Forecasting travelers in Spain with Google queries

Abstract

We examine whether Google query trends helps economic agents with predictions about the checking in and overnight stays of travelers in Spain in real time. 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 query trends outperform models that exclude these leading indicators. In this way, we aim to contribute to the literature on the link between the Internet and the tourismmarkets.