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 (1, 2) , Stephen Pratt , Yasuo Ohe

1 UPF - Université de la Polynésie Française
2 LARSH - Laboratoire de Recherche Sociétés & Humanités

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.

Mots clés: Tourisme

Domaines: Économie et finance quantitative [q-fin]

Richard T.R. Qiu, Doris Chenguang Wu, Vincent Dropsy, Sylvain Petit, Stephen Pratt, et al.. TOURIST ARRIVAL FORECAST AMID COVID-19: A perspective from the Asia and Pacific team. Annals of Tourism Research, 2021, pp.103155. ⟨10.1016/j.annals.2021.103155⟩. ⟨hal-03138092⟩