Forecasting travellers in Spain with Google's search volume indices. Issue 4 (June 2018)

• Record Type: Journal Article
• Authors: Camacho, Maximo; Pacce, Matías José
• Is Part Of: Tourism economics. Volume 24:Issue 4(2018)
• Page Start: 434
• Page End: 448
• Publication Date: 2018-06
• Subjects: big data analysis -- time series -- tourism; Tourism -- Periodicals; 338.4791
• DOI: 10.1177/1354816617737227
• Languages: English
• ISSNs: 1354-8166

Abstract

We examine whether Google's search volume indices help economic agents with real-time predictions about the checked-in and overnight stays of travellers in Spain. Using a dynamic factor approach and a real-time database of vintages that reproduces the exact information that was available to a forecaster at each particular point in time, we show that the models, including Google's query volume indices, outperform models that exclude these leading indicators. In this way, we are the first in finding conclusive evidence that tourism-related queries help to improve tourism forecast in Spain. Our finding is of significance in this literature, since Spain is one of the world's top tourism destinations and extremely depends on tourism.