关键词: 面板数据, 随机效应, 分位回归, Gibbs抽样

Abstract: The paper discusses the random effects panel data model and establishes a hierarchical Bayesian quantile regression model by using of the relationship between asymmetric Laplace distribution (ALD) and quantile regression. The point and interval estimate of unknown parameters are obtained by Gibbs sampling algorithm based on decomposition of ALD. Monte Carlo simulation study also indicates that the proposed method is better than mean regression methods when dealing with the panel data model with random effects, especially when the error term is non-normal. Finally, we use the new method to study an economy and employment panel data of our country and obtain much useful information for macro-economic control.

Key words: Panel Data, Random Effects, Quantile Regression, Gibbs Sampler