Bootstrap long memory processes in the frequency domain

Hidalgo, Javier (2021) Bootstrap long memory processes in the frequency domain. Annals of Statistics, 49 (3). 1407 - 1435. ISSN 0090-5364

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Abstract

The aim of the paper is to describe a bootstrap, contrary to the sieve boot- strap, valid under either long memory (LM) or short memory (SM) depen- dence. One of the reasons of the failure of the sieve bootstrap in our context is that under LM dependence, the sieve bootstrap may not be able to capture the true covariance structure of the original data. We also describe and ex- amine the validity of the bootstrap scheme for the least squares estimator of the parameter in a regression model and for model specification. The moti- vation for the latter example comes from the observation that the asymptotic distribution of the test is intractable.

Item Type:	Article
Official URL:	https://projecteuclid.org/euclid.aos
Additional Information:	© 2021 Institute of Mathematical Statistics
Divisions:	Economics
Subjects:	H Social Sciences > HB Economic Theory H Social Sciences > HA Statistics
Date Deposited:	13 Aug 2020 08:18
Last Modified:	16 Nov 2024 00:12
URI:	http://eprints.lse.ac.uk/id/eprint/106149

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