In this paper, we consider the variable selection problem for the quantile regression model based on panel data. By adding an improved adaptive lasso penalty term,we realize the quantile regression and variable selection for the panel data with fixed effect simultaneously, and obtain the consistency and asymptotical normality for the selection of the parameters. Simulation studies show the validity of the proposed method, which extend that of[14].
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