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Valid Edgeworth expansion of the bootstrap t-statistic of the Whittle MLE for linear regression models with long-memory residuals. (English) Zbl 07892655

Summary: In this paper we provide a valid Edgeworth expansion of the parametric bootstrap t-statistic for the Whittle maximum likelihood estimator of a linear regression time series model whose residuals are stationary, Gaussian, and long-memory. Under some sets of conditions on the spectral density function and the parametric values, an Edgeworth expansion of the bootstrap t-statistic of arbitrarily large order of the model is established to have an error of \(o(n^{1-s/2})\), where \(s \geq 3\) is a positive integer. The result is obtained by extending the Edgeworth expansion obtained by Andrew et al. (2006), which was established for the parametric bootstrap t-statistic of the same model without the linear regression component.

MSC:

62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
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