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

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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Year of publication:	2009-09-28
Authors:	Beneki, Christina ; Eeckels, Bruno ; Leon, Costas
Institutions:	Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München
Subject:	Singular Spectrum Analysis \| Singular Value Decomposition \| Business Cycle Decomposition \| Tourism Income \| United Kingdom \| Signal Extraction \| Forecasting

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Extent:	application/pdf
Series:	MPRA Paper.
Type of publication:	Book / Working Paper
Classification:	C53 - Forecasting and Other Model Applications ; E32 - Business Fluctuations; Cycles ; C14 - Semiparametric and Nonparametric Methods
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008567977