Empirical likelihood confidence intervals for the mean of a long-range dependent process
AbstractThis paper considers blockwise empirical likelihood for real-valued linear time processes which may exhibit either short- or long-range dependence. Empirical likelihood approaches intended for weakly dependent time series can fail in the presence of strong dependence. However, a modified blockwise method is proposed for confidence interval estimation of the process mean, which is valid for various dependence structures including long-range dependence. The finite-sample performance of the method is evaluated through a simulation study and compared to other confidence interval procedures involving subsampling or normal approximations.
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Bibliographic InfoPaper provided by Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät in its series Hannover Economic Papers (HEP) with number dp-327.
Length: 26 pages
Date of creation: Nov 2005
Date of revision:
blocking; confidence interval; empirical likelihood; FARIMA; long-range dependence;
Other versions of this item:
- Daniel J. Nordman & Philipp Sibbertsen & Soumendra N. Lahiri, 2007. "Empirical likelihood confidence intervals for the mean of a long-range dependent process," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(4), pages 576-599, 07.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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