Semiparametric Trending Panel Data Models with Cross-Sectional Dependence

By Jia Chen, Jiti Gao, Degui Li. 2012

124 citations recorded by the source corpus.

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.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/37c4134cf10fa32fa1746ac52dbb5656629933ad

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Liangjun Su
2. Xia Wang
3. Jiti Gao
4. Peter C. B. Phillips
5. Yikui Zhang
6. Degui Li
7. Jia Chen
8. Sainan Jin

Citations in the corpus

• Testing for Common Trends in Semiparametric Panel Data Models with Fixed Effects, forthcoming (2012, methodology): “Empirical applications include Fomby and Vogelsang (2003) and Bacigál (2005), who apply the Vogelsang-Franses test to temperature data and geodetic data, respectively.”
• On Time-Varying Factor Models: Estimation and Testing ∗ (2017, methodology): “…the model via a Gibbs sampling procedure. nonparametric literature on time-varying models (see, e.g., Cai 2007, Robinson 2012, Chen and Hong 2012, Chen et al. 2012, Su et al. 2015) and model as a nonrandom function of : = ( ) where (·) is an unknown piece-wise smooth function of on (0 1] for…”
• Estimation in Partially Linear Single-Index Panel Data Models With Fixed Effects (2013, background): “Recent studies include those by Ullah and Roy (1998), Hjellvik, Chen, and Tjøstheim (2004), Cai and Li (2008), Henderson, Carroll, and Li (2008), Mammen, Støve, and Tjøstheim (2009), and Chen, Gao, and Li (2012).”