Forecasting Unemployment with Google Searches

Data on Google searches help predict the unemployment rate in the U.S. But the predictive power of Google searches is limited to short-term predictions, the value of Google data for forecasting purposes is episodic, and the improvements in forecasting accuracy are only modest. The results, obtained by (pseudo) out-of-sample forecast comparison, are robust to a state-level fixed effects model and to different search terms. Joint analysis by cross-correlation function and Granger non-causality tests verifies that Google searches anticipate the unemployment rate. The results illustrate both the potentials and limitations of using big data to predict economic indicators.

JEL: C22, C53, C55, C82, E27
Date: 02.03.2016
Pages: 34
Price: 15 €
Language: English
ISSN: 2323-2420
ETLA Working Papers 35