TY - JOUR
T1 - Ex Ante Tourism Forecasting Assessment
AU - Liu, Anyu
AU - Lin, Vera Shanshan
AU - Li, Gang
AU - Song, Haiyan
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by The Hong Kong Polytechnic University [grant number ZGAQ].
Publisher Copyright:
© The Author(s) 2020.
PY - 2020/11/26
Y1 - 2020/11/26
N2 - Although numerous studies have focused on forecasting international tourism demand, minimal light has been shed on the factors influencing the accuracy of real-world ex ante forecasting. This study evaluates the forecasting errors across various prediction horizons by analyzing the annually published forecasts of the Pacific Asia Tourism Association (PATA) from 2013 to 2017, comprising 765 origin–destination pairs covering 31 destinations in the region. The regression analysis shows that the variation in tourism demand and gross domestic product (GDP), covariation between tourism demand and GDP, order of lagged variables, origin, destination, and forecasting method all have significant effects on the forecasting accuracy over different horizons. This suggests that tourism forecasting should account for these factors in the future.
AB - Although numerous studies have focused on forecasting international tourism demand, minimal light has been shed on the factors influencing the accuracy of real-world ex ante forecasting. This study evaluates the forecasting errors across various prediction horizons by analyzing the annually published forecasts of the Pacific Asia Tourism Association (PATA) from 2013 to 2017, comprising 765 origin–destination pairs covering 31 destinations in the region. The regression analysis shows that the variation in tourism demand and gross domestic product (GDP), covariation between tourism demand and GDP, order of lagged variables, origin, destination, and forecasting method all have significant effects on the forecasting accuracy over different horizons. This suggests that tourism forecasting should account for these factors in the future.
KW - data characteristics
KW - ex ante forecasts
KW - forecasting errors
KW - forecasting horizons
KW - international tourism demand
UR - http://www.scopus.com/inward/record.url?scp=85096819026&partnerID=8YFLogxK
U2 - 10.1177/0047287520974456
DO - 10.1177/0047287520974456
M3 - Journal article
AN - SCOPUS:85096819026
SN - 0047-2875
JO - Journal of Travel Research
JF - Journal of Travel Research
ER -