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On the Distribution of the Break-Date Estimator Implied by the Perron-Type Statistics When the Form of Break is Misspecified

Author

Listed:
  • Amit Sen

    () (Xavier University)

Abstract

Montañés, Olloqui, and Calvo (2005, Journal of Econometrics) argue that use of the Perron-type minimum t-statistics will lead the practitioner to incorrectly assess the time series properties of the variable under investigation when the form of break is misspecified. However, their simulations do not provide insight into the distribution of the estimated break-date implied by the unknown break-date Perron-type statistics when the form of break is misspecified. Using finite sample simulations, we show that the break-date implied by the Mixed model will tend to estimate the break-date consistently even when the form of break is misspecified. The practitioner should, therefore, use the Mixed model as the appropriate trend-break stationary alternative when testing for a unit root with an endogenous break-date.

Suggested Citation

  • Amit Sen, 2007. "On the Distribution of the Break-Date Estimator Implied by the Perron-Type Statistics When the Form of Break is Misspecified," Economics Bulletin, AccessEcon, vol. 3(6), pages 1-19.
  • Handle: RePEc:ebl:ecbull:eb-06c20065
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    References listed on IDEAS

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    1. Banerjee, Anindya & Lumsdaine, Robin L & Stock, James H, 1992. "Recursive and Sequential Tests of the Unit-Root and Trend-Break Hypotheses: Theory and International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 271-287, July.
    2. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    3. Perron, Pierre, 1997. "Further evidence on breaking trend functions in macroeconomic variables," Journal of Econometrics, Elsevier, vol. 80(2), pages 355-385, October.
    4. Montanes, Antonio & Olloqui, Irene & Calvo, Elena, 2005. "Selection of the break in the Perron-type tests," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 41-64.
    5. 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.
    6. Monta s, Antonio & Reyes, Marcelo, 1998. "Effect Of A Shift In The Trend Function On Dickey Fuller Unit Root Tests," Econometric Theory, Cambridge University Press, vol. 14(03), pages 355-363, June.
    7. Vogelsang, Timothy J & Perron, Pierre, 1998. "Additional Tests for a Unit Root Allowing for a Break in the Trend Function at an Unknown Time," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 1073-1100, November.
    8. Perron, Pierre & Vogelsang, Timothy J, 1992. "Nonstationarity and Level Shifts with an Application to Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 301-320, July.
    9. 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.
    10. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    11. Sen, Amit, 2003. "On Unit-Root Tests When the Alternative Is a Trend-Break Stationary Process," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 174-184, January.
    12. Montañés, Antonio & Reyes, Marcelo, 1999. "The asymptotic behaviour of the Dickey-Fuller tests under the crash hypothesis," Statistics & Probability Letters, Elsevier, vol. 42(1), pages 81-89, March.
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    More about this item

    Keywords

    Break-Date;

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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