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时间维度较小时异质性面板分位数回归的 CCE 估计AI 解读

We consider a common correlated effects estimator for panel quantile regression models featuring heterogeneous slope coefficients and interactive fixed effects. Using convolution smoothing to facilitate the derivation of asymptotic properties, our method allows the number of time periods (T) to grow at a much slower rate than the number of cross-sectional units (N). We establish that the mean group estimator converges to a limiting normal distribution, which may have a…

非线性面板数据模型的共同相关效应估计AI 解读

Summary This paper focuses on estimating the coefficients and average partial effects of observed regressors in nonlinear panel data models with interactive fixed effects, using the common correlated effects framework. The proposed two-step estimation method involves applying principal component analysis to estimate the latent factors based on cross-sectional averages of the regressors in the first step, and jointly estimating the coefficients of the regressors and the…