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The Bootstrap of Mean for Dependent Heterogeneous Arrays

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  • GONÇALVES, Silvia
  • 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 ( 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.

Suggested Citation

  • GONÇALVES, Silvia & WHITE, Halbert, 2001. "The Bootstrap of Mean for Dependent Heterogeneous Arrays," Cahiers de recherche 2001-19, Universite de Montreal, Departement de sciences economiques.
    • Handle: RePEc:mtl:montde:2001-19
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    File URL: http://hdl.handle.net/1866/359
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    References listed on IDEAS

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    More about this item

    Keywords

    block bootstra near ech dendence; same mean;

    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

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