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A Hybrid Bootstrap Approach To Unit Root Tests

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  • Guodong Li
  • Chenlei Leng
  • Chih-Ling Tsai

Abstract

type="main" xml:id="jtsa12019-abs-0001"> This article proposes a hybrid bootstrap approach to approximate the augmented Dickey–Fuller test by perturbing both the residual sequence and the minimand of the objective function. Since innovations can be dependent, this allows the inclusion of conditional heteroscedasticity models. The new bootstrap method is also applied to least absolute deviation-based unit root test statistics, which are efficient in handling heavy-tailed time-series data. The asymptotic distributions of resulting bootstrap tests are presented, and Monte Carlo studies demonstrate the usefulness of the proposed tests.

Suggested Citation

  • Guodong Li & Chenlei Leng & Chih-Ling Tsai, 2014. "A Hybrid Bootstrap Approach To Unit Root Tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(4), pages 299-321, July.
    • Handle: RePEc:bla:jtsera:v:35:y:2014:i:4:p:299-321
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    References listed on IDEAS

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    7. Zhenming Zhang & Shishun Zhao & Jianhua Cheng & Jiamin Li, 2025. "Conditional quantile estimation for GARCH model based on mixed-frequency data," Statistical Papers, Springer, vol. 66(4), pages 1-56, June.

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