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, G
Wong, KKF
Song, H 
Witt, SF
Keywords: 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
Source: Journal of travel research, 1 Nov. 2006, v. 45, no. 2, p. 175-185 How to cite?
Journal: Journal of travel research 
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.
URI: http://hdl.handle.net/10397/1322
ISSN: 0047-2875 (print)
1552-6763 (online)
DOI: 10.1177/0047287506291596
Rights: © 2006 Sage Publications
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
05-TVP-ECM LI et al SSOL version.pdfPre-published version261.65 kBAdobe PDFView/Open
Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

54
Last Week
0
Last month
0
Citations as of Apr 10, 2016

Page view(s)

384
Last Week
3
Last month
Checked on May 22, 2016

Download(s)

2,735
Checked on May 22, 2016

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.