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Impact of Seasonal Level Shift (SLS) on Time Series Forecasting

Author

Listed:
  • Hayat SHAHID

    (Pakistan Institute of Development Economics, Islamabad.)

  • Amena UROOJ

    (Pakistan Institute of Development Economics, Islamabad.)

  • Zahid ASGHAR

    (Quaid-i-Azam University, Islamabad.)

Abstract

The effect of not treating Seasonal Level Shift (SLS) outliers on forecast accuracy, and prediction intervals is the focus of this study. We examine the impact of SLS on point and interval forecasts using simulation experiment for time series models including SAR (1) and SMA (1) for different parameter values, sample sizes and time of occurrences. We extend the strategy suggested by Asghar and Urooj (2017) to forecasting in the presence of SLS by looking at forecast accuracy and prediction interval. We demonstrate that SLS significantly increases the inaccuracy of the SARIMA models, increases the bias in the SARIMA estimates, and significantly affects the prediction intervals. However, after detection and adjustment of SLS, SARIMA estimates become less biased, and forecast accuracy measure and prediction interval significantly improve. The difference of location of SLS from forecast origin has similar effect on bias and forecast accuracy in SAR (1) model. While, in SMA (1) model, the SLS occurring at the beginning of the series has greater adverse effect than that occurring at the middle or end of the series. Three monthly time series data from Pakistan are used to explore the issue.

Suggested Citation

  • Hayat SHAHID & Amena UROOJ & Zahid ASGHAR, 2023. "Impact of Seasonal Level Shift (SLS) on Time Series Forecasting," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 107-128, March.
  • Handle: RePEc:rjr:romjef:v::y:2023:i:1:p:107-128
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    More about this item

    Keywords

    Seasonal Level Shift (SLS); SARIMA; forecast accuracy; point forecasts; interval forecasts;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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