Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team

Nikolaos Kourentzes, Andrea Saayman, Philippe Jean-Pierre, Davide Provenzano, Mondher Sahli, Neelu Seetaram and Serena Volo

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

Abstract: COVID-19 disrupted international tourism worldwide, subsequently presenting forecasters with a challenging conundrum. In this competition, we predict international arrivals for 20 destinations in two phases: (i) Ex post forecasts pre-COVID; (ii) Ex ante forecasts during and after the pandemic up to end 2021. Our results show that univariate combined with cross-sectional hierarchical forecasting techniques (THieF-ETS) outperform multivariate models pre-COVID. Scenarios were developed based on judgemental adjustment of the THieF-ETS baseline forecasts. Analysts provided a regional view on the most likely path to normal, based on country-specific regulations, macroeconomic conditions, seasonal factors and vaccine development. Results show an average recovery of 58% compared to 2019 tourist arrivals in the 20 destinations under the medium scenario; severe, it is 34% and mild, 80%.

Keywords: COVID-19; Forecasting; Hierarchical forecasts; Visitor arrivals; Scenario forecasting (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (19)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:anture:v:88:y:2021:i:c:s0160738321000694

DOI: 10.1016/j.annals.2021.103197

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