Extending the Range of Validity of the Autoregressive (Sieve) Bootstrap

Maria Fragkeskou and Efstathios Paparoditis

Journal of Time Series Analysis, 2018, vol. 39, issue 3, 356-379

Abstract: Two modifications of the autoregressive†sieve and of the autoregressive bootstrap are proposed. The first modification replaces the classical i.i.d. resampling scheme applied to the residuals of the autoregressive fit by the generation of i.i.d. wild pseudo†innovations that appropriately mimic to the appropriate extent, also the fourth†order moment structure of the true innovations driving the underlying linear process. This modification extends the validity of the autoregressive†sieve bootstrap to classes of statistics for which the classical residual†based autoregressive†sieve bootstrap fails. In the second modification, an autoregressive bootstrap applied to an appropriately transformed time series is proposed, which, together with a dependent wild†type generation of pseudo†innovations, delivers a bootstrap procedure that is valid for large classes of statistics and for stochastic processes satisfying quite general, weak, dependent conditions. A fully data†driven selection of the bootstrap parameters involved in both modifications is proposed, and extensive simulations, including comparisons with alternative bootstrap methods, show a good finite sample performance of the proposed bootstrap procedures.

Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1111/jtsa.12275

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:bla:jtsera:v:39:y:2018:i:3:p:356-379

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0143-9782

Access Statistics for this article

Journal of Time Series Analysis is currently edited by M.B. Priestley

More articles in Journal of Time Series Analysis from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().