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    A sieve bootstrap test for stationarity

    Psaradakis, Zacharias (2003) A sieve bootstrap test for stationarity. Statistics and Probability Letters 62 (3), pp. 263-274. ISSN 0167-7152.

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    This paper proposes a bootstrap test for testing the null hypothesis that a time series is stationary against the alternative hypothesis that it is integrated of order one. Our approach makes use of a sieve bootstrap scheme based on residual resampling from autoregressive approximations the order of which increases with the sample size at a suitable rate. The first-order asymptotic correctness of the sieve bootstrap for testing the stationarity hypothesis is established for a subclass of linear processes. The small-sample properties of the method are also investigated by means of Monte Carlo experiments.


    Item Type: Article
    School: Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School
    Depositing User: Sarah Hall
    Date Deposited: 21 Jul 2020 08:53
    Last Modified: 02 Aug 2023 18:01


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