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A simple, robust and powerful test of the trend hypothesis

  • Harvey, David I.
  • Leybourne, Stephen J.
  • Taylor, A.M. Robert

In this paper we develop a simple test procedure for a linear trend which does not require knowledge of the form of serial correlation in the data, is robust to strong serial correlation, and has a standard normal limiting null distribution under either I(0) or I(1) shocks. In contrast to other available robust linear trend tests, our proposed test achieves the Gaussian asymptotic local power envelope in both the I(0) and I(1) cases. For near- I(1) errors our proposed procedure is conservative and a modification for this situation is suggested. An estimator of the trend parameter, together with an associated confidence interval, which is asymptotically efficient, again regardless of whether the shocks are I(0) or I(1), is also provided.

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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 141 (2007)
Issue (Month): 2 (December)
Pages: 1302-1330

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Handle: RePEc:eee:econom:v:141:y:2007:i:2:p:1302-1330
Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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  1. Helle Bunzel & Timothy Vogelsang, 2003. "Powerful Trend Function Tests That are Robust to Strong Serial Correlation with an Application to the Prebisch Singer Hypothesis," Econometrics 0304002, EconWPA.
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  12. Perron, P., 1986. "Trends and Random Walks in Macroeconomic Time Series: Further Evidence From a New Approach," Cahiers de recherche 8650, Universite de Montreal, Departement de sciences economiques.
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  14. Grilli, Enzo R & Yang, Maw Cheng, 1988. "Primary Commodity Prices, Manufactured Goods Prices, and the Terms of Trade of Developing Countries: What the Long Run Shows," World Bank Economic Review, World Bank Group, vol. 2(1), pages 1-47, January.
  15. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
  16. Benedikt M. Pötscher, 1999. "Lower Risk Bounds and Properties of Confidence Sets For Ill-Posed Estimation Problems with Applications to Spectral Density and Persistence Estimation, Unit Roots,and Estimation of Long Memory Paramet," Vienna Economics Papers 0202, University of Vienna, Department of Economics.
  17. Jansson, Michael, 2002. "Consistent Covariance Matrix Estimation For Linear Processes," Econometric Theory, Cambridge University Press, vol. 18(06), pages 1449-1459, December.
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