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

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

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)


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%.
Original languageEnglish
Number of pages18
JournalAnnals of Tourism Research
Publication statusPublished - 2021

All Science Journal Classification (ASJC) codes

  • Development
  • Tourism, Leisure and Hospitality Management


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