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

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  • Liu, Anyu
  • Vici, Laura
  • Ramos, Vicente
  • Giannoni, Sauveur
  • Blake, Adam

Abstract

In a context in which the tourism industry is jeopardised by the COVID-19 pandemic, and potentially by other pandemics in the future, the capacity to produce accurate forecasts is crucial to stakeholders and policy-makers. This paper attempts to forecast the recovery of tourism demand for 2021 in 20 destinations worldwide. An original scenario-based judgemental forecast based on the definition of a Covid-19 Risk Exposure index is proposed to overcome the limitations of traditional forecasting methods. Three scenarios are proposed, and ex ante forecasts are generated for each destination using a baseline forecast, the developed index and a judgemental approach. The limitations and potential developments of this new forecasting model are then discussed.

Suggested Citation

  • Liu, Anyu & Vici, Laura & Ramos, Vicente & Giannoni, Sauveur & Blake, Adam, 2021. "Visitor arrivals forecasts amid COVID-19: A perspective from the Europe team," Annals of Tourism Research, Elsevier, vol. 88(C).
    • Handle: RePEc:eee:anture:v:88:y:2021:i:c:s016073832100044x
    DOI: 10.1016/j.annals.2021.103182
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    6. Liu, Anyu & Kim, Yoo Ri & O'Connell, John Frankie, 2021. "COVID-19 and the aviation industry: The interrelationship between the spread of the COVID-19 pandemic and the frequency of flights on the EU market," Annals of Tourism Research, Elsevier, vol. 91(C).
    7. Xi Wu & Adam Blake, 2023. "Does the combination of models with different explanatory variables improve tourism demand forecasting performance?," Tourism Economics, , vol. 29(8), pages 2032-2056, December.
    8. Yamaka, Woraphon & Zhang, Xuefeng & Maneejuk, Paravee & Ramos, Vicente, 2023. "Asymmetric effects of third-country exchange rate risk: A Markov switching approach," Annals of Tourism Research, Elsevier, vol. 103(C).
    9. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
    10. Liu, Ying & Wen, Long & Liu, Han & Song, Haiyan, 2024. "Predicting tourism recovery from COVID-19: A time-varying perspective," Economic Modelling, Elsevier, vol. 135(C).
    11. Davide Provenzano & Serena Volo, 2022. "Tourism recovery amid COVID-19: The case of Lombardy, Italy," Tourism Economics, , vol. 28(1), pages 110-130, February.
    12. Miguel-Ángel García-Madurga & Miguel-Ángel Esteban-Navarro & Tamara Morte-Nadal, 2021. "CoVid Key Figures and New Challenges in the HoReCa Sector: The Way towards a New Supply-Chain," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    13. Yang, Yang & Fan, Yawen & Jiang, Lan & Liu, Xiaohui, 2022. "Search query and tourism forecasting during the pandemic: When and where can digital footprints be helpful as predictors?," Annals of Tourism Research, Elsevier, vol. 93(C).
    14. Ljubotina Predrag & Raspor Andrej, 2022. "Recovery of Slovenian Tourism After Covid-19 and Ukraine Crisis," Economics, Sciendo, vol. 10(1), pages 55-72, June.
    15. Marcus Roller, 2022. "Pre-Crisis Determinants of Tourism Resilience," Diskussionsschriften credresearchpaper39, Universitaet Bern, Departement Volkswirtschaft - CRED.
    16. Xi Wu & Adam Blake, 2023. "The Impact of the COVID-19 Crisis on Air Travel Demand: Some Evidence From China," SAGE Open, , vol. 13(1), pages 21582440231, January.
    17. Fangming Qin & Gezhi Chen, 2022. "Vulnerability of Tourist Cities’ Economic Systems Amid the COVID-19 Pandemic: System Characteristics and Formation Mechanisms—A Case Study of 46 Major Tourist Cities in China," Sustainability, MDPI, vol. 14(5), pages 1-18, February.
    18. Li, Hengyun & Gao, Huicai & Song, Haiyan, 2023. "Tourism forecasting with granular sentiment analysis," Annals of Tourism Research, Elsevier, vol. 103(C).

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