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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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    3. Ke Zhu, 2016. "Bootstrapping the portmanteau tests in weak auto-regressive moving average models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 463-485, March.
    4. Good, Clara, 2016. "Environmental impact assessments of hybrid photovoltaic–thermal (PV/T) systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 234-239.
    5. Guo, Shaojun & Li, Dong & Li, Muyi, 2019. "Strict stationarity testing and GLAD estimation of double autoregressive models," Journal of Econometrics, Elsevier, vol. 211(2), pages 319-337.

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