Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/238183 
Year of Publication: 
2021
Series/Report no.: 
NBB Working Paper No. 396
Publisher: 
National Bank of Belgium, Brussels
Abstract: 
Policymakers, firms, and investors closely monitor traditional survey-based consumer confidence indicators and treat it as an important piece of economic information. We propose a latent factor model for the vector of monthly survey-based consumer confidence and daily sentiment embedded in economic media news articles. The proposed mixed-frequency dynamic factor model framework uses a novel covariance matrix specification. Model estimation and real-time filtering of the latent consumer confidence index are computationally simple. In a Monte Carlo simulation study and an empirical application concerning Belgian consumer confidence, we document the economically significant accuracy gains obtained by including daily news sentiment in the dynamic factor model for nowcasting consumer confidence.
Subjects: 
dynamic factor model
mixed-frequency
nowcasting
sentiment index
sentometrics
state space
JEL: 
C32
C51
C53
C55
Document Type: 
Working Paper

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