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Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1322

Title: Tourism demand forecasting: A time varying parameter error correction model
Authors: Li, Gang
Wong, Kevin K. F.
Song, Haiyan
Witt, Stephen F.
Subjects: Time-varying parameter
Error correction model
Tourism demand
Ex post forecasting
Kalman filter
Issue Date: 1-Nov-2006
Publisher: Published by Sage on behalf of Travel and Tourism Research Association
Citation: Journal of travel research, 1 Nov. 2006, v. 45, no. 2, p. 175-185.
Abstract: The advantages of error correction models (ECMs) and time varying parameter (TVP) models have been discussed in the tourism forecasting literature. These models are now combined to give a new single-equation model, the time varying parameter error correction model (TVP-ECM), which is applied for the first time in the context of tourism demand forecasting. The empirical study focuses on tourism demand, measured by tourism spending per capita, by U.K. residents for five key Western European destinations. The empirical results show that the TVP-ECM can be expected to outperform a number of alternative econometric and time-series models in forecasting the demand for tourism, especially in forecasting the growth rate of tourism demand. A practical implication of this result is that the TVP-ECM approach should be used when forecasting tourism growth is concerned.
Description: DOI: 10.1177/0047287506291596
Rights: © 2006 Sage Publications
Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/1322
ISSN: 0047-2875 (Print)
1552-6763 (Online)
Appears in Collections:SHTM Journal/Magazine Articles

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