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A maximal moment inequality for long range dependent time series with applications to estimation and model selection

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Author Info
Ching-Kang Ing (Institute of Statistical Science, Academia Sinica)
Ching-Zong Wei (Institute of Statistical Science, Academia Sinica)

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Abstract

We establish a maximal moment inequality for the weighted sum of a long- range dependent process. An extension to H$\acute{a}$jek-R$\acute{e}$ny and Chow's type inequality is then obtained. It enables us to deduce a strong law for the weighted sum of a stationary long-range dependent time series. To illustrate its usefulness, applications of the inequality to estimation and model selection in multiple regression models with long-range dependent errors are given.

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File URL: http://129.3.20.41/eps/em/papers/0508/0508009.pdf
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Publisher Info
Paper provided by EconWPA in its series Econometrics with number 0508009.

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Length: 22 pages
Date of creation: 07 Aug 2005
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Handle: RePEc:wpa:wuwpem:0508009

Note: Type of Document - pdf; pages: 22
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Web page: http://129.3.20.41

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Related research
Keywords: Autoregressive fractionally integrated moving average long range dependence maximal inequality model selection convergence system strong consistency.

Find related papers by JEL classification:
C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General
C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
C5 - Mathematical and Quantitative Methods - - Econometric Modeling
C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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This page was last updated on 2008-8-11.

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