The Bootstrap of Mean for Dependent Heterogeneous Arrays

Silvia Goncalves () and Halbert White

Cahiers de recherche from Universite de Montreal, Departement de sciences economiques

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 ( 989) and Liu and Singh ( 992), and the stationary bootstrap of Politis and Romano ( 994). 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.

Keywords: block bootstra near ech dendence; same mean (search for similar items in EconPapers)
JEL-codes: C40 C42 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2001
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Citations: View citations in EconPapers (5)

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http://hdl.handle.net/1866/359 (application/pdf)

Related works:
Journal Article: THE BOOTSTRAP OF THE MEAN FOR DEPENDENT HETEROGENEOUS ARRAYS (2002)
Working Paper: The Bootstrap of the Mean for Dependent Heterogeneous Arrays (2001)
Working Paper: The Bootstrap of Mean for Dependent Heterogeneous Arrays (2001)
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Persistent link: https://EconPapers.repec.org/RePEc:mtl:montde:2001-19

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