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On the Behaviour of Phillips–Perron Tests in the Presence of Persistent Cycles

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Listed:
  • Tomás Del Barrio Castro
  • Paulo M. M. Rodrigues
  • A. M. Robert Taylor

Abstract

type="main" xml:id="obes12091-abs-0001"> In this paper, we analyse the impact of persistent cycles on the well-known semi-parametric unit root tests of Phillips and Perron (1988, Biometrika, Vol. 75, pp. 335–346). It is shown, both analytically and through Monte Carlo simulations, that the presence of complex (near) unit roots can severely bias the size properties of these tests. Given the popularity of these tests with applied researchers and their routine presence in most econometric software packages, the results presented in this paper suggest that practitioners should treat the outcomes of these tests with some caution when applied to data which display a strong cyclical component.

Suggested Citation

  • Tomás Del Barrio Castro & Paulo M. M. Rodrigues & A. M. Robert Taylor, 2015. "On the Behaviour of Phillips–Perron Tests in the Presence of Persistent Cycles," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(4), pages 495-511, August.
    • Handle: RePEc:bla:obuest:v:77:y:2015:i:4:p:495-511
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    File URL: http://hdl.handle.net/10.1111/obes.2015.77.issue-4
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Unit Root Tests and Seasonally Adjusted Data
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2014-09-13 01:03:00

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    Cited by:

    1. Benedict Belobo Ateba & Johannes Jurgens Prinsloo, 2018. "The Electricity Security in South Africa: Analysing Significant Determinants to the Grid Reliability," International Journal of Energy Economics and Policy, Econjournals, vol. 8(6), pages 70-79.
    2. Hwang, Jen-Te & Wen, Min, 2024. "Electronic payments and money demand in China," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 47-64.
    3. Yii, Kwang-Jing & Tan, Chai-Thing & Ho, Wing-Ken & Kwan, Xiao-Hui & Nerissa, Feng-Ting Shim & Tan, Yan-Yi & Wong, Kar-Horn, 2022. "Land availability and housing price in China: Empirical evidence from nonlinear autoregressive distributed lag (NARDL)," Land Use Policy, Elsevier, vol. 113(C).
    4. Koutmos, Dimitrios, 2019. "Asset pricing factors and bank CDS spreads," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 19-41.
    5. Dimitrios Koutmos, 2018. "Interdependencies between CDS spreads in the European Union: Is Greece the black sheep or black swan?," Annals of Operations Research, Springer, vol. 266(1), pages 441-498, July.
    6. Ricardo Quineche & Gabriel Rodríguez, 2017. "Selecting the Lag Length for the M GLS Unit Root Tests with Structural Change: A Warning Note for Practitioners Based on Simulations," Econometrics, MDPI, vol. 5(2), pages 1-10, April.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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