Identification of the differencing operator of a non-stationary time series via testing for zeroes in the spectral density

Tucker McElroy*, Agnieszka Jach

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

A nonparametric procedure for identifying the differencing operator of a non-stationary time series is presented and tested. Any proposed differencing operator is first applied to the time series, and the spectral density is tested for zeroes corresponding to the polynomial roots of the operator. A nonparametric tapered spectral density estimator is used, and the subsampling methodology is applied to obtain critical values. Simulations explore the effectiveness of the procedure under a variety of scenarios involving non-stationary processes.
Original languageEnglish
Article number107580
Peer-reviewed scientific journalComputational Statistics & Data Analysis
Volume177
ISSN0167-9473
DOIs
Publication statusPublished - 29.07.2022
MoE publication typeA1 Journal article - refereed

Keywords

  • 112 Statistics and probability
  • seasonality
  • subsampling
  • unit roots

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