Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/25066 
Year of Publication: 
2005
Series/Report no.: 
SFB 649 Discussion Paper No. 2005,047
Publisher: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
Abstract: 
We propose marginal integration estimation and testing methods for the coefficients of varying coefficient multivariate regression model. Asymptotic distribution theory is developed for the estimation method which enjoys the same rate of convergence as univariate function estimation. For the test statistic, asymptotic normal theory is es- tablished. These theoretical results are derived under the fairly general conditions of absolute regularity (b-mixing). Application of the test procedure to the West Ger- man real GNP data reveals that a partially linear varying coefficient model is best parsimonious in fitting the data dynamics, a fact that is also confirmed with residual diagnostics.
Subjects: 
Equivalent kernels
German real GNP
Local polynomial
Marginal integration
Rate of convergence
Document Type: 
Working Paper

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