Visitor arrivals forecasts 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

Annals of Tourism Research, 2021, vol. 88, issue C

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 models 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-shaped recovery, a medium one with a V/U-shaped, and a severe one with an L-shaped. The forecast results show a wide range of recovery (10%–70%) in 2021 compared to 2019. This two-stage three-scenario framework contributes to the improvement in the accuracy and robustness of tourism demand forecasting.

Keywords: COVID-19; Tourism forecasting competition; Stacking models; Recovery scenarios; Judgmental-adjusted forecasting (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (25)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:anture:v:88:y:2021:i:c:s0160738321000177

DOI: 10.1016/j.annals.2021.103155

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