Higher-order improvements of the parametric bootstrap for long-memory Gaussian processes

DOI10.1016/j.jeconom.2005.06.010zbMath1345.62055OpenAlexW1970653570MaRDI QIDQ275259

Offer Lieberman, Vadim Marmer, Donald W. K. Andrews

Publication date: 25 April 2016

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jeconom.2005.06.010

zbMATH Keywords

confidence intervalsasymptoticsGaussian processmaximum likelihood estimatorlong memorydelta methodEdgeworth expansionparametric bootstrapWhittle likelihood\(t\) statistic

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Gaussian processes (60G15) Bootstrap, jackknife and other resampling methods (62F40)

Related Items (10)

Unnamed Item ⋮ A bootstrap approximation for the distribution of the local Whittle estimator ⋮ Properties of a block bootstrap under long-range dependence ⋮ BIAS CORRECTION OF SEMIPARAMETRIC LONG MEMORY PARAMETER ESTIMATORS VIA THE PREFILTERED SIEVE BOOTSTRAP ⋮ Block Bootstrap for the Empirical Process of Long‐Range Dependent Data ⋮ Bootstrap tests for fractional integration and cointegration: a comparison study ⋮ Using the bootstrap for finite sample confidence intervals of the log periodogram regression ⋮ Properties of the Sieve Bootstrap for Fractionally Integrated and Non-Invertible Processes ⋮ Bootstrap testing for discontinuities under long-range dependence ⋮ Higher-order improvements of the sieve bootstrap for fractionally integrated processes

Uses Software

• longmemo

Cites Work

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• Identification and Inference for Econometric Models
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