Semiparametric trending panel data models with cross-sectional dependence

Chen, Jia, Gao, Jiti and Li, Degui (2012) Semiparametric trending panel data models with cross-sectional dependence. Journal of Econometrics, 171 1: 71-85. doi:10.1016/j.jeconom.2012.07.001


Author Chen, Jia
Gao, Jiti
Li, Degui
Title Semiparametric trending panel data models with cross-sectional dependence
Journal name Journal of Econometrics   Check publisher's open access policy
ISSN 0304-4076
1872-6895
Publication date 2012-11-01
Sub-type Article (original research)
DOI 10.1016/j.jeconom.2012.07.001
Volume 171
Issue 1
Start page 71
End page 85
Total pages 15
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Language eng
Formatted abstract
A semiparametric fixed effects model is introduced to describe the nonlinear trending phenomenon in panel data analysis and it allows for the cross-sectional dependence in both the regressors and the residuals. A pooled semiparametric profile likelihood dummy variable approach based on the first-stage local linear fitting is developed to estimate both the parameter vector and the nonlinear time trend function. As both the time series length T and the cross-sectional size N tend to infinity, the resulting estimator of the parameter vector is asymptotically normal with a root-(NT) convergence rate. Meanwhile, the asymptotic distribution for the nonparametric estimator of the trend function is also established with a root-(NTh) convergence rate. Two simulated examples are provided to illustrate the finite sample performance of the proposed method. In addition, the proposed model and estimation method are applied to a CPI data set as well as an input–output data set.
Keyword Cross-sectional dependence
Local linear fitting
Nonlinear time trend
Panel data
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mathematics and Physics
Official 2013 Collection
 
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