Scenario Forecasting for Global Tourism

Doris Chenguang Wu, Zheng Cao, Long Wen, Haiyan Song

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

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 policy makers. 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.

Original languageEnglish
Pages (from-to)28-51
Number of pages24
JournalJournal of Hospitality and Tourism Research
Volume45
Issue number1
DOIs
Publication statusPublished - Jan 2021

Keywords

  • Brier score
  • economic growth
  • scenario forecasting
  • time-varying parameter panel vector autoregressive
  • tourism growth

ASJC Scopus subject areas

  • Education
  • Tourism, Leisure and Hospitality Management

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