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

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

ABSTRACT We present and apply singular spectrum analysis (SSA), a relatively new, non‐parametric and data‐driven method for signal extraction (trends, seasonal and business cycle components) and forecasting of UK tourism income. Our results show that SSA slightly outperforms SARIMA and time‐varying‐...

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Veröffentlicht in:Journal of forecasting 2012-08, Vol.31 (5), p.391-400
Hauptverfasser: Beneki, Christina, Eeckels, Bruno, Leon, Costas
Format: Artikel
Sprache:eng
Schlagworte:
business cycle decomposition
Business cycles
Economic forecasts
Error
forecasting
Forecasting techniques
Income
signal extraction
Signalling
singular spectrum analysis
singular value decomposition
Spectrum analysis
Studies
Time series
Tourism
tourism income
United Kingdom
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Zusammenfassung:ABSTRACT We present and apply singular spectrum analysis (SSA), a relatively new, non‐parametric and data‐driven method for signal extraction (trends, seasonal and business cycle components) and forecasting of UK tourism income. Our results show that SSA slightly outperforms SARIMA and time‐varying‐parameter state space models in terms of root mean square error, mean absolute error and mean absolute percentage error forecasting criteria. Copyright © 2011 John Wiley & Sons, Ltd.
ISSN:0277-6693
1099-131X
DOI:10.1002/for.1220