TOURIST ARRIVAL FORECAST AMID COVID-19: A perspective from the Asia and Pacific team
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.
Domains
Quantitative Finance [q-fin]Origin | Files produced by the author(s) |
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