Estimation of semi-varying coefficient models with nonstationary regressors |
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Authors: | Kunpeng Li Degui Li Zhongwen Liang |
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Institution: | 1. School of Economics &2. Management, Capital University of Economics and Business, Beijing, China;3. Department of Mathematics, University of York, York, United Kingdom;4. Department of Economics, University at Albany, SUNY, Albany, New York, USA |
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Abstract: | We study a semivarying 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. |
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Keywords: | Functional coefficients local polynomial fitting semiparametric estimation super-consistency unit root process |
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