Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/79632
Authors: 
Chen, Haiqiang
Fang, Ying
Li, Yingxing
Year of Publication: 
2013
Series/Report no.: 
SFB 649 Discussion Paper 2013-033
Abstract: 
This paper considers estimation and inference for varying-coefficient models with nonstationary regressors. We propose a nonparametric estimation method using penalized splines, which achieves the same optimal convergence rate as kernel-based methods, but enjoys computation advantages. Utilizing the mixed model representation of penalized splines, we develop a likelihood ratio test statistic for checking the stability of the regression coefficients. We derive both the exact and the asymptotic null distributions of this test statistic. We also demonstrate its optimality by examining its local power performance. These theoretical fundings are well supported by simulation studies.
Subjects: 
Nonstationary Time Series
Varying-coefficient Model
Likelihood Ratio Test
Penalized Splines
JEL: 
C12
C14
C22
Document Type: 
Working Paper

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