Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence

Andres Algaba, Samuel Borms, Kris Boudt and Brecht Verbeken

International Journal of Forecasting, 2023, vol. 39, issue 1, 266-278

Abstract: Policymakers, firms, and investors closely monitor traditional survey-based consumer confidence indicators and treat them as an important piece of economic information. To obtain a daily nowcast of monthly consumer confidence, we introduce 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 uses a Toeplitz correlation matrix to account for the serial correlation in the high-frequency sentiment measurement errors. We find significant accuracy gains in nowcasting survey-based Belgian consumer confidence with economic media news sentiment.

Keywords: Dynamic factor model; Mixed frequency; Nowcasting; Sentometrics; State space; Toeplitz matrix (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (4)

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Working Paper: Daily news sentiment and monthly surveys: A mixed–frequency dynamic factor model for nowcasting consumer confidence (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:39:y:2023:i:1:p:266-278

DOI: 10.1016/j.ijforecast.2021.11.005

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