EconPapers    
Economics at your fingertips  
 

Nonparametric Kernel Estimation for Semiparametric Models

Donald W. K. Andrews ()

Econometric Theory, 1995, vol. 11, issue 03, pages 560-586

Abstract: This paper presents a number of consistency results for nonparametric kernel estimators of density and regression functions and their derivatives. These results are particularly useful in semiparametric estimation and testing problems that rely on preliminary nonparametric estimators, as in Andrews (1994, Econometrica 62, 43 72). The results allow for near-epoch dependent, nonidentically distributed random variables, data-dependent bandwidth sequences, preliminary estimation of parameters (e.g., nonparametric regression based on residuals), and nonparametric regression on index functions.

Date: 1995
View citations in EconPapers

Downloads: (external link)
http://journals.cambridge.org/abstract_S0266466600009427 link to article abstract page (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:cup:etheor:v:11:y:1995:i:03:p:560-586_00

Access Statistics for this article

More articles in Econometric Theory from Cambridge University Press
Address: The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU UK
Series data maintained by Mike Eden ().

 
Page updated 2009-11-28
Handle: RePEc:cup:etheor:v:11:y:1995:i:03:p:560-586_00