Nowcasting in real time using popularity priors

George Monokroussos and Yongchen Zhao

International Journal of Forecasting, 2020, vol. 36, issue 3, 1173-1180

Abstract: We construct a “Google Recession Index” (GRI) using Google Trends data on internet search popularity, which tracks the public’s attention to recession-related keywords in real time. We then compare nowcasts made with and without this index using both a standard dynamic factor model and a Bayesian approach with alternative prior setups. Our results indicate that using the Bayesian model with GRI-based “popularity priors,” we could identify the 2008Q3 turning point in real time, without sacrificing the accuracy of the nowcasts over the rest of the sample periods.

Keywords: Gibbs sampling; Factor models; Kalman filter; Real-time data; Google Trends; Monetary policy; Great Recession (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Working Paper: Nowcasting in Real Time Using Popularity Priors (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:36:y:2020:i:3:p:1173-1180

DOI: 10.1016/j.ijforecast.2020.03.004

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