Estimation and Inference for Varying-Coefficient Models With Nonstationary Regressors Using Penalized Splines

44 Pages Posted: 30 Jun 2013

See all articles by Haiqiang Chen

Haiqiang Chen

Xiamen University - Wang Yanan Institute for studies in Economics

Ying Fang

Xiamen University

Yingxing Li

Xiamen University

Date Written: June 30, 2013

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 findings are well supported by simulation studies.

Keywords: Nonstationary Time Series, Varying-coefficient Model, Likelihood Ratio Test, Penalized Splines

JEL Classification: C12, C22, C52

Suggested Citation

Chen, Haiqiang and Fang, Ying and Li, Yingxing, Estimation and Inference for Varying-Coefficient Models With Nonstationary Regressors Using Penalized Splines (June 30, 2013). Available at SSRN: https://ssrn.com/abstract=2287449 or http://dx.doi.org/10.2139/ssrn.2287449

Haiqiang Chen (Contact Author)

Xiamen University - Wang Yanan Institute for studies in Economics ( email )

Economics Building A307
Xiamen University
Xiamen, Fujian 361005
China

Ying Fang

Xiamen University ( email )

Xiamen
China

HOME PAGE: http://www.wise.xmu.edu.cn/homepage.asp

Yingxing Li

Xiamen University ( email )

Xiamen, Fujian 361005
China

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