Generated covariates in nonparametric estimation: A short review

Arbeitspapier

In many applications, covariates are not observed but have to be estimated from data. We outline some regression-type models where such a situation occurs and discuss estimation of the regression function in this context.We review theoretical results on how asymptotic properties of nonparametric estimators differ in the presence of generated covariates from the standard case where all covariates are observed. These results also extend to settings where the focus of interest is on average functionals of the regression function.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: SFB 649 Discussion Paper ; No. 2012-042

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Semiparametric and Nonparametric Methods: General ; Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
• Thema: Nonparametric estimation ; generated covariates ; Varianzanalyse ; Schätztheorie ; Nichtparametrisches Verfahren ; Theorie

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Mammen, Enno ; Rothe, Christoph ; Schienle, Melanie
• Ereignis: Veröffentlichung
• (wer): Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
• (wo): Berlin
• (wann): 2012

Weitere Informationen

• Handle: http://hdl.handle.net/10419/79567
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ