Estimation of Semi-Varying Coefficient Models with Nonstationary Regressors

Kunpeng Li, Degui Li, Zhongwen Liang, Cheng Hsiao

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We study a semi-varying coefficient model where the regressors are generated by the multivariate unit root I(1) processes. The influence of the explanatory vectors on the response variable satisfies the semiparametric partially linear structure with the nonlinear component being functional coefficients. A semiparametric estimation methodology with the first-stage local polynomial smoothing is applied to estimate both the constant coefficients in the linear component and the functional coefficients in the nonlinear component. The asymptotic distribution theory for the proposed semiparametric estimators is established under some mild conditions, from which both the parametric and nonparametric estimators are shown to enjoy the well-known super-consistency property. Furthermore, a simulation study is conducted to investigate the finite sample performance of the developed methodology and results.
Original languageEnglish
Pages (from-to)354-369
Number of pages16
JournalEconometric Reviews
Issue number1-3
Early online date7 Nov 2015
Publication statusPublished - 2017

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© 2017 Taylor & Francis Group, LLC. This is an author produced version of a paper accepted for publication in Econometric Reviews. Uploaded in accordance with the publisher's self-archiving policy.

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