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Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9754959/ https://www.ncbi.nlm.nih.gov/pubmed/36540371 http://dx.doi.org/10.1016/j.annals.2021.103197 |
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author | Kourentzes, Nikolaos Saayman, Andrea Jean-Pierre, Philippe Provenzano, Davide Sahli, Mondher Seetaram, Neelu Volo, Serena |
author_facet | Kourentzes, Nikolaos Saayman, Andrea Jean-Pierre, Philippe Provenzano, Davide Sahli, Mondher Seetaram, Neelu Volo, Serena |
author_sort | Kourentzes, Nikolaos |
collection | PubMed |
description | 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%. |
format | Online Article Text |
id | pubmed-9754959 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97549592022-12-16 Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team Kourentzes, Nikolaos Saayman, Andrea Jean-Pierre, Philippe Provenzano, Davide Sahli, Mondher Seetaram, Neelu Volo, Serena Ann Tour Res Article 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%. Elsevier Ltd. 2021-05 2021-03-20 /pmc/articles/PMC9754959/ /pubmed/36540371 http://dx.doi.org/10.1016/j.annals.2021.103197 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Kourentzes, Nikolaos Saayman, Andrea Jean-Pierre, Philippe Provenzano, Davide Sahli, Mondher Seetaram, Neelu Volo, Serena Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team |
title | Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team |
title_full | Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team |
title_fullStr | Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team |
title_full_unstemmed | Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team |
title_short | Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team |
title_sort | visitor arrivals forecasts amid covid-19: a perspective from the africa team |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9754959/ https://www.ncbi.nlm.nih.gov/pubmed/36540371 http://dx.doi.org/10.1016/j.annals.2021.103197 |
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