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.
| Original language | English |
|---|---|
| Article number | 1 |
| Pages (from-to) | 266-278 |
| Number of pages | 13 |
| Journal | International Journal of Forecasting |
| Volume | 39 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2023 |
Bibliographical note
Funding Information:We thank the Editor and two anonymous referees, as well as David Ardia, Raïsa Basselier, Keven Bluteau, Nabil Bouamara, Leopoldo Catania, Selien De Schryder, Eric Ghysels, Koen Inghelbrecht, Hande Karabiyik, Siem Jan Koopman, Geert Langenus, Geoffrey Minne, Juan Rubio Ramírez, Peter Reusens, James Thewissen, Steven Vanduffel, Jeroen Van Pelt, Marjan Wauters, and Raf Wouters, for stimulating discussions and feedback on earlier drafts of this work. We further thank the seminar participants at Ghent University, Vrije Universiteit Brussel, and the National Bank of Belgium, as well as the participants at the 2019 CFE conference in London and the 2020 SoFiE summer school in Chicago. We are grateful to the Belgian News Agency (Belga) for providing us with their media news archive. Part of this research was conducted while Andres Algaba was a visiting researcher at the National Bank of Belgium. This project benefited from financial support from the National Bank of Belgium , the Swiss National Science Foundation ( https://www.snf.ch , grant #17928 ), and Innoviris . Any remaining errors or shortcomings are those of the authors.
Funding Information:
We thank the Editor and two anonymous referees, as well as David Ardia, Raïsa Basselier, Keven Bluteau, Nabil Bouamara, Leopoldo Catania, Selien De Schryder, Eric Ghysels, Koen Inghelbrecht, Hande Karabiyik, Siem Jan Koopman, Geert Langenus, Geoffrey Minne, Juan Rubio Ramírez, Peter Reusens, James Thewissen, Steven Vanduffel, Jeroen Van Pelt, Marjan Wauters, and Raf Wouters, for stimulating discussions and feedback on earlier drafts of this work. We further thank the seminar participants at Ghent University, Vrije Universiteit Brussel, and the National Bank of Belgium, as well as the participants at the 2019 CFE conference in London and the 2020 SoFiE summer school in Chicago. We are grateful to the Belgian News Agency (Belga) for providing us with their media news archive. Part of this research was conducted while Andres Algaba was a visiting researcher at the National Bank of Belgium. This project benefited from financial support from the National Bank of Belgium, the Swiss National Science Foundation (https://www.snf.ch, grant #17928), and Innoviris. Any remaining errors or shortcomings are those of the authors.
Publisher Copyright:
© 2021 International Institute of Forecasters
Copyright:
Copyright 2022 Elsevier B.V., All rights reserved.