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Comparisons of robust tests for shifts in trend with an application to trend deviations of real exchange rates in the long run

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  • Sungju Chun
  • Pierre Perron

Abstract

We study the finite sample properties of tests for structural changes in the trend function of a time series that do not require knowledge of the degree of persistence in the noise component. The tests of interest are the quasi-Feasible Generalized Least Squares (FGLS) procedure by Perron and Yabu (2009b) and the weighted average of the regression t -statistics by Harvey et al . (2009), both of which have the same limit distribution whether the noise component is stationary or has a unit-root. We analyse the finite sample size and power properties of these tests under a variety of Data-Generating Processes (DGPs). The results show that the Perron--Yabu test has greater power overall. With respect to the size, the Harvey--Leybourne--Taylor test exhibits larger size distortions unless a moving-average component is present. Using the Perron and Yabu procedure to test for structural changes in the trend function of long-run real exchange rates with respect to the US dollar indicates that for 17 out of 19 countries, the series have experienced a shift in trend since the late nineteenth century.

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  • Sungju Chun & Pierre Perron, 2013. "Comparisons of robust tests for shifts in trend with an application to trend deviations of real exchange rates in the long run," Applied Economics, Taylor & Francis Journals, vol. 45(24), pages 3512-3528, August.
    • Handle: RePEc:taf:applec:v:45:y:2013:i:24:p:3512-3528
    DOI: 10.1080/00036846.2012.724160
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    Cited by:

    1. Paraskevi Salamaliki, 2015. "Economic Policy Uncertainty and Economic Activity: A Focus on Infrequent Structural Shifts," Working Paper Series of the Department of Economics, University of Konstanz 2015-08, Department of Economics, University of Konstanz.
    2. Kurozumi Eiji, 2015. "Testing for Multiple Structural Changes with Non-Homogeneous Regressors," Journal of Time Series Econometrics, De Gruyter, vol. 7(1), pages 1-35, January.
    3. Nuno Sobreira & Luis C. Nunes, 2016. "Tests for Multiple Breaks in the Trend with Stationary or Integrated Shocks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(3), pages 394-411, June.
    4. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Papers 1805.03807, arXiv.org.
    5. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    6. Ioanna Konstantakopoulou, 2017. "The aggregate exports-GDP relation under the prism of infrequent trend breaks and multi-horizon causality," International Economics and Economic Policy, Springer, vol. 14(4), pages 661-689, October.

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