A Bayesian approach for inference on probabilistic surveys

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Bibliographic Details
Authors and Corporations:	Del Negro, Marco (Author), Casarin, Roberto (Author), Bassetti, Federico (Author)
Other Authors:	Casarin, Roberto [Author] • Bassetti, Federico [Author]
Type of Resource:	E-Book
Language:	English
published:	New York, NY Federal Reserve Bank of New York [2022]
Series:	Federal Reserve Bank of New York: Staff reports ; no. 1025 (July 2022)
Subjects:	Bayesian interface Bayesian nonparametric Survey of Professional Forecasters noisy rational expectations Graue Literatur
Source:	Verbunddaten SWB Lizenzfreie Online-Ressourcen

Description
Summary:	We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We find that in contrast to theory, for horizons close to two years, there is no relationship whatsoever between subjective uncertainty and forecast accuracy for output growth density projections, both across forecasters and over time, and only a mild relationship for inflation projections. As the horizon shortens, the relationship becomes one-to-one, as the theory would predict.
Physical Description:	1 Online-Ressource (circa 95 Seiten); Illustrationen