Publication Type
Journal Article
Version
acceptedVersion
Publication Date
1-2010
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.
Keywords
Discrete variables, Functional coefficient estimation, Local linear estimation, Crossvalidation
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
Citation
SU, Liangjun; CHEN, Ye; and ULLAH, Aman.
Functional Coefficient Estimation with Both Categorical and Continuous Data. (2010). Advances in Econometrics. 25, 131-167.
Available at: https://ink.library.smu.edu.sg/soe_research/336
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1108/S0731-9053(2009)0000025007