Publication Type

Journal Article

Publication Date

3-2010

Abstract

We propose a local linear functional coefficient estimator that admits a mix of discrete and continuous data for stationary time series. Under weak conditions our estimator is asymptotically normally distributed. A small set of simulation studies is carried out to illustrate the finite sample performance of our estimator. As an application, we estimate a wage determination function that explicitly allows the return to education to depend on other variables. We find evidence of the complex interacting patterns among the regressors in the wage equation, such as increasing returns to education when experience is very low, high return to education for workers with several years of experience, and diminishing returns to education when experience is high. Compared with the commonly used parametric and semi-parametric methods, our estimator performs better in both goodness-of-fit and in yielding economically interesting interpretation.

Discipline

Econometrics

Research Areas

Econometrics

Publication

Advances in Econometrics

Volume

25

First Page

131

Last Page

167

ISSN

0731-9053

Identifier

10.1108/S0731-9053(2009)0000025007

Publisher

Emerald

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.1108/S0731-9053(2009)0000025007

Included in

Econometrics Commons

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