Using survey information for improving the density nowcasting of U.S. GDP
Year of publication: |
2023
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Authors: | Çakmaklı, Cem ; Demircan, Hamza |
Published in: |
Journal of business & economic statistics : JBES ; a publication of the American Statistical Association. - Abingdon : Taylor & Francis, ISSN 1537-2707, ZDB-ID 2043744-4. - Vol. 41.2023, 3, p. 667-682
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Subject: | Bayesian inference | Disagreement | Dynamic factor model | Predictive density evaluation | Stochastic volatility | Survey of professional forecasters | USA | United States | Prognoseverfahren | Forecasting model | Bayes-Statistik | Wirtschaftsprognose | Economic forecast | Theorie | Theory | Stochastischer Prozess | Stochastic process | Faktorenanalyse | Factor analysis | Schätzung | Estimation | Nationaleinkommen | National income |
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Çakmaklı, Cem, (2020)
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Nowcasting GDP with a pool of factor models and a fast estimation algorithm
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