Arbeitspapier
Text-based recession probabilities
This paper proposes a new methodology based on textual analysis to forecast U.S. recessions. Specifically, the paper develops an index in the spirit of Baker et al. (2016) and Caldara and Iacoviello (2018) which tracks developments in U.S. real activity. When used in a standard recession probability model, the index outperforms the yield curve based forecast, a standard method to forecast recessions, at medium horizons, up to 8 months. Moreover, the index contains information not included in yield data that are useful to understand recession episodes. When included as an additional control to the slope of the yield curve, it improves the forecast accuracy by 5% to 30% depending on the horizon. These results are stable to a number of different robustness checks, including changes to the estimation method, the definition of recessions and controlling for asset purchases by major central banks. Yield and textual analysis data also outperform other popular leading indicators for the U.S. business cycle such as PMIs, consumers' surveys or employment data.
- ISBN
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978-92-899-4516-5
- Language
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Englisch
- Bibliographic citation
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Series: ECB Working Paper ; No. 2516
- Classification
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Wirtschaft
General Aggregative Models: Forecasting and Simulation: Models and Applications
Money and Interest Rates: Forecasting and Simulation: Models and Applications
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
Forecasting Models; Simulation Methods
- Subject
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U.S. recessions
forecast
textual analysis
- Event
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Geistige Schöpfung
- (who)
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Ferrari, Massimo
Le Mezo, Helena
- Event
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Veröffentlichung
- (who)
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European Central Bank (ECB)
- (where)
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Frankfurt a. M.
- (when)
-
2021
- DOI
-
doi:10.2866/864540
- Handle
- Last update
-
10.03.2025, 11:42 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Ferrari, Massimo
- Le Mezo, Helena
- European Central Bank (ECB)
Time of origin
- 2021
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Estimating Subjective Probabilities
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Tail Probabilities for Regression Estimators
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