Limit theory for moderate deviations from a unit root

被引:256
作者
Phillips, Peter C. B. [1 ]
Magdalinos, Tassos
机构
[1] Yale Univ, Cowles Fdn Res Econ, New Haven, CT 06520 USA
[2] Univ Auckland, Auckland 1, New Zealand
[3] Univ York, York YO10 5DD, N Yorkshire, England
基金
英国工程与自然科学研究理事会; 美国国家科学基金会;
关键词
central limit theory; explosive autoregression; local to unity; moderate deviations; unit root distribution;
D O I
10.1016/j.jeconom.2005.08.002
中图分类号
F [经济];
学科分类号
02 ;
摘要
An asymptotic theory is given for autoregressive time series with a root of the form p(n) = 1 + c/k(n), which represents moderate deviations from unity when (k(n))(n is an element of N) is a deterministic sequence increasing to infinity at a rate slower than n, so that k(n) = o(n) as n -> infinity. For c < 0, the results provide a root nk(n) rate of convergence and asymptotic normality for the first order serial correlation, partially bridging the root n and n convergence rates for the stationary (k(n) = 1) and conventional local to unity (k(n) = n) cases. For c > 0, the serial correlation coefficient is shown to have a k(n)rho(n)(n) convergence rate and a Cauchy limit distribution without assuming Gaussian errors, so an invariance principle applies when p(n) > 1. This result links moderate deviation asymptotics to earlier results on the explosive autoregression proved under Gaussian errors for k(n) = 1, where the convergence rate of the serial correlation coefficient is (1 + c)(n) and no invariance principle applies. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:115 / 130
页数:16
相关论文
共 11 条
[1]   STOPPING TIMES AND TIGHTNESS [J].
ALDOUS, D .
ANNALS OF PROBABILITY, 1978, 6 (02) :335-340
[2]   ON ASYMPTOTIC DISTRIBUTIONS OF ESTIMATES OF PARAMETERS OF STOCHASTIC DIFFERENCE-EQUATIONS [J].
ANDERSON, TW .
ANNALS OF MATHEMATICAL STATISTICS, 1959, 30 (03) :676-687
[3]   ASYMPTOTIC CONDITIONAL INFERENCE FOR REGULAR NONERGODIC MODELS WITH AN APPLICATION TO AUTOREGRESSIVE PROCESSES [J].
BASAWA, IV ;
BROCKWELL, PJ .
ANNALS OF STATISTICS, 1984, 12 (01) :161-171
[4]   ASYMPTOTIC INFERENCE FOR NEARLY NONSTATIONARY AR(1) PROCESSES [J].
CHAN, NH ;
WEI, CZ .
ANNALS OF STATISTICS, 1987, 15 (03) :1050-1063
[5]  
GIRAITIS L, 2006, IN PRESS J TIME SERI
[6]  
Kallenberg O, 2002, FDN MODERN PROBABILI
[7]  
PARK JY, 2003, UNPUB WEAK UNIT ROOT
[8]  
PHILLIPS PCB, 1987, BIOMETRIKA, V74, P535, DOI 10.2307/2336692
[9]  
PHILLIPS PCB, 2005, 1471 YAL U
[10]  
Pollard D., 2012, Convergence of Stochastic Processes