Economic forecasting with non-specific Google Trends sentiments: Insights from US Data

Abstract

[EN] The influence of specific Google Trends search queries measuring various sentiments on economic performance and stock markets has been extensively documented and used for many purposes. This paper examines the predictive power of queries measuring non-specific sentiment on key macroeconomic variables when linked to a comprehensive sentiment dictionary. The analysis shows that non-specific sentiments do not improve the forecasting quality of the US economy as a whole, except for unemployment, which was found to be predictable for all sentiments. Consequently, the authors suggest that economic-related sentiments with carefully selected words should be used in Google Trends search queries to improve predictive performance. However, if a socio-cultural analysis is to be performed, non-specific sentiments would be suggested, as they can be predicted by the real economic time series of unemployment.