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Nearly Efficient Likelihood Ratio Tests for Seasonal Unit Roots

Author

Listed:
  • Michael Jansson

    (UC Berkeley and CREATES)

  • Morten Ørregaard Nielsen

    (Queen's University and CREATES)

Abstract

In an important generalization of zero frequency autoregressive unit root tests, Hylleberg, Engle, Granger, and Yoo (1990) developed regression-based tests for unit roots at the seasonal frequencies in quarterly time series. We develop likelihood ratio tests for seasonal unit roots and show that these tests are "nearly efficient" in the sense of Elliott, Rothenberg, and Stock (1996), i.e. that their local asymptotic power functions are indistinguishable from the Gaussian power envelope. Currently available nearly efficient testing procedures for seasonal unit roots are regression-based and require the choice of a GLS detrending parameter, which our likelihood ratio tests do not.

Suggested Citation

  • Michael Jansson & Morten Ørregaard Nielsen, 2009. "Nearly Efficient Likelihood Ratio Tests for Seasonal Unit Roots," CREATES Research Papers 2009-55, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2009-55
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    Cited by:

    1. Jansson Michael & Nielsen Morten Ørregaard, 2011. "Nearly Efficient Likelihood Ratio Tests for Seasonal Unit Roots," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-21, February.
    2. Eroğlu, Burak Alparslan & Göğebakan, Kemal Çağlar & Trokić, Mirza, 2018. "Powerful nonparametric seasonal unit root tests," Economics Letters, Elsevier, vol. 167(C), pages 75-80.
    3. Skrobotov, Anton, 2018. "On bootstrap implementation of likelihood ratio test for a unit root," Economics Letters, Elsevier, vol. 171(C), pages 154-158.
    4. Samuel Brien & Michael Jansson & Morten Ørregaard Nielsen, 2022. "Nearly Efficient Likelihood Ratio Tests of a Unit Root in an Autoregressive Model of Arbitrary Order," Working Paper 1429, Economics Department, Queen's University.

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    Keywords

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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