Forecasting air passenger numbers with a GVAR model

Ulrich Gunter and Bozana Zekan

Annals of Tourism Research, 2021, vol. 89, issue C

Abstract: This study employs a GVAR model on the passenger numbers of the top 20 busiest airports of the world and the Asia-Pacific and Latin America-Caribbean regions. With air passenger numbers representing a demand measure, country-level proxies for economic drivers are included as domestic and foreign variables. In terms of ex-ante forecast accuracy, the GVAR model performs best for several airports – yet not for the entirety of airports – compared to four benchmarks for horizons one and three quarters ahead. It also achieves several second and third ranks for these and two other horizons and when all horizons are evaluated jointly. Considering the connectivity of airports is worthwhile to achieve accurate and economically interpretable air passenger demand forecasts.

Keywords: Air passenger demand forecasting; Airport connectivity; Ex-ante tourism demand forecasting; Forecast evaluation; Global network of airports; Global vector autoregressive model (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:anture:v:89:y:2021:i:c:s0160738321001304

DOI: 10.1016/j.annals.2021.103252

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