Beyond point forecasting : evaluation of alternative prediction intervals for tourist arrivals

Kim, Jae H., Wong, Kevin, Athanasopoulos, George, & Liu, Shen (2011) Beyond point forecasting : evaluation of alternative prediction intervals for tourist arrivals. International Journal of Forecasting, 27(3), pp. 887-901.

View at publisher


This paper evaluates the performances of prediction intervals generated from alternative time series models, in the context of tourism forecasting. The forecasting methods considered include the autoregressive (AR) model, the AR model using the bias-corrected bootstrap, seasonal ARIMA models, innovations state space models for exponential smoothing, and Harvey’s structural time series models. We use thirteen monthly time series for the number of tourist arrivals to Hong Kong and Australia. The mean coverage rates and widths of the alternative prediction intervals are evaluated in an empirical setting. It is found that all models produce satisfactory prediction intervals, except for the autoregressive model. In particular, those based on the biascorrected bootstrap perform best in general, providing tight intervals with accurate coverage rates, especially when the forecast horizon is long.

Impact and interest:

13 citations in Scopus
Search Google Scholar™
10 citations in Web of Science®

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 73234
Item Type: Journal Article
Refereed: Yes
Keywords: Automatic forecasting, Bootstrapping, Interval forecasting
DOI: 10.1016/j.ijforecast.2010.02.014
ISSN: 0169-2070
Subjects: Australian and New Zealand Standard Research Classification > ECONOMICS (140000) > ECONOMETRICS (140300) > Economic Models and Forecasting (140303)
Australian and New Zealand Standard Research Classification > COMMERCE MANAGEMENT TOURISM AND SERVICES (150000) > TOURISM (150600) > Tourism Forecasting (150602)
Divisions: Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2010 International Institute of Forecasters
Deposited On: 02 Jul 2014 23:37
Last Modified: 03 Jul 2014 23:50

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page