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Testing for a unit root in a time series with mean shifts

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  • Param Silvapulle

Abstract

The study considers the ADF and KPSS tests for unit root testing in a time series characterized by a number of structural changes in its mean. Using the Monte Carlo simulation method the percentage points of the tests distributions are estimated. These two tests are biased towards non-rejection of the unit root. The bias of these tests appears to increase as the number of breaks in the series increases. The overall results in the study indicate that when a time series is subjected to a number of changes, provided the appropriate critical values are used, the unit root tests can erroneously reject the hypothesis of unit root. The tabulated critical values can be used in hypothesis testing.

Suggested Citation

  • Param Silvapulle, 1996. "Testing for a unit root in a time series with mean shifts," Applied Economics Letters, Taylor & Francis Journals, vol. 3(10), pages 629-635.
    • Handle: RePEc:taf:apeclt:v:3:y:1996:i:10:p:629-635
    DOI: 10.1080/135048596355826
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    1. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    2. Christiano, Lawrence J, 1992. "Searching for a Break in GNP," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 237-250, July.
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    Cited by:

    1. Surajit Deb, 2003. "Terms of Trade and Supply Response of Indian Agriculture: Analysis in Cointegration Framework," Working papers 115, Centre for Development Economics, Delhi School of Economics.
    2. Deb, Surajit, 2004. "Terms of Trade and Investment Behaviour in Indian Agriculture: A Cointegration Analysis," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 59(2), pages 1-22.

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