonstationary processes with poles at several potential frequencies are analyzed. By allowing for several poles in the disaggregated process, their interaction in the aggregated series is investigated. Further, by defining the process according to the truncated Type II definition, the proposed approach encompasses both stationary and nonstationary processes without requiring prior knowledge of the case. The frequencies in the aggregated series to which the poles in the disaggregated series are mapped can be directly deduced. Specifically, unlike cumulation sampling, skip sampling can impact on non-seasonal memory properties. Moreover, with cumulation sampling, seasonal long-memory can vanish in some cases. Using simulations, the mapping of the frequencies implied by temporal aggregation is illustrated and the estimation of the memory at the different frequencies is analyzed.

Suggested Citation

  • del Barrio Castro, Tomás & Rachinger, Heiko, 2021. "Aggregation of Seasonal Long-Memory Processes," Econometrics and Statistics, Elsevier, vol. 17(C), pages 95-106.
  • Handle: RePEc:eee:ecosta:v:17:y:2021:i:c:p:95-106
    DOI: 10.1016/j.ecosta.2020.06.002
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    References listed on IDEAS

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    1. Tomás del Barrio Castro & Paulo M. M. Rodrigues & A. M. Robert Taylor, 2019. "Temporal Aggregation of Seasonally Near‐Integrated Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(6), pages 872-886, November.
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    Cited by:

    1. del Barrio Castro, Tomás & Osborn, Denise R., 2023. "Periodic Integration and Seasonal Unit Roots," MPRA Paper 117935, University Library of Munich, Germany, revised 2023.

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    More about this item

    Keywords

    Aggregation; Cumulation sampling; Skip sampling; Seasonal long memory;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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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