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

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Author Info

  • 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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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 31 (2012)
Issue (Month): 5 (08)
Pages: 391-400

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Handle: RePEc:wly:jforec:v:31:y:2012:i:5:p:391-400

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. Leon, Costas & Eeckels, Bruno, 2009. "A Dynamic Correlation Approach of the Swiss Tourism Income," MPRA Paper 15215, University Library of Munich, Germany.
  2. Hassani, Hossein, 2007. "Singular Spectrum Analysis: Methodology and Comparison," MPRA Paper 4991, University Library of Munich, Germany.
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Cited by:
  1. 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 & Management Discussion Papers em-dp2013-04, Henley Business School, Reading University.
  2. repec:rdg:wpaper:em-dp2013-04 is not listed on IDEAS

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