Rank test of unit‐root hypothesis with AR‐GARCH errors

Guili Liao, Qimeng Liu, Rongmao Zhang and Shifang Zhang

Journal of Time Series Analysis, 2022, vol. 43, issue 5, 695-719

Abstract: A robust rank test based on the regression rank score process is proposed to test the unit‐root hypothesis under linear GARCH noises in this article. It is shown that the limit distribution of the rank test is a function of a stable process and a Brownian motion. The finite sample studies indicate that the proposed test statistic exhibits a reliable size and a remarkable power under a variety of tail index α, and performs better than other unit‐root tests based on least square procedure, such as the augmented Dick Fuller (ADF) and the Phillips–Perron (PP) tests.

Date: 2022
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https://doi.org/10.1111/jtsa.12635

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