Wavelets and estimation of long memory in nonstationary models: Does anything beat the exact local whittle estimator?

In this article, we analyze the performance of five estimation methods for the long memory parameter d. The goal of our article is to construct a wavelet estimate for the fractional differencing parameter in nonstationary long memory processes that dominate the well-known estimate of Shimotsu and Ph...

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Bibliographic Details
Published in:Communications in statistics. Simulation and computation 2017-02, Vol.46 (2), p.1189-1218
Main Authors: Boubaker, H., Boutahar, M., Khalfaoui, R.
Format: Article
Language:English
Subjects:
Computer simulation
Economic models
Estimates
Estimating techniques
Estimators
Long memory
Mathematical models
Mathematics
Nonstationary models
Parameter estimation
Parameters
Statistics
Tapering
Wavelet
Wavelets
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Summary:In this article, we analyze the performance of five estimation methods for the long memory parameter d. The goal of our article is to construct a wavelet estimate for the fractional differencing parameter in nonstationary long memory processes that dominate the well-known estimate of Shimotsu and Phillips (2005) . The simulation results show that the wavelet estimation method of Lee (2005) with several tapering techniques performs better under most cases in nonstationary long memory. The comparison is based on the empirical root mean squared error of each estimate.
ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2014.995814