Estimation and testing stationarity for double-autoregressive models

被引:97
|
作者
Ling, SQ [1 ]
机构
[1] Hong Kong Univ Sci & Technol, Dept Math, Hong Hom, Hong Kong, Peoples R China
关键词
asymptotic normality; Brownian motion; consistency; double-autoregressive model; Lagrange multiplier test; maximum likelihood estimator; stationarity;
D O I
10.1111/j.1467-9868.2004.00432.x
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The paper considers the double-autoregressive model y(t) = phiy(t-1)+epsilon(t) with epsilon(t) = eta(t) root(omega + alphay(t-1)(2)). Consistency and asymptotic normality of the estimated parameters are proved under the condition E ln |phi +rootalphaeta(t)|<0, which includes the cases with |phi|=1 or |phi|>1 as well as E(epsilon(t)(2)) = infinity. It is well known that all kinds of estimators of phi in these cases are not normal when epsilon(t) are independent and identically distributed. Our result is novel and surprising. Two tests are proposed for testing stationarity of the model and their asymptotic distributions are shown to be a function of bivariate Brownian motions. Critical values of the tests are tabulated and some simulation results are reported. An application to the US 90-day treasury bill rate series is given.
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页码:63 / 78
页数:16
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