Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1464
Title: An assessment of combining tourism demand forecasts over different time horizons
Authors: Shen, S
Li, G
Song, H 
Keywords: Combination forecast
Tourism demand
Econometric model
Forecast performance
Encompassing test
Issue Date: 1-Nov-2008
Publisher: Published by Sage on behalf of Travel and Tourism Research Association
Source: Journal of travel research, 1 Nov. 2008, v. 47, no. 2, p. 197-207 How to cite?
Journal: Journal of travel research 
Abstract: This study investigates the performance of combination forecasts in comparison to individual forecasts. The empirical study focuses on the U.K. outbound leisure tourism demand for the United States. The combination forecasts are based on the competing forecasts generated from seven individual forecasting techniques. The three combination methods examined in this study are the simple average combination method, the variance–covariance combination method, and the discounted mean square forecast error method. The empirical results suggest that combination forecasts overall play an important role in the improvement of forecasting accuracy in that they are superior to the best of the individual forecasts over different forecasting horizons. The variance–covariance combination method turns out to be the best among the three combination methods. Another finding is that the encompassing test does not significantly contribute to the improved accuracy of combination forecasts. This study provides robust evidence for the efficiency of combination forecasts.
URI: http://hdl.handle.net/10397/1464
ISSN: 0047-2875 (print)
1552-6763 (online)
DOI: 10.1177/0047287508321199
Rights: © 2008 Sage Publications
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
16-An Assessmentl.pdfPre-published version131.43 kBAdobe PDFView/Open
Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

18
Last Week
0
Last month
2
Citations as of Apr 10, 2016

WEB OF SCIENCETM
Citations

15
Last Week
0
Last month
1
Citations as of Jun 20, 2016

Page view(s)

328
Last Week
2
Last month
Checked on Jul 24, 2016

Download(s)

616
Checked on Jul 24, 2016

Google ScholarTM

Check

Altmetric



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