Abstract
To simultaneously deal with serial correlations and cross-sectional dependences for a panel linear fixed effects model, we propose a new approach based on an extended score vector and a moving blocks empirical likelihood method. Large sample properties of the proposed method are studied. Simulation results show that the new method works well under the situations of either strong or weak cross-sectional dependences, and the method performs better than the methods in Gonçalves (2011) and Vogelsang (2012). The proposed method is also applied to an application in carbon emission, and the results show that urbanization has a significant effect on carbon emission. Moreover, the effect varies in different stage of urbanization.
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