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A Generalized Block Bootstrap For Seasonal Time Series

Author

Listed:
  • Anna E. Dudek
  • Jacek Leśkow
  • Efstathios Paparoditis
  • Dimitris N. Politis

Abstract

type="main" xml:id="jtsa12053-abs-0001"> When time-series data contain a periodic/seasonal component, the usual block bootstrap procedures are not directly applicable. We propose a modification of the block bootstrap – the generalized seasonal block bootstrap (GSBB) – and show its asymptotic consistency without undue restrictions on the relative size of the period and block size. Notably, it is exactly such restrictions that limit the applicability of other proposals of block bootstrap methods for time series with periodicities. The finite-sample performance of the GSBB is also illustrated by means of a small simulation experiment.

Suggested Citation

  • Anna E. Dudek & Jacek Leśkow & Efstathios Paparoditis & Dimitris N. Politis, 2014. "A Generalized Block Bootstrap For Seasonal Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(2), pages 89-114, March.
    • Handle: RePEc:bla:jtsera:v:35:y:2014:i:2:p:89-114
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    File URL: http://hdl.handle.net/10.1002/jtsa.12053
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    Citations

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    Cited by:

    1. Politis, Dimitris, 2016. "HEGY test under seasonal heterogeneity," University of California at San Diego, Economics Working Paper Series qt2q4054kf, Department of Economics, UC San Diego.
    2. Daniel Dzikowski & Carsten Jentsch, 2024. "Structural Periodic Vector Autoregressions," Papers 2401.14545, arXiv.org.
    3. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2017. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
    4. Leprince, Julien & Schledorn, Amos & Guericke, Daniela & Dominkovic, Dominik Franjo & Madsen, Henrik & Zeiler, Wim, 2023. "Can occupant behaviors affect urban energy planning? Distributed stochastic optimization for energy communities," Applied Energy, Elsevier, vol. 348(C).
    5. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2016. "Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach," CREATES Research Papers 2016-27, Department of Economics and Business Economics, Aarhus University.
    6. Zou, Nan & Politis, Dimitris N., 2021. "Bootstrap seasonal unit root test under periodic variation," Econometrics and Statistics, Elsevier, vol. 19(C), pages 1-21.

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