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Estimation and testing stationarity for double-autoregressive models
Authors:Shiqing Ling
Affiliation:Hong Kong University of Science and Technology, People's Republic of China
Abstract:
Summary.  The paper considers the double-autoregressive model y t  =  φ y t −1+ ɛ t with ɛ t  =     . Consistency and asymptotic normality of the estimated parameters are proved under the condition E  ln | φ  +√ α η t |<0, which includes the cases with | φ |=1 or | φ |>1 as well as     . It is well known that all kinds of estimators of φ in these cases are not normal when ɛ 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.
Keywords:Asymptotic normality    Brownian motion    Consistency    Double-autoregressive model    Lagrange multiplier test    Maximum likelihood estimator    Stationarity
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