Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/86866 
Year of Publication: 
2008
Series/Report no.: 
Tinbergen Institute Discussion Paper No. 08-046/4
Publisher: 
Tinbergen Institute, Amsterdam and Rotterdam
Abstract: 
We study the problem of selecting the optimal functional form among a set of non-nested nonlinear mean functions for a semiparametric kernel based regression model. To this end we consider Rissanen's minimum description length (MDL) principle. We prove the consistency of the proposed MDL criterion. Its performance is examined via simulated data sets of univariate and bivariate nonlinear regression models.
Subjects: 
Kernel density estimator
Maximum likelihood estimator
Minimum description length
Nonlinear regression
Semiparametric model
JEL: 
C14
Document Type: 
Working Paper

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