Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/61304
Authors: 
Lavergne, Pascal
Vuong, Quang
Year of Publication: 
1998
Series/Report no.: 
Discussion Papers, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes 1998,75
Abstract: 
A procedure for testing the signicance of a subset of explanatory variables in a nonparametric regression is proposed. Our test statistic uses the kernel method. Under the null hypothesis of no effect of the variables under test, we show that our test statistic has a nhp2/2 standard normal limiting distribution, where p2 is the dimension of the complete set of regressors. Our test is one-sided, consistent against all alternatives and detect local alternatives approaching the null at rate slower than n-1/2 h-p2/4. Our Monte-Carlo experiments indicate that it outperforms the test proposed by Fan and Li (1996).
Subjects: 
Hypothesis testing
Kernel estimation
Nested models
JEL: 
C52
C14
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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