Arbeitspapier
Asymptotic distribution of linear unbiased estimators in the presence of heavy-tailed stochastic regressors and residuals
Under the symmetric α-stable distributional assumption for the disturbances, Blattberg et al (1971) consider unbiased linear estimators for a regression model with non-stochastic regressors. We consider both the rate of convergence to the true value and the asymptotic distribution of the normalized error of the linear unbiased estimators. By doing this, we allow the regressors to be stochastic and disturbances to be heavy-tailed with either finite or infinite variances, where the tail-thickness parameters of the regressors and disturbances may be different.
- Sprache
-
Englisch
- Erschienen in
-
Series: Discussion Paper Series 1 ; No. 2005,21
- Klassifikation
-
Wirtschaft
- Thema
-
Asymptotic distribution
rate of convergence
stochastic regressor
stable non-Gaussian
finite or infinite variance
heavy tails
Regression
Schätztheorie
Statistische Verteilung
Theorie
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Samorodnitsky, Gennady
Rachev, Svetlozar T.
Kurz-Kim, Jeong-Ryeol
- Ereignis
-
Veröffentlichung
- (wer)
-
Deutsche Bundesbank
- (wo)
-
Frankfurt a. M.
- (wann)
-
2005
- 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
- Samorodnitsky, Gennady
- Rachev, Svetlozar T.
- Kurz-Kim, Jeong-Ryeol
- Deutsche Bundesbank
Entstanden
- 2005
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