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Signal Extraction and Forecasting of the UK Tourism Income Time Series: A Singular Spectrum Analysis Approach

Author

Listed:
  • Christina Beneki
  • Bruno Eeckels
  • Costas Leon

Abstract

We present and apply the Singular Spectrum Analysis (SSA), a relatively new, non-parametric and data-driven method used for signal extraction (trends, seasonal and business cycle components) and forecasting of the UK tourism income. Our results show that SSA outperforms slightly SARIMA and time-varying parameter State Space Models in terms of RMSE, MAE and MAPE forecasting criteria.
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Suggested Citation

  • Christina Beneki & Bruno Eeckels & Costas Leon, 2012. "Signal Extraction and Forecasting of the UK Tourism Income Time Series: A Singular Spectrum Analysis Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 31(5), pages 391-400, August.
    • Handle: RePEc:wly:jforec:v:31:y:2012:i:5:p:391-400
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    Cited by:

    1. Marinoiu Cristian, 2018. "Average Monthly Temperature Forecast In Romania By Using Singular Spectrum Analysis," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 3, pages 48-57, June.
    2. Hassani, Hossein & Silva, Emmanuel Sirimal & Gupta, Rangan & Das, Sonali, 2018. "Predicting global temperature anomaly: A definitive investigation using an ensemble of twelve competing forecasting models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 121-139.
    3. Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
    4. Yong Zhang & Miner Zhong & Nana Geng & Yunjian Jiang, 2017. "Forecasting electric vehicles sales with univariate and multivariate time series models: The case of China," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-15, May.
    5. Lai, Lin & Guo, Kun, 2017. "The performance of one belt and one road exchange rate: Based on improved singular spectrum analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 299-308.
    6. repec:rdg:wpaper:em-dp2013-04 is not listed on IDEAS
    7. Bi, Jian-Wu & Liu, Yang & Li, Hui, 2020. "Daily tourism volume forecasting for tourist attractions," Annals of Tourism Research, Elsevier, vol. 83(C).
    8. Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2015. "Forecasting implied volatility indices worldwide: A new approach," MPRA Paper 72084, University Library of Munich, Germany.
    9. Chengyuan Zhang & Fuxin Jiang & Shouyang Wang & Shaolong Sun, 2020. "A New Decomposition Ensemble Approach for Tourism Demand Forecasting: Evidence from Major Source Countries," Papers 2002.09201, arXiv.org.
    10. Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2018. "Forecasting global stock market implied volatility indices," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 111-129.
    11. Jihong Xiao & Xuehong Zhu & Chuangxia Huang & Xiaoguang Yang & Fenghua Wen & Meirui Zhong, 2019. "A New Approach for Stock Price Analysis and Prediction Based on SSA and SVM," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 287-310, January.
    12. Andrea Saayman & Jacques de Klerk, 2019. "Forecasting tourist arrivals using multivariate singular spectrum analysis," Tourism Economics, , vol. 25(3), pages 330-354, May.
    13. Silva, Emmanuel Sirimal & Ghodsi, Zara & Ghodsi, Mansi & Heravi, Saeed & Hassani, Hossein, 2017. "Cross country relations in European tourist arrivals," Annals of Tourism Research, Elsevier, vol. 63(C), pages 151-168.
    14. Silva, Emmanuel Sirimal & Hassani, Hossein & Heravi, Saeed & Huang, Xu, 2019. "Forecasting tourism demand with denoised neural networks," Annals of Tourism Research, Elsevier, vol. 74(C), pages 134-154.
    15. Rocco S, Claudio M., 2013. "Singular spectrum analysis and forecasting of failure time series," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 126-136.
    16. Andrea Saayman & Ilsé Botha, 2017. "Non-linear models for tourism demand forecasting," Tourism Economics, , vol. 23(3), pages 594-613, May.
    17. Ping Jiang & Zeng Wang & Kequan Zhang & Wendong Yang, 2017. "An Innovative Hybrid Model Based on Data Pre-Processing and Modified Optimization Algorithm and Its Application in Wind Speed Forecasting," Energies, MDPI, vol. 10(7), pages 1-29, July.
    18. Leon, Costas, 2018. "An Evaluation of Singular Spectrum Analysis-Based Seasonal Adjustment," MPRA Paper 84594, University Library of Munich, Germany.
    19. Eden Xiaoying Jiao & Jason Li Chen, 2019. "Tourism forecasting: A review of methodological developments over the last decade," Tourism Economics, , vol. 25(3), pages 469-492, May.
    20. Jian-Wu Bi & Tian-Yu Han & Hui Li, 2022. "International tourism demand forecasting with machine learning models: The power of the number of lagged inputs," Tourism Economics, , vol. 28(3), pages 621-645, May.
    21. Dimitrios Thomakos & Hossein Hassani & Kerry Patterson, 2013. "Optimal Linear Filtering, Smoothing and Trend Extraction for the m-th Differences of a Unit Root Process: A Singular Spectrum Analysis Approach," Economics Discussion Papers em-dp2013-04, Department of Economics, University of Reading.
    22. Hassani, Hossein & Webster, Allan & Silva, Emmanuel Sirimal & Heravi, Saeed, 2015. "Forecasting U.S. Tourist arrivals using optimal Singular Spectrum Analysis," Tourism Management, Elsevier, vol. 46(C), pages 322-335.
    23. Jian-Wu Bi & Tian-Yu Han & Yanbo Yao, 2024. "Collaborative forecasting of tourism demand for multiple tourist attractions with spatial dependence: A combined deep learning model," Tourism Economics, , vol. 30(2), pages 361-388, March.
    24. Josu Arteche & Javier García‐Enríquez, 2022. "Singular spectrum analysis for value at risk in stochastic volatility models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 3-16, January.
    25. Leon, Costas, 2015. "Decomposition of the European GDP based on Singular Spectrum Analysis," MPRA Paper 65812, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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