Arbeitspapier
Testing for differences in survey-based density expectations: A compositional data approach
We propose to treat survey-based density expectations as compositional data when testing either for heterogeneity in density forecasts across different groups of agents or for changes over time. Monte Carlo simulations show that the proposed test has more power relative to both a bootstrap approach based on the KLIC and an approach which involves multiple testing for differences of individual parts of the density. In addition, the test is computaionally much faster than the KLIC-based one, which relies on simulations, and allows for comparisons across multiple groups. Using density expectations from the ECB Survey of Professional Forecasters and the U.S. Survey of Consumer Expectations, we show the usefulness of the test in detecting possible changes in density expectations over time and across different types of forecasters.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Papers of the Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour" ; No. 39
- Klassifikation
-
Wirtschaft
Hypothesis Testing: General
Expectations; Speculations
Macroeconomics: Consumption, Saving, Production, Employment, and Investment: Forecasting and Simulation: Models and Applications
- Thema
-
compositional data
density forecasts
survey forecasts
disagreement
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Dovern, Jonas
Glas, Alexander
Kenny, Geoff
- Ereignis
-
Veröffentlichung
- (wer)
-
Humboldt University Berlin
- (wo)
-
Berlin
- (wann)
-
2023
- DOI
-
doi:10.18452/25967
- Handle
- URN
-
urn:nbn:de:kobv:11-110-18452/26651-1
- Letzte Aktualisierung
-
10.03.2025, 11:43 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
- Dovern, Jonas
- Glas, Alexander
- Kenny, Geoff
- Humboldt University Berlin
Entstanden
- 2023
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