Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/66285 
Year of Publication: 
1997
Series/Report no.: 
SFB 373 Discussion Paper No. 1997,37
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
Abstract: 
Semiparametric single-index regression involves an unknown finite dimensional parameter and an unknown (link) function. We consider estimation of the parameter via the pseudo maximum likelihood method. For this purpose we estimate the conditional density of the response given a candidate index and maximize the obtained likelihood. We show that this technique of adaptation yields an asymptotically efficient estimator : it has minimal variance among all estimators.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
281.61 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.