Premium
Where should we go? Internet searches and tourist arrivals
Author(s) -
Cevik Serhan
Publication year - 2022
Publication title -
international journal of finance and economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.505
H-Index - 39
eISSN - 1099-1158
pISSN - 1076-9307
DOI - 10.1002/ijfe.2358
Subject(s) - autoregressive integrated moving average , tourism , autoregressive model , econometrics , the internet , multivariate statistics , computer science , economics , time series , geography , machine learning , world wide web , archaeology
The widespread availability of internet search data is a new source of high‐frequency information that can potentially improve the precision of macroeconomic forecasting, especially in areas with data constraints. This paper investigates whether travel‐related online search queries enhance accuracy in the forecasting of tourist arrivals to The Bahamas from the United States. The results indicate that Google Trends‐augmented forecast models improve forecast accuracy by about 30% compared to the traditional autoregressive integrated moving average (ARIMA) model and more than 20% compared to the multivariate model incorporating macroeconomic indicators.