Functional coefficient regression models with time trend Academic Article

abstract

• 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.

authors

• Li, Qi

published proceedings

• JOURNAL OF ECONOMETRICS

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

publisher

• Elsevier  Publisher

published in

• Journal of Econometrics  Journal

keywords

• Partially Linear Model
• Specification Tests
• Time Trend
• Varying Coefficient Model

Digital Object Identifier (DOI)

• 10.1016/j.jeconom.2011.08.009

start page

• 15

end page

• 31

volume

• 170

issue

• 1

URL

• http://dx.doi.org/10.1016/j.jeconom.2011.08.009