Author:
Gonçalves Sílvia,White Halbert
Abstract
Presently, conditions ensuring the validity of bootstrap methods
for the sample mean of (possibly heterogeneous) near epoch
dependent (NED) functions of mixing processes are unknown. Here
we establish the validity of the bootstrap in this context,
extending the applicability of bootstrap methods to a class
of processes broadly relevant for applications in economics
and finance. Our results apply to two block bootstrap methods:
the moving blocks bootstrap of Künsch (1989, Annals
of Statistics 17, 1217–1241) and Liu and Singh (1992,
in R. LePage & L. Billiard (eds.), Exploring the Limits
of the Bootstrap, 224–248) and the stationary bootstrap
of Politis and Romano (1994a, Journal of the American
Statistical Association 89, 1303–1313). In particular,
the consistency of the bootstrap variance estimator for the
sample mean is shown to be robust against heteroskedasticity
and dependence of unknown form. The first-order asymptotic validity
of the bootstrap approximation to the actual distribution of
the sample mean is also established in this heterogeneous NED
context.
Publisher
Cambridge University Press (CUP)
Subject
Economics and Econometrics,Social Sciences (miscellaneous)
Cited by
71 articles.
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