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Masking of volatility by seasonal adjustment methods

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  • Hayat, Aziz
  • Bhatti, M. Ishaq

Abstract

We report that the X-12 ARIMA and TRAMO–SEATS seasonal adjustment methods consistently underestimate the variability of the differenced seasonally adjusted series. We show that underestimation is due to a non-zero estimation error in estimating the seasonal component at each time period, which is the result of the use of low order seasonal filter in X12-ARIMA for estimating the seasonal component. Hence, we propose the use of high order seasonal filter for estimating the seasonal component, which helps reducing the estimation error noticeably, helps amending the underestimation problem, and helps improving the forecasting accuracy of the series. In TRAMO–SEATS, Airline model is found to deliver the best seasonal filter among other ARIMA models.

Suggested Citation

  • Hayat, Aziz & Bhatti, M. Ishaq, 2013. "Masking of volatility by seasonal adjustment methods," Economic Modelling, Elsevier, vol. 33(C), pages 676-688.
    • Handle: RePEc:eee:ecmode:v:33:y:2013:i:c:p:676-688
    DOI: 10.1016/j.econmod.2013.05.016
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    Cited by:

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    2. Magee, Gary & Ishaq Bhatti, M. & Li, Alice Shuaishuai, 2015. "The economic modeling of migration and consumption patterns in the English-speaking world," Economic Modelling, Elsevier, vol. 50(C), pages 322-330.

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    More about this item

    Keywords

    Seasonality; TRAMO–SEATS; X-12 ARIMA; Variability; Under-estimation; Seasonal adjustments;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

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