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.

本研究对全球前 20 名最繁忙机场以及亚太和拉丁美洲-加勒比地区的乘客数量采用 GVAR 模型。航空乘客数量代表需求量度，经济驱动因素的国家级代理被包括为国内和国外变量。就事前预测的准确性而言，与未来一季度和四分之三的四个基准相比，GVAR 模型在几个机场（但不是整个机场）中表现最佳。当所有的视野都被联合评估时，它还在这些视野和其他两个视野中获得了几个第二和第三名。考虑机场的连通性对于实现准确且经济上可解释的航空旅客需求预测是值得的。