Functional coefficient regression models with time trend Academic Article uri icon


  • We consider the problem of estimating a varying coefficient regression model when regressors include a time trend. We show that the commonly used local constant kernel estimation method leads to an inconsistent estimation result, while a local polynomial estimator yields a consistent estimation result. We establish the asymptotic normality result for the proposed estimator. We also provide asymptotic analysis of the data-driven (least squares cross validation) method of selecting the smoothing parameters. In addition, we consider a partially linear time trend model and establish the asymptotic distribution of our proposed estimator. Two test statistics are proposed to test the null hypotheses of a linear and of a partially linear time trend models. Simulations are reported to examine the finite sample performances of the proposed estimators and the test statistics. 2012 Elsevier B.V. All rights reserved.

published proceedings


altmetric score

  • 0.25

author list (cited authors)

  • Liang, Z., & Li, Q. i.

citation count

  • 5

complete list of authors

  • Liang, Zhongwen||Li, Qi

publication date

  • January 2012