Sieve Bootstrap for Strongly Dependent Stationary Processes

George Kapetanios and Zacharias Psaradakis

No 552, Working Papers from Queen Mary University of London, School of Economics and Finance

Abstract: This paper studies the properties of the sieve bootstrap for a class of linear processes which exhibit strong dependence. The sieve bootstrap scheme is based on residual resampling from autoregressive approximations the order of which increases slowly with the sample size. The first-order asymptotic validity of the sieve bootstrap is established in the case of the sample mean and sample autocovariances. The finite-sample properties of the method are also investigated by means of Monte Carlo experiments.

Keywords: Autoregressive approximation; Linear process; Strong dependence; Sieve bootstrap; Stationary process (search for similar items in EconPapers)
JEL-codes: C10 C22 C50 (search for similar items in EconPapers)
Date: 2006-01-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.qmul.ac.uk/sef/media/econ/research/wor ... 2006/items/wp552.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:qmw:qmwecw:552

Access Statistics for this paper

More papers in Working Papers from Queen Mary University of London, School of Economics and Finance Contact information at EDIRC.
Bibliographic data for series maintained by Nicholas Owen ( this e-mail address is bad, please contact ).