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Testing For Trend Stationarity Versus Difference Stationarity

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  • Consuelo Arellano
  • Sastry G. Pantula

Abstract

. Testing the null hypothesis that a process is difference stationary has received considerable attention in the past decade. Recently, there has been some interest in testing the null hypothesis that a process is a sum of a linear trend and a stationary invertible noise sequence. In this paper we present procedures for testing the null hypothesis that a process is trend stationary against the alternative that the process is difference stationary. A Monte Carlo study is presented to study the behavior of the proposed test criteria. Average global temperature data are used to illustrate the test criteria.

Suggested Citation

  • Consuelo Arellano & Sastry G. Pantula, 1995. "Testing For Trend Stationarity Versus Difference Stationarity," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(2), pages 147-164, March.
    • Handle: RePEc:bla:jtsera:v:16:y:1995:i:2:p:147-164
    DOI: 10.1111/j.1467-9892.1995.tb00227.x
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    References listed on IDEAS

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    1. Pantula, Sastry G., 1989. "Testing for Unit Roots in Time Series Data," Econometric Theory, Cambridge University Press, vol. 5(2), pages 256-271, August.
    2. John Y. Campbell & N. Gregory Mankiw, 1987. "Are Output Fluctuations Transitory?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(4), pages 857-880.
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    7. T. W. Anderson & Akimichi Takemura, 1986. "Why Do Noninvertible Estimated Moving Averages Occur?," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(4), pages 235-254, July.
    8. Tanaka, Katsuto, 1990. "Testing for a Moving Average Unit Root," Econometric Theory, Cambridge University Press, vol. 6(4), pages 433-444, December.
    9. Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
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    Cited by:

    1. Kurozumi, Eiji, 2009. "Construction of Stationarity Tests with Less Size Distortions," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 50(1), pages 87-105, June.
    2. Sun, Hongguang & Pantula, Sastry G., 1999. "Testing for trends in correlated data," Statistics & Probability Letters, Elsevier, vol. 41(1), pages 87-95, January.
    3. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871.

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