Arbeitspapier
An Investigation into the Uncertainty Revision Process of Professional Forecasters
Following Manzan (2021), this paper examines how professional forecasters revise their uncertainty (variance) forecasts. We show that popular first moment "efficiency" tests are not applicable to study variance forecasts and instead employ monotonicity tests developed by Patton and Timmermann (2012). We find strong support for the Bayesian learning prediction of decreasing patterns in the variance of fixed-event density forecasts and their revisions as the forecast horizon declines. We explore the role of financial conditions indices in variance forecasts and document their predictive content for the revision process of US professional forecasters, although the evidence is weaker for euro area forecasters.
- Sprache
-
Englisch
- Erschienen in
-
Series: AEI Economics Working Paper ; No. 2023-14
- Klassifikation
-
Wirtschaft
- Thema
-
Variance forecasts
survey expectations
Bayesian learning
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Clements, Michael P.
Rich, Robert W.
Tracy, Joseph S.
- Ereignis
-
Veröffentlichung
- (wer)
-
American Enterprise Institute (AEI)
- (wo)
-
Washington, DC
- (wann)
-
2023
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Clements, Michael P.
- Rich, Robert W.
- Tracy, Joseph S.
- American Enterprise Institute (AEI)
Entstanden
- 2023
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