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Quantile regression for static panel data models with time-invariant regressors.

Li Tao1, Lingnan Tai2, Maozai Tian2,3

  • 1School of Information, Beijing Wuzi University, Beijing, China.

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This study introduces two novel weighted quantile regression estimators for static panel data, enhancing coefficient estimation for time-invariant regressors. These methods are computationally efficient and validated through simulations and an export trade gravity model application.

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Area of Science:

  • Econometrics
  • Statistical Modeling
  • Panel Data Analysis

Background:

  • Panel data models with time-invariant regressors present estimation challenges.
  • Existing methods may lack efficiency or computational simplicity for such models.

Purpose of the Study:

  • To propose two new weighted quantile regression estimators for static panel data.
  • To improve the estimation of coefficients for time-invariant regressors.
  • To provide computationally convenient and simple-to-implement estimation techniques.

Main Methods:

  • Development of two novel weighted quantile regression estimators.
  • Theoretical analysis of consistency and asymptotic normality under sequential and simultaneous N, T asymptotics.
  • Monte Carlo simulations to validate the proposed estimators across various parameter sets.
  • Empirical application using a trade gravity model for China's exports.

Main Results:

  • The proposed estimators demonstrate improved coefficient estimation for time-invariant regressors.
  • Theoretical properties including consistency and asymptotic normality are established.
  • Simulation results confirm the validity and performance of the new estimators.
  • The empirical application successfully utilizes the estimators to analyze export determinants.

Conclusions:

  • The new weighted quantile regression estimators offer a valuable and practical advancement for static panel data analysis.
  • These estimators provide a computationally efficient and statistically sound approach for handling time-invariant regressors.
  • The findings have implications for empirical economic research, particularly in international trade analysis.