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Modelling and forecasting European Airbnb occupancy during the pandemic

The specific merits of panel-data and Markov-switching models

Bibliographic Data

ID21689372
AuthorsUlrich Gunter (0000-0003-3347-810X, MODUL University Vienna), Bozana Zekan (0000-0002-9393-005X, MODUL University Vienna, corresponding author), Francesco Luigi Milone (0000-0001-6697-8536, Politecnico di Torino)
Year2025
Volume31
Issue4
Pages695-713
Publication date2025-06-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueTourism Economics (JOURNAL)
Journal identifiersISSN: 1354-8166 • E-ISSN: 2044-0375
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/13548166241283510
OpenAlexW4402545143
LanguageEN
Citations received1
References cited66

This study models European Airbnb occupancy from January 2017 to December 2020 for 43 European countries within an econometric panel-data framework. Besides typical economic covariates, the COVID-19 Stringency Index is employed to allow for the recent pandemic. The counterfactual observations created by two versions of the econometric model (one with and one without European aggregates of macroeconomic controls) are benchmarked against traditional univariate time-series models and a seasonal Markov-switching autoregression. For pandemic times, the latter performs very well in terms of several forecast accuracy measures due to its ability of (a) detecting the pandemic-induced structural break and (b) accounting for seasonal patterns in the data. The econometric models also predict well as they outperform the time-series models in the majority of cases. Hence, the panel-data approach is suitable when looking for economically interpretable Airbnb occupancy forecasts, even during the time of the pandemic

Econometrics · Economics · Geography · Markov chain · Occupancy · Panel data · Tourism · Computer Science · Engineering · Housing Market and Economics · Sharing Economy and Platforms · Transportation and Mobility Innovations

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Unique citing works1
Citations per year1
Citation span2025 - 2025 (1)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 1

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