Estimation and testing stationarity for double-autoregressive models |
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Authors: | Shiqing Ling |
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Affiliation: | Hong Kong University of Science and Technology, People's Republic of China |
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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. |
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Keywords: | Asymptotic normality Brownian motion Consistency Double-autoregressive model Lagrange multiplier test Maximum likelihood estimator Stationarity |
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