Mean and autocovariance function estimation near the boundary of stationarity

被引：6

作者：

Giraitis, Liudas ^{[1
]}

Phillips, Peter C. B. ^{[2
,3
,4
,5
]}

机构：

[1] Queen Mary Univ London, London, England

[2] Yale Univ, New Haven, CT 06520 USA

[3] Univ Auckland, Auckland 1, New Zealand

[4] Univ Southampton, Southampton SO9 5NH, Hants, England

[5] Singapore Management Univ, Singapore, Singapore

来源：

JOURNAL OF ECONOMETRICS | 2012年 / 169卷 / 02期

基金：

美国国家科学基金会;

关键词：

Asymptotic normality; Integrated periodogram; Linear process; Local to unity; Localizing coefficient; LIMIT THEORY; ASYMPTOTIC THEORY;

D O I：

10.1016/j.jeconom.2012.01.020

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

We analyze the applicability of standard normal asymptotic theory for linear process models near the boundary of stationarity. Limit results are given for estimation of the mean, autocovariance and autocorrelation functions within the broad region of stationarity that includes near boundary cases which vary with the sample size. The rate of consistency and the validity of the normal asymptotic approximation for the corresponding estimators is determined both by the sample size n and a parameter measuring the proximity of the model to the unit root boundary. (C) 2012 Elsevier B.V. All rights reserved.

引用

页码：166 / 178

页数：13

共 16 条

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Bartlett M.S., 1955, INTRO STOCHASTIC PRO

[2] Approximations and limit theory for quadratic forms of linear processes [J].