Using Google Trend Data to Predict the Italian Unemployment Rate

The increased availability of online information in recent years has aroused interest as to the possibility of deriving indications on phenomena under studies. In the more specifically economic and statistical context, numerous studies suggest the use of online search data to improve the nowcasting and forecasting of the official economic indicators with a view to increasing the promptness of their circulation. In the same way, this paper puts forward a model for multiple time series that harnesses cointegration of the official time series of the Italian unemployment rate and the series of the Google Trend job offers query share to nowcast the monthly unemployment rate. Nowcasting is to be understood here as estimating the monthly unemployment rate for the month in which official survey is actually under way. The aim is thus to assess whether the use of Internet search data can improve the nowcasting of the economic indicator considered.