This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Tourism Forecasting: Accuracy of Alternative Econometric Models Revisited

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Haiyan Song
Egon Smeral (WIFO)
Gang Li
Jason L. Chen

Additional information is available for the following registered author(s):

Abstract

This study evaluates the forecasting accuracy of five alternative econometric models in the context of predicting the quarterly international tourism demand in 25 countries or country groupings. Tourism demand is measured in terms of tourist expenditure by inbound international visitors in a destination. Two univariate time series models are included in the forecasting comparison as benchmarks. Accuracy is assessed in terms of error magnitude. Seasonality is an important feature of forecasting models and requires careful handling. For each of the 25 destinations, individual models are estimated over the 1980Q1-2005Q1 period, and forecasting performance is assessed using data covering the 2005Q2-2007Q1 period. The empirical results show that the time-varying parameter (TVP) model provides the most accurate short-term forecasts, whereas the naïve (no-change) model performs best in long-term forecasting up to two years. This study provides new evidence of the TVP model's outstanding performance in short-term forecasting. Through the incorporation of a seasonal component into the model, the TVP model forecasts short-run seasonal tourism demand well.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.wifo.ac.at/wwa/jsp/index.jsp?fid=23923&id=33239&typeid=8&display_mode=2&pub_language=2&language=2
File Format: text/html
File Function: Abstract
Download Restriction: no
File URL: http://www.wifo.ac.at/wwa/servlet/wwa.upload.DownloadServlet/bdoc/PRIVATE40475/WP_2007_326$.PDF
File Format: application/pdf
File Function: full text
Download Restriction: no

Publisher Info
Paper provided by WIFO in its series WIFO Working Papers with number 326.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 33 pages
Date of creation: 13 Aug 2008
Date of revision:
Handle: RePEc:wfo:wpaper:y:2008:i:326

Contact details of provider:
Postal: A-1103 Wien, Postfach 91
Phone: (+43 1) 798 26 01-0
Fax: (+43 1) 798 93 86
Web page: http://www.wifo.ac.at/
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Ilse Schulz).

Related research
Keywords: tourism forecasting; econometric models; time series models; forecasting accuracy;

This paper has been announced in the following NEP Reports:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Song, Haiyan & Romilly, Peter & Liu, Xiaming, 2000. "An Empirical Study of Outbound Tourism Demand in the UK," Applied Economics, Taylor and Francis Journals, vol. 32(5), pages 611-24, April. [Downloadable!] (restricted)
  2. Darne, Olivier & Diebolt, Claude, 2004. "Unit roots and infrequent large shocks: new international evidence on output," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1449-1465, October. [Downloadable!] (restricted)
  3. Witt, Stephen F. & Witt, Christine A., 1995. "Forecasting tourism demand: A review of empirical research," International Journal of Forecasting, Elsevier, vol. 11(3), pages 447-475, September. [Downloadable!] (restricted)
  4. McNees, Stephen K, 1986. "Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 5-15, January.
  5. Li, Gang & Song, Haiyan & Witt, Stephen F., 2006. "Time varying parameter and fixed parameter linear AIDS: An application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 22(1), pages 57-71. [Downloadable!] (restricted)
  6. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238. [Downloadable!] (restricted)
    Other versions:
  7. Brown, Jane P. & Song, Haiyan & McGillivray, Alan, 1997. "Forecasting UK house prices: A time varying coefficient approach," Economic Modelling, Elsevier, vol. 14(4), pages 529-548, October. [Downloadable!] (restricted)
  8. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June. [Downloadable!] (restricted)
  9. Song, Haiyan & Romilly, Peter & Liu, Xiaming, 1998. "The UK Consumption Function and Structural Instability: Improving Forecasting Performance Using a Time-Varying Parameter Approach," Applied Economics, Taylor and Francis Journals, vol. 30(7), pages 975-83, July. [Downloadable!] (restricted)
  10. Riddington, GL, 1993. "Time varying coefficient models and their forecasting performance," Omega, Elsevier, vol. 21(5), pages 573-583, September. [Downloadable!] (restricted)
  11. Martin, Christine A. & Witt, Stephen F., 1989. "Forecasting tourism demand: A comparison of the accuracy of several quantitative methods," International Journal of Forecasting, Elsevier, vol. 5(1), pages 7-19. [Downloadable!] (restricted)
  12. Bohara, Alok K & Sauer, Christine, 1992. "Competing Macro-hypotheses in the United States: A Kalman Filtering Approach," Applied Economics, Taylor and Francis Journals, vol. 24(4), pages 389-99, April.
  13. Makridakis, Spyros, 1986. "The art and science of forecasting An assessment and future directions," International Journal of Forecasting, Elsevier, vol. 2(1), pages 15-39. [Downloadable!] (restricted)
  14. Newey, Whitney K & West, Kenneth D, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, Blackwell Publishing, vol. 61(4), pages 631-53, October. [Downloadable!] (restricted)
    Other versions:
  15. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
    Other versions:
  16. Song, Haiyan & Witt, Stephen F. & Jensen, Thomas C., 2003. "Tourism forecasting: accuracy of alternative econometric models," International Journal of Forecasting, Elsevier, vol. 19(1), pages 123-141. [Downloadable!] (restricted)
  17. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
    Other versions:
  18. Greenslade, Jennifer V. & Hall, Stephen G., 1996. "Modelling economies subject to structural change: The case of Germany," Economic Modelling, Elsevier, vol. 13(4), pages 545-559, October. [Downloadable!] (restricted)
  19. Ashley, Richard, 1988. "On the relative worth of recent macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 4(3), pages 363-376. [Downloadable!] (restricted)
Full references

Statistics
Access and download statistics

Did you know? RePEc data is maintained by each archive holder on its own website. Nothing is held centrally.

This page was last updated on 2009-12-8.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.