Arbeitspapier
Robust confidence regions for incomplete models
Call an economic model incomplete if it does not generate a probabilistic prediction even given knowledge of all parameter values. We propose a method of inference about unknown parameters for such models that is robust to heterogeneity and dependence of unknown form. The key is a Central Limit Theorem for belief functions; robust con.dence regions are then constructed in a fashion paralleling the classical approach. Monte Carlo simulations support tractability of the method and demonstrate its enhanced robustness relative to existing methods.
- Sprache
-
Englisch
- Erschienen in
-
Series: cemmap working paper ; No. CWP65/15
- Klassifikation
-
Wirtschaft
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Epstein, Larry G.
Kaido, Hiroaki
Seo, Kyoungwon
- Ereignis
-
Veröffentlichung
- (wer)
-
Centre for Microdata Methods and Practice (cemmap)
- (wo)
-
London
- (wann)
-
2015
- DOI
-
doi:10.1920/wp.cem.2015.6515
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:46 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
- Epstein, Larry G.
- Kaido, Hiroaki
- Seo, Kyoungwon
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2015
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