Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/85936
Authors: 
de Gooijer, Jan G.
Zerom, Dawit
Year of Publication: 
2002
Series/Report no.: 
Tinbergen Institute Discussion Paper 02-032/4
Abstract: 
With the aim to mitigate the possibleproblem of negativity in the estimation of the conditionaldensity function, we introduce a so-called re-weightedNadaraya-Watson (RNW) estimator. The proposed RNWestimator is constructed by a slight modificationof the well-known Nadaraya-Watson smoother.Because the estimator is explicitly defined in terms ofthe data, its practical implementation is quite simple.With a detailed asymptotic analysis, we demonstratethat the RNW smoother preserves thesuperior large-sample bias property of thelocal linear smoother of the conditional densityproposed by Fan, Yao and Tong (1996).As a matter of independent statistical interest,the limit distribution of the RNW estimator is alsoderived.
Subjects: 
alpha-mixing
asymptotic properties
negativity
nonparametric
re-weighted
JEL: 
C22
Document Type: 
Working Paper

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