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Nearly Efficient Likelihood Ratio Tests of the Unit Root Hypothesis

Author

Listed:
  • Jansson, Michael
  • AYrregaard Nielsen, Morten

Abstract

Seemingly absent from the arsenal of currently available "nearly efficient" testing procedures for the unit root hypothesis, i.e. tests whose asymptotic local power functions are virtually indistinguishable from the Gaussian power envelope, is a test admitting a (quasi-)likelihood ratio interpretation. We study the large sample properties of a quasi-likelihood ratio unit root test based on a Gaussian likelihood and show that this test is nearly efficient.

Suggested Citation

  • Jansson, Michael & AYrregaard Nielsen, Morten, 2009. "Nearly Efficient Likelihood Ratio Tests of the Unit Root Hypothesis," Queen's Economics Department Working Papers 273699, Queen's University - Department of Economics.
  • Handle: RePEc:ags:quedwp:273699
    DOI: 10.22004/ag.econ.273699
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    Cited by:

    1. is not listed on IDEAS
    2. Maggie E. C. Jones & Morten Ørregaard Nielsen & Michał Ksawery Popiel, 2014. "A fractionally cointegrated VAR analysis of economic voting and political support," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 47(4), pages 1078-1130, November.
    3. 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.
    4. Bo Zhou, 2023. "Semiparametrically Optimal Cointegration Test," Papers 2305.08880, arXiv.org.
    5. Petrenko, Victoria (Петренко, ВИктория) & Skrobotov, Anton (Скроботов, Антон) & Turuntseva, Maria (Турунцева, Мария), 2016. "Testing of Changes in Persistence and Their Effect on the Forecasting Quality [Тестирование Изменения Инерционности И Влияние На Качество Прогнозов]," Working Papers 542, Russian Presidential Academy of National Economy and Public Administration.
    6. Bent Jesper Christensen & Robinson Kruse & Philipp Sibbertsen, 2013. "A unified framework for testing in the linear regression model under unknown order of fractional integration," CREATES Research Papers 2013-35, Department of Economics and Business Economics, Aarhus University.
    7. Mehdi Hosseinkouchack & Uwe Hassler, 2016. "Powerful Unit Root Tests Free of Nuisance Parameters," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(4), pages 533-554, July.
    8. Skrobotov, Anton, 2018. "On bootstrap implementation of likelihood ratio test for a unit root," Economics Letters, Elsevier, vol. 171(C), pages 154-158.
    9. Popiel Michal Ksawery, 2017. "Interest rate pass-through: a nonlinear vector error-correction approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(5), pages 1-20, December.
    10. repec:rnp:ppaper:skr001 is not listed on IDEAS
    11. Boswijk, H. Peter & Jansson, Michael & Nielsen, Morten Ørregaard, 2015. "Improved likelihood ratio tests for cointegration rank in the VAR model," Journal of Econometrics, Elsevier, vol. 184(1), pages 97-110.
    12. Gaowen Wang, 2017. "Modified Unit Root Tests with Nuisance Parameter Free Asymptotic Distributions," Methodology and Computing in Applied Probability, Springer, vol. 19(2), pages 519-538, June.
    13. Zhou, Bo, 2024. "Semiparametrically optimal cointegration test," Journal of Econometrics, Elsevier, vol. 242(2).
    14. Walter Distaso & Rustam Ibragimov & Alexander Semenov & Anton Skrobotov, 2020. "COVID-19: Tail Risk and Predictive Regressions," Papers 2009.02486, arXiv.org, revised Oct 2021.
    15. James Morley & Irina B. Panovska & Tara M. Sinclair, 2014. "Testing Stationarity for Unobserved Components Models," Discussion Papers 2012-41B, School of Economics, The University of New South Wales.
    16. Hernández Juan R., 2016. "Unit Root Testing in ARMA Models: A Likelihood Ratio Approach," Working Papers 2016-03, Banco de México.
    17. 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.
    18. Hernández, Juan R., 2016. "Unit Root Testing in ARMA Models: A Likelihood Ratio Approach," MPRA Paper 100857, University Library of Munich, Germany.

    More about this item

    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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