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Exponential smoothing and spurious correlation: a note

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  • Keith Blackburn
  • Felipe Orduna
  • Martin Sola

Abstract

Exponential smoothing can introduce spurious auto-correlation in detrended data. The extent of this depends on the length of lag, the value of the smoothing parameter and the nature of the input process. The most widely-used version of exponential smoothing is the Hodrick-Prescott low-frequency filter.

Suggested Citation

  • Keith Blackburn & Felipe Orduna & Martin Sola, 1995. "Exponential smoothing and spurious correlation: a note," Applied Economics Letters, Taylor & Francis Journals, vol. 2(3), pages 76-79.
  • Handle: RePEc:taf:apeclt:v:2:y:1995:i:3:p:76-79
    DOI: 10.1080/135048595357618
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    References listed on IDEAS

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    1. Backus, David K & Kehoe, Patrick J, 1992. "International Evidence of the Historical Properties of Business Cycles," American Economic Review, American Economic Association, vol. 82(4), pages 864-888, September.
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    Cited by:

    1. Tawadros, George B., 2011. "The stylised facts of Australia's business cycle," Economic Modelling, Elsevier, vol. 28(1), pages 549-556.
    2. Galimberti, Jaqueson K. & Moura, Marcelo L., 2016. "Improving the reliability of real-time output gap estimates using survey forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 358-373.
    3. Jaqueson K. Galimberti & Marcelo L. Moura, 2011. "Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts," Centre for Growth and Business Cycle Research Discussion Paper Series 159, Economics, The Univeristy of Manchester.

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