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Tests Against Stationary and Explosive Alternatives in Vector Autoregressive Models

Author

Listed:
  • Ahlgren, Niklas

    (Swedish School of Economics and Business Administration)

  • Nyblom, Jukka

    (University of Joensuu)

Abstract

The article proposes new tests for the number of unit roots in vector autoregressive models based on the eigenvalues of the companion matrix. Both stationary and explosive alternatives are considered. The limiting distributions of test statistics depend only on the number of unit roots. Size and power are investigated and it is found that the new test against stationary alternatives compares favorably with the widely used likelihood ratio test for the cointegrating rank. The powers are prominently higher against explosive than stationary alternatives. Some empirical examples are provided to show how to use the new tests with real data.

Suggested Citation

  • Ahlgren, Niklas & Nyblom, Jukka, 2005. "Tests Against Stationary and Explosive Alternatives in Vector Autoregressive Models," Working Papers 511, Hanken School of Economics.
    • Handle: RePEc:hhb:hanken:0511
    Note: This paper is published as: Ahlgren, Niklas and Nyblom, Jukka (2008), 'Tests against Stationary and Explosive Alternatives in Vector Autoregressive Models', Journal of Time Series Analysis, 29, 421-443.
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    References listed on IDEAS

    as
    1. Nielsen, Bent, 2001. "The Asymptotic Distribution of Unit Root Tests of Unstable Autoregressive Processes," Econometrica, Econometric Society, vol. 69(1), pages 211-219, January.
    2. Katarina Juselius & Zorica Mladenovic, 2002. "High Inflation, Hyperinflation and Explosive Roots: The Case of Yugoslavia," Discussion Papers 02-23, University of Copenhagen. Department of Economics.
    3. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
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    More about this item

    Keywords

    Asymptotic local power; Cointegration; Companion matrix; Unit root;
    All these keywords.

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