Selecting seasonal filters in X-13-ARIMA via cross-validation

Daniel Ollech

No 16/2026, Discussion Papers from Deutsche Bundesbank

Abstract: Official statistics routinely employs the X-13-ARIMA method to seasonally adjust economic time series. A key step is choosing the length of the seasonal moving av- erage. Traditionally, this choice relies on ad hoc criteria and expert judgement. We propose a cross-validation-based filter selection scheme that offers greater flexibility, including the possibility of incorporating novel filters. This approach is particularly promising for the seasonal adjustment of weekly, daily, and high-frequency time series. We demonstrate how to integrate cross-validation into the X-13-ARIMA method and discuss the advantages of various implementation options. Evaluation on monthly and quarterly time series demonstrates that this selection method performs at least as well as, and often better than, conventional selection criteria.

Keywords: Seasonal adjustment; time series characteristics; non-parametric methods (search for similar items in EconPapers)
JEL-codes: C13 C14 C22 C53 (search for similar items in EconPapers)
Date: 2026
New Economics Papers: this item is included in nep-ets
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/341639/1/1973502143.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:bubdps:341639

DOI: 10.71734/DP-2026-16

Access Statistics for this paper

More papers in Discussion Papers from Deutsche Bundesbank Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().