TOURIST ARRIVAL FORECAST AMID COVID-19: A perspective from the Asia and Pacific team

Richard T.R. Qiu, Doris Chenguang Wu, Vincent Dropsy, Sylvain Petit (), Stephen Pratt and Yasuo Ohe

Post-Print from HAL

Abstract: It is important to provide scientific assessments concerning the future of tourism under the uncertainty surrounding COVID-19. To this purpose, this paper presents a two-stage three-scenario forecast framework for inbound-tourism demand across 20 countries. The main findings are as follows: in the first-stage ex-post forecasts, the stacking-based algorithms are more accurate and robust, especially when combining five single models. The second-stage ex-ante forecasts are based on three recovery scenarios: a mild case assuming a V-shape recovery, a medium one with a V/U-shape, and a severe one with an L-shape. The forecast results show a wide range of recovery (10%-70%) in 2021 compared to 2019. This two-stage three-scenario framework contributes to improvement in the accuracy and robustness of tourism demand forecasting.

Keywords: Tourisme (search for similar items in EconPapers)
Date: 2021-01
Note: View the original document on HAL open archive server: https://hal.science/hal-03138092
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published in Annals of Tourism Research, 2021, pp.103155. ⟨10.1016/j.annals.2021.103155⟩

Downloads: (external link)
https://hal.science/hal-03138092/document (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03138092

DOI: 10.1016/j.annals.2021.103155

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().