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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

Author

Listed:
  • Pierre Perron

    (Department of Economics, Boston University)

  • Sungju Chun

    (Department of Economics, Boston University)

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 procedure by Perron and Yabu (2009b) and the weighted average of the regression t-statistics by Harvey, Leybourne and Taylor (2009), both of which have the same limit distribution whether the noise component is stationary or has a unit-root. We analyze the finite sample size and power properties of these tests under a variety of data-generating processes. The results show that the Perron-Yabu test has greater power overall. With respect to 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 U.S. dollar indicate that for 17 out of 19 countries the series have experienced a shift in trend since the late nineteenth centrury.

Suggested Citation

  • Pierre Perron & Sungju Chun, 2011. "Comparisons of Robust Tests for Shifts in Trend with an Application to Trend Deviations of Real Exchange Rates in the Long Run," Boston University - Department of Economics - Working Papers Series WP2011-056, Boston University - Department of Economics.
    • Handle: RePEc:bos:wpaper:wp2011-056
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    Cited by:

    1. Anton Skrobotov, 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.
    2. 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.
    3. 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.
    4. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Papers 1805.03807, arXiv.org.
    5. 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.
    6. 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.

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