Empirical likelihood confidence intervals for the mean of a long-range dependent process
This 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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- James Davidson & Philipp Sibbertsen, 2008.
"Tests of Bias in Log-Periodogram Regression,"
0805, Exeter University, Department of Economics.
- Lahiri, S. N., 1993. "On the moving block bootstrap under long range dependence," Statistics & Probability Letters, Elsevier, vol. 18(5), pages 405-413, December.
- Donald W.K. Andrews & Yixiao Sun, 2002.
"Adaptive Local Polynomial Whittle Estimation of Long-range Dependence,"
Cowles Foundation Discussion Papers
1384, Cowles Foundation for Research in Economics, Yale University.
- Donald W. K. Andrews & Yixiao Sun, 2004. "Adaptive Local Polynomial Whittle Estimation of Long-range Dependence," Econometrica, Econometric Society, vol. 72(2), pages 569-614, 03.
- ANDREWS, DONALD W & Sun, Yixiao X, 2002. "Adaptive Local Polynomial Whittle Estimation of Long-Range Dependence," University of California at San Diego, Economics Working Paper Series qt9wt048tt, Department of Economics, UC San Diego.
- Nordman, Daniel J. & Lahiri, Soumendra N., 2005. "Validity Of The Sampling Window Method For Long-Range Dependent Linear Processes," Econometric Theory, Cambridge University Press, vol. 21(06), pages 1087-1111, December.
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