Scenario forecasting for global tourism

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Wu, Doris Chenguang, Cao, Zheng, Wen, Long and Song, Haiyan (2020) Scenario forecasting for global tourism. Journal of Hospitality & Tourism Research . p. 109634802091999. ISSN 1096-3480

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Abstract

This study provides innovative forecasts of the probabilities of certain scenarios of tourism demand. The scenarios of interest are constructed in relation to tourism growth and economic growth. The probability forecasts based on these scenarios provide valuable information for destination policymakers. The time-varying parameter panel vector autoregressive (TVP-PVAR) model is adopted for scenario forecasting. Both the accuracy rate and the Brier score are used to evaluate the forecasting performance. A global set of 25 tourism destinations is empirically examined, and the results confirm that the TVP-PVAR model with a time-varying error covariance matrix is generally a promising tool for forecasting. Our study contributes to tourism forecasting literature in advocating the use of scenario forecasting to facilitate industry decision-making in situations wherein forecasts are defined by two or more dimensions simultaneously. In addition, it is the first study to introduce the TVP-PVAR model to tourism demand forecasting.

Item Type: Article
Keywords: scenario forecasting, time-varying parameter panel vector autoregressive, tourism growth, economic growth, Brier score
Schools/Departments: University of Nottingham Ningbo China > Faculty of Humanities and Social Sciences > School of Economics
Identification Number: 10.1177/1096348020919990
Depositing User: Zhou, Elsie
Date Deposited: 22 Jun 2020 02:14
Last Modified: 22 Jun 2020 02:14
URI: https://eprints.nottingham.ac.uk/id/eprint/60947

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