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Tests against stationary and explosive alternatives in vector autoregressive models

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  • Niklas Ahlgren
  • Jukka Nyblom

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 some stationary alternatives compares favourably with the widely used likelihood ratio test for the cointegrating rank. The powers are prominently higher against explosive than against stationary alternatives. Some empirical examples are provided to show how to use the new tests with real data.

Suggested Citation

  • Niklas Ahlgren & Jukka Nyblom, 2008. "Tests against stationary and explosive alternatives in vector autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(3), pages 421-443, May.
    • Handle: RePEc:bla:jtsera:v:29:y:2008:i:3:p:421-443
    DOI: 10.1111/j.1467-9892.2007.00560.x
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Ai, Xiaohui & Li, Wenbo V. & Liu, Guoqing, 2012. "Karhunen–Loeve expansions for the detrended Brownian motion," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1235-1241.
    2. Niklas Ahlgren & Mikael Juselius, 2012. "Tests for cointegration rank and the initial condition," Empirical Economics, Springer, vol. 42(3), pages 667-691, June.
    3. Nyblom, Jukka & Suomala, Jaakko, 2014. "Tests for real and complex unit roots in vector autoregressive models," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 224-239.
    4. Kaddour Hadri & Eiji Kurozumi & Daisuke Yamazaki, 2015. "Synergy between an Improved Covariate Unit Root Test and Cross-sectionally Dependent Panel Data Unit Root Tests," Manchester School, University of Manchester, vol. 83(6), pages 676-700, December.

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